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• Can't connect to Wireless

  - by SimplyRed37

  Good day all! I hope you are doing good. I have performed a WUBI installation of 12.04 on my HP G62 laptop, which has an Atheros AR9285 wireless chipset. Everything works fine with my wired network connection. However, wireless is unable to connect to my wifi network. I enter the WPA2 key and then it attemps to connect, but eventually comes back, asking for the WPA2 key again, as if it was not good. All of the other laptops in the household are able to connect, using the same key (I configured them all, so I am 500% sure of the WPA2 key). Any idea as to what could be causing this? I can definitely post the output of CLI commands like "rfkill list" or "sudo lshw -class network", or "ifconfig". I have installed Ubuntu a few time but I am definitely still a newbie, but I am definitely computer savyy. Looking forward to suggestions . Thanks in advance !!! Dan...

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• Adding DTrace Probes to PHP Extensions

  - by cj

  The powerful DTrace tracing facility has some PHP-specific probes that can be enabled with --enable-dtrace. DTrace for Linux is being created by Oracle and is currently in tech preview. Currently it doesn't support userspace tracing so, in the meantime, Systemtap can be used to monitor the probes implemented in PHP. This was recently outlined in David Soria Parra's post Probing PHP with Systemtap on Linux. My post shows how DTrace probes can be added to PHP extensions and traced on Linux. I was using Oracle Linux 6.3. Not all Linux kernels are built with Systemtap, since this can impact stability. Check whether your running kernel (or others installed) have Systemtap enabled, and reboot with such a kernel: # grep CONFIG_UTRACE /boot/config-`uname -r` # grep CONFIG_UTRACE /boot/config-* When you install Systemtap itself, the package systemtap-sdt-devel is needed since it provides the sdt.h header file: # yum install systemtap-sdt-devel You can now install and build PHP as shown in David's article. Basically the build is with: $ cd ~/php-src $ ./configure --disable-all --enable-dtrace $ make (For me, running 'make' a second time failed with an error. The workaround is to do 'git checkout Zend/zend_dtrace.d' and then rerun 'make'. See PHP Bug 63704) David's article shows how to trace the probes already implemented in PHP. You can also use Systemtap to trace things like userspace PHP function calls. For example, create test.php: <?php $c = oci_connect('hr', 'welcome', 'localhost/orcl'); $s = oci_parse($c, "select dbms_xmlgen.getxml('select * from dual') xml from dual"); $r = oci_execute($s); $row = oci_fetch_array($s, OCI_NUM); $x = $row[0]->load(); $row[0]->free(); echo $x; ?> The normal output of this file is the XML form of Oracle's DUAL table: $ ./sapi/cli/php ~/test.php <?xml version="1.0"?> <ROWSET> <ROW> <DUMMY>X</DUMMY> </ROW> </ROWSET> To trace the PHP function calls, create the tracing file functrace.stp: probe process("sapi/cli/php").function("zif_*") { printf("Started function %s\n", probefunc()); } probe process("sapi/cli/php").function("zif_*").return { printf("Ended function %s\n", probefunc()); } This makes use of the way PHP userspace functions (not builtins) like oci_connect() map to C functions with a "zif_" prefix. Login as root, and run System tap on the PHP script: # cd ~cjones/php-src # stap -c 'sapi/cli/php ~cjones/test.php' ~cjones/functrace.stp Started function zif_oci_connect Ended function zif_oci_connect Started function zif_oci_parse Ended function zif_oci_parse Started function zif_oci_execute Ended function zif_oci_execute Started function zif_oci_fetch_array Ended function zif_oci_fetch_array Started function zif_oci_lob_load <?xml version="1.0"?> <ROWSET> <ROW> <DUMMY>X</DUMMY> </ROW> </ROWSET> Ended function zif_oci_lob_load Started function zif_oci_free_descriptor Ended function zif_oci_free_descriptor Each call and return is logged. The Systemtap scripting language allows complex scripts to be built. There are many examples on the web. To augment this generic capability and the PHP probes in PHP, other extensions can have probes too. Below are the steps I used to add probes to OCI8: I created a provider file ext/oci8/oci8_dtrace.d, enabling three probes. The first one will accept a parameter that runtime tracing can later display: provider php { probe oci8__connect(char *username); probe oci8__nls_start(); probe oci8__nls_done(); }; I updated ext/oci8/config.m4 with the PHP_INIT_DTRACE macro. The patch is at the end of config.m4. The macro takes the provider prototype file, a name of the header file that 'dtrace' will generate, and a list of sources files with probes. When --enable-dtrace is used during PHP configuration, then the outer $PHP_DTRACE check is true and my new probes will be enabled. I've chosen to define an OCI8 specific macro, HAVE_OCI8_DTRACE, which can be used in the OCI8 source code: diff --git a/ext/oci8/config.m4 b/ext/oci8/config.m4 index 34ae76c..f3e583d 100644 --- a/ext/oci8/config.m4 +++ b/ext/oci8/config.m4 @@ -341,4 +341,17 @@ if test "$PHP_OCI8" != "no"; then PHP_SUBST_OLD(OCI8_ORACLE_VERSION) fi + + if test "$PHP_DTRACE" = "yes"; then + AC_CHECK_HEADERS([sys/sdt.h], [ + PHP_INIT_DTRACE([ext/oci8/oci8_dtrace.d], + [ext/oci8/oci8_dtrace_gen.h],[ext/oci8/oci8.c]) + AC_DEFINE(HAVE_OCI8_DTRACE,1, + [Whether to enable DTrace support for OCI8 ]) + ], [ + AC_MSG_ERROR( + [Cannot find sys/sdt.h which is required for DTrace support]) + ]) + fi + fi In ext/oci8/oci8.c, I added the probes at, for this example, semi-arbitrary places: diff --git a/ext/oci8/oci8.c b/ext/oci8/oci8.c index e2241cf..ffa0168 100644 --- a/ext/oci8/oci8.c +++ b/ext/oci8/oci8.c @@ -1811,6 +1811,12 @@ php_oci_connection *php_oci_do_connect_ex(char *username, int username_len, char } } +#ifdef HAVE_OCI8_DTRACE + if (DTRACE_OCI8_CONNECT_ENABLED()) { + DTRACE_OCI8_CONNECT(username); + } +#endif + /* Initialize global handles if they weren't initialized before */ if (OCI_G(env) == NULL) { php_oci_init_global_handles(TSRMLS_C); @@ -1870,11 +1876,22 @@ php_oci_connection *php_oci_do_connect_ex(char *username, int username_len, char size_t rsize = 0; sword result; +#ifdef HAVE_OCI8_DTRACE + if (DTRACE_OCI8_NLS_START_ENABLED()) { + DTRACE_OCI8_NLS_START(); + } +#endif PHP_OCI_CALL_RETURN(result, OCINlsEnvironmentVariableGet, (&charsetid_nls_lang, 0, OCI_NLS_CHARSET_ID, 0, &rsize)); if (result != OCI_SUCCESS) { charsetid_nls_lang = 0; } smart_str_append_unsigned_ex(&hashed_details, charsetid_nls_lang, 0); + +#ifdef HAVE_OCI8_DTRACE + if (DTRACE_OCI8_NLS_DONE_ENABLED()) { + DTRACE_OCI8_NLS_DONE(); + } +#endif } timestamp = time(NULL); The oci_connect(), oci_pconnect() and oci_new_connect() calls all use php_oci_do_connect_ex() internally. The first probe simply records that the PHP application made a connection call. I already showed a way to do this without needing a probe, but adding a specific probe lets me record the username. The other two probes can be used to time how long the globalization initialization takes. The relationships between the oci8_dtrace.d names like oci8__connect, the probe guards like DTRACE_OCI8_CONNECT_ENABLED() and probe names like DTRACE_OCI8_CONNECT() are obvious after seeing the pattern of all three probes. I included the new header that will be automatically created by the dtrace tool when PHP is built. I did this in ext/oci8/php_oci8_int.h: diff --git a/ext/oci8/php_oci8_int.h b/ext/oci8/php_oci8_int.h index b0d6516..c81fc5a 100644 --- a/ext/oci8/php_oci8_int.h +++ b/ext/oci8/php_oci8_int.h @@ -44,6 +44,10 @@ # endif # endif /* osf alpha */ +#ifdef HAVE_OCI8_DTRACE +#include "oci8_dtrace_gen.h" +#endif + #if defined(min) #undef min #endif Now PHP can be rebuilt: $ cd ~/php-src $ rm configure && ./buildconf --force $ ./configure --disable-all --enable-dtrace \ --with-oci8=instantclient,/home/cjones/instantclient $ make If 'make' fails, do the 'git checkout Zend/zend_dtrace.d' trick I mentioned. The new probes can be seen by logging in as root and running: # stap -l 'process.provider("php").mark("oci8*")' -c 'sapi/cli/php -i' process("sapi/cli/php").provider("php").mark("oci8__connect") process("sapi/cli/php").provider("php").mark("oci8__nls_done") process("sapi/cli/php").provider("php").mark("oci8__nls_start") To test them out, create a new trace file, oci.stp: global numconnects; global start; global numcharlookups = 0; global tottime = 0; probe process.provider("php").mark("oci8-connect") { printf("Connected as %s\n", user_string($arg1)); numconnects += 1; } probe process.provider("php").mark("oci8-nls_start") { start = gettimeofday_us(); numcharlookups++; } probe process.provider("php").mark("oci8-nls_done") { tottime += gettimeofday_us() - start; } probe end { printf("Connects: %d, Charset lookups: %ld\n", numconnects, numcharlookups); printf("Total NLS charset initalization time: %ld usecs/connect\n", (numcharlookups 0 ? tottime/numcharlookups : 0)); } This calculates the average time that the NLS character set lookup takes. It also prints out the username of each connection, as an example of using parameters. Login as root and run Systemtap over the PHP script: # cd ~cjones/php-src # stap -c 'sapi/cli/php ~cjones/test.php' ~cjones/oci.stp Connected as cj <?xml version="1.0"?> <ROWSET> <ROW> <DUMMY>X</DUMMY> </ROW> </ROWSET> Connects: 1, Charset lookups: 1 Total NLS charset initalization time: 164 usecs/connect This shows the time penalty of making OCI8 look up the default character set. This time would be zero if a character set had been passed as the fourth argument to oci_connect() in test.php.

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• How to subscribe to the free Oracle Linux errata yum repositories

  - by Lenz Grimmer

  Now that updates and errata for Oracle Linux are available for free (both as in beer and freedom), here's a quick HOWTO on how to subscribe your Oracle Linux system to the newly added yum repositories on our public yum server, assuming that you just installed Oracle Linux from scratch, e.g. by using the installation media (ISO images) available from the Oracle Software Delivery Cloud You need to download the appropriate yum repository configuration file from the public yum server and install it in the yum repository directory. For Oracle Linux 6, the process would look as follows: as the root user, run the following command: [root@oraclelinux62 ~]# wget http://public-yum.oracle.com/public-yum-ol6.repo \ -P /etc/yum.repos.d/ --2012-03-23 00:18:25-- http://public-yum.oracle.com/public-yum-ol6.repo Resolving public-yum.oracle.com... 141.146.44.34 Connecting to public-yum.oracle.com|141.146.44.34|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 1461 (1.4K) [text/plain] Saving to: “/etc/yum.repos.d/public-yum-ol6.repo” 100%[=================================================>] 1,461 --.-K/s in 0s 2012-03-23 00:18:26 (37.1 MB/s) - “/etc/yum.repos.d/public-yum-ol6.repo” saved [1461/1461] For Oracle Linux 5, the file name would be public-yum-ol5.repo in the URL above instead. The "_latest" repositories that contain the errata packages are already enabled by default — you can simply pull in all available updates by running "yum update" next: [root@oraclelinux62 ~]# yum update Loaded plugins: refresh-packagekit, security ol6_latest | 1.1 kB 00:00 ol6_latest/primary | 15 MB 00:42 ol6_latest 14643/14643 Setting up Update Process Resolving Dependencies --> Running transaction check ---> Package at.x86_64 0:3.1.10-43.el6 will be updated ---> Package at.x86_64 0:3.1.10-43.el6_2.1 will be an update ---> Package autofs.x86_64 1:5.0.5-39.el6 will be updated ---> Package autofs.x86_64 1:5.0.5-39.el6_2.1 will be an update ---> Package bind-libs.x86_64 32:9.7.3-8.P3.el6 will be updated ---> Package bind-libs.x86_64 32:9.7.3-8.P3.el6_2.2 will be an update ---> Package bind-utils.x86_64 32:9.7.3-8.P3.el6 will be updated ---> Package bind-utils.x86_64 32:9.7.3-8.P3.el6_2.2 will be an update ---> Package cvs.x86_64 0:1.11.23-11.el6_0.1 will be updated ---> Package cvs.x86_64 0:1.11.23-11.el6_2.1 will be an update [...] ---> Package yum.noarch 0:3.2.29-22.0.1.el6 will be updated ---> Package yum.noarch 0:3.2.29-22.0.2.el6_2.2 will be an update ---> Package yum-plugin-security.noarch 0:1.1.30-10.el6 will be updated ---> Package yum-plugin-security.noarch 0:1.1.30-10.0.1.el6 will be an update ---> Package yum-utils.noarch 0:1.1.30-10.el6 will be updated ---> Package yum-utils.noarch 0:1.1.30-10.0.1.el6 will be an update --> Finished Dependency Resolution Dependencies Resolved ===================================================================================== Package Arch Version Repository Size ===================================================================================== Installing: kernel x86_64 2.6.32-220.7.1.el6 ol6_latest 24 M kernel-uek x86_64 2.6.32-300.11.1.el6uek ol6_latest 21 M kernel-uek-devel x86_64 2.6.32-300.11.1.el6uek ol6_latest 6.3 M Updating: at x86_64 3.1.10-43.el6_2.1 ol6_latest 60 k autofs x86_64 1:5.0.5-39.el6_2.1 ol6_latest 470 k bind-libs x86_64 32:9.7.3-8.P3.el6_2.2 ol6_latest 839 k bind-utils x86_64 32:9.7.3-8.P3.el6_2.2 ol6_latest 178 k cvs x86_64 1.11.23-11.el6_2.1 ol6_latest 711 k [...] xulrunner x86_64 10.0.3-1.0.1.el6_2 ol6_latest 12 M yelp x86_64 2.28.1-13.el6_2 ol6_latest 778 k yum noarch 3.2.29-22.0.2.el6_2.2 ol6_latest 987 k yum-plugin-security noarch 1.1.30-10.0.1.el6 ol6_latest 36 k yum-utils noarch 1.1.30-10.0.1.el6 ol6_latest 94 k Transaction Summary ===================================================================================== Install 3 Package(s) Upgrade 96 Package(s) Total download size: 173 M Is this ok [y/N]: y Downloading Packages: (1/99): at-3.1.10-43.el6_2.1.x86_64.rpm | 60 kB 00:00 (2/99): autofs-5.0.5-39.el6_2.1.x86_64.rpm | 470 kB 00:01 (3/99): bind-libs-9.7.3-8.P3.el6_2.2.x86_64.rpm | 839 kB 00:02 (4/99): bind-utils-9.7.3-8.P3.el6_2.2.x86_64.rpm | 178 kB 00:00 [...] (96/99): yelp-2.28.1-13.el6_2.x86_64.rpm | 778 kB 00:02 (97/99): yum-3.2.29-22.0.2.el6_2.2.noarch.rpm | 987 kB 00:03 (98/99): yum-plugin-security-1.1.30-10.0.1.el6.noarch.rpm | 36 kB 00:00 (99/99): yum-utils-1.1.30-10.0.1.el6.noarch.rpm | 94 kB 00:00 ------------------------------------------------------------------------------------- Total 306 kB/s | 173 MB 09:38 warning: rpmts_HdrFromFdno: Header V3 RSA/SHA256 Signature, key ID ec551f03: NOKEY Retrieving key from http://public-yum.oracle.com/RPM-GPG-KEY-oracle-ol6 Importing GPG key 0xEC551F03: Userid: "Oracle OSS group (Open Source Software group) " From : http://public-yum.oracle.com/RPM-GPG-KEY-oracle-ol6 Is this ok [y/N]: y Running rpm_check_debug Running Transaction Test Transaction Test Succeeded Running Transaction Updating : yum-3.2.29-22.0.2.el6_2.2.noarch 1/195 Updating : xorg-x11-server-common-1.10.4-6.el6_2.3.x86_64 2/195 Updating : kernel-uek-headers-2.6.32-300.11.1.el6uek.x86_64 3/195 Updating : 12:dhcp-common-4.1.1-25.P1.el6_2.1.x86_64 4/195 Updating : tzdata-java-2011n-2.el6.noarch 5/195 Updating : tzdata-2011n-2.el6.noarch 6/195 Updating : glibc-common-2.12-1.47.el6_2.9.x86_64 7/195 Updating : glibc-2.12-1.47.el6_2.9.x86_64 8/195 [...] Cleanup : kernel-firmware-2.6.32-220.el6.noarch 191/195 Cleanup : kernel-uek-firmware-2.6.32-300.3.1.el6uek.noarch 192/195 Cleanup : glibc-common-2.12-1.47.el6.x86_64 193/195 Cleanup : glibc-2.12-1.47.el6.x86_64 194/195 Cleanup : tzdata-2011l-4.el6.noarch 195/195 Installed: kernel.x86_64 0:2.6.32-220.7.1.el6 kernel-uek.x86_64 0:2.6.32-300.11.1.el6uek kernel-uek-devel.x86_64 0:2.6.32-300.11.1.el6uek Updated: at.x86_64 0:3.1.10-43.el6_2.1 autofs.x86_64 1:5.0.5-39.el6_2.1 bind-libs.x86_64 32:9.7.3-8.P3.el6_2.2 bind-utils.x86_64 32:9.7.3-8.P3.el6_2.2 cvs.x86_64 0:1.11.23-11.el6_2.1 dhclient.x86_64 12:4.1.1-25.P1.el6_2.1 [...] xorg-x11-server-common.x86_64 0:1.10.4-6.el6_2.3 xulrunner.x86_64 0:10.0.3-1.0.1.el6_2 yelp.x86_64 0:2.28.1-13.el6_2 yum.noarch 0:3.2.29-22.0.2.el6_2.2 yum-plugin-security.noarch 0:1.1.30-10.0.1.el6 yum-utils.noarch 0:1.1.30-10.0.1.el6 Complete! At this point, your system is fully up to date. As the kernel was updated as well, a reboot is the recommended next action. If you want to install the latest release of the Unbreakable Enterprise Kernel Release 2 as well, you need to edit the .repo file and enable the respective yum repository (e.g. "ol6_UEK_latest" for Oracle Linux 6 and "ol5_UEK_latest" for Oracle Linux 5) manually, by setting enabled to "1". The next yum update run will download and install the second release of the Unbreakable Enterprise Kernel, which will be enabled after the next reboot. -Lenz

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• MySQL Syslog Audit Plugin

  - by jonathonc

  This post shows the construction process of the Syslog Audit plugin that was presented at MySQL Connect 2012. It is based on an environment that has the appropriate development tools enabled including gcc,g++ and cmake. It also assumes you have downloaded the MySQL source code (5.5.16 or higher) and have compiled and installed the system into the /usr/local/mysql directory ready for use.  The information provided below is designed to show the different components that make up a plugin, and specifically an audit type plugin, and how it comes together to be used within the MySQL service. The MySQL Reference Manual contains information regarding the plugin API and how it can be used, so please refer there for more detailed information. The code in this post is designed to give the simplest information necessary, so handling every return code, managing race conditions etc is not part of this example code. Let's start by looking at the most basic implementation of our plugin code as seen below: /*    Copyright (c) 2012, Oracle and/or its affiliates. All rights reserved.    Author:  Jonathon Coombes    Licence: GPL    Description: An auditing plugin that logs to syslog and                 can adjust the loglevel via the system variables. */ #include <stdio.h> #include <string.h> #include <mysql/plugin_audit.h> #include <syslog.h> There is a commented header detailing copyright/licencing and meta-data information and then the include headers. The two important include statements for our plugin are the syslog.h plugin, which gives us the structures for syslog, and the plugin_audit.h include which has details regarding the audit specific plugin api. Note that we do not need to include the general plugin header plugin.h, as this is done within the plugin_audit.h file already. To implement our plugin within the current implementation we need to add it into our source code and compile. > cd /usr/local/src/mysql-5.5.28/plugin > mkdir audit_syslog > cd audit_syslog A simple CMakeLists.txt file is created to manage the plugin compilation: MYSQL_ADD_PLUGIN(audit_syslog audit_syslog.cc MODULE_ONLY) Run the cmake  command at the top level of the source and then you can compile the plugin using the 'make' command. This results in a compiled audit_syslog.so library, but currently it is not much use to MySQL as there is no level of api defined to communicate with the MySQL service. Now we need to define the general plugin structure that enables MySQL to recognise the library as a plugin and be able to install/uninstall it and have it show up in the system. The structure is defined in the plugin.h file in the MySQL source code.  /*   Plugin library descriptor */ mysql_declare_plugin(audit_syslog) {   MYSQL_AUDIT_PLUGIN,           /* plugin type                    */   &audit_syslog_descriptor,     /* descriptor handle               */   "audit_syslog",               /* plugin name                     */   "Author Name",                /* author                          */   "Simple Syslog Audit",        /* description                     */   PLUGIN_LICENSE_GPL,           /* licence                         */   audit_syslog_init,            /* init function     */   audit_syslog_deinit,          /* deinit function */   0x0001,                       /* plugin version                  */   NULL,                         /* status variables        */   NULL,                         /* system variables                */   NULL,                         /* no reserves                     */   0,                            /* no flags                        */ } mysql_declare_plugin_end; The general plugin descriptor above is standard for all plugin types in MySQL. The plugin type is defined along with the init/deinit functions and interface methods into the system for sharing information, and various other metadata information. The descriptors have an internally recognised version number so that plugins can be matched against the api on the running server. The other details are usually related to the type-specific methods and structures to implement the plugin. Each plugin has a type-specific descriptor as well which details how the plugin is implemented for the specific purpose of that plugin type. /*   Plugin type-specific descriptor */ static struct st_mysql_audit audit_syslog_descriptor= {   MYSQL_AUDIT_INTERFACE_VERSION,                        /* interface version    */   NULL,                                                 /* release_thd function */   audit_syslog_notify,                                  /* notify function      */   { (unsigned long) MYSQL_AUDIT_GENERAL_CLASSMASK |                     MYSQL_AUDIT_CONNECTION_CLASSMASK }  /* class mask           */ }; In this particular case, the release_thd function has not been defined as it is not required. The important method for auditing is the notify function which is activated when an event occurs on the system. The notify function is designed to activate on an event and the implementation will determine how it is handled. For the audit_syslog plugin, the use of the syslog feature sends all events to the syslog for recording. The class mask allows us to determine what type of events are being seen by the notify function. There are currently two major types of event: 1. General Events: This includes general logging, errors, status and result type events. This is the main one for tracking the queries and operations on the database. 2. Connection Events: This group is based around user logins. It monitors connections and disconnections, but also if somebody changes user while connected. With most audit plugins, the principle behind the plugin is to track changes to the system over time and counters can be an important part of this process. The next step is to define and initialise the counters that are used to track the events in the service. There are 3 counters defined in total for our plugin - the # of general events, the # of connection events and the total number of events.  static volatile int total_number_of_calls; /* Count MYSQL_AUDIT_GENERAL_CLASS event instances */ static volatile int number_of_calls_general; /* Count MYSQL_AUDIT_CONNECTION_CLASS event instances */ static volatile int number_of_calls_connection; The init and deinit functions for the plugin are there to be called when the plugin is activated and when it is terminated. These offer the best option to initialise the counters for our plugin: /*  Initialize the plugin at server start or plugin installation. */ static int audit_syslog_init(void *arg __attribute__((unused))) {     openlog("mysql_audit:",LOG_PID|LOG_PERROR|LOG_CONS,LOG_USER);     total_number_of_calls= 0;     number_of_calls_general= 0;     number_of_calls_connection= 0;     return(0); } The init function does a call to openlog to initialise the syslog functionality. The parameters are the service to log under ("mysql_audit" in this case), the syslog flags and the facility for the logging. Then each of the counters are initialised to zero and a success is returned. If the init function is not defined, it will return success by default. /*  Terminate the plugin at server shutdown or plugin deinstallation. */ static int audit_syslog_deinit(void *arg __attribute__((unused))) {     closelog();     return(0); } The deinit function will simply close our syslog connection and return success. Note that the syslog functionality is part of the glibc libraries and does not require any external factors.  The function names are what we define in the general plugin structure, so these have to match otherwise there will be errors. The next step is to implement the event notifier function that was defined in the type specific descriptor (audit_syslog_descriptor) which is audit_syslog_notify. /* Event notifier function */ static void audit_syslog_notify(MYSQL_THD thd __attribute__((unused)), unsigned int event_class, const void *event) { total_number_of_calls++; if (event_class == MYSQL_AUDIT_GENERAL_CLASS) { const struct mysql_event_general *event_general= (const struct mysql_event_general *) event; number_of_calls_general++; syslog(audit_loglevel,"%lu: User: %s Command: %s Query: %s\n", event_general->general_thread_id, event_general->general_user, event_general->general_command, event_general->general_query ); } else if (event_class == MYSQL_AUDIT_CONNECTION_CLASS) { const struct mysql_event_connection *event_connection= (const struct mysql_event_connection *) event; number_of_calls_connection++; syslog(audit_loglevel,"%lu: User: %s@%s[%s] Event: %d Status: %d\n", event_connection->thread_id, event_connection->user, event_connection->host, event_connection->ip, event_connection->event_subclass, event_connection->status ); } }   In the case of an event, the notifier function is called. The first step is to increment the total number of events that have occurred in our database.The event argument is then cast into the appropriate event structure depending on the class type, of general event or connection event. The event type counters are incremented and details are sent via the syslog() function out to the system log. There are going to be different line formats and information returned since the general events have different data compared to the connection events, even though some of the details overlap, for example, user, thread id, host etc. On compiling the code now, there should be no errors and the resulting audit_syslog.so can be loaded into the server and ready to use. Log into the server and type: mysql> INSTALL PLUGIN audit_syslog SONAME 'audit_syslog.so'; This will install the plugin and will start updating the syslog immediately. Note that the audit plugin attaches to the immediate thread and cannot be uninstalled while that thread is active. This means that you cannot run the UNISTALL command until you log into a different connection (thread) on the server. Once the plugin is loaded, the system log will show output such as the following: Oct  8 15:33:21 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: (null)  Query: INSTALL PLUGIN audit_syslog SONAME 'audit_syslog.so' Oct  8 15:33:21 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: Query  Query: INSTALL PLUGIN audit_syslog SONAME 'audit_syslog.so' Oct  8 15:33:40 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: (null)  Query: show tables Oct  8 15:33:40 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: Query  Query: show tables Oct  8 15:33:43 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: (null)  Query: select * from t1 Oct  8 15:33:43 machine mysql_audit:[8337]: 87: User: root[root] @ localhost []  Command: Query  Query: select * from t1 It appears that two of each event is being shown, but in actuality, these are two separate event types - the result event and the status event. This could be refined further by changing the audit_syslog_notify function to handle the different event sub-types in a different manner.  So far, it seems that the logging is working with events showing up in the syslog output. The issue now is that the counters created earlier to track the number of events by type are not accessible when the plugin is being run. Instead there needs to be a way to expose the plugin specific information to the service and vice versa. This could be done via the information_schema plugin api, but for something as simple as counters, the obvious choice is the system status variables. This is done using the standard structure and the declaration: /*  Plugin status variables for SHOW STATUS */ static struct st_mysql_show_var audit_syslog_status[]= {   { "Audit_syslog_total_calls",     (char *) &total_number_of_calls,     SHOW_INT },   { "Audit_syslog_general_events",     (char *) &number_of_calls_general,     SHOW_INT },   { "Audit_syslog_connection_events",     (char *) &number_of_calls_connection,     SHOW_INT },   { 0, 0, SHOW_INT } };   The structure is simply the name that will be displaying in the mysql service, the address of the associated variables, and the data type being used for the counter. It is finished with a blank structure to show that there are no more variables. Remember that status variables may have the same name for variables from other plugin, so it is considered appropriate to add the plugin name at the start of the status variable name to avoid confusion. Looking at the status variables in the mysql client shows something like the following: mysql> show global status like "audit%"; +--------------------------------+-------+ | Variable_name                  | Value | +--------------------------------+-------+ | Audit_syslog_connection_events | 1     | | Audit_syslog_general_events    | 2     | | Audit_syslog_total_calls       | 3     | +--------------------------------+-------+ 3 rows in set (0.00 sec) The final connectivity piece for the plugin is to allow the interactive change of the logging level between the plugin and the system. This requires the ability to send changes via the mysql service through to the plugin. This is done using the system variables interface and defining a single variable to keep track of the active logging level for the facility. /* Plugin system variables for SHOW VARIABLES */ static MYSQL_SYSVAR_STR(loglevel, audit_loglevel,                         PLUGIN_VAR_RQCMDARG,                         "User can specify the log level for auditing",                         audit_loglevel_check, audit_loglevel_update, "LOG_NOTICE"); static struct st_mysql_sys_var* audit_syslog_sysvars[] = {     MYSQL_SYSVAR(loglevel),     NULL }; So now the system variable 'loglevel' is defined for the plugin and associated to the global variable 'audit_loglevel'. The check or validation function is defined to make sure that no garbage values are attempted in the update of the variable. The update function is used to save the new value to the variable. Note that the audit_syslog_sysvars structure is defined in the general plugin descriptor to associate the link between the plugin and the system and how much they interact. Next comes the implementation of the validation function and the update function for the system variable. It is worth noting that if you have a simple numeric such as integers for the variable types, the validate function is often not required as MySQL will handle the automatic check and validation of simple types. /* longest valid value */ #define MAX_LOGLEVEL_SIZE 100 /* hold the valid values */ static const char *possible_modes[]= { "LOG_ERROR", "LOG_WARNING", "LOG_NOTICE", NULL };  static int audit_loglevel_check(     THD*                        thd,    /*!< in: thread handle */     struct st_mysql_sys_var*    var,    /*!< in: pointer to system                                         variable */     void*                       save,   /*!< out: immediate result                                         for update function */     struct st_mysql_value*      value)  /*!< in: incoming string */ {     char buff[MAX_LOGLEVEL_SIZE];     const char *str;     const char **found;     int length;     length= sizeof(buff);     if (!(str= value->val_str(value, buff, &length)))         return 1;     /*         We need to return a pointer to a locally allocated value in "save".         Here we pick to search for the supplied value in an global array of         constant strings and return a pointer to one of them.         The other possiblity is to use the thd_alloc() function to allocate         a thread local buffer instead of the global constants.     */     for (found= possible_modes; *found; found++)     {         if (!strcmp(*found, str))         {             *(const char**)save= *found;             return 0;         }     }     return 1; } The validation function is simply to take the value being passed in via the SET GLOBAL VARIABLE command and check if it is one of the pre-defined values allowed  in our possible_values array. If it is found to be valid, then the value is assigned to the save variable ready for passing through to the update function. static void audit_loglevel_update(     THD*                        thd,        /*!< in: thread handle */     struct st_mysql_sys_var*    var,        /*!< in: system variable                                             being altered */     void*                       var_ptr,    /*!< out: pointer to                                             dynamic variable */     const void*                 save)       /*!< in: pointer to                                             temporary storage */ {     /* assign the new value so that the server can read it */     *(char **) var_ptr= *(char **) save;     /* assign the new value to the internal variable */     audit_loglevel= *(char **) save; } Since all the validation has been done already, the update function is quite simple for this plugin. The first part is to update the system variable pointer so that the server can read the value. The second part is to update our own global plugin variable for tracking the value. Notice that the save variable is passed in as a void type to allow handling of various data types, so it must be cast to the appropriate data type when assigning it to the variables. Looking at how the latest changes affect the usage of the plugin and the interaction within the server shows: mysql> show global variables like "audit%"; +-----------------------+------------+ | Variable_name         | Value      | +-----------------------+------------+ | audit_syslog_loglevel | LOG_NOTICE | +-----------------------+------------+ 1 row in set (0.00 sec) mysql> set global audit_syslog_loglevel="LOG_ERROR"; Query OK, 0 rows affected (0.00 sec) mysql> show global status like "audit%"; +--------------------------------+-------+ | Variable_name                  | Value | +--------------------------------+-------+ | Audit_syslog_connection_events | 1     | | Audit_syslog_general_events    | 11    | | Audit_syslog_total_calls       | 12    | +--------------------------------+-------+ 3 rows in set (0.00 sec) mysql> show global variables like "audit%"; +-----------------------+-----------+ | Variable_name         | Value     | +-----------------------+-----------+ | audit_syslog_loglevel | LOG_ERROR | +-----------------------+-----------+ 1 row in set (0.00 sec)   So now we have a plugin that will audit the events on the system and log the details to the system log. It allows for interaction to see the number of different events within the server details and provides a mechanism to change the logging level interactively via the standard system methods of the SET command. A more complex auditing plugin may have more detailed code, but each of the above areas is what will be involved and simply expanded on to add more functionality. With the above skeleton code, it is now possible to create your own audit plugins to implement your own auditing requirements. If, however, you are not of the coding persuasion, then you could always consider the option of the MySQL Enterprise Audit plugin that is available to purchase.

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• Regression testing with Selenium GRID

  - by Ben Adderson

  A lot of software teams out there are tasked with supporting and maintaining systems that have grown organically over time, and the web team here at Red Gate is no exception. We're about to embark on our first significant refactoring endeavour for some time, and as such its clearly paramount that the code be tested thoroughly for regressions. Unfortunately we currently find ourselves with a codebase that isn't very testable - the three layers (database, business logic and UI) are currently tightly coupled. This leaves us with the unfortunate problem that, in order to confidently refactor the code, we need unit tests. But in order to write unit tests, we need to refactor the code :S To try and ease the initial pain of decoupling these layers, I've been looking into the idea of using UI automation to provide a sort of system-level regression test suite. The idea being that these tests can help us identify regressions whilst we work towards a more testable codebase, at which point the more traditional combination of unit and integration tests can take over. Ending up with a strong battery of UI tests is also a nice bonus :) Following on from my previous posts (here, here and here) I knew I wanted to use Selenium. I also figured that this would be a good excuse to put my xUnit [Browser] attribute to good use. Pretty quickly, I had a raft of tests that looked like the following (this particular example uses Reflector Pro). In a nut shell the test traverses our shopping cart and, for a particular combination of number of users and months of support, checks that the price calculations all come up with the correct values. [BrowserTheory] [Browser(Browsers.Firefox3_6, "http://www.red-gate.com")] public void Purchase1UserLicenceNoSupport(SeleniumProvider seleniumProvider) {     //Arrange     _browser = seleniumProvider.GetBrowser();     _browser.Open("http://www.red-gate.com/dynamic/shoppingCart/ProductOption.aspx?Product=ReflectorPro");                  //Act     _browser = ShoppingCartHelpers.TraverseShoppingCart(_browser, 1, 0, ".NET Reflector Pro");     //Assert     var priceResult = PriceHelpers.GetNewPurchasePrice(db, "ReflectorPro", 1, 0, Currencies.Euros);         Assert.Equal(priceResult.Price, _browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl01_Price"));     Assert.Equal(priceResult.Tax, _browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl02_Tax"));     Assert.Equal(priceResult.Total, _browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl02_Total")); } These tests are pretty concise, with much of the common code in the TraverseShoppingCart() and GetNewPurchasePrice() methods. The (inevitable) problem arose when it came to execute these tests en masse. Selenium is a very slick tool, but it can't mask the fact that UI automation is very slow. To give you an idea, the set of cases that covers all of our products, for all combinations of users and support, came to 372 tests (for now only considering purchases in dollars). In the world of automated integration tests, that's a very manageable number. For unit tests, it's a trifle. However for UI automation, those 372 tests were taking just over two hours to run. Two hours may not sound like a lot, but those cases only cover one of the three currencies we deal with, and only one of the many different ways our systems can be asked to calculate a price. It was already pretty clear at this point that in order for this approach to be viable, I was going to have to find a way to speed things up. Up to this point I had been using Selenium Remote Control to automate Firefox, as this was the approach I had used previously and it had worked well. Fortunately,  the guys at SeleniumHQ also maintain a tool for executing multiple Selenium RC tests in parallel: Selenium Grid. Selenium Grid uses a central 'hub' to handle allocation of Selenium tests to individual RCs. The Remote Controls simply register themselves with the hub when they start, and then wait to be assigned work. The (for me) really clever part is that, as far as the client driver library is concerned, the grid hub looks exactly the same as a vanilla remote control. To create a new browser session against Selenium RC, the following C# code suffices: new DefaultSelenium("localhost", 4444, "*firefox", "http://www.red-gate.com"); This assumes that the RC is running on the local machine, and is listening on port 4444 (the default). Assuming the hub is running on your local machine, then to create a browser session in Selenium Grid, via the hub rather than directly against the control, the code is exactly the same! Behind the scenes, the hub will take this request and hand it off to one of the registered RCs that provides the "*firefox" execution environment. It will then pass all communications back and forth between the test runner and the remote control transparently. This makes running existing RC tests on a Selenium Grid a piece of cake, as the developers intended. For a more detailed description of exactly how Selenium Grid works, see this page. Once I had a test environment capable of running multiple tests in parallel, I needed a test runner capable of doing the same. Unfortunately, this does not currently exist for xUnit (boo!). MbUnit on the other hand, has the concept of concurrent execution baked right into the framework. So after swapping out my assembly references, and fixing up the resulting mismatches in assertions, my example test now looks like this: [Test] public void Purchase1UserLicenceNoSupport() {    //Arrange    ISelenium browser = BrowserHelpers.GetBrowser();    var db = DbHelpers.GetWebsiteDBDataContext();    browser.Start();    browser.Open("http://www.red-gate.com/dynamic/shoppingCart/ProductOption.aspx?Product=ReflectorPro");                 //Act     browser = ShoppingCartHelpers.TraverseShoppingCart(browser, 1, 0, ".NET Reflector Pro");    var priceResult = PriceHelpers.GetNewPurchasePrice(db, "ReflectorPro", 1, 0, Currencies.Euros);    //Assert     Assert.AreEqual(priceResult.Price, browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl01_Price"));     Assert.AreEqual(priceResult.Tax, browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl02_Tax"));     Assert.AreEqual(priceResult.Total, browser.GetText("ctl00_content_InvoiceShoppingItemRepeater_ctl02_Total")); } This is pretty much the same as the xUnit version. The exceptions are that the attributes have changed,  the //Arrange phase now has to handle setting up the ISelenium object, as the attribute that previously did this has gone away, and the test now sets up its own database connection. Previously I was using a shared database connection, but this approach becomes more complicated when tests are being executed concurrently. To avoid complexity each test has its own connection, which it is responsible for closing. For the sake of readability, I snipped out the code that closes the browser session and the db connection at the end of the test. With all that done, there was only one more step required before the tests would execute concurrently. It is necessary to tell the test runner which tests are eligible to run in parallel, via the [Parallelizable] attribute. This can be done at the test, fixture or assembly level. Since I wanted to run all tests concurrently, I marked mine at the assembly level in the AssemblyInfo.cs using the following: [assembly: DegreeOfParallelism(3)] [assembly: Parallelizable(TestScope.All)] The second attribute marks all tests in the assembly as [Parallelizable], whilst the first tells the test runner how many concurrent threads to use when executing the tests. I set mine to three since I was using 3 RCs in separate VMs. With everything now in place, I fired up the Icarus* test runner that comes with MbUnit. Executing my 372 tests three at a time instead of one at a time reduced the running time from 2 hours 10 minutes, to 55 minutes, that's an improvement of about 58%! I'd like to have seen an improvement of 66%, but I can understand that either inefficiencies in the hub code, my test environment or the test runner code (or some combination of all three most likely) contributes to a slightly diminished improvement. That said, I'd love to hear about any experience you have in upping this efficiency. Ultimately though, it was a saving that was most definitely worth having. It makes regression testing via UI automation a far more plausible prospect. The other obvious point to make is that this approach scales far better than executing tests serially. So if ever we need to improve performance, we just register additional RC's with the hub, and up the DegreeOfParallelism. *This was just my personal preference for a GUI runner. The MbUnit/Gallio installer also provides a command line runner, a TestDriven.net runner, and a Resharper 4.5 runner. For now at least, Resharper 5 isn't supported.

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• Base de Datos Oracle, su mejor opción para reducir costos de IT

  - by Ivan Hassig

  Por Victoria Cadavid Sr. Sales Cosultant Oracle Direct Uno de los principales desafíos en la administración de centros de datos es la reducción de costos de operación. A medida que las compañías crecen y los proveedores de tecnología ofrecen soluciones cada vez más robustas, conservar el equilibrio entre desempeño, soporte al negocio y gestión del Costo Total de Propiedad es un desafío cada vez mayor para los Gerentes de Tecnología y para los Administradores de Centros de Datos. Las estrategias más comunes para conseguir reducción en los costos de administración de Centros de Datos y en la gestión de Tecnología de una organización en general, se enfocan en la mejora del desempeño de las aplicaciones, reducción del costo de administración y adquisición de hardware, reducción de los costos de almacenamiento, aumento de la productividad en la administración de las Bases de Datos y mejora en la atención de requerimientos y prestación de servicios de mesa de ayuda, sin embargo, las estrategias de reducción de costos deben contemplar también la reducción de costos asociados a pérdida y robo de información, cumplimiento regulatorio, generación de valor y continuidad del negocio, que comúnmente se conciben como iniciativas aisladas que no siempre se adelantan con el ánimo de apoyar la reducción de costos. Una iniciativa integral de reducción de costos de TI, debe contemplar cada uno de los factores que  generan costo y pueden ser optimizados. En este artículo queremos abordar la reducción de costos de tecnología a partir de la adopción del que según los expertos es el motor de Base de Datos # del mercado.Durante años, la base de datos Oracle ha sido reconocida por su velocidad, confiabilidad, seguridad y capacidad para soportar cargas de datos tanto de aplicaciones altamente transaccionales, como de Bodegas de datos e incluso análisis de Big Data , ofreciendo alto desempeño y facilidades de administración, sin embrago, cuando pensamos en proyectos de reducción de costos de IT, además de la capacidad para soportar aplicaciones (incluso aplicaciones altamente transaccionales) con alto desempeño, pensamos en procesos de automatización, optimización de recursos, consolidación, virtualización e incluso alternativas más cómodas de licenciamiento. La Base de Datos Oracle está diseñada para proveer todas las capacidades que un área de tecnología necesita para reducir costos, adaptándose a los diferentes escenarios de negocio y a las capacidades y características de cada organización.Es así, como además del motor de Base de Datos, Oracle ofrece una serie de soluciones para optimizar la administración de la información a través de mecanismos de optimización del uso del storage, continuidad del Negocio, consolidación de infraestructura, seguridad y administración automática, que propenden por un mejor uso de los recursos de tecnología, ofrecen opciones avanzadas de configuración y direccionan la reducción de los tiempos de las tareas operativas más comunes. Una de las opciones de la base de datos que se pueden provechar para reducir costos de hardware es Oracle Real Application Clusters. Esta solución de clustering permite que varios servidores (incluso servidores de bajo costo) trabajen en conjunto para soportar Grids o Nubes Privadas de Bases de Datos, proporcionando los beneficios de la consolidación de infraestructura, los esquemas de alta disponibilidad, rápido desempeño y escalabilidad por demanda, haciendo que el aprovisionamiento, el mantenimiento de las bases de datos y la adición de nuevos nodos se lleve e cabo de una forma más rápida y con menos riesgo, además de apalancar las inversiones en servidores de menor costo. Otra de las soluciones que promueven la reducción de costos de Tecnología es Oracle In-Memory Database Cache que permite almacenar y procesar datos en la memoria de las aplicaciones, permitiendo el máximo aprovechamiento de los recursos de procesamiento de la capa media, lo que cobra mucho valor en escenarios de alta transaccionalidad. De este modo se saca el mayor provecho de los recursos de procesamiento evitando crecimiento innecesario en recursos de hardware. Otra de las formas de evitar inversiones innecesarias en hardware, aprovechando los recursos existentes, incluso en escenarios de alto crecimiento de los volúmenes de información es la compresión de los datos. Oracle Advanced Compression permite comprimir hasta 4 veces los diferentes tipos de datos, mejorando la capacidad de almacenamiento, sin comprometer el desempeño de las aplicaciones. Desde el lado del almacenamiento también se pueden conseguir reducciones importantes de los costos de IT. En este escenario, la tecnología propia de la base de Datos Oracle ofrece capacidades de Administración Automática del Almacenamiento que no solo permiten una distribución óptima de los datos en los discos físicos para garantizar el máximo desempeño, sino que facilitan el aprovisionamiento y la remoción de discos defectuosos y ofrecen balanceo y mirroring, garantizando el uso máximo de cada uno de los dispositivos y la disponibilidad de los datos. Otra de las soluciones que facilitan la administración del almacenamiento es Oracle Partitioning, una opción de la Base de Datos que permite dividir grandes tablas en estructuras más pequeñas. Esta aproximación facilita la administración del ciclo de vida de la información y permite por ejemplo, separar los datos históricos (que generalmente se convierten en información de solo lectura y no tienen un alto volumen de consulta) y enviarlos a un almacenamiento de bajo costos, conservando la data activa en dispositivos de almacenamiento más ágiles. Adicionalmente, Oracle Partitioning facilita la administración de las bases de datos que tienen un gran volumen de registros y mejora el desempeño de la base de datos gracias a la posibilidad de optimizar las consultas haciendo uso únicamente de las particiones relevantes de una tabla o índice en el proceso de búsqueda. Otros factores adicionales, que pueden generar costos innecesarios a los departamentos de Tecnología son: La pérdida, corrupción o robo de datos y la falta de disponibilidad de las aplicaciones para dar soporte al negocio. Para evitar este tipo de situaciones que pueden acarrear multas y pérdida de negocios y de dinero, Oracle ofrece soluciones que permiten proteger y auditar la base de datos, recuperar la información en caso de corrupción o ejecución de acciones que comprometan la integridad de la información y soluciones que permitan garantizar que la información de las aplicaciones tenga una disponibilidad de 7x24. Ya hablamos de los beneficios de Oracle RAC, para facilitar los procesos de Consolidación y mejorar el desempeño de las aplicaciones, sin embrago esta solución, es sumamente útil en escenarios dónde las organizaciones de quieren garantizar una alta disponibilidad de la información, ante fallo de los servidores o en eventos de desconexión planeada para realizar labores de mantenimiento. Además de Oracle RAC, existen soluciones como Oracle Data Guard y Active Data Guard que permiten replicar de forma automática las bases de datos hacia un centro de datos de contingencia, permitiendo una recuperación inmediata ante eventos que deshabiliten por completo un centro de datos. Además de lo anterior, Active Data Guard, permite aprovechar la base de datos de contingencia para realizar labores de consulta, mejorando el desempeño de las aplicaciones. Desde el punto de vista de mejora en la seguridad, Oracle cuenta con soluciones como Advanced security que permite encriptar los datos y los canales a través de los cueles se comparte la información, Total Recall, que permite visualizar los cambios realizados a la base de datos en un momento determinado del tiempo, para evitar pérdida y corrupción de datos, Database Vault que permite restringir el acceso de los usuarios privilegiados a información confidencial, Audit Vault, que permite verificar quién hizo qué y cuándo dentro de las bases de datos de una organización y Oracle Data Masking que permite enmascarar los datos para garantizar la protección de la información sensible y el cumplimiento de las políticas y normas relacionadas con protección de información confidencial, por ejemplo, mientras las aplicaciones pasan del ambiente de desarrollo al ambiente de producción. Como mencionamos en un comienzo, las iniciativas de reducción de costos de tecnología deben apalancarse en estrategias que contemplen los diferentes factores que puedan generar sobre costos, los factores de riesgo que puedan acarrear costos no previsto, el aprovechamiento de los recursos actuales, para evitar inversiones innecesarias y los factores de optimización que permitan el máximo aprovechamiento de las inversiones actuales. Como vimos, todas estas iniciativas pueden ser abordadas haciendo uso de la tecnología de Oracle a nivel de Base de Datos, lo más importante es detectar los puntos críticos a nivel de riesgo, diagnosticar las proporción en que están siendo aprovechados los recursos actuales y definir las prioridades de la organización y del área de IT, para así dar inicio a todas aquellas iniciativas que de forma gradual, van a evitar sobrecostos e inversiones innecesarias, proporcionando un mayor apoyo al negocio y un impacto significativo en la productividad de la organización. Más información http://www.oracle.com/lad/products/database/index.html?ssSourceSiteId=otnes 1Fuente: Market Share: All Software Markets, Worldwide 2011 by Colleen Graham, Joanne Correia, David Coyle, Fabrizio Biscotti, Matthew Cheung, Ruggero Contu, Yanna Dharmasthira, Tom Eid, Chad Eschinger, Bianca Granetto, Hai Hong Swinehart, Sharon Mertz, Chris Pang, Asheesh Raina, Dan Sommer, Bhavish Sood, Marianne D'Aquila, Laurie Wurster and Jie Zhang. - March 29, 2012 2Big Data: Información recopilada desde fuentes no tradicionales como blogs, redes sociales, email, sensores, fotografías, grabaciones en video, etc. que normalmente se encuentran de forma no estructurada y en un gran volumen

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• How To - Guide to Importing Data from a MySQL Database to Excel using MySQL for Excel

  - by Javier Treviño

  Fetching data from a database to then get it into an Excel spreadsheet to do analysis, reporting, transforming, sharing, etc. is a very common task among users. There are several ways to extract data from a MySQL database to then import it to Excel; for example you can use the MySQL Connector/ODBC to configure an ODBC connection to a MySQL database, then in Excel use the Data Connection Wizard to select the database and table from which you want to extract data from, then specify what worksheet you want to put the data into.  Another way is to somehow dump a comma delimited text file with the data from a MySQL table (using the MySQL Command Line Client, MySQL Workbench, etc.) to then in Excel open the file using the Text Import Wizard to attempt to correctly split the data in columns. These methods are fine, but involve some degree of technical knowledge to make the magic happen and involve repeating several steps each time data needs to be imported from a MySQL table to an Excel spreadsheet. So, can this be done in an easier and faster way? With MySQL for Excel you can. MySQL for Excel features an Import MySQL Data action where you can import data from a MySQL Table, View or Stored Procedure literally with a few clicks within Excel.  Following is a quick guide describing how to import data using MySQL for Excel. This guide assumes you already have a working MySQL Server instance, Microsoft Office Excel 2007 or 2010 and MySQL for Excel installed. 1. Opening MySQL for Excel Being an Excel Add-In, MySQL for Excel is opened from within Excel, so to use it open Excel, go to the Data tab located in the Ribbon and click MySQL for Excel at the far right of the Ribbon. 2. Creating a MySQL Connection (may be optional) If you have MySQL Workbench installed you will automatically see the same connections that you can see in MySQL Workbench, so you can use any of those and there may be no need to create a new connection. If you want to create a new connection (which normally you will do only once), in the Welcome Panel click New Connection, which opens the Setup New Connection dialog. Here you only need to give your new connection a distinctive Connection Name, specify the Hostname (or IP address) where the MySQL Server instance is running on (if different than localhost), the Port to connect to and the Username for the login. If you wish to test if your setup is good to go, click Test Connection and an information dialog will pop-up stating if the connection is successful or errors were found. 3.Opening a connection to a MySQL Server To open a pre-configured connection to a MySQL Server you just need to double-click it, so the Connection Password dialog is displayed where you enter the password for the login. 4. Selecting a MySQL Schema After opening a connection to a MySQL Server, the Schema Selection Panel is shown, where you can select the Schema that contains the Tables, Views and Stored Procedures you want to work with. To do so, you just need to either double-click the desired Schema or select it and click Next >. 5. Importing data… All previous steps were really the basic minimum needed to drill-down to the DB Object Selection Panel  where you can see the Database Objects (grouped by type: Tables, Views and Procedures in that order) that you want to perform actions against; in the case of this guide, the action of importing data from them. a. From a MySQL Table To import from a Table you just need to select it from the list of Database Objects’ Tables group, after selecting it you will note actions below the list become available; then click Import MySQL Data. The Import Data dialog is displayed; you can see some basic information here like the name of the Excel worksheet the data will be imported to (in the window title), the Table Name, the total Row Count and a 10 row preview of the data meant for the user to see the columns that the table contains and to provide a way to select which columns to import. The Import Data dialog is designed with defaults in place so all data is imported (all rows and all columns) by just clicking Import; this is important to minimize the number of clicks needed to get the job done. After the import is performed you will have the data in the Excel worksheet formatted automatically. If you need to override the defaults in the Import Data dialog to change the columns selected for import or to change the number of imported rows you can easily do so before clicking Import. In the screenshot below the defaults are overridden to import only the first 3 columns and rows 10 – 60 (Limit to 50 Rows and Start with Row 10). If the number of rows to be imported exceeds the maximum number of rows Excel can hold in its worksheet, a warning will be displayed in the dialog, meaning the imported number of rows will be limited by that maximum number (65,535 rows if the worksheet is in Compatibility Mode).  In the screenshot below you can see the Table contains 80,559 rows, but only 65,534 rows will be imported since the first row is used for the column names if the Include Column Names as Headers checkbox is checked. b. From a MySQL View Similar to the way of importing from a Table, to import from a View you just need to select it from the list of Database Objects’ Views group, then click Import MySQL Data. The Import Data dialog is displayed; identically to the way everything looks when importing from a table, the dialog displays the View Name, the total Row Count and the data preview grid. Since Views are really a filtered way to display data from Tables, it is actually as if we are extracting data from a Table; so the Import Data dialog is actually identical for those 2 Database Objects. After the import is performed, the data in the Excel spreadsheet looks like the following screenshot. Note that you can override the defaults in the Import Data dialog in the same way described above for importing data from Tables. Also the Compatibility Mode warning will be displayed if data exceeds the maximum number of rows explained before. c. From a MySQL Procedure Too import from a Procedure you just need to select it from the list of Database Objects’ Procedures group (note you can see Procedures here but not Functions since these return a single value, so by design they are filtered out). After the selection is made, click Import MySQL Data. The Import Data dialog is displayed, but this time you can see it looks different to the one used for Tables and Views.  Given the nature of Store Procedures, they require first that values are supplied for its Parameters and also Procedures can return multiple Result Sets; so the Import Data dialog shows the Procedure Name and the Procedure Parameters in a grid where their values are input. After you supply the Parameter Values click Call. After calling the Procedure, the Result Sets returned by it are displayed at the bottom of the dialog; output parameters and the return value of the Procedure are appended as the last Result Set of the group. You can see each Result Set is displayed as a tab so you can see a preview of the returned data.  You can specify if you want to import the Selected Result Set (default), All Result Sets – Arranged Horizontally or All Result Sets – Arranged Vertically using the Import drop-down list; then click Import. After the import is performed, the data in the Excel spreadsheet looks like the following screenshot.  Note in this example all Result Sets were imported and arranged vertically. As you can see using MySQL for Excel importing data from a MySQL database becomes an easy task that requires very little technical knowledge, so it can be done by any type of user. Hope you enjoyed this guide! Remember that your feedback is very important for us, so drop us a message: MySQL on Windows (this) Blog - https://blogs.oracle.com/MySqlOnWindows/ Forum - http://forums.mysql.com/list.php?172 Facebook - http://www.facebook.com/mysql Cheers!

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• Hard drive mounted at / , duplicate mounted hard drive after using MountManager

  - by HellHarvest

  possible duplicate post I'm running 12.04 64bit. My system is a dual boot for both Ubuntu and Windows7. Both operating systems are sharing the drive named "Elements". My volume named "Elements" is a 1TB SATA NTFS hard drive that shows up twice in the side bar in nautilus. One of the icons is functional and even has the convenient "eject" icon next to it. Below is a picture of the left menu in Nautilus, with System Monitor-File Systems tab open on top of it. Can someone advise me about how to get rid of this extra icon? I think the problem is much more deep-rooted than just a GUI glitch on Nautilus' part. The other icon does nothing but spit out the following error when I click on it (image below). This only happened AFTER I tried using Mount Manager to automate mounting the drive at start up. I've already uninstalled Mount Manager, and restarted, but the problem didn't go away. The hard drive does mount automatically now, so I guess that's cool. But now, every time I boot up now and open Nautilus, BOTH of these icons appear, one of which is fictitious and useless. According to the image above and the outputs of several other commands, it appears to be mounted at / In which case, no matter where I am in Nautilus when I try to click on that icon, of course it will tell me that that drive is in use by another program... Nautilus. I'm afraid of trying to unmount this hard drive (sdb6) because of where it appears to be mounted. I'm kind of a noob, and I have this gut feeling that tells me trying to unmount a drive at / will destroy my entire file system. This fear was further strengthened by the output of "$ fsck" at the very bottom of this post. Error immediately below when that 2nd "Elements" hard drive is clicked in Nautilus: Unable to mount Elements Mount is denied because the NTFS volume is already exclusively opened. The volume may be already mounted, or another software may use it which could be identified for example by the help of the 'fuser' command. It's odd to me that that error message above claims that it's an NTFS volume when everything else tell me that it's an ext4 volume. The actual hard drive "Elements" is in fact an NTFS volume. Here's the output of a few commands and configuration files that may be of interest: $ fuser -a / /: 2120r 2159rc 2160rc 2172r 2178rc 2180rc 2188r 2191rc 2200rc 2203rc 2205rc 2206r 2211r 2212r 2214r 2220r 2228r 2234rc 2246rc 2249rc 2254rc 2260rc 2261r 2262r 2277rc 2287rc 2291rc 2311rc 2313rc 2332rc 2334rc 2339rc 2343rc 2344rc 2352rc 2372rc 2389rc 2422r 2490r 2496rc 2501rc 2566r 2573rc 2581rc 2589rc 2592r 2603r 2611rc 2613rc 2615rc 2678rc 2927r 2981r 3104rc 4156rc 4196rc 4206rc 4213rc 4240rc 4297rc 5032rc 7609r 7613r 7648r 9593rc 18829r 18833r 19776r $ sudo df -h Filesystem Size Used Avail Use% Mounted on /dev/sdb6 496G 366G 106G 78% / udev 2.0G 4.0K 2.0G 1% /dev tmpfs 791M 1.5M 790M 1% /run none 5.0M 0 5.0M 0% /run/lock none 2.0G 672K 2.0G 1% /run/shm /dev/sda1 932G 312G 620G 34% /media/Elements /home/solderblob/.Private 496G 366G 106G 78% /home/solderblob /dev/sdb2 188G 100G 88G 54% /media/A2B24EACB24E852F /dev/sdb1 100M 25M 76M 25% /media/System Reserved $ sudo fdisk -l Disk /dev/sda: 1000.2 GB, 1000204886016 bytes 255 heads, 63 sectors/track, 121601 cylinders, total 1953525168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x00093cab Device Boot Start End Blocks Id System /dev/sda1 2048 1953519615 976758784 7 HPFS/NTFS/exFAT Disk /dev/sdb: 750.2 GB, 750156374016 bytes 255 heads, 63 sectors/track, 91201 cylinders, total 1465149168 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0x000e8d9b Device Boot Start End Blocks Id System /dev/sdb1 * 2048 206847 102400 7 HPFS/NTFS/exFAT /dev/sdb2 206848 392378768 196085960+ 7 HPFS/NTFS/exFAT /dev/sdb3 392380414 1465147391 536383489 5 Extended /dev/sdb5 1456762880 1465147391 4192256 82 Linux swap / Solaris /dev/sdb6 392380416 1448374271 527996928 83 Linux /dev/sdb7 1448376320 1456758783 4191232 82 Linux swap / Solaris Partition table entries are not in disk order $ cat /etc/fstab # <file system> <mount point> <type> <options> <dump> <pass> UUID=77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e / ext4 defaults 0 1 UUID=F6549CC4549C88CF /media/Elements ntfs-3g users 0 0 $ sudo blkid /dev/sda1: LABEL="Elements" UUID="F6549CC4549C88CF" TYPE="ntfs" /dev/sdb1: LABEL="System Reserved" UUID="5CDE130FDE12E156" TYPE="ntfs" /dev/sdb2: UUID="A2B24EACB24E852F" TYPE="ntfs" /dev/sdb6: UUID="77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e" TYPE="ext4" $ sudo blkid -c /dev/null (appears to be exactly the same as above) /dev/sda1: LABEL="Elements" UUID="F6549CC4549C88CF" TYPE="ntfs" /dev/sdb1: LABEL="System Reserved" UUID="5CDE130FDE12E156" TYPE="ntfs" /dev/sdb2: UUID="A2B24EACB24E852F" TYPE="ntfs" /dev/sdb6: UUID="77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e" TYPE="ext4" $ mount /dev/sdb6 on / type ext4 (rw) proc on /proc type proc (rw,noexec,nosuid,nodev) sysfs on /sys type sysfs (rw,noexec,nosuid,nodev) none on /sys/fs/fuse/connections type fusectl (rw) none on /sys/kernel/debug type debugfs (rw) none on /sys/kernel/security type securityfs (rw) udev on /dev type devtmpfs (rw,mode=0755) devpts on /dev/pts type devpts (rw,noexec,nosuid,gid=5,mode=0620) tmpfs on /run type tmpfs (rw,noexec,nosuid,size=10%,mode=0755) none on /run/lock type tmpfs (rw,noexec,nosuid,nodev,size=5242880) none on /run/shm type tmpfs (rw,nosuid,nodev) /dev/sda1 on /media/Elements type fuseblk (rw,noexec,nosuid,nodev,allow_other,blksize=4096) binfmt_misc on /proc/sys/fs/binfmt_misc type binfmt_misc (rw,noexec,nosuid,nodev) /home/solderblob/.Private on /home/solderblob type ecryptfs (ecryptfs_check_dev_ruid,ecryptfs_cipher=aes,ecryptfs_key_bytes=16,ecryptfs_unlink_sigs,ecryptfs_sig=76a47b0175afa48d,ecryptfs_fnek_sig=391b2d8b155215f7) gvfs-fuse-daemon on /home/solderblob/.gvfs type fuse.gvfs-fuse-daemon (rw,nosuid,nodev,user=solderblob) /dev/sdb2 on /media/A2B24EACB24E852F type fuseblk (rw,nosuid,nodev,allow_other,default_permissions,blksize=4096) /dev/sdb1 on /media/System Reserved type fuseblk (rw,nosuid,nodev,allow_other,default_permissions,blksize=4096) $ ls -a . A2B24EACB24E852F Ubuntu 12.04.1 LTS amd64 .. Elements System Reserved $ cat /proc/mounts rootfs / rootfs rw 0 0 sysfs /sys sysfs rw,nosuid,nodev,noexec,relatime 0 0 proc /proc proc rw,nosuid,nodev,noexec,relatime 0 0 udev /dev devtmpfs rw,relatime,size=2013000k,nr_inodes=503250,mode=755 0 0 devpts /dev/pts devpts rw,nosuid,noexec,relatime,gid=5,mode=620,ptmxmode=000 0 0 tmpfs /run tmpfs rw,nosuid,relatime,size=809872k,mode=755 0 0 /dev/disk/by-uuid/77039a2a-83d4-47a1-8a8c-a2ec4e4dfd0e / ext4 rw,relatime,user_xattr,acl,barrier=1,data=ordered 0 0 none /sys/fs/fuse/connections fusectl rw,relatime 0 0 none /sys/kernel/debug debugfs rw,relatime 0 0 none /sys/kernel/security securityfs rw,relatime 0 0 none /run/lock tmpfs rw,nosuid,nodev,noexec,relatime,size=5120k 0 0 none /run/shm tmpfs rw,nosuid,nodev,relatime 0 0 /dev/sda1 /media/Elements fuseblk rw,nosuid,nodev,noexec,relatime,user_id=0,group_id=0,allow_other,blksize=4096 0 0 binfmt_misc /proc/sys/fs/binfmt_misc binfmt_misc rw,nosuid,nodev,noexec,relatime 0 0 /home/solderblob/.Private /home/solderblob ecryptfs rw,relatime,ecryptfs_fnek_sig=391b2d8b155215f7,ecryptfs_sig=76a47b0175afa48d,ecryptfs_cipher=aes,ecryptfs_key_bytes=16,ecryptfs_unlink_sigs 0 0 gvfs-fuse-daemon /home/solderblob/.gvfs fuse.gvfs-fuse-daemon rw,nosuid,nodev,relatime,user_id=1000,group_id=1000 0 0 /dev/sdb2 /media/A2B24EACB24E852F fuseblk rw,nosuid,nodev,relatime,user_id=0,group_id=0,default_permissions,allow_other,blksize=4096 0 0 /dev/sdb1 /media/System\040Reserved fuseblk rw,nosuid,nodev,relatime,user_id=0,group_id=0,default_permissions,allow_other,blksize=4096 0 0 gvfs-fuse-daemon /root/.gvfs fuse.gvfs-fuse-daemon rw,nosuid,nodev,relatime,user_id=0,group_id=0 0 0 $ fsck fsck from util-linux 2.20.1 e2fsck 1.42 (29-Nov-2011) /dev/sdb6 is mounted. WARNING!!! The filesystem is mounted. If you continue you ***WILL*** cause ***SEVERE*** filesystem damage. Do you really want to continue<n>? no check aborted.

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• No root file system is defined error after installation

  - by LearnCode

  I installed ubuntu through Wubi and once i rebooted I get no root file system defined error. here's the output of the boot_info_script.Could anyone point me out where the error is. Boot Info Script 0.60 from 17 May 2011 ============================= Boot Info Summary: =============================== => Windows is installed in the MBR of /dev/sda. => Windows is installed in the MBR of /dev/sdb. sda1: __________________________________________________________________________ File system: ntfs Boot sector type: Windows Vista/7 Boot sector info: No errors found in the Boot Parameter Block. Operating System: Windows 7 Boot files: /bootmgr /Boot/BCD /Windows/System32/winload.exe /ntldr /ntdetect.com /wubildr /ubuntu/winboot/wubildr /wubildr.mbr /ubuntu/winboot/wubildr.mbr /ubuntu/disks/root.disk /ubuntu/disks/swap.disk sda1/Wubi: _____________________________________________________________________ File system: Boot sector type: Unknown Boot sector info: Mounting failed: mount: unknown filesystem type '' sda2: __________________________________________________________________________ File system: vfat Boot sector type: Unknown Boot sector info: No errors found in the Boot Parameter Block. Operating System: Boot files: /boot.ini /ntldr /NTDETECT.COM sdb1: __________________________________________________________________________ File system: ntfs Boot sector type: Windows Vista/7 Boot sector info: No errors found in the Boot Parameter Block. Operating System: Boot files: ============================ Drive/Partition Info: ============================= Drive: sda _____________________________________________________________________ Disk /dev/sda: 160.0 GB, 160041885696 bytes 240 heads, 63 sectors/track, 20673 cylinders, total 312581808 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes Partition Boot Start Sector End Sector # of Sectors Id System /dev/sda1 * 63 301,250,879 301,250,817 7 NTFS / exFAT / HPFS /dev/sda2 301,250,943 312,575,759 11,324,817 c W95 FAT32 (LBA) GUID Partition Table detected, but does not seem to be used. Partition Start Sector End Sector # of Sectors System /dev/sda1 323,465,741,313,502,988275,962,973,585-323,465,465,350,529,402 - /dev/sda2 242,728,591,638,290,720578,721,383,108,845,578335,992,791,470,554,859 - /dev/sda3 1,827,498,311,425,204,2562,091,935,274,843,009,907264,436,963,417,805,652 - /dev/sda4 579,711,218,081,401,3572,006,665,459,744,645,1521,426,954,241,663,243,796 - /dev/sda11 270,286,346,402,038,1183,786,543,326,404,525,9543,516,256,980,002,487,837 - /dev/sda12 4,179,681,002,230,769,6684,179,389,374,010,033,387-291,628,220,736,280 - /dev/sda13 232,556,480,979,456,1311,160,152,593,793,119,235927,596,112,813,663,105 - /dev/sda14 98,342,784,050,266,9183,691,264,578,843,725,1953,592,921,794,793,458,278 - /dev/sda15 2,307,845,219,957,882,4961,850,841,032,955,276,350-457,004,187,002,606,145 - /dev/sda16 512,592,046,878,946,497368,458,231,024,779,444-144,133,815,854,167,052 - /dev/sda17 2,504,135,232,870,384,3923,665,087,872,719,320,8291,160,952,639,848,936,438 - /dev/sda18 3,783,181,605,270,691,304122,034,509,624,708,942-3,661,147,095,645,982,361 - /dev/sda19 3,519,661,520,275,829,5122,376,243,094,723,723,587-1,143,418,425,552,105,924 - /dev/sda20 3,867,920,076,859,0744,494,691,111,933,625,1044,490,823,191,856,766,031 - /dev/sda21 1,500,144,061,909,253,7612,511,182,033,846,676,3401,011,037,971,937,422,580 - /dev/sda22 13,035,625,499,900,0062,360,168,613,941,394,9472,347,132,988,441,494,942 - /dev/sda23 4,228,978,682,068,599,48813,159,423,631,648,263-4,215,819,258,436,951,224 - /dev/sda24 3,695,955,742,872,046,9084,561,928,726,501,845,776865,972,983,629,798,869 - /dev/sda25 1,297,460,286,683,948,0461,444,350,486,339,417,957146,890,199,655,469,912 - /dev/sda26 1,228,858,248,533,131,831 0-1,228,858,248,533,131,830 - /dev/sda121 3,189,184,846,146,487,1461,849,820,258,006,914,852-1,339,364,588,139,572,293 - /dev/sda122 1,226,215,547,991,800,578389,781,518,734,546,300-836,434,029,257,254,277 - /dev/sda123 3,851,660,168,574,583,4654,046,215,657,583,031,556194,555,489,008,448,092 - /dev/sda124 1,197,460,980,174,153,341699,103,965,005,093,246-498,357,015,169,060,094 - Drive: sdb _____________________________________________________________________ Disk /dev/sdb: 750.2 GB, 750153367552 bytes 255 heads, 63 sectors/track, 91200 cylinders, total 1465143296 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes Partition Boot Start Sector End Sector # of Sectors Id System /dev/sdb1 2,048 1,465,143,295 1,465,141,248 7 NTFS / exFAT / HPFS "blkid" output: ________________________________________________________________ Device UUID TYPE LABEL /dev/loop0 iso9660 Ubuntu 11.04 amd64 /dev/loop1 squashfs /dev/sda1 E814B55B14B52E06 ntfs /dev/sda2 01CD-023B vfat HP_RECOVERY /dev/sdb1 7836F22A36F1E8D0 ntfs Elements ================================ Mount points: ================================= Device Mount_Point Type Options /dev/loop0 /cdrom iso9660 (ro,noatime) /dev/loop1 /rofs squashfs (ro,noatime) /dev/sdb1 /mnt fuseblk (rw,nosuid,nodev,allow_other,blksize=4096) ================================ sda2/boot.ini: ================================ -------------------------------------------------------------------------------- [boot loader] timeout=0 default=C:\CMDCONS\BOOTSECT.DAT [operating systems] multi(0)disk(0)rdisk(0)partition(1)\WINDOWS="Microsoft Windows XP Professional" /fastdetect C:\CMDCONS\BOOTSECT.DAT="Microsoft Windows Recovery Console" /cmdcons -------------------------------------------------------------------------------- ======================== Unknown MBRs/Boot Sectors/etc: ======================== Unknown GPT Partiton Type c104043000e9b9040dff24b580010100 Unknown GPT Partiton Type 46313020746f20737461727420746865 Unknown GPT Partiton Type 65727920706172746974696f6e207761 Unknown GPT Partiton Type 727920706172746974696f6e0d0a0000 Unknown GPT Partiton Type 000f84e5f7668b162404e82804744066 Unknown GPT Partiton Type ce01e8dc038bfe66391624047505e8d9 Unknown GPT Partiton Type 0345086603f0e881030bd2740333d240 Unknown GPT Partiton Type bece01e8db0287fec645041266895508 Unknown GPT Partiton Type 01f60634010175078b363b01e854f5e8 Unknown GPT Partiton Type 313825740ffec03865107408fec03824 Unknown GPT Partiton Type 02f60634014074088bfdbece01e85101 Unknown GPT Partiton Type 263401f9e894f30f858ef4e8e201e8ec Unknown GPT Partiton Type f7e960f35245434f5645525966606633 Unknown GPT Partiton Type 660faf1e00106603dac3668b0e001066 Unknown GPT Partiton Type 8bfd386d04740583c710e2f6c36660c6 Unknown GPT Partiton Type 04ebf132c0b91000f3aac3bf0c04ebf3 Unknown GPT Partiton Type 02662bc1660fb71e0e02662bc366031e Unknown GPT Partiton Type f4b40ebb0700b901003c08751381ff25 Unknown GPT Partiton Type 534f465448494e4b90653f62011b0100 Unknown GPT Partiton Type 0b050900027777772e68702e636f6d00 Unknown GPT Partiton Type d441a0f5030003000ecb744a08bb3746 Unknown GPT Partiton Type f8579a116b4a7aa931cde97a4b9b5c09 Unknown GPT Partiton Type 7229990415b77c0a1970e7e824237a3a Unknown GPT Partiton Type afb6e34d6b4bd8c7c0eada19a9786cc3 Unknown BootLoader on sda1/Wubi 00000000 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 |0000000000000000| * 00000200 Unknown BootLoader on sda2 00000000 e9 a7 00 52 45 43 4f 56 45 52 59 00 02 08 20 00 |...RECOVERY... .| 00000010 02 00 00 00 00 f8 00 00 3f 00 f0 00 7f b9 f4 11 |........?.......| 00000020 8c cd ac 00 1e 2b 00 00 00 00 00 00 02 00 00 00 |.....+..........| 00000030 01 00 06 00 00 00 00 00 00 00 00 00 00 00 00 00 |................| 00000040 80 00 29 3b 02 cd 01 20 20 20 20 20 20 20 20 20 |..);... | 00000050 20 20 46 41 54 33 32 20 20 20 8b d0 c1 e2 02 80 | FAT32 ......| 00000060 e6 01 66 c1 e8 07 66 3b 46 f8 74 2a 66 89 46 f8 |..f...f;F.t*f.F.| 00000070 66 03 46 f4 66 0f b6 5e 28 80 e3 0f 74 0f 3a 5e |f.F.f..^(...t.:^| 00000080 10 0f 83 90 00 66 0f af 5e 24 66 03 c3 bb e0 07 |.....f..^$f.....| 00000090 b9 01 00 e8 cf 00 8b da 66 8b 87 00 7e 66 25 ff |........f...~f%.| 000000a0 ff ff 0f 66 3d f8 ff ff 0f c3 33 c9 8e d9 8e c1 |...f=.....3.....| 000000b0 8e d1 66 bc f4 7b 00 00 bd 00 7c 66 0f b6 46 10 |..f..{....|f..F.| 000000c0 66 f7 66 24 66 0f b7 56 0e 66 03 56 1c 66 89 56 |f.f$f..V.f.V.f.V| 000000d0 f4 66 03 c2 66 89 46 fc 66 c7 46 f8 ff ff ff ff |.f..f.F.f.F.....| 000000e0 66 8b 46 2c 66 50 e8 af 00 bb 70 00 b9 01 00 e8 |f.F,fP....p.....| 000000f0 73 00 bf 00 07 b1 0b be a9 7d f3 a6 74 2a 03 f9 |s........}..t*..| 00000100 83 c7 15 81 ff 00 09 72 ec 66 40 4a 75 db 66 58 |[email protected]| 00000110 e8 47 ff 72 cf be b4 7d ac 84 c0 74 09 b4 0e bb |.G.r...}...t....| 00000120 07 00 cd 10 eb f2 cd 19 66 58 ff 75 09 ff 75 0f |........fX.u..u.| 00000130 66 58 bb 00 20 66 83 f8 02 72 da 66 3d f8 ff ff |fX.. f...r.f=...| 00000140 0f 73 d2 66 50 e8 50 00 0f b6 4e 0d e8 16 00 c1 |.s.fP.P...N.....| 00000150 e1 05 03 d9 66 58 53 e8 00 ff 5b 72 d8 8a 56 40 |....fXS...[r..V@| 00000160 ea 00 00 00 20 66 60 66 6a 00 66 50 53 6a 00 66 |.... f`fj.fPSj.f| 00000170 68 10 00 01 00 8b f4 b8 00 42 8a 56 40 cd 13 be |h........B.V@...| 00000180 c7 7d 72 94 67 83 44 24 06 20 66 67 ff 44 24 08 |.}r.g.D$. fg.D$.| 00000190 e2 e3 83 c4 10 66 61 c3 66 48 66 48 66 0f b6 56 |.....fa.fHfHf..V| 000001a0 0d 66 f7 e2 66 03 46 fc c3 4e 54 4c 44 52 20 20 |.f..f.F..NTLDR | 000001b0 20 20 20 20 0d 0a 4e 6f 20 53 79 73 74 65 6d 20 | ..No System | 000001c0 44 69 73 6b 20 6f 72 0d 0a 44 69 73 6b 20 49 2f |Disk or..Disk I/| 000001d0 4f 20 65 72 72 6f 72 0d 0a 50 72 65 73 73 20 61 |O error..Press a| 000001e0 20 6b 65 79 20 74 6f 20 72 65 73 74 61 72 74 0d | key to restart.| 000001f0 0a 00 00 00 00 00 00 00 00 00 00 00 00 00 55 aa |..............U.| 00000200 =============================== StdErr Messages: =============================== umount: /isodevice: device is busy. (In some cases useful info about processes that use the device is found by lsof(8) or fuser(1))

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• Testing Workflows &ndash; Test-After

  - by Timothy Klenke

  Originally posted on: http://geekswithblogs.net/TimothyK/archive/2014/05/30/testing-workflows-ndash-test-after.aspxIn this post I’m going to outline a few common methods that can be used to increase the coverage of of your test suite.  This won’t be yet another post on why you should be doing testing; there are plenty of those types of posts already out there.  Assuming you know you should be testing, then comes the problem of how do I actual fit that into my day job.  When the opportunity to automate testing comes do you take it, or do you even recognize it? There are a lot of ways (workflows) to go about creating automated tests, just like there are many workflows to writing a program.  When writing a program you can do it from a top-down approach where you write the main skeleton of the algorithm and call out to dummy stub functions, or a bottom-up approach where the low level functionality is fully implement before it is quickly wired together at the end.  Both approaches are perfectly valid under certain contexts. Each approach you are skilled at applying is another tool in your tool belt.  The more vectors of attack you have on a problem – the better.  So here is a short, incomplete list of some of the workflows that can be applied to increasing the amount of automation in your testing and level of quality in general.  Think of each workflow as an opportunity that is available for you to take. Test workflows basically fall into 2 categories:  test first or test after.  Test first is the best approach.  However, this post isn’t about the one and only best approach.  I want to focus more on the lesser known, less ideal approaches that still provide an opportunity for adding tests.  In this post I’ll enumerate some test-after workflows.  In my next post I’ll cover test-first. Bug Reporting When someone calls you up or forwards you a email with a vague description of a bug its usually standard procedure to create or verify a reproduction plan for the bug via manual testing and log that in a bug tracking system.  This can be problematic.  Often reproduction plans when written down might skip a step that seemed obvious to the tester at the time or they might be missing some crucial environment setting. Instead of data entry into a bug tracking system, try opening up the test project and adding a failing unit test to prove the bug.  The test project guarantees that all aspects of the environment are setup properly and no steps are missing.  The language in the test project is much more precise than the English that goes into a bug tracking system. This workflow can easily be extended for Enhancement Requests as well as Bug Reporting. Exploratory Testing Exploratory testing comes in when you aren’t sure how the system will behave in a new scenario.  The scenario wasn’t planned for in the initial system requirements and there isn’t an existing test for it.  By definition the system behaviour is “undefined”. So write a new unit test to define that behaviour.  Add assertions to the tests to confirm your assumptions.  The new test becomes part of the living system specification that is kept up to date with the test suite. Examples This workflow is especially good when developing APIs.  When you are finally done your production API then comes the job of writing documentation on how to consume the API.  Good documentation will also include code examples.  Don’t let these code examples merely exist in some accompanying manual; implement them in a test suite. Example tests and documentation do not have to be created after the production API is complete.  It is best to write the example code (tests) as you go just before the production code. Smoke Tests Every system has a typical use case.  This represents the basic, core functionality of the system.  If this fails after an upgrade the end users will be hosed and they will be scratching their heads as to how it could be possible that an update got released with this core functionality broken. The tests for this core functionality are referred to as “smoke tests”.  It is a good idea to have them automated and run with each build in order to avoid extreme embarrassment and angry customers. Coverage Analysis Code coverage analysis is a tool that reports how much of the production code base is exercised by the test suite.  In Visual Studio this can be found under the Test main menu item. The tool will report a total number for the code coverage, which can be anywhere between 0 and 100%.  Coverage Analysis shouldn’t be used strictly for numbers reporting.  Companies shouldn’t set minimum coverage targets that mandate that all projects must have at least 80% or 100% test coverage.  These arbitrary requirements just invite gaming of the coverage analysis, which makes the numbers useless. The analysis tool will break down the coverage by the various classes and methods in projects.  Instead of focusing on the total number, drill down into this view and see which classes have high or low coverage.  It you are surprised by a low number on a class this is an opportunity to add tests. When drilling through the classes there will be generally two types of reaction to a surprising low test coverage number.  The first reaction type is a recognition that there is low hanging fruit to be picked.  There may be some classes or methods that aren’t being tested, which could easy be.  The other reaction type is “OMG”.  This were you find a critical piece of code that isn’t under test.  In both cases, go and add the missing tests. Test Refactoring The general theme of this post up to this point has been how to add more and more tests to a test suite.  I’ll step back from that a bit and remind that every line of code is a liability.  Each line of code has to be read and maintained, which costs money.  This is true regardless whether the code is production code or test code. Remember that the primary goal of the test suite is that it be easy to read so that people can easily determine the specifications of the system.  Make sure that adding more and more tests doesn’t interfere with this primary goal. Perform code reviews on the test suite as often as on production code.  Hold the test code up to the same high readability standards as the production code.  If the tests are hard to read then change them.  Look to remove duplication.  Duplicate setup code between two or more test methods that can be moved to a shared function.  Entire test methods can be removed if it is found that the scenario it tests is covered by other tests.  Its OK to delete a test that isn’t pulling its own weight anymore. Remember to only start refactoring when all the test are green.  Don’t refactor the tests and the production code at the same time.  An automated test suite can be thought of as a double entry book keeping system.  The unchanging, passing production code serves as the tests for the test suite while refactoring the tests. As with all refactoring, it is best to fit this into your regular work rather than asking for time later to get it done.  Fit this into the standard red-green-refactor cycle.  The refactor step no only applies to production code but also the tests, but not at the same time.  Perhaps the cycle should be called red-green-refactor production-refactor tests (not quite as catchy).   That about covers most of the test-after workflows I can think of.  In my next post I’ll get into test-first workflows.

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• Using SSIS to send a HTML E-Mail Message with built-in table of Counts.

  - by Kevin Shyr

  For the record, this can be just as easily done with a .NET class with a DLL call.  The two major reasons for this ending up as a SSIS package are: There are a lot of SQL resources for maintenance, but not as many .NET developers. There is an existing automated process that links up SQL Jobs (more on that in the next post), and this is part of that process.   To start, this is what the SSIS looks like: The first part of the control flow is just for the override scenario.   In the Execute SQL Task, it calls a stored procedure, which already formats the result into XML by using "FOR XML PATH('Row'), ROOT(N'FieldingCounts')".  The result XML string looks like this: <FieldingCounts>   <Row>     <CellId>M COD</CellId>     <Mailed>64</Mailed>     <ReMailed>210</ReMailed>     <TotalMail>274</TotalMail>     <EMailed>233</EMailed>     <TotalSent>297</TotalSent>   </Row>   <Row>     <CellId>M National</CellId>     <Mailed>11</Mailed>     <ReMailed>59</ReMailed>     <TotalMail>70</TotalMail>     <EMailed>90</EMailed>     <TotalSent>101</TotalSent>   </Row>   <Row>     <CellId>U COD</CellId>     <Mailed>91</Mailed>     <ReMailed>238</ReMailed>     <TotalMail>329</TotalMail>     <EMailed>291</EMailed>     <TotalSent>382</TotalSent>   </Row>   <Row>     <CellId>U National</CellId>     <Mailed>63</Mailed>     <ReMailed>286</ReMailed>     <TotalMail>349</TotalMail>     <EMailed>374</EMailed>     <TotalSent>437</TotalSent>   </Row> </FieldingCounts>  This result is saved into an internal SSIS variable with the following settings on the General tab and the Result Set tab:   Now comes the trickier part.  We need to use the XML Task to format the XML string result into an HTML table, and I used Direct input XSLT And here is the code of XSLT: <xsl:stylesheet version="1.0" xmlns:xsl="http://www.w3.org/1999/XSL/Transform"> <xsl:output method="html" indent="yes"/>   <xsl:template match="/ROOT">         <table border="1" cellpadding="6">           <tr>             <td></td>             <td>Mailed</td>             <td>Re-mailed</td>             <td>Total Mail (Mailed, Re-mailed)</td>             <td>E-mailed</td>             <td>Total Sent (Mailed, E-mailed)</td>           </tr>           <xsl:for-each select="FieldingCounts/Row">             <tr>               <xsl:for-each select="./*">                 <td>                   <xsl:value-of select="." />                 </td>               </xsl:for-each>             </tr>           </xsl:for-each>         </table>   </xsl:template> </xsl:stylesheet>    Then a script task is used to send out an HTML email (as we are all painfully aware that SSIS Send Mail Task only sends plain text) Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 using System; using System.Data; using Microsoft.SqlServer.Dts.Runtime; using System.Windows.Forms; using System.Net.Mail; using System.Net;   namespace ST_b829a2615e714bcfb55db0ce97be3901.csproj {     [System.AddIn.AddIn("ScriptMain", Version = "1.0", Publisher = "", Description = "")]     public partial class ScriptMain : Microsoft.SqlServer.Dts.Tasks.ScriptTask.VSTARTScriptObjectModelBase     {           #region VSTA generated code         enum ScriptResults         {             Success = Microsoft.SqlServer.Dts.Runtime.DTSExecResult.Success,             Failure = Microsoft.SqlServer.Dts.Runtime.DTSExecResult.Failure         };         #endregion           public void Main()         {             String EmailMsgBody = String.Format("<HTML><BODY><P>{0}</P><P>{1}</P></BODY></HTML>"                                                 , Dts.Variables["Config_SMTP_MessageSourceText"].Value.ToString()                                                 , Dts.Variables["InternalStr_CountResultAfterXSLT"].Value.ToString());             MailMessage EmailCountMsg = new MailMessage(Dts.Variables["Config_SMTP_From"].Value.ToString().Replace(";", ",")                                                         , Dts.Variables["Config_SMTP_Success_To"].Value.ToString().Replace(";", ",")                                                         , Dts.Variables["Config_SMTP_SubjectLinePrefix"].Value.ToString() + " " + Dts.Variables["InternalStr_FieldingDate"].Value.ToString()                                                         , EmailMsgBody);             //EmailCountMsg.From.             EmailCountMsg.CC.Add(Dts.Variables["Config_SMTP_Success_CC"].Value.ToString().Replace(";", ","));             EmailCountMsg.IsBodyHtml = true;               SmtpClient SMTPForCount = new SmtpClient(Dts.Variables["Config_SMTP_ServerAddress"].Value.ToString());             SMTPForCount.Credentials = CredentialCache.DefaultNetworkCredentials;               SMTPForCount.Send(EmailCountMsg);               Dts.TaskResult = (int)ScriptResults.Success;         }     } } Note on this code: notice the email list has Replace(";", ",").  This is only here because the list is configurable in the SQL Job Step at Set Values, which does not react well with colons as email separator, but system.Net.Mail only handles comma as email separator, hence the extra replace in the string. The result is a nicely formatted email message with count information:

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• External File Upload Optimizations for Windows Azure

  - by rgillen

  [Cross posted from here: http://rob.gillenfamily.net/post/External-File-Upload-Optimizations-for-Windows-Azure.aspx] I’m wrapping up a bit of the work we’ve been doing on data movement optimizations for cloud computing and the latest set of data yielded some interesting points I thought I’d share. The work done here is not really rocket science but may, in some ways, be slightly counter-intuitive and therefore seemed worthy of posting. Summary: for those who don’t like to read detailed posts or don’t have time, the synopsis is that if you are uploading data to Azure, block your data (even down to 1MB) and upload in parallel. Set your block size based on your source file size, but if you must choose a fixed value, use 1MB. Following the above will result in significant performance gains… upwards of 10x-24x and a reduction in overall file transfer time of upwards of 90% (eg, uploading a 1GB file averaged 46.37 minutes prior to optimizations and averaged 1.86 minutes afterwards). Detail: For those of you who want more detail, or think that the claims at the end of the preceding paragraph are over-reaching, what follows is information and code supporting these claims. As the title would indicate, these tests were run from our research facility pointing to the Azure cloud (specifically US North Central as it is physically closest to us) and do not represent intra-cloud results… we have performed intra-cloud tests and the overall results are similar in notion but the data rates are significantly different as well as the tipping points for the various block sizes… this will be detailed separately). We started by building a very simple console application that would loop through a directory and upload each file to Azure storage. This application used the shipping storage client library from the 1.1 version of the azure tools. The only real variation from the client library is that we added code to collect and record the duration (in ms) and size (in bytes) for each file transferred. The code is available here. We then created a directory that had a collection of files for the following sizes: 2KB, 32KB, 64KB, 128KB, 512KB, 1MB, 5MB, 10MB, 25MB, 50MB, 100MB, 250MB, 500MB, 750MB, and 1GB (50 files for each size listed). These files contained randomly-generated binary data and do not benefit from compression (a separate discussion topic). Our file generation tool is available here. The baseline was established by running the application described above against the directory containing all of the data files. This application uploads the files in a random order so as to avoid transferring all of the files of a given size sequentially and thereby spreading the affects of periodic Internet delays across the collection of results.  We then ran some scripts to split the resulting data and generate some reports. The raw data collected for our non-optimized tests is available via the links in the Related Resources section at the bottom of this post. For each file size, we calculated the average upload time (and standard deviation) and the average transfer rate (and standard deviation). As you likely are aware, transferring data across the Internet is susceptible to many transient delays which can cause anomalies in the resulting data. It is for this reason that we randomized the order of source file processing as well as executed the tests 50x for each file size. We expect that these steps will yield a sufficiently balanced set of results. Once the baseline was collected and analyzed, we updated the test harness application with some methods to split the source file into user-defined block sizes and then to upload those blocks in parallel (using the PutBlock() method of Azure storage). The parallelization was handled by simply relying on the Parallel Extensions to .NET to provide a Parallel.For loop (see linked source for specific implementation details in Program.cs, line 173 and following… less than 100 lines total). Once all of the blocks were uploaded, we called PutBlockList() to assemble/commit the file in Azure storage. For each block transferred, the MD5 was calculated and sent ensuring that the bits that arrived matched was was intended. The timer for the blocked/parallelized transfer method wraps the entire process (source file splitting, block transfer, MD5 validation, file committal). A diagram of the process is as follows: We then tested the affects of blocking & parallelizing the transfers by running the updated application against the same source set and did a parameter sweep on the block size including 256KB, 512KB, 1MB, 2MB, and 4MB (our assumption was that anything lower than 256KB wasn’t worth the trouble and 4MB is the maximum size of a block supported by Azure). The raw data for the parallel tests is available via the links in the Related Resources section at the bottom of this post. This data was processed and then compared against the single-threaded / non-optimized transfer numbers and the results were encouraging. The Excel version of the results is available here. Two semi-obvious points need to be made prior to reviewing the data. The first is that if the block size is larger than the source file size you will end up with a “negative optimization” due to the overhead of attempting to block and parallelize. The second is that as the files get smaller, the clock-time cost of blocking and parallelizing (overhead) is more apparent and can tend towards negative optimizations. For this reason (and is supported in the raw data provided in the linked worksheet) the charts and dialog below ignore source file sizes less than 1MB. (click chart for full size image) The chart above illustrates some interesting points about the results: When the block size is smaller than the source file, performance increases but as the block size approaches and then passes the source file size, you see decreasing benefit to the point of negative gains (see the values for the 1MB file size) For some of the moderately-sized source files, small blocks (256KB) are best As the size of the source file gets larger (see values for 50MB and up), the smallest block size is not the most efficient (presumably due, at least in part, to the increased number of blocks, increased number of individual transfer requests, and reassembly/committal costs). Once you pass the 250MB source file size, the difference in rate for 1MB to 4MB blocks is more-or-less constant The 1MB block size gives the best average improvement (~16x) but the optimal approach would be to vary the block size based on the size of the source file.    (click chart for full size image) The above is another view of the same data as the prior chart just with the axis changed (x-axis represents file size and plotted data shows improvement by block size). It again highlights the fact that the 1MB block size is probably the best overall size but highlights the benefits of some of the other block sizes at different source file sizes. This last chart shows the change in total duration of the file uploads based on different block sizes for the source file sizes. Nothing really new here other than this view of the data highlights the negative affects of poorly choosing a block size for smaller files.   Summary What we have found so far is that blocking your file uploads and uploading them in parallel results in significant performance improvements. Further, utilizing extension methods and the Task Parallel Library (.NET 4.0) make short work of altering the shipping client library to provide this functionality while minimizing the amount of change to existing applications that might be using the client library for other interactions.   Related Resources Source code for upload test application Source code for random file generator ODatas feed of raw data from non-optimized transfer tests Experiment Metadata Experiment Datasets 2KB Uploads 32KB Uploads 64KB Uploads 128KB Uploads 256KB Uploads 512KB Uploads 1MB Uploads 5MB Uploads 10MB Uploads 25MB Uploads 50MB Uploads 100MB Uploads 250MB Uploads 500MB Uploads 750MB Uploads 1GB Uploads Raw Data OData feeds of raw data from blocked/parallelized transfer tests Experiment Metadata Experiment Datasets Raw Data 256KB Blocks 512KB Blocks 1MB Blocks 2MB Blocks 4MB Blocks Excel worksheet showing summarizations and comparisons

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• Benchmarking MySQL Replication with Multi-Threaded Slaves

  - by Mat Keep

  0 0 1 1145 6530 Homework 54 15 7660 14.0 Normal 0 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6. As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to: · Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data) · Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog) The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application data using databases - e.g. multi-tenant systems deployed in cloud environments. Multi-Threaded Slaves are just one of many enhancements to replication previewed as part of the MySQL 5.6 Development Release, which include: · Global Transaction Identifiers coupled with MySQL utilities for automatic failover / switchover and slave promotion · Crash Safe Slaves and Binlog · Optimized Row Based Replication · Replication Event Checksums · Time Delayed Replication These and many more are discussed in the “MySQL 5.6 Replication: Enabling the Next Generation of Web & Cloud Services” Developer Zone article  Back to the benchmark - details are as follows. Environment The test environment consisted of two Linux servers: · one running the replication master · one running the replication slave. Only the slave was involved in the actual measurements, and was based on the following configuration: - Hardware: Oracle Sun Fire X4170 M2 Server - CPU: 2 sockets, 6 cores with hyper-threading, 2930 MHz. - OS: 64-bit Oracle Enterprise Linux 6.1 - Memory: 48 GB Test Procedure Initial Setup: Two MySQL servers were started on two different hosts, configured as replication master and slave. 10 sysbench schemas were created, each with a single table: CREATE TABLE `sbtest` (    `id` int(10) unsigned NOT NULL AUTO_INCREMENT,    `k` int(10) unsigned NOT NULL DEFAULT '0',    `c` char(120) NOT NULL DEFAULT '',    `pad` char(60) NOT NULL DEFAULT '',    PRIMARY KEY (`id`),    KEY `k` (`k`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 10,000 rows were inserted in each of the 10 tables, for a total of 100,000 rows. When the inserts had replicated to the slave, the slave threads were stopped. The slave data directory was copied to a backup location and the slave threads position in the master binlog noted. 10 sysbench clients, each configured with 10 threads, were spawned at the same time to generate a random schema load against each of the 10 schemas on the master. Each sysbench client executed 10,000 "update key" statements: UPDATE sbtest set k=k+1 WHERE id = <random row> In total, this generated 100,000 update statements to later replicate during the test itself. Test Methodology: The number of slave workers to test with was configured using: SET GLOBAL slave_parallel_workers=<workers> Then the slave IO thread was started and the test waited for all the update queries to be copied over to the relay log on the slave. The benchmark clock was started and then the slave SQL thread was started. The test waited for the slave SQL thread to finish executing the 100k update queries, doing "select master_pos_wait()". When master_pos_wait() returned, the benchmark clock was stopped and the duration calculated. The calculated duration from the benchmark clock should be close to the time it took for the SQL thread to execute the 100,000 update queries. The 100k queries divided by this duration gave the benchmark metric, reported as Queries Per Second (QPS). Test Reset: The test-reset cycle was implemented as follows: · the slave was stopped · the slave data directory replaced with the previous backup · the slave restarted with the slave threads replication pointer repositioned to the point before the update queries in the binlog. The test could then be repeated with identical set of queries but a different number of slave worker threads, enabling a fair comparison. The Test-Reset cycle was repeated 3 times for 0-24 number of workers and the QPS metric calculated and averaged for each worker count. MySQL Configuration The relevant configuration settings used for MySQL are as follows: binlog-format=STATEMENT relay-log-info-repository=TABLE master-info-repository=TABLE As described in the test procedure, the slave_parallel_workers setting was modified as part of the test logic. The consequence of changing this setting is: 0 worker threads:    - current (i.e. single threaded) sequential mode    - 1 x IO thread and 1 x SQL thread    - SQL thread both reads and executes the events 1 worker thread:    - sequential mode    - 1 x IO thread, 1 x Coordinator SQL thread and 1 x Worker thread    - coordinator reads the event and hands it to the worker who executes 2+ worker threads:    - parallel execution    - 1 x IO thread, 1 x Coordinator SQL thread and 2+ Worker threads    - coordinator reads events and hands them to the workers who execute them Results Figure 1 below shows that Multi-Threaded Slaves deliver ~5x higher replication performance when configured with 10 worker threads, with the load evenly distributed across our 10 x schemas. This result is compared to the current replication implementation which is based on a single SQL thread only (i.e. zero worker threads). Figure 1: 5x Higher Performance with Multi-Threaded Slaves The following figure shows more detailed results, with QPS sampled and reported as the worker threads are incremented. The raw numbers behind this graph are reported in the Appendix section of this post. Figure 2: Detailed Results As the results above show, the configuration does not scale noticably from 5 to 9 worker threads. When configured with 10 worker threads however, scalability increases significantly. The conclusion therefore is that it is desirable to configure the same number of worker threads as schemas. Other conclusions from the results: · Running with 1 worker compared to zero workers just introduces overhead without the benefit of parallel execution. · As expected, having more workers than schemas adds no visible benefit. Aside from what is shown in the results above, testing also demonstrated that the following settings had a very positive effect on slave performance: relay-log-info-repository=TABLE master-info-repository=TABLE For 5+ workers, it was up to 2.3 times as fast to run with TABLE compared to FILE. Conclusion As the results demonstrate, Multi-Threaded Slaves deliver significant performance increases to MySQL replication when handling multiple schemas. This, and the other replication enhancements introduced in MySQL 5.6 are fully available for you to download and evaluate now from the MySQL Developer site (select Development Release tab). You can learn more about MySQL 5.6 from the documentation  Please don’t hesitate to comment on this or other replication blogs with feedback and questions. Appendix – Detailed Results

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• Possible SWITCH Optimization in DAX – #powerpivot #dax #tabular

  - by Marco Russo (SQLBI)

  In one of the Advanced DAX Workshop I taught this year, I had an interesting discussion about how to optimize a SWITCH statement (which could be frequently used checking a slicer, like in the Parameter Table pattern). Let’s start with the problem. What happen when you have such a statement? Sales :=     SWITCH (         VALUES ( Period[Period] ),         "Current", [Internet Total Sales],         "MTD", [MTD Sales],         "QTD", [QTD Sales],         "YTD", [YTD Sales],          BLANK ()     ) The SWITCH statement is in reality just syntax sugar for a nested IF statement. When you place such a measure in a pivot table, for every cell of the pivot table the IF options are evaluated. In order to optimize performance, the DAX engine usually does not compute cell-by-cell, but tries to compute the values in bulk-mode. However, if a measure contains an IF statement, every cell might have a different execution path, so the current implementation might evaluate all the possible IF branches in bulk-mode, so that for every cell the result from one of the branches will be already available in a pre-calculated dataset. The price for that could be high. If you consider the previous Sales measure, the YTD Sales measure could be evaluated for all the cells where it’s not required, and also when YTD is not selected at all in a Pivot Table. The actual optimization made by the DAX engine could be different in every build, and I expect newer builds of Tabular and Power Pivot to be better than older ones. However, we still don’t live in an ideal world, so it could be better trying to help the engine finding a better execution plan. One student (Niek de Wit) proposed this approach: Selection := IF (     HASONEVALUE ( Period[Period] ),     VALUES ( Period[Period] ) ) Sales := CALCULATE (     [Internet Total Sales],     FILTER (         VALUES ( 'Internet Sales'[Order Quantity] ),         'Internet Sales'[Order Quantity]             = IF (                 [Selection] = "Current",                 'Internet Sales'[Order Quantity],                 -1             )     ) )     + CALCULATE (         [MTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "MTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     )     + CALCULATE (         [QTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "QTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     )     + CALCULATE (         [YTD Sales],         FILTER (             VALUES ( 'Internet Sales'[Order Quantity] ),             'Internet Sales'[Order Quantity]                 = IF (                     [Selection] = "YTD",                     'Internet Sales'[Order Quantity],                     -1                 )         )     ) At first sight, you might think it’s impossible that this approach could be faster. However, if you examine with the profiler what happens, there is a different story. Every original IF’s execution branch is now a separate CALCULATE statement, which applies a filter that does not execute the required measure calculation if the result of the FILTER is empty. I used the ‘Internet Sales’[Order Quantity] column in this example just because in Adventure Works it has only one value (every row has 1): in the real world, you should use a column that has a very low number of distinct values, or use a column that has always the same value for every row (so it will be compressed very well!). Because the value –1 is never used in this column, the IF comparison in the filter discharge all the values iterated in the filter if the selection does not match with the desired value. I hope to have time in the future to write a longer article about this optimization technique, but in the meantime I’ve seen this optimization has been useful in many other implementations. Please write your feedback if you find scenarios (in both Power Pivot and Tabular) where you obtain performance improvements using this technique!

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• Scheduling thread tiles with C++ AMP

  - by Daniel Moth

  This post assumes you are totally comfortable with, what some of us call, the simple model of C++ AMP, i.e. you could write your own matrix multiplication. We are now ready to explore the tiled model, which builds on top of the non-tiled one. Tiling the extent We know that when we pass a grid (which is just an extent under the covers) to the parallel_for_each call, it determines the number of threads to schedule and their index values (including dimensionality). For the single-, two-, and three- dimensional cases you can go a step further and subdivide the threads into what we call tiles of threads (others may call them thread groups). So here is a single-dimensional example: extent<1> e(20); // 20 units in a single dimension with indices from 0-19 grid<1> g(e);      // same as extent tiled_grid<4> tg = g.tile<4>(); …on the 3rd line we subdivided the single-dimensional space into 5 single-dimensional tiles each having 4 elements, and we captured that result in a concurrency::tiled_grid (a new class in amp.h). Let's move on swiftly to another example, in pictures, this time 2-dimensional: So we start on the left with a grid of a 2-dimensional extent which has 8*6=48 threads. We then have two different examples of tiling. In the first case, in the middle, we subdivide the 48 threads into tiles where each has 4*3=12 threads, hence we have 2*2=4 tiles. In the second example, on the right, we subdivide the original input into tiles where each has 2*2=4 threads, hence we have 4*3=12 tiles. Notice how you can play with the tile size and achieve different number of tiles. The numbers you pick must be such that the original total number of threads (in our example 48), remains the same, and every tile must have the same size. Of course, you still have no clue why you would do that, but stick with me. First, we should see how we can use this tiled_grid, since the parallel_for_each function that we know expects a grid. Tiled parallel_for_each and tiled_index It turns out that we have additional overloads of parallel_for_each that accept a tiled_grid instead of a grid. However, those overloads, also expect that the lambda you pass in accepts a concurrency::tiled_index (new in amp.h), not an index<N>. So how is a tiled_index different to an index? A tiled_index object, can have only 1 or 2 or 3 dimensions (matching exactly the tiled_grid), and consists of 4 index objects that are accessible via properties: global, local, tile_origin, and tile. The global index is the same as the index we know and love: the global thread ID. The local index is the local thread ID within the tile. The tile_origin index returns the global index of the thread that is at position 0,0 of this tile, and the tile index is the position of the tile in relation to the overall grid. Confused? Here is an example accompanied by a picture that hopefully clarifies things: array_view<int, 2> data(8, 6, p_my_data); parallel_for_each(data.grid.tile<2,2>(), [=] (tiled_index<2,2> t_idx) restrict(direct3d) { /* todo */ }); Given the code above and the picture on the right, what are the values of each of the 4 index objects that the t_idx variables exposes, when the lambda is executed by T (highlighted in the picture on the right)? If you can't work it out yourselves, the solution follows: t_idx.global       = index<2> (6,3) t_idx.local          = index<2> (0,1) t_idx.tile_origin = index<2> (6,2) t_idx.tile             = index<2> (3,1) Don't move on until you are comfortable with this… the picture really helps, so use it. Tiled Matrix Multiplication Example – part 1 Let's paste here the C++ AMP matrix multiplication example, bolding the lines we are going to change (can you guess what the changes will be?) 01: void MatrixMultiplyTiled_Part1(vector<float>& vC, const vector<float>& vA, const vector<float>& vB, int M, int N, int W) 02: { 03: 04: array_view<const float,2> a(M, W, vA); 05: array_view<const float,2> b(W, N, vB); 06: array_view<writeonly<float>,2> c(M, N, vC); 07: parallel_for_each(c.grid, 08: [=](index<2> idx) restrict(direct3d) { 09: 10: int row = idx[0]; int col = idx[1]; 11: float sum = 0.0f; 12: for(int i = 0; i < W; i++) 13: sum += a(row, i) * b(i, col); 14: c[idx] = sum; 15: }); 16: } To turn this into a tiled example, first we need to decide our tile size. Let's say we want each tile to be 16*16 (which assumes that we'll have at least 256 threads to process, and that c.grid.extent.size() is divisible by 256, and moreover that c.grid.extent[0] and c.grid.extent[1] are divisible by 16). So we insert at line 03 the tile size (which must be a compile time constant). 03: static const int TS = 16; ...then we need to tile the grid to have tiles where each one has 16*16 threads, so we change line 07 to be as follows 07: parallel_for_each(c.grid.tile<TS,TS>(), ...that means that our index now has to be a tiled_index with the same characteristics as the tiled_grid, so we change line 08 08: [=](tiled_index<TS, TS> t_idx) restrict(direct3d) { ...which means, without changing our core algorithm, we need to be using the global index that the tiled_index gives us access to, so we insert line 09 as follows 09: index<2> idx = t_idx.global; ...and now this code just works and it is tiled! Closing thoughts on part 1 The process we followed just shows the mechanical transformation that can take place from the simple model to the tiled model (think of this as step 1). In fact, when we wrote the matrix multiplication example originally, the compiler was doing this mechanical transformation under the covers for us (and it has additional smarts to deal with the cases where the total number of threads scheduled cannot be divisible by the tile size). The point is that the thread scheduling is always tiled, even when you use the non-tiled model. But with this mechanical transformation, we haven't gained anything… Hint: our goal with explicitly using the tiled model is to gain even more performance. In the next post, we'll evolve this further (beyond what the compiler can automatically do for us, in this first release), so you can see the full usage of the tiled model and its benefits… Comments about this post by Daniel Moth welcome at the original blog.

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• laptop crashed: why?

  - by sds

  my linux (ubuntu 12.04) laptop crashed, and I am trying to figure out why. # last sds pts/4 :0 Tue Sep 4 10:01 still logged in sds pts/3 :0 Tue Sep 4 10:00 still logged in reboot system boot 3.2.0-29-generic Tue Sep 4 09:43 - 11:23 (01:40) sds pts/8 :0 Mon Sep 3 14:23 - crash (19:19) this seems to indicate a crash at 09:42 (= 14:23+19:19). as per another question, I looked at /var/log: auth.log: Sep 4 09:17:02 t520sds CRON[32744]: pam_unix(cron:session): session closed for user root Sep 4 09:43:17 t520sds lightdm: pam_unix(lightdm:session): session opened for user lightdm by (uid=0) no messages file syslog: Sep 4 09:24:19 t520sds kernel: [219104.819975] CPU0: Package power limit normal Sep 4 09:43:16 t520sds kernel: imklog 5.8.6, log source = /proc/kmsg started. kern.log: Sep 4 09:24:19 t520sds kernel: [219104.819969] CPU1: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819971] CPU2: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819974] CPU3: Package power limit normal Sep 4 09:24:19 t520sds kernel: [219104.819975] CPU0: Package power limit normal Sep 4 09:43:16 t520sds kernel: imklog 5.8.6, log source = /proc/kmsg started. Sep 4 09:43:16 t520sds kernel: [ 0.000000] Initializing cgroup subsys cpuset Sep 4 09:43:16 t520sds kernel: [ 0.000000] Initializing cgroup subsys cpu I had a computation running until 9:24, but the system crashed 18 minutes later! kern.log has many pages of these: Sep 4 09:43:16 t520sds kernel: [ 0.000000] total RAM covered: 8086M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 64K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 128K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 256K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 512K num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 1M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 2M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 4M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 8M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 16M num_reg: 10 lose cover RAM: 38M Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 32M num_reg: 10 lose cover RAM: -16M Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 64M num_reg: 10 lose cover RAM: -16M Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 128M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 256M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 512M num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] gran_size: 64K chunk_size: 1G num_reg: 10 lose cover RAM: 0G Sep 4 09:43:16 t520sds kernel: [ 0.000000] *BAD*gran_size: 64K chunk_size: 2G num_reg: 10 lose cover RAM: -1G does this mean that my RAM is bad?! it also says Sep 4 09:43:16 t520sds kernel: [ 2.944123] EXT4-fs (sda1): INFO: recovery required on readonly filesystem Sep 4 09:43:16 t520sds kernel: [ 2.944126] EXT4-fs (sda1): write access will be enabled during recovery Sep 4 09:43:16 t520sds kernel: [ 3.088001] firewire_core: created device fw0: GUID f0def1ff8fbd7dff, S400 Sep 4 09:43:16 t520sds kernel: [ 8.929243] EXT4-fs (sda1): orphan cleanup on readonly fs Sep 4 09:43:16 t520sds kernel: [ 8.929249] EXT4-fs (sda1): ext4_orphan_cleanup: deleting unreferenced inode 658984 ... Sep 4 09:43:16 t520sds kernel: [ 9.343266] EXT4-fs (sda1): ext4_orphan_cleanup: deleting unreferenced inode 525343 Sep 4 09:43:16 t520sds kernel: [ 9.343270] EXT4-fs (sda1): 56 orphan inodes deleted Sep 4 09:43:16 t520sds kernel: [ 9.343271] EXT4-fs (sda1): recovery complete Sep 4 09:43:16 t520sds kernel: [ 9.645799] EXT4-fs (sda1): mounted filesystem with ordered data mode. Opts: (null) does this mean my HD is bad? As per FaultyHardware, I tried smartctl -l selftest, which uncovered no errors: smartctl 5.41 2011-06-09 r3365 [x86_64-linux-3.2.0-30-generic] (local build) Copyright (C) 2002-11 by Bruce Allen, http://smartmontools.sourceforge.net === START OF INFORMATION SECTION === Model Family: Seagate Momentus 7200.4 Device Model: ST9500420AS Serial Number: 5VJE81YK LU WWN Device Id: 5 000c50 0440defe3 Firmware Version: 0003LVM1 User Capacity: 500,107,862,016 bytes [500 GB] Sector Size: 512 bytes logical/physical Device is: In smartctl database [for details use: -P show] ATA Version is: 8 ATA Standard is: ATA-8-ACS revision 4 Local Time is: Mon Sep 10 16:40:04 2012 EDT SMART support is: Available - device has SMART capability. SMART support is: Enabled === START OF READ SMART DATA SECTION === SMART overall-health self-assessment test result: PASSED See vendor-specific Attribute list for marginal Attributes. General SMART Values: Offline data collection status: (0x82) Offline data collection activity was completed without error. Auto Offline Data Collection: Enabled. Self-test execution status: ( 0) The previous self-test routine completed without error or no self-test has ever been run. Total time to complete Offline data collection: ( 0) seconds. Offline data collection capabilities: (0x7b) SMART execute Offline immediate. Auto Offline data collection on/off support. Suspend Offline collection upon new command. Offline surface scan supported. Self-test supported. Conveyance Self-test supported. Selective Self-test supported. SMART capabilities: (0x0003) Saves SMART data before entering power-saving mode. Supports SMART auto save timer. Error logging capability: (0x01) Error logging supported. General Purpose Logging supported. Short self-test routine recommended polling time: ( 1) minutes. Extended self-test routine recommended polling time: ( 109) minutes. Conveyance self-test routine recommended polling time: ( 2) minutes. SCT capabilities: (0x103b) SCT Status supported. SCT Error Recovery Control supported. SCT Feature Control supported. SCT Data Table supported. SMART Attributes Data Structure revision number: 10 Vendor Specific SMART Attributes with Thresholds: ID# ATTRIBUTE_NAME FLAG VALUE WORST THRESH TYPE UPDATED WHEN_FAILED RAW_VALUE 1 Raw_Read_Error_Rate 0x000f 117 099 034 Pre-fail Always - 162843537 3 Spin_Up_Time 0x0003 100 100 000 Pre-fail Always - 0 4 Start_Stop_Count 0x0032 100 100 020 Old_age Always - 571 5 Reallocated_Sector_Ct 0x0033 100 100 036 Pre-fail Always - 0 7 Seek_Error_Rate 0x000f 069 060 030 Pre-fail Always - 17210154023 9 Power_On_Hours 0x0032 095 095 000 Old_age Always - 174362787320258 10 Spin_Retry_Count 0x0013 100 100 097 Pre-fail Always - 0 12 Power_Cycle_Count 0x0032 100 100 020 Old_age Always - 571 184 End-to-End_Error 0x0032 100 100 099 Old_age Always - 0 187 Reported_Uncorrect 0x0032 100 100 000 Old_age Always - 0 188 Command_Timeout 0x0032 100 100 000 Old_age Always - 1 189 High_Fly_Writes 0x003a 100 100 000 Old_age Always - 0 190 Airflow_Temperature_Cel 0x0022 061 043 045 Old_age Always In_the_past 39 (0 11 44 26) 191 G-Sense_Error_Rate 0x0032 100 100 000 Old_age Always - 84 192 Power-Off_Retract_Count 0x0032 100 100 000 Old_age Always - 20 193 Load_Cycle_Count 0x0032 099 099 000 Old_age Always - 2434 194 Temperature_Celsius 0x0022 039 057 000 Old_age Always - 39 (0 15 0 0) 195 Hardware_ECC_Recovered 0x001a 041 041 000 Old_age Always - 162843537 196 Reallocated_Event_Count 0x000f 095 095 030 Pre-fail Always - 4540 (61955, 0) 197 Current_Pending_Sector 0x0012 100 100 000 Old_age Always - 0 198 Offline_Uncorrectable 0x0010 100 100 000 Old_age Offline - 0 199 UDMA_CRC_Error_Count 0x003e 200 200 000 Old_age Always - 0 254 Free_Fall_Sensor 0x0032 100 100 000 Old_age Always - 0 SMART Error Log Version: 1 No Errors Logged SMART Self-test log structure revision number 1 Num Test_Description Status Remaining LifeTime(hours) LBA_of_first_error # 1 Extended offline Completed without error 00% 4545 - SMART Selective self-test log data structure revision number 1 SPAN MIN_LBA MAX_LBA CURRENT_TEST_STATUS 1 0 0 Not_testing 2 0 0 Not_testing 3 0 0 Not_testing 4 0 0 Not_testing 5 0 0 Not_testing Selective self-test flags (0x0): After scanning selected spans, do NOT read-scan remainder of disk. If Selective self-test is pending on power-up, resume after 0 minute delay. Googling for the messages proved inconclusive, I can't even figure out whether the messages are routine or catastrophic. So, what do I do now?

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• The True Cost of a Solution

  - by D'Arcy Lussier

  I had a Twitter chat recently with someone suggesting Oracle and SQL Server were losing out to OSS (Open Source Software) in the enterprise due to their issues with scaling or being too generic (one size fits all). I challenged that a bit, as my experience with enterprise sized clients has been different – adverse to OSS but receptive to an established vendor. The response I got was: Found it easier to influence change by showing how X can’t solve our problems or X is extremely costly to scale. Money talks. I think this is definitely the right approach for anyone pitching an alternate or alien technology as part of a solution: identify the issue, identify the solution, then present pros and cons including a cost/benefit analysis. What can happen though is we get tunnel vision and don’t present a full view of the costs associated with a solution. An “Acura”te Example (I’m so clever…) This is my dream vehicle, a Crystal Black Pearl coloured Acura MDX with the SH-AWD package! We’re a family of 4 (5 if my daughters ever get their wish of adding a dog), and I’ve always wanted a luxury type of vehicle, so this is a perfect replacement in a few years when our Rav 4 has hit the 8 – 10 year mark. MSRP – $62,890 But as we all know, that’s not *really* the cost of the vehicle. There’s taxes and fees added on, there’s the extended warranty if I choose to purchase it, there’s the finance rate that needs to be factored in… MSRP –   $62,890 Taxes –      $7,546 Warranty - $2,500 SubTotal – $72,936 Finance Charge – $ 1094.04 Grand Total – $74,030 Well! Glad we did that exercise – we discovered an extra $11k added on to the MSRP! Well now we have our true price…or do we? Lifetime of the Vehicle I’m expecting to have this vehicle for 7 – 10 years. While the hard cost of the vehicle is known and dealt with, the costs to run and maintain the vehicle are on top of this. I did some research, and here’s what I’ve found: Fuel and Mileage Gas prices are high as it is for regular fuel, but getting into an MDX will require that I *only* purchase premium fuel, which comes at a premium price. I need to expect my bill at the pump to be higher. Comparing the MDX to my 2007 Rav4 also shows I’ll be gassing up more often. The Rav4 has a city MPG of 21, while the MDX plummets to 16! The MDX does have a bigger fuel tank though, so all in all the number of times I hit the pumps might even out. Still, I estimate I’ll be spending approximately $8000 – $10000 more on gas over a 10 year period than my current Rav4. Service Options Limited Although I have options with my Toyota here in Winnipeg (we have 4 Toyota dealerships), I do go to my original dealer for any service work. Still, I like the fact that I have options. However, there’s only one Acura dealership in all of Winnipeg! So if, for whatever reason, I’m not satisfied with the level of service I’m stuck. Non Warranty Service Work Also let’s not forget that there’s a bulk of work required every year that is *not* covered under warranty – oil changes, tire rotations, brake pads, etc. I expect I’ll need to get new tires at the 5 years mark as well, which can easily be $1200 – $1500 (I just paid $1000 for new tires for the Rav4 and we’re at the 5 year mark). Now these aren’t going to be *new* costs that I’m not used to from our existing vehicles, but they should still be factored in. I’d budget $500/year, or $5000 over the 10 years I’ll own the vehicle. Final Assessment So let’s re-assess the true cost of my dream MDX: MSRP                    $62,890 Taxes                       $7,546 Warranty                 $2,500 Finance Charge         $1094 Gas                        $10,000 Service Work            $5000 Grand Total           $89,030 So now I have a better idea of 10 year cost overall, and I’ve identified some concerns with local service availability. And there’s now much more to consider over the original $62,890 price tag. Tying This Back to Technology Solutions The process that we just went through is no different than what organizations do when considering implementing a new system, technology, or technology based solution, within their environments. It’s easy to tout the short term cost savings of particular product/platform/technology in a vacuum. But its when you consider the wider impact that the true cost comes into play. Let’s create a scenario: A company is not happy with its current data reporting suite. An employee suggests moving to an open source solution. The selling points are: - Because its open source its free - The organization would have access to the source code so they could alter it however they wished - It provided features not available with the current reporting suite At first this sounds great to the management and executive, but then they start asking some questions and uncover more information: - The OSS product is built on a technology not used anywhere within the organization - There are no vendors offering product support for the OSS product - The OSS product requires a specific server platform to operate on, one that’s not standard in the organization All of a sudden, the true cost of implementing this solution is starting to become clearer. The company might save money on licensing costs, but their training costs would increase significantly – developers would need to learn how to develop in the technology the OSS solution was built on, IT staff must learn how to set up and maintain a new server platform within their existing infrastructure, and if a problem was found there was no vendor to contact for support. The true cost of implementing a “free” OSS solution is actually spinning up a project to implement it within the organization – no small cost. And that’s just the short-term cost. Now the organization must ensure they maintain trained staff who can make changes to the OSS reporting solution and IT staff that will stay knowledgeable in the new server platform. If those skills are very niche, then higher labour costs could be incurred if those people are hard to find or if trained employees use that knowledge as leverage for higher pay. Maybe a vendor exists that will contract out support, but then there are those costs to consider as well. And let’s not forget end-user training – in our example, anyone that runs reports will need to be trained on how to use the new system. Here’s the Point We still tend to look at software in an “off the shelf” kind of way. It’s very easy to say “oh, this product is better than vendor x’s product – and its free because its OSS!” but the reality is that implementing any new technology within an organization has a cost regardless of the retail price of the product. Training, integration, support – these are real costs that impact an organization and span multiple departments. Whether you’re pitching an improved business process, a new system, or a new technology, you need to consider the bigger picture costs of implementation. What you define as success (in our example, having better reporting functionality) might not be what others define as success if implementing your solution causes them issues. A true enterprise solution needs to consider the entire enterprise.

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• BI Applications overview

  - by sv744

  Welcome to Oracle BI applications blog! This blog will talk about various features, general roadmap, description of functionality and implementation steps related to Oracle BI applications. In the first post we start with an overview of the BI apps and will delve deeper into some of the topics below in the upcoming weeks and months. If there are other topics you would like us to talk about, pl feel free to provide feedback on that. The Oracle BI applications are a set of pre-built applications that enable pervasive BI by providing role-based insight for each functional area, including sales, service, marketing, contact center, finance, supplier/supply chain, HR/workforce, and executive management. For example, Sales Analytics includes role-based applications for sales executives, sales management, as well as front-line sales reps, each of whom have different needs. The applications integrate and transform data from a range of enterprise sources—including Siebel, Oracle, PeopleSoft, SAP, and others—into actionable intelligence for each business function and user role. This blog  starts with the key benefits and characteristics of Oracle BI applications. In a series of subsequent blogs, each of these points will be explained in detail. Why BI apps? Demonstrate the value of BI to a business user, show reports / dashboards / model that can answer their business questions as part of the sales cycle. Demonstrate technical feasibility of BI project and significantly lower risk and improve success Build Vs Buy benefit Don’t have to start with a blank sheet of paper. Help consolidate disparate systems Data integration in M&A situations Insulate BI consumers from changes in the OLTP Present OLTP data and highlight issues of poor data / missing data – and improve data quality and accuracy Prebuilt Integrations BI apps support prebuilt integrations against leading ERP sources: Fusion Applications, E- Business Suite, Peoplesoft, JD Edwards, Siebel, SAP Co-developed with inputs from functional experts in BI and Applications teams. Out of the box dimensional model to source model mappings Multi source and Multi Instance support Rich Data Model    BI apps have a very rich dimensionsal data model built over 10 years that incorporates best practises from BI modeling perspective as well as reflect the source system complexities  Thanks for reading a long post, and be on the lookout for future posts.  We will look forward to your valuable feedback on these topics as well as suggestions on what other topics would you like us to cover. I Conformed dimensional model across all business subject areas allows cross functional reporting, e.g. customer / supplier 360 Over 360 fact tables across 7 product areas CRM – 145, SCM – 47, Financials – 28, Procurement – 20, HCM – 27, Projects – 18, Campus Solutions – 21, PLM - 56 Supported by 300 physical dimensions Support for extensive calendars; Gregorian, enterprise and ledger based Conformed data model and metrics for real time vs warehouse based reporting  Multi-tenant enabled Extensive BI related transformations BI apps ETL and data integration support various transformations required for dimensional models and reporting requirements. All these have been distilled into common patterns and abstracted logic which can be readily reused across different modules Slowly Changing Dimension support Hierarchy flattening support Row / Column Hybrid Hierarchy Flattening As Is vs. As Was hierarchy support Currency Conversion :-  Support for 3 corporate, CRM, ledger and transaction currencies UOM conversion Internationalization / Localization Dynamic Data translations Code standardization (Domains) Historical Snapshots Cycle and process lifecycle computations Balance Facts Equalization of GL accounting chartfields/segments Standardized values for categorizing GL accounts Reconciliation between GL and subledgers to track accounted/transferred/posted transactions to GL Materialization of data only available through costly and complex APIs e.g. Fusion Payroll, EBS / Fusion Accruals Complex event Interpretation of source data – E.g. o    What constitutes a transfer o    Deriving supervisors via position hierarchy o    Deriving primary assignment in PSFT o    Categorizing and transposition to measures of Payroll Balances to specific metrics to support side by side comparison of measures of for example Fixed Salary, Variable Salary, Tax, Bonus, Overtime Payments. o    Counting of Events – E.g. converting events to fact counters so that for example the number of hires can easily be added up and compared alongside the total transfers and terminations. Multi pass processing of multiple sources e.g. headcount, salary, promotion, performance to allow side to side comparison. Adding value to data to aid analysis through banding, additional domain classifications and groupings to allow higher level analytical reporting and data discovery Calculation of complex measures examples: o    COGs, DSO, DPO, Inventory turns  etc o    Transfers within a Hierarchy or out of / into a hierarchy relative to view point in hierarchy. Configurability and Extensibility support  BI apps offer support for extensibility for various entities as automated extensibility or part of extension methodology Key Flex fields and Descriptive Flex support  Extensible attribute support (JDE)  Conformed Domains ETL Architecture BI apps offer a modular adapter architecture which allows support of multiple product lines into a single conformed model Multi Source Multi Technology Orchestration – creates load plan taking into account task dependencies and customers deployment to generate a plan based on a customers of multiple complex etl tasks Plan optimization allowing parallel ETL tasks Oracle: Bit map indexes and partition management High availability support    Follow the sun support. TCO BI apps support several utilities / capabilities that help with overall total cost of ownership and ensure a rapid implementation Improved cost of ownership – lower cost to deploy On-going support for new versions of the source application Task based setups flows Data Lineage Functional setup performed in Web UI by Functional person Configuration Test to Production support Security BI apps support both data and object security enabling implementations to quickly configure the application as per the reporting security needs Fine grain object security at report / dashboard and presentation catalog level Data Security integration with source systems  Extensible to support external data security rules Extensive Set of KPIs Over 7000 base and derived metrics across all modules Time series calculations (YoY, % growth etc) Common Currency and UOM reporting Cross subject area KPIs (analyzing HR vs GL data, drill from GL to AP/AR, etc) Prebuilt reports and dashboards 3000+ prebuilt reports supporting a large number of industries Hundreds of role based dashboards Dynamic currency conversion at dashboard level Highly tuned Performance The BI apps have been tuned over the years for both a very performant ETL and dashboard performance. The applications use best practises and advanced database features to enable the best possible performance. Optimized data model for BI and analytic queries Prebuilt aggregates& the ability for customers to create their own aggregates easily on warehouse facts allows for scalable end user performance Incremental extracts and loads Incremental Aggregate build Automatic table index and statistics management Parallel ETL loads Source system deletes handling Low latency extract with Golden Gate Micro ETL support Bitmap Indexes Partitioning support Modularized deployment, start small and add other subject areas seamlessly Source Specfic Staging and Real Time Schema Support for source specific operational reporting schema for EBS, PSFT, Siebel and JDE Application Integrations The BI apps also allow for integration with source systems as well as other applications that provide value add through BI and enable BI consumption during operational decision making Embedded dashboards for Fusion, EBS and Siebel applications Action Link support Marketing Segmentation Sales Predictor Dashboard Territory Management External Integrations The BI apps data integration choices include support for loading extenral data External data enrichment choices : UNSPSC, Item class etc. Extensible Spend Classification Broad Deployment Choices Exalytics support Databases :  Oracle, Exadata, Teradata, DB2, MSSQL ETL tool of choice : ODI (coming), Informatica Extensible and Customizable Extensible architecture and Methodology to add custom and external content Upgradable across releases

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• ?Oracle????SELECT????UNDO

  - by Liu Maclean(???)

  ????????Oracle?????(dirty read),?Oracle??????Asktom????????Oracle???????, ???undo??????????(before image)??????Consistent, ???????????????Oracle????????????? ????????? ??,??,Oracle?????????????RDBMS,???????????? ?????????2?????: _offline_rollback_segments or _corrupted_rollback_segments ?2?????????Oracle???????????ORA-600[4XXX]???????????????,???2??????Undo??Corruption????????????,?????2????????????????? ??????????????_offline_rollback_segments ? _corrupted_rollback_segments ?2?????: ???????(FORCE OPEN DATABASE) ????????????(consistent read & delayed block cleanout) ??????rollback segment??? ?????:???????Oracle????????,??????????2?????,?????????????!! _offline_rollback_segments ? _corrupted_rollback_segments ???????????: ??2???????Undo Segments(???/???)????????online ?UNDO$???????????OFFLINE??? ???instance??????????????????? ??????Undo Segments????????active transaction????????????dead??SMON???(????????SMON??(?):Recover Dead transaction) _OFFLINE_ROLLBACK_SEGMENTS(offline undo segment list)????(hidden parameter)?????: ???startup???open database???????_OFFLINE_ROLLBACK_SEGMENTS????Undo segments(???/???),?????undo segments????????alert.log???TRACE?????,???????startup?? ?????????????,?ITL?????undo segments?: ???undo segments?transaction table?????????????????? ???????????commit,?????CR??? ????undo segments????(???corrupted??,???missed??)???????????alert.log,??????? ?DML?????????????????????????????????CPU,????????????????????? _CORRUPTED_ROLLBACK_SEGMENTS(corrupted undo segment list)??????????: ?????startup?open database???_CORRUPTED_ROLLBACK_SEGMENTS????undo segments(???/???)???????? ???????_CORRUPTED_ROLLBACK_SEGMENTS???undo segments????????????commit,???undo segments???drop??? ??????????? ??????????????????,?????????????????? ??bootstrap???????????,?????????ORA-00704: bootstrap process failure??,???????????(???Oracle????:??ORA-00600:[4000] ORA-00704: bootstrap process failure????) ??????_CORRUPTED_ROLLBACK_SEGMENTS????????????????????,??????????????? Oracle???????TXChecker??????????? ???????2?????,??????????????_CORRUPTED_ROLLBACK_SEGMENTS?????SELECT????UNDO???????: SQL> alter system set event= '10513 trace name context forever, level 2' scope=spfile; System altered. SQL> alter system set "_in_memory_undo"=false scope=spfile; System altered. 10513 level 2 event????SMON ??rollback ??? dead transaction _in_memory_undo ?? in memory undo ?? SQL> startup force; ORACLE instance started. Total System Global Area 3140026368 bytes Fixed Size 2232472 bytes Variable Size 1795166056 bytes Database Buffers 1325400064 bytes Redo Buffers 17227776 bytes Database mounted. Database opened. session A: SQL> conn maclean/maclean Connected. SQL> create table maclean tablespace users as select 1 t1 from dual connect by level exec dbms_stats.gather_table_stats('','MACLEAN'); PL/SQL procedure successfully completed. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 1 recursive calls 0 db block gets 3 consistent gets 0 physical reads 0 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processe ???????????,????current block, ????????,consistent gets??3? SQL> update maclean set t1=0; 501 rows updated. SQL> alter system checkpoint; System altered. ??session A?commit; ???? session: SQL> conn maclean/maclean Connected. SQL> SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 505 consistent gets 0 physical reads 108 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ?????? ?????????undo??CR?,???consistent gets??? 505 [oracle@vrh8 ~]$ ps -ef|grep LOCAL=YES |grep -v grep oracle 5841 5839 0 09:17 ? 00:00:00 oracleG10R25 (DESCRIPTION=(LOCAL=YES)(ADDRESS=(PROTOCOL=beq))) [oracle@vrh8 ~]$ kill -9 5841 ??session A???Server Process????,???dead transaction ????smon?? select ktuxeusn, to_char(sysdate, 'DD-MON-YYYY HH24:MI:SS') "Time", ktuxesiz, ktuxesta from x$ktuxe where ktuxecfl = 'DEAD'; KTUXEUSN Time KTUXESIZ KTUXESTA ---------- -------------------- ---------- ---------------- 2 06-AUG-2012 09:20:45 7 ACTIVE ???1?active rollback segment SQL> conn maclean/maclean Connected. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 501 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 411 consistent gets 0 physical reads 108 redo size 515 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ????? ????kill?? ???smon ??dead transaction , ???????????? ?????undo??????? ????active?rollback segment??? SQL> select segment_name from dba_rollback_segs where segment_id=2; SEGMENT_NAME ------------------------------ _SYSSMU2$ SQL> alter system set "_corrupted_rollback_segments"='_SYSSMU2$' scope=spfile; System altered. ? _corrupted_rollback_segments ?? ???2?rollback segment, ????????undo SQL> startup force; ORACLE instance started. Total System Global Area 3140026368 bytes Fixed Size 2232472 bytes Variable Size 1795166056 bytes Database Buffers 1325400064 bytes Redo Buffers 17227776 bytes Database mounted. Database opened. SQL> conn maclean/maclean Connected. SQL> set autotrace on; SQL> select sum(t1) from maclean; SUM(T1) ---------- 94 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 228 recursive calls 0 db block gets 29 consistent gets 5 physical reads 116 redo size 514 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 4 sorts (memory) 0 sorts (disk) 1 rows processed SQL> / SUM(T1) ---------- 94 Execution Plan ---------------------------------------------------------- Plan hash value: 1679547536 ------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 1 | 3 | 3 (0)| 00:00:01 | | 1 | SORT AGGREGATE | | 1 | 3 | | | | 2 | TABLE ACCESS FULL| MACLEAN | 501 | 1503 | 3 (0)| 00:00:01 | ------------------------------------------------------------------------------ Statistics ---------------------------------------------------------- 0 recursive calls 0 db block gets 3 consistent gets 0 physical reads 0 redo size 514 bytes sent via SQL*Net to client 492 bytes received via SQL*Net from client 2 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 1 rows processed ?????? consistent gets???3,?????????????????,??ITL???UNDO SEGMENTS?_corrupted_rollback_segments????,???????????COMMIT??,????UNDO? ???????,?????????????????????????(????????????????????),????????????????? ???? , ?????

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• how to use 3D map Actionscript class in mxml file for display map.

  - by nemade-vipin

  hello friends, I have created the application in which I have to use 3D map Action Script class in mxml file to display a map in form. that is in tab navigator last tab. My ActionScript 3D map class is(FlyingDirections):- package src.SBTSCoreObject { import src.SBTSCoreObject.JSONDecoder; import com.google.maps.InfoWindowOptions; import com.google.maps.LatLng; import com.google.maps.LatLngBounds; import com.google.maps.Map3D; import com.google.maps.MapEvent; import com.google.maps.MapOptions; import com.google.maps.MapType; import com.google.maps.MapUtil; import com.google.maps.View; import com.google.maps.controls.NavigationControl; import com.google.maps.geom.Attitude; import com.google.maps.interfaces.IPolyline; import com.google.maps.overlays.Marker; import com.google.maps.overlays.MarkerOptions; import com.google.maps.services.Directions; import com.google.maps.services.DirectionsEvent; import com.google.maps.services.Route; import flash.display.Bitmap; import flash.display.DisplayObject; import flash.display.DisplayObjectContainer; import flash.display.Loader; import flash.display.LoaderInfo; import flash.display.Sprite; import flash.events.Event; import flash.events.IOErrorEvent; import flash.events.MouseEvent; import flash.events.TimerEvent; import flash.filters.DropShadowFilter; import flash.geom.Point; import flash.net.URLLoader; import flash.net.URLRequest; import flash.net.navigateToURL; import flash.text.TextField; import flash.text.TextFieldAutoSize; import flash.text.TextFormat; import flash.utils.Timer; import flash.utils.getTimer; public class FlyingDirections extends Map3D { /** * Panoramio home page. */ private static const PANORAMIO_HOME:String = "http://www.panoramio.com/"; /** * The icon for the car. */ [Embed("assets/car-icon-24px.png")] private static const Car:Class; /** * The Panoramio icon. */ [Embed("assets/iw_panoramio.png")] private static const PanoramioIcon:Class; /** * We animate a zoom in to the start the route before the car starts * to move. This constant sets the time in seconds over which this * zoom occurs. */ private static const LEAD_IN_DURATION:Number = 3; /** * Duration of the trip in seconds. */ private static const TRIP_DURATION:Number = 40; /** * Constants that define the geometry of the Panoramio image markers. */ private static const BORDER_T:Number = 3; private static const BORDER_L:Number = 10; private static const BORDER_R:Number = 10; private static const BORDER_B:Number = 3; private static const GAP_T:Number = 2; private static const GAP_B:Number = 1; private static const IMAGE_SCALE:Number = 1; /** * Trajectory that the camera follows over time. Each element is an object * containing properties used to generate parameter values for flyTo(..). * fraction = 0 corresponds to the start of the trip; fraction = 1 * correspondsto the end of the trip. */ private var FLY_TRAJECTORY:Array = [ { fraction: 0, zoom: 6, attitude: new Attitude(0, 0, 0) }, { fraction: 0.2, zoom: 8.5, attitude: new Attitude(30, 30, 0) }, { fraction: 0.5, zoom: 9, attitude: new Attitude(30, 40, 0) }, { fraction: 1, zoom: 8, attitude: new Attitude(50, 50, 0) }, { fraction: 1.1, zoom: 8, attitude: new Attitude(130, 50, 0) }, { fraction: 1.2, zoom: 8, attitude: new Attitude(220, 50, 0) }, ]; /** * Number of panaramio photos for which we load data. We&apos;ll select a * subset of these approximately evenly spaced along the route. */ private static const NUM_GEOTAGGED_PHOTOS:int = 50; /** * Number of panaramio photos that we actually show. */ private static const NUM_SHOWN_PHOTOS:int = 7; /** * Scaling between real trip time and animation time. */ private static const SCALE_TIME:Number = 0.001; /** * getTimer() value at the instant that we start the trip. If this is 0 then * we have not yet started the car moving. */ private var startTimer:int = 0; /** * The current route. */ private var route:Route; /** * The polyline for the route. */ private var polyline:IPolyline; /** * The car marker. */ private var marker:Marker; /** * The cumulative duration in seconds over each step in the route. * cumulativeStepDuration[0] is 0; cumulativeStepDuration[1] adds the * duration of step 0; cumulativeStepDuration[2] adds the duration * of step 1; etc. */ private var cumulativeStepDuration:/*Number*/Array = []; /** * The cumulative distance in metres over each vertex in the route polyline. * cumulativeVertexDistance[0] is 0; cumulativeVertexDistance[1] adds the * distance to vertex 1; cumulativeVertexDistance[2] adds the distance to * vertex 2; etc. */ private var cumulativeVertexDistance:Array; /** * Array of photos loaded from Panoramio. This array has the same format as * the &apos;photos&apos; property within the JSON returned by the Panoramio API * (see http://www.panoramio.com/api/), with additional properties added to * individual photo elements to hold the loader structures that fetch * the actual images. */ private var photos:Array = []; /** * Array of polyline vertices, where each element is in world coordinates. * Several computations can be faster if we can use world coordinates * instead of LatLng coordinates. */ private var worldPoly:/*Point*/Array; /** * Whether the start button has been pressed. */ private var startButtonPressed:Boolean = false; /** * Saved event from onDirectionsSuccess call. */ private var directionsSuccessEvent:DirectionsEvent = null; /** * Start button. */ private var startButton:Sprite; /** * Alpha value used for the Panoramio image markers. */ private var markerAlpha:Number = 0; /** * Index of the current driving direction step. Used to update the * info window content each time we progress to a new step. */ private var currentStepIndex:int = -1; /** * The fly directions map constructor. * * @constructor */ public function FlyingDirections() { key="ABQIAAAA7QUChpcnvnmXxsjC7s1fCxQGj0PqsCtxKvarsoS-iqLdqZSKfxTd7Xf-2rEc_PC9o8IsJde80Wnj4g"; super(); addEventListener(MapEvent.MAP_PREINITIALIZE, onMapPreinitialize); addEventListener(MapEvent.MAP_READY, onMapReady); } /** * Handles map preintialize. Initializes the map center and zoom level. * * @param event The map event. */ private function onMapPreinitialize(event:MapEvent):void { setInitOptions(new MapOptions({ center: new LatLng(-26.1, 135.1), zoom: 4, viewMode: View.VIEWMODE_PERSPECTIVE, mapType:MapType.PHYSICAL_MAP_TYPE })); } /** * Handles map ready and looks up directions. * * @param event The map event. */ private function onMapReady(event:MapEvent):void { enableScrollWheelZoom(); enableContinuousZoom(); addControl(new NavigationControl()); // The driving animation will be updated on every frame. addEventListener(Event.ENTER_FRAME, enterFrame); addStartButton(); // We start the directions loading now, so that we&apos;re ready to go when // the user hits the start button. var directions:Directions = new Directions(); directions.addEventListener( DirectionsEvent.DIRECTIONS_SUCCESS, onDirectionsSuccess); directions.addEventListener( DirectionsEvent.DIRECTIONS_FAILURE, onDirectionsFailure); directions.load("48 Pirrama Rd, Pyrmont, NSW to Byron Bay, NSW"); } /** * Adds a big blue start button. */ private function addStartButton():void { startButton = new Sprite(); startButton.buttonMode = true; startButton.addEventListener(MouseEvent.CLICK, onStartClick); startButton.graphics.beginFill(0x1871ce); startButton.graphics.drawRoundRect(0, 0, 150, 100, 10, 10); startButton.graphics.endFill(); var startField:TextField = new TextField(); startField.autoSize = TextFieldAutoSize.LEFT; startField.defaultTextFormat = new TextFormat("_sans", 20, 0xffffff, true); startField.text = "Start!"; startButton.addChild(startField); startField.x = 0.5 * (startButton.width - startField.width); startField.y = 0.5 * (startButton.height - startField.height); startButton.filters = [ new DropShadowFilter() ]; var container:DisplayObjectContainer = getDisplayObject() as DisplayObjectContainer; container.addChild(startButton); startButton.x = 0.5 * (container.width - startButton.width); startButton.y = 0.5 * (container.height - startButton.height); var panoField:TextField = new TextField(); panoField.autoSize = TextFieldAutoSize.LEFT; panoField.defaultTextFormat = new TextFormat("_sans", 11, 0x000000, true); panoField.text = "Photos provided by Panoramio are under the copyright of their owners."; container.addChild(panoField); panoField.x = container.width - panoField.width - 5; panoField.y = 5; } /** * Handles directions success. Starts flying the route if everything * is ready. * * @param event The directions event. */ private function onDirectionsSuccess(event:DirectionsEvent):void { directionsSuccessEvent = event; flyRouteIfReady(); } /** * Handles click on the start button. Starts flying the route if everything * is ready. */ private function onStartClick(event:MouseEvent):void { startButton.removeEventListener(MouseEvent.CLICK, onStartClick); var container:DisplayObjectContainer = getDisplayObject() as DisplayObjectContainer; container.removeChild(startButton); startButtonPressed = true; flyRouteIfReady(); } /** * If we have loaded the directions and the start button has been pressed * start flying the directions route. */ private function flyRouteIfReady():void { if (!directionsSuccessEvent || !startButtonPressed) { return; } var directions:Directions = directionsSuccessEvent.directions; // Extract the route. route = directions.getRoute(0); // Draws the polyline showing the route. polyline = directions.createPolyline(); addOverlay(directions.createPolyline()); // Creates a car marker that is moved along the route. var car:DisplayObject = new Car(); marker = new Marker(route.startGeocode.point, new MarkerOptions({ icon: car, iconOffset: new Point(-car.width / 2, -car.height) })); addOverlay(marker); transformPolyToWorld(); createCumulativeArrays(); // Load Panoramio data for the region covered by the route. loadPanoramioData(directions.bounds); var duration:Number = route.duration; // Start a timer that will trigger the car moving after the lead in time. var leadInTimer:Timer = new Timer(LEAD_IN_DURATION * 1000, 1); leadInTimer.addEventListener(TimerEvent.TIMER, onLeadInDone); leadInTimer.start(); var flyTime:Number = -LEAD_IN_DURATION; // Set up the camera flight trajectory. for each (var flyStep:Object in FLY_TRAJECTORY) { var time:Number = flyStep.fraction * duration; var center:LatLng = latLngAt(time); var scaledTime:Number = time * SCALE_TIME; var zoom:Number = flyStep.zoom; var attitude:Attitude = flyStep.attitude; var elapsed:Number = scaledTime - flyTime; flyTime = scaledTime; flyTo(center, zoom, attitude, elapsed); } } /** * Loads Panoramio data for the route bounds. We load data about more photos * than we need, then select a subset lying along the route. * @param bounds Bounds within which to fetch images. */ private function loadPanoramioData(bounds:LatLngBounds):void { var params:Object = { order: "popularity", set: "full", from: "0", to: NUM_GEOTAGGED_PHOTOS.toString(10), size: "small", minx: bounds.getWest(), miny: bounds.getSouth(), maxx: bounds.getEast(), maxy: bounds.getNorth() }; var loader:URLLoader = new URLLoader(); var request:URLRequest = new URLRequest( "http://www.panoramio.com/map/get_panoramas.php?" + paramsToString(params)); loader.addEventListener(Event.COMPLETE, onPanoramioDataLoaded); loader.addEventListener(IOErrorEvent.IO_ERROR, onPanoramioDataFailed); loader.load(request); } /** * Transforms the route polyline to world coordinates. */ private function transformPolyToWorld():void { var numVertices:int = polyline.getVertexCount(); worldPoly = new Array(numVertices); for (var i:int = 0; i < numVertices; ++i) { var vertex:LatLng = polyline.getVertex(i); worldPoly[i] = fromLatLngToPoint(vertex, 0); } } /** * Returns the time at which the route approaches closest to the * given point. * @param world Point in world coordinates. * @return Route time at which the closest approach occurs. */ private function getTimeOfClosestApproach(world:Point):Number { var minDistSqr:Number = Number.MAX_VALUE; var numVertices:int = worldPoly.length; var x:Number = world.x; var y:Number = world.y; var minVertex:int = 0; for (var i:int = 0; i < numVertices; ++i) { var dx:Number = worldPoly[i].x - x; var dy:Number = worldPoly[i].y - y; var distSqr:Number = dx * dx + dy * dy; if (distSqr < minDistSqr) { minDistSqr = distSqr; minVertex = i; } } return cumulativeVertexDistance[minVertex]; } /** * Returns the array index of the first element that compares greater than * the given value. * @param ordered Ordered array of elements. * @param value Value to use for comparison. * @return Array index of the first element that compares greater than * the given value. */ private function upperBound(ordered:Array, value:Number, first:int=0, last:int=-1):int { if (last < 0) { last = ordered.length; } var count:int = last - first; var index:int; while (count > 0) { var step:int = count >> 1; index = first + step; if (value >= ordered[index]) { first = index + 1; count -= step - 1; } else { count = step; } } return first; } /** * Selects up to a given number of photos approximately evenly spaced along * the route. * @param ordered Array of photos, each of which is an object with * a property &apos;closestTime&apos;. * @param number Number of photos to select. */ private function selectEvenlySpacedPhotos(ordered:Array, number:int):Array { var start:Number = cumulativeVertexDistance[0]; var end:Number = cumulativeVertexDistance[cumulativeVertexDistance.length - 2]; var closestTimes:Array = []; for each (var photo:Object in ordered) { closestTimes.push(photo.closestTime); } var selectedPhotos:Array = []; for (var i:int = 0; i < number; ++i) { var idealTime:Number = start + ((end - start) * (i + 0.5) / number); var index:int = upperBound(closestTimes, idealTime); if (index < 1) { index = 0; } else if (index >= ordered.length) { index = ordered.length - 1; } else { var errorToPrev:Number = Math.abs(idealTime - closestTimes[index - 1]); var errorToNext:Number = Math.abs(idealTime - closestTimes[index]); if (errorToPrev < errorToNext) { --index; } } selectedPhotos.push(ordered[index]); } return selectedPhotos; } /** * Handles completion of loading the Panoramio index data. Selects from the * returned photo indices a subset of those that lie along the route and * initiates load of each of these. * @param event Load completion event. */ private function onPanoramioDataLoaded(event:Event):void { var loader:URLLoader = event.target as URLLoader; var decoder:JSONDecoder = new JSONDecoder(loader.data as String); var allPhotos:Array = decoder.getValue().photos; for each (var photo:Object in allPhotos) { var latLng:LatLng = new LatLng(photo.latitude, photo.longitude); photo.closestTime = getTimeOfClosestApproach(fromLatLngToPoint(latLng, 0)); } allPhotos.sortOn("closestTime", Array.NUMERIC); photos = selectEvenlySpacedPhotos(allPhotos, NUM_SHOWN_PHOTOS); for each (photo in photos) { var photoLoader:Loader = new Loader(); // The images aren&apos;t on panoramio.com: we can&apos;t acquire pixel access // using "new LoaderContext(true)". photoLoader.load( new URLRequest(photo.photo_file_url)); photo.loader = photoLoader; // Save the loader info: we use this to find the original element when // the load completes. photo.loaderInfo = photoLoader.contentLoaderInfo; photoLoader.contentLoaderInfo.addEventListener( Event.COMPLETE, onPhotoLoaded); } } /** * Creates a MouseEvent listener function that will navigate to the given * URL in a new window. * @param url URL to which to navigate. */ private function createOnClickUrlOpener(url:String):Function { return function(event:MouseEvent):void { navigateToURL(new URLRequest(url)); }; } /** * Handles completion of loading an individual Panoramio image. * Adds a custom marker that displays the image. Initially this is made * invisible so that it can be faded in as needed. * @param event Load completion event. */ private function onPhotoLoaded(event:Event):void { var loaderInfo:LoaderInfo = event.target as LoaderInfo; // We need to find which photo element this image corresponds to. for each (var photo:Object in photos) { if (loaderInfo == photo.loaderInfo) { var imageMarker:Sprite = createImageMarker(photo.loader, photo.owner_name, photo.owner_url); var options:MarkerOptions = new MarkerOptions({ icon: imageMarker, hasShadow: true, iconAlignment: MarkerOptions.ALIGN_BOTTOM | MarkerOptions.ALIGN_LEFT }); var latLng:LatLng = new LatLng(photo.latitude, photo.longitude); var marker:Marker = new Marker(latLng, options); photo.marker = marker; addOverlay(marker); // A hack: we add the actual image after the overlay has been added, // which creates the shadow, so that the shadow is valid even if we // don&apos;t have security privileges to generate the shadow from the // image. marker.foreground.visible = false; marker.shadow.alpha = 0; var imageHolder:Sprite = new Sprite(); imageHolder.addChild(photo.loader); imageHolder.buttonMode = true; imageHolder.addEventListener( MouseEvent.CLICK, createOnClickUrlOpener(photo.photo_url)); imageMarker.addChild(imageHolder); return; } } trace("An image was loaded which could not be found in the photo array."); } /** * Creates a custom marker showing an image. */ private function createImageMarker(child:DisplayObject, ownerName:String, ownerUrl:String):Sprite { var content:Sprite = new Sprite(); var panoramioIcon:Bitmap = new PanoramioIcon(); var iconHolder:Sprite = new Sprite(); iconHolder.addChild(panoramioIcon); iconHolder.buttonMode = true; iconHolder.addEventListener(MouseEvent.CLICK, onPanoramioIconClick); panoramioIcon.x = BORDER_L; panoramioIcon.y = BORDER_T; content.addChild(iconHolder); // NOTE: we add the image as a child only after we&apos;ve added the marker // to the map. Currently the API requires this if it&apos;s to generate the // shadow for unprivileged content. // Shrink the image, so that it doesn&apos;t obcure too much screen space. // Ideally, we&apos;d subsample, but we don&apos;t have pixel level access. child.scaleX = IMAGE_SCALE; child.scaleY = IMAGE_SCALE; var imageW:Number = child.width; var imageH:Number = child.height; child.x = BORDER_L + 30; child.y = BORDER_T + iconHolder.height + GAP_T; var authorField:TextField = new TextField(); authorField.autoSize = TextFieldAutoSize.LEFT; authorField.defaultTextFormat = new TextFormat("_sans", 12); authorField.text = "author:"; content.addChild(authorField); authorField.x = BORDER_L; authorField.y = BORDER_T + iconHolder.height + GAP_T + imageH + GAP_B; var ownerField:TextField = new TextField(); ownerField.autoSize = TextFieldAutoSize.LEFT; var textFormat:TextFormat = new TextFormat("_sans", 14, 0x0e5f9a); ownerField.defaultTextFormat = textFormat; ownerField.htmlText = "<a href=\"" + ownerUrl + "\" target=\"_blank\">" + ownerName + "</a>"; content.addChild(ownerField); ownerField.x = BORDER_L + authorField.width; ownerField.y = BORDER_T + iconHolder.height + GAP_T + imageH + GAP_B; var totalW:Number = BORDER_L + Math.max(imageW, ownerField.width + authorField.width) + BORDER_R; var totalH:Number = BORDER_T + iconHolder.height + GAP_T + imageH + GAP_B + ownerField.height + BORDER_B; content.graphics.beginFill(0xffffff); content.graphics.drawRoundRect(0, 0, totalW, totalH, 10, 10); content.graphics.endFill(); var marker:Sprite = new Sprite(); marker.addChild(content); content.x = 30; content.y = 0; marker.graphics.lineStyle(); marker.graphics.beginFill(0xff0000); marker.graphics.drawCircle(0, totalH + 30, 3); marker.graphics.endFill(); marker.graphics.lineStyle(2, 0xffffff); marker.graphics.moveTo(30 + 10, totalH - 10); marker.graphics.lineTo(0, totalH + 30); return marker; } /** * Handles click on the Panoramio icon. */ private function onPanoramioIconClick(event:MouseEvent):void { navigateToURL(new URLRequest(PANORAMIO_HOME)); } /** * Handles failure of a Panoramio image load. */ private function onPanoramioDataFailed(event:IOErrorEvent):void { trace("Load of image failed: " + event); } /** * Returns a string containing cgi query parameters. * @param Associative array mapping query parameter key to value. * @return String containing cgi query parameters. */ private static function paramsToString(params:Object):String { var result:String = ""; var separator:String = ""; for (var key:String in params) { result += separator + encodeURIComponent(key) + "=" + encodeURIComponent(params[key]); separator = "&"; } return result; } /** * Called once the lead-in flight is done. Starts the car driving along * the route and starts a timer to begin fade in of the Panoramio * images in 1.5 seconds. */ private function onLeadInDone(event:Event):void { // Set startTimer non-zero so that the car starts to move. startTimer = getTimer(); // Start a timer that will fade in the Panoramio images. var fadeInTimer:Timer = new Timer(1500, 1); fadeInTimer.addEventListener(TimerEvent.TIMER, onFadeInTimer); fadeInTimer.start(); } /** * Handles the fade in timer&apos;s TIMER event. Sets markerAlpha above zero * which causes the frame enter handler to fade in the markers. */ private function onFadeInTimer(event:Event):void { markerAlpha = 0.01; } /** * The end time of the flight. */ private function get endTime():Number { if (!cumulativeStepDuration || cumulativeStepDuration.length == 0) { return startTimer; } return startTimer + cumulativeStepDuration[cumulativeStepDuration.length - 1]; } /** * Creates the cumulative arrays, cumulativeStepDuration and * cumulativeVertexDistance. */ private function createCumulativeArrays():void { cumulativeStepDuration = new Array(route.numSteps + 1); cumulativeVertexDistance = new Array(polyline.getVertexCount() + 1); var polylineTotal:Number = 0; var total:Number = 0; var numVertices:int = polyline.getVertexCount(); for (var stepIndex:int = 0; stepIndex < route.numSteps; ++stepIndex) { cumulativeStepDuration[stepIndex] = total; total += route.getStep(stepIndex).duration; var startVertex:int = stepIndex >= 0 ? route.getStep(stepIndex).polylineIndex : 0; var endVertex:int = stepIndex < (route.numSteps - 1) ? route.getStep(stepIndex + 1).polylineIndex : numVertices; var duration:Number = route.getStep(stepIndex).duration; var stepVertices:int = endVertex - startVertex; var latLng:LatLng = polyline.getVertex(startVertex); for (var vertex:int = startVertex; vertex < endVertex; ++vertex) { cumulativeVertexDistance[vertex] = polylineTotal; if (vertex < numVertices - 1) { var nextLatLng:LatLng = polyline.getVertex(vertex + 1); polylineTotal += nextLatLng.distanceFrom(latLng); } latLng = nextLatLng; } } cumulativeStepDuration[stepIndex] = total; } /** * Opens the info window above the car icon that details the given * step of the driving directions. * @param stepIndex Index of the current step. */ private function openInfoForStep(stepIndex:int):void { // Sets the content of the info window. var content:String; if (stepIndex >= route.numSteps) { content = "<b>" + route.endGeocode.address + "</b>" + "<br /><br />" + route.summaryHtml; } else { content = "<b>" + stepIndex + ".</b> " + route.getStep(stepIndex).descriptionHtml; } marker.openInfoWindow(new InfoWindowOptions({ contentHTML: content })); } /** * Displays the driving directions step appropriate for the given time. * Opens the info window showing the step instructions each time we * progress to a new step. * @param time Time for which to display the step. */ private function displayStepAt(time:Number):void { var stepIndex:int = upperBound(cumulativeStepDuration, time) - 1; var minStepIndex:int = 0; var maxStepIndex:int = route.numSteps - 1; if (stepIndex >= 0 && stepIndex <= maxStepIndex && currentStepIndex != stepIndex) { openInfoForStep(stepIndex); currentStepIndex = stepIndex; } } /** * Returns the LatLng at which the car should be positioned at the given * time. * @param time Time for which LatLng should be found. * @return LatLng. */ private function latLngAt(time:Number):LatLng { var stepIndex:int = upperBound(cumulativeStepDuration, time) - 1; var minStepIndex:int = 0; var maxStepIndex:int = route.numSteps - 1; if (stepIndex < minStepIndex) { return route.startGeocode.point; } else if (stepIndex > maxStepIndex) { return route.endGeocode.point; } var stepStart:Number = cumulativeStepDuration[stepIndex]; var stepEnd:Number = cumulativeStepDuration[stepIndex + 1]; var stepFraction:Number = (time - stepStart) / (stepEnd - stepStart); var startVertex:int = route.getStep(stepIndex).polylineIndex; var endVertex:int = (stepIndex + 1) < route.numSteps ? route.getStep(stepIndex + 1).polylineIndex : polyline.getVertexCount(); var stepVertices:int = endVertex - startVertex; var stepLeng

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• datagrid binding

  - by abcdd007

  using System; using System.Data; using System.Configuration; using System.Collections; using System.Web; using System.Web.Security; using System.Web.UI; using System.Web.UI.WebControls; using System.Web.UI.WebControls.WebParts; using System.Web.UI.HtmlControls; using System.Data.SqlClient; public partial class OrderMaster : System.Web.UI.Page { BLLOrderMaster objMaster = new BLLOrderMaster(); protected void Page_Load(object sender, EventArgs e) { if (!Page.IsPostBack) { SetInitialRow(); string OrderNumber = objMaster.SelectDetails().ToString(); if (OrderNumber != "") { txtOrderNo.Text = OrderNumber.ToString(); txtOrderDate.Focus(); } } } private void InsertEmptyRow() { DataTable dt = new DataTable(); DataRow dr = null; dt.Columns.Add(new DataColumn("ItemCode", typeof(string))); dt.Columns.Add(new DataColumn("Description", typeof(string))); dt.Columns.Add(new DataColumn("Unit", typeof(string))); dt.Columns.Add(new DataColumn("Qty", typeof(string))); dt.Columns.Add(new DataColumn("Rate", typeof(string))); dt.Columns.Add(new DataColumn("Disc", typeof(string))); dt.Columns.Add(new DataColumn("Amount", typeof(string))); for (int i = 0; i < 5; i++) { dr = dt.NewRow(); dr["ItemCode"] = string.Empty; dr["Description"] = string.Empty; dr["Unit"] = string.Empty; dr["Qty"] = string.Empty; dr["Rate"] = string.Empty; dr["Disc"] = string.Empty; dr["Amount"] = string.Empty; dt.Rows.Add(dr); } //GridView1.DataSource = dt; //GridView1.DataBind(); } private void SetInitialRow() { DataTable dt = new DataTable(); DataRow dr = null; dt.Columns.Add(new DataColumn("RowNumber", typeof(string))); dt.Columns.Add(new DataColumn("ItemCode", typeof(string))); dt.Columns.Add(new DataColumn("Description", typeof(string))); dt.Columns.Add(new DataColumn("Unit", typeof(string))); dt.Columns.Add(new DataColumn("Qty", typeof(string))); dt.Columns.Add(new DataColumn("Rate", typeof(string))); dt.Columns.Add(new DataColumn("Disc", typeof(string))); dt.Columns.Add(new DataColumn("Amount", typeof(string))); dr = dt.NewRow(); dr["RowNumber"] = 1; dr["ItemCode"] = string.Empty; dr["Description"] = string.Empty; dr["Unit"] = string.Empty; dr["Qty"] = string.Empty; dr["Rate"] = string.Empty; dr["Disc"] = string.Empty; dr["Amount"] = string.Empty; dt.Rows.Add(dr); //Store DataTable ViewState["OrderDetails"] = dt; Gridview1.DataSource = dt; Gridview1.DataBind(); } protected void AddNewRowToGrid() { int rowIndex = 0; if (ViewState["OrderDetails"] != null) { DataTable dtCurrentTable = (DataTable)ViewState["OrderDetails"]; DataRow drCurrentRow = null; if (dtCurrentTable.Rows.Count > 0) { for (int i = 1; i <= dtCurrentTable.Rows.Count; i++) { //extract the TextBox values TextBox box1 = (TextBox)Gridview1.Rows[rowIndex].Cells[1].FindControl("txtItemCode"); TextBox box2 = (TextBox)Gridview1.Rows[rowIndex].Cells[2].FindControl("txtdescription"); TextBox box3 = (TextBox)Gridview1.Rows[rowIndex].Cells[3].FindControl("txtunit"); TextBox box4 = (TextBox)Gridview1.Rows[rowIndex].Cells[4].FindControl("txtqty"); TextBox box5 = (TextBox)Gridview1.Rows[rowIndex].Cells[5].FindControl("txtRate"); TextBox box6 = (TextBox)Gridview1.Rows[rowIndex].Cells[6].FindControl("txtdisc"); TextBox box7 = (TextBox)Gridview1.Rows[rowIndex].Cells[7].FindControl("txtamount"); drCurrentRow = dtCurrentTable.NewRow(); drCurrentRow["RowNumber"] = i + 1; drCurrentRow["ItemCode"] = box1.Text; drCurrentRow["Description"] = box2.Text; drCurrentRow["Unit"] = box3.Text; drCurrentRow["Qty"] = box4.Text; drCurrentRow["Rate"] = box5.Text; drCurrentRow["Disc"] = box6.Text; drCurrentRow["Amount"] = box7.Text; rowIndex++; } //add new row to DataTable dtCurrentTable.Rows.Add(drCurrentRow); //Store the current data to ViewState ViewState["OrderDetails"] = dtCurrentTable; //Rebind the Grid with the current data Gridview1.DataSource = dtCurrentTable; Gridview1.DataBind(); } } else { // } //Set Previous Data on Postbacks SetPreviousData(); } private void SetPreviousData() { int rowIndex = 0; if (ViewState["OrderDetails"] != null) { DataTable dt = (DataTable)ViewState["OrderDetails"]; if (dt.Rows.Count > 0) { for (int i = 1; i < dt.Rows.Count; i++) { TextBox box1 = (TextBox)Gridview1.Rows[rowIndex].Cells[1].FindControl("txtItemCode"); TextBox box2 = (TextBox)Gridview1.Rows[rowIndex].Cells[2].FindControl("txtdescription"); TextBox box3 = (TextBox)Gridview1.Rows[rowIndex].Cells[3].FindControl("txtunit"); TextBox box4 = (TextBox)Gridview1.Rows[rowIndex].Cells[4].FindControl("txtqty"); TextBox box5 = (TextBox)Gridview1.Rows[rowIndex].Cells[5].FindControl("txtRate"); TextBox box6 = (TextBox)Gridview1.Rows[rowIndex].Cells[6].FindControl("txtdisc"); TextBox box7 = (TextBox)Gridview1.Rows[rowIndex].Cells[7].FindControl("txtamount"); box1.Text = dt.Rows[i]["ItemCode"].ToString(); box2.Text = dt.Rows[i]["Description"].ToString(); box3.Text = dt.Rows[i]["Unit"].ToString(); box4.Text = dt.Rows[i]["Qty"].ToString(); box5.Text = dt.Rows[i]["Rate"].ToString(); box6.Text = dt.Rows[i]["Disc"].ToString(); box7.Text = dt.Rows[i]["Amount"].ToString(); rowIndex++; } dt.AcceptChanges(); } ViewState["OrderDetails"] = dt; } } protected void BindOrderDetails() { DataTable dtOrderDetails = new DataTable(); if (ViewState["OrderDetails"] != null) { dtOrderDetails = (DataTable)ViewState["OrderDetails"]; } else { dtOrderDetails.Columns.Add(""); dtOrderDetails.Columns.Add(""); dtOrderDetails.Columns.Add(""); dtOrderDetails.Columns.Add(""); dtOrderDetails.Columns.Add(""); dtOrderDetails.Columns.Add(""); dtOrderDetails.AcceptChanges(); DataRow dr = dtOrderDetails.NewRow(); dtOrderDetails.Rows.Add(dr); ViewState["OrderDetails"] = dtOrderDetails; } if (dtOrderDetails != null) { Gridview1.DataSource = dtOrderDetails; Gridview1.DataBind(); if (Gridview1.Rows.Count > 0) { ((LinkButton)Gridview1.Rows[Gridview1.Rows.Count - 1].FindControl("btnDelete")).Visible = false; } } } protected void btnSave_Click(object sender, EventArgs e) { if (txtOrderDate.Text != "" && txtOrderNo.Text != "" && txtPartyName.Text != "" && txttotalAmount.Text !="") { BLLOrderMaster bllobj = new BLLOrderMaster(); DataTable dtdetails = new DataTable(); UpdateItemDetailRow(); dtdetails = (DataTable)ViewState["OrderDetails"]; SetValues(bllobj); int k = 0; k = bllobj.Insert_Update_Delete(1, bllobj, dtdetails); if (k > 0) { ScriptManager.RegisterStartupScript(this, this.GetType(), "Login Denied", "<Script>alert('Order Code Alraddy Exist');</Script>", false); } else { ScriptManager.RegisterStartupScript(this, this.GetType(), "Login Denied", "<Script>alert('Record Saved Successfully');</Script>", false); } dtdetails.Clear(); SetInitialRow(); txttotalAmount.Text = ""; txtOrderNo.Text = ""; txtPartyName.Text = ""; txtOrderDate.Text = ""; txttotalQty.Text = ""; string OrderNumber = objMaster.SelectDetails().ToString(); if (OrderNumber != "") { txtOrderNo.Text = OrderNumber.ToString(); txtOrderDate.Focus(); } } else { txtOrderNo.Text = ""; } } public void SetValues(BLLOrderMaster bllobj) { if (txtOrderNo.Text != null && txtOrderNo.Text.ToString() != "") { bllobj.OrNumber = Convert.ToInt16(txtOrderNo.Text); } if (txtOrderDate.Text != null && txtOrderDate.Text.ToString() != "") { bllobj.Date = DateTime.Parse(txtOrderDate.Text.ToString()).ToString("dd/MM/yyyy"); } if (txtPartyName.Text != null && txtPartyName.Text.ToString() != "") { bllobj.PartyName = txtPartyName.Text; } bllobj.TotalBillAmount = txttotalAmount.Text == "" ? 0 : int.Parse(txttotalAmount.Text); bllobj.TotalQty = txttotalQty.Text == "" ? 0 : int.Parse(txttotalQty.Text); } protected void txtdisc_TextChanged(object sender, EventArgs e) { double total = 0; double totalqty = 0; foreach (GridViewRow dgvr in Gridview1.Rows) { TextBox tb = (TextBox)dgvr.Cells[7].FindControl("txtamount"); double sum; if (double.TryParse(tb.Text.Trim(), out sum)) { total += sum; } TextBox tb1 = (TextBox)dgvr.Cells[4].FindControl("txtqty"); double qtysum; if (double.TryParse(tb1.Text.Trim(), out qtysum)) { totalqty += qtysum; } } txttotalAmount.Text = total.ToString(); txttotalQty.Text = totalqty.ToString(); AddNewRowToGrid(); Gridview1.TabIndex = 1; } public void UpdateItemDetailRow() { DataTable dt = new DataTable(); if (ViewState["OrderDetails"] != null) { dt = (DataTable)ViewState["OrderDetails"]; } if (dt.Rows.Count > 0) { for (int i = 0; i < Gridview1.Rows.Count; i++) { dt.Rows[i]["ItemCode"] = (Gridview1.Rows[i].FindControl("txtItemCode") as TextBox).Text.ToString(); if (dt.Rows[i]["ItemCode"].ToString() == "") { dt.Rows[i].Delete(); break; } else { dt.Rows[i]["Description"] = (Gridview1.Rows[i].FindControl("txtdescription") as TextBox).Text.ToString(); dt.Rows[i]["Unit"] = (Gridview1.Rows[i].FindControl("txtunit") as TextBox).Text.ToString(); dt.Rows[i]["Qty"] = (Gridview1.Rows[i].FindControl("txtqty") as TextBox).Text.ToString(); dt.Rows[i]["Rate"] = (Gridview1.Rows[i].FindControl("txtRate") as TextBox).Text.ToString(); dt.Rows[i]["Disc"] = (Gridview1.Rows[i].FindControl("txtdisc") as TextBox).Text.ToString(); dt.Rows[i]["Amount"] = (Gridview1.Rows[i].FindControl("txtamount") as TextBox).Text.ToString(); } } dt.AcceptChanges(); } ViewState["OrderDetails"] = dt; } }

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• Why can't HTC Droid running OTA 2.1 communicate with RFCOMM?

  - by Brad Hein

  Yesterday we received OTA Android 2.1 on my wife's HTC Droid - HOORAY!!! I am finally able to load my carputer app on her phone. Well we loaded it, but it doesn't work. Specifically, it connects but sees no I/O!!! I paired, re-paired, and re-paired again, every time its the same problem: connect() says we connected successfully, but any attempt to send or receive data appears to work but no data ever arrives in the input buffer. The device I'm connecting to uses AT commands. ATI should respond with a device ID. That works fine when I run the app on my Moto Droid, but on the HTC droid, no data is ever present in the inputstream/buffer. Personally, I'm feeling pretty sure it's a bug or limitation in this release for the HTC (because the app works great on my Moto A855 Droid). Can anybody comment on the issue? Obligatory code snippets: Member variable defining my RFCOMM UUID static final UUID UUID_RFCOMM_GENERIC = UUID.fromString("00001101-0000-1000-8000-00805F9B34FB"); Parts of my connect() // make sure peer is defined as a valid device based on their MAC. If not then do it. if (mBTDevice == null) mBTDevice = mBTAdapter.getRemoteDevice(mPeerMAC); // Make an RFCOMM binding. try {mBTSocket = mBTDevice.createRfcommSocketToServiceRecord(UUID_RFCOMM_GENERIC); } catch (Exception e1) { msg ("connect(): Failed to bind to RFCOMM by UUID. msg=" + e1.getMessage()); return false; } msg ("connect(): Try to connect."); try { mBTSocket.connect(); } catch (Exception e) { msg ("connect(): Exception thrown during connect: " + e.getMessage()); return false; // there was a problem connecting... make a note of the particulars and move on. } msg ("connect(): CONNECTED!"); try { mBTOutputStream = mBTSocket.getOutputStream(); mBTInputStream = new BufferedInputStream (mBTSocket.getInputStream(),INPUT_BUFFER_SIZE); //msg ("Connecting non-buffered input stream..."); //mBTInputStream = mBTSocket.getInputStream(); } catch (Exception e) { msg ("connect(): Error attaching i/o streams to socket. msg=" + e.getMessage()); return false; } resetErrorCounters(); setConnected(true); return true; } Then I send "ATI\r" and expect something like "CAN OBD II" but I get nothing. mBTInputStream.available(), it seems, is ALWAYS zero, even when data should be in the input buffer. There are GOBS of trace messages being generated by the OS as viewed with adb logcat -v time Some of the more interesting ones: 05-17 19:44:21.447 D/BluetoothSppPort( 5809): connected to device service! 05-17 19:44:21.447 D/BluetoothSppPort( 5809): Creating a BluetoothSpp proxy object 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort called! 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort checking uuid 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort UUID=00001101-0000-1000-8000-00805f9b34fb auth=true encrypt=true 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort enforcing bluetooth perm 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort creating a jbtlspp object 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort checking if the btl spp object is valid 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort try to create an spp container 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort try to create security params 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort Set Security L2 05-17 19:44:21.467 D/BluetoothSppService( 74): createPort spp port create 05-17 19:44:21.467 D/JBtlSpp ( 74): create: Entered 05-17 19:44:21.467 D/JBtlSpp ( 74): Calling NativeJBtlSpp_Create 05-17 19:44:21.467 D/JBtlSppNative( 74): NativeJBtlSpp_Create: Entered 05-17 19:44:21.467 D/JBtlSppNative( 74): NativeJBtlSpp_Create: Calling BTL_SPP_Remote_Create 05-17 19:44:21.477 D/JBtlSppNative( 74): NativeJBtlSpp_Create: BTL_SPP_Remote_Create returned 0, context:18 05-17 19:44:21.477 D/JBtlSppNative( 74): NativeJBtlSpp_Create: Setting context value in jContext out parm 05-17 19:44:21.477 D/JBtlSppNative( 74): NativeJBtlSpp_Create: Calling Java setValue(0x18) in context's class 05-17 19:44:21.477 D/JBtlProfileContext( 74): setValue: setValue called, value:24 05-17 19:44:21.477 D/JBtlSppNative( 74): create_spp_port_data: will use context struct 0 for the port 24 05-17 19:44:21.477 D/JBtlSppNative( 74): create_spp_port_data: spp port context 0 added 05-17 19:44:21.477 D/JBtlSppNative( 74): NativeJBtlSpp_Create:Exiting Successfully 05-17 19:44:21.477 D/JBtlSpp ( 74): After NativeJBtlSpp_Create, status=SUCCESS, Context = 24 05-17 19:44:21.477 D/JBtlRbtlServices( 74): addUser: Entered, userRefCount = 1 05-17 19:44:21.477 D/BluetoothSppService( 74): port create returned status SUCCESS 05-17 19:44:21.477 D/JBtlSpp ( 74): enable: Entered 05-17 19:44:21.477 D/JBtlSpp ( 74): enable: UUID=00001101-0000-1000-8000-00805f9b34fb 05-17 19:44:21.477 D/JBtlSppNative( 74): NativeJBtlSpp_Enable: Entered 05-17 19:44:21.487 D/JBtlSppNative( 74): NativeJBtlSpp_Enable: BTL_SPP_Enable returned 0 05-17 19:44:21.487 D/JBtlSppNative( 74): NativeJBtlSpp_Enable:Exiting 05-17 19:44:21.487 D/JBtlSpp ( 74): After NativeJBtlSpp_Enable, status=SUCCESS 05-17 19:44:21.487 D/JBtlSpp ( 74): enable: Exiting 05-17 19:44:21.487 D/BluetoothSppService( 74): port enable returned status SUCCESS 05-17 19:44:21.487 D/BluetoothSppService( 74): connectPort called! 05-17 19:44:21.497 D/BluetoothSppService( 74): connectPort received bdaddress:00:18:E4:1D:23:9B 05-17 19:44:21.527 D/BluetoothSppService( 74): Trying to connect to 00:18:E4:1D:23:9B 05-17 19:44:21.527 D/JBtlSpp ( 74): setServiceName: Entered 05-17 19:44:21.527 D/JBtlSppNative( 74): NativeJBtlSpp_SetServiceName: Entered 05-17 19:44:21.547 D/JBtlSppNative( 74): NativeJBtlSpp_SetServiceName: native func returned 0 05-17 19:44:21.547 D/JBtlSppNative( 74): NativeJBtlSpp_SetServiceName:Exiting 05-17 19:44:21.547 D/JBtlSpp ( 74): After setServiceName, status=SUCCESS 05-17 19:44:21.547 D/JBtlSpp ( 74): setServiceName: Exiting 05-17 19:44:21.557 D/BluetoothSppService( 74): port setServiceName returned status SUCCESS 05-17 19:44:21.587 D/JBtlSpp ( 74): connect: Entered connecting to 00:18:E4:1D:23:9B 05-17 19:44:21.587 D/JBtlSppNative( 74): NativeJBtlSpp_Connect: Entered 05-17 19:44:21.597 D/JBtlSppNative( 74): NativeJBtlSpp_Connect: BTL_SPP_Connect returned 2 05-17 19:44:21.597 D/JBtlSppNative( 74): NativeJBtlSpp_Connect:Exiting 05-17 19:44:21.597 D/JBtlSpp ( 74): After NativeJBtlSpp_Connect, status=PENDING 05-17 19:44:21.747 D/AK8973 ( 61): Compass CLOSE 05-17 19:44:21.887 W/Process ( 74): Unable to open /proc/5749/status 05-17 19:44:21.917 I/ActivityManager( 74): Displayed activity com.gtosoft.dash/.Dash: 1279 ms (total 1279 ms) 05-17 19:44:24.047 D/ ( 74): signal_BTEVENT_ACCESSIBLE_CHANGE: Entered 05-17 19:44:24.047 D/ ( 74): signal_BTEVENT_ACCESSIBLE_CHANGE: Calling Java Accessible Change callback 05-17 19:44:24.047 D/JBtlBmg ( 74): nativeAccessibleChange 05-17 19:44:24.087 D/BluetoothService( 74): Callback - accessbileChange, btErrCode = NO_ERROR, mode = CONNECTABLE_ONLY 05-17 19:44:24.087 D/BluetoothService( 74): Sending ACTION_SCAN_MODE_CHANGED intent, mode = 21 05-17 19:44:24.087 D/ ( 74): signal_BTEVENT_ACCESSIBLE_CHANGE: Exiting 05-17 19:44:24.097 D/ ( 74): signal_BTEVENT_LINK_CONNECT_CNF: Entered 05-17 19:44:24.097 D/ ( 74): signal_BTEVENT_LINK_CONNECT_CNF: context: 1, errCode: 0 05-17 19:44:24.097 D/ ( 74): signal_BTEVENT_LINK_CONNECT_CNF: Calling Java Link Connect Confirmation callback 05-17 19:44:24.097 D/JBtlBmg ( 74): nativeLinkConnectCnf 05-17 19:44:24.107 D/BluetoothService( 74): Callback - linkConnectCnf, btErrCode = NO_ERROR, bdAddr = 00:18:E4:1D:23:9B 05-17 19:44:24.117 D/JBtlBmg ( 74): getKnownDeviceInfo: Entered 05-17 19:44:24.117 D/JBtlBmg ( 74): getKnownDeviceInfo: Calling NativeJBtlBmg_GetKnownDeviceInfo 05-17 19:44:24.137 D/ ( 74): NativeJBtlBmg_GetKnownDeviceInfo: Entered 05-17 19:44:24.137 D/ ( 74): NativeJBtlBmg_GetKnownDeviceInfo: Calling BTL_BMG_GetKnownDeviceInfo 05-17 19:44:24.227 D/JBtlBmgJniKnownDeviceInfo( 74): setValues: Entered 05-17 19:44:24.227 D/ ( 74): NativeJBtlBmg_GetKnownDeviceInfo:Exiting 05-17 19:44:24.227 D/JBtlBmg ( 74): getKnownDeviceInfo: After NativeJBtlBmg_GetKnownDeviceInfo, status=SUCCESS 05-17 19:44:24.227 D/JBtlBmg ( 74): getKnownDeviceInfo: Exiting 05-17 19:44:24.227 D/BluetoothService( 74): onRemoteDeviceConnected, device 00:18:E4:1D:23:9B is Paired 05-17 19:44:24.227 D/BluetoothService( 74): Sending ACTION_ACL_CONNECTED intent, address = 00:18:E4:1D:23:9B 05-17 19:44:24.227 D/BluetoothA2dpService( 74): Received intent with action: android.bluetooth.device.action.ACL_CONNECTED 05-17 19:44:24.227 D/ ( 74): signal_BTEVENT_LINK_CONNECT_CNF: Exiting 05-17 19:44:24.757 D/JBtlAg ( 163): setIndicatorValue: entered 05-17 19:44:24.767 I/JBtlAg ( 163): After NativeJBtlAg_SetIndicatorValue, status = SUCCESS 05-17 19:44:24.767 D/JBtlAg ( 163): setIndicatorValue: exiting 05-17 19:44:24.807 D/JBtlSppNative( 74): signal_SPP_EVENT_OPEN: Entered 05-17 19:44:24.807 D/JBtlSppNative( 74): signal_SPP_EVENT_OPEN: status: 0 context:24 05-17 19:44:24.827 D/JBtlSpp ( 74): nativeCb_open: Entered from 00:18:E4:1D:23:9B 05-17 19:44:24.827 D/JBtlSpp ( 74): nativeCb_open: Calling callback 05-17 19:44:24.827 D/BluetoothSppService( 74): connected called! 05-17 19:44:24.847 D/JBtlSpp ( 74): connect: Exiting 05-17 19:44:24.847 D/BluetoothSppService( 74): port connect returned status SUCCESS 05-17 19:44:24.847 D/JBtlSppNative( 74): signal_SPP_EVENT_OPEN: Exiting 05-17 19:44:24.847 D/JBtlSppNative( 74): signal_SPP_EVENT_MODEM_STATUS_IND: Entered 05-17 19:44:24.847 D/JBtlSppNative( 74): signal_SPP_EVENT_MODEM_STATUS_IND: Exiting 05-17 19:44:25.424 D/BluetoothSppService( 74): writeSync called! 05-17 19:44:25.424 D/JBtlSpp ( 74): write: Entered 05-17 19:44:25.427 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: Entered 05-17 19:44:25.427 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: BTL_SPP_WriteSync returned 0 written: 6 total: 0/6 05-17 19:44:25.437 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: Entered 05-17 19:44:25.437 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: status: 0 context:24 txDataLen:6 05-17 19:44:25.437 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: Exiting ok 05-17 19:44:25.437 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: written 6 05-17 19:44:25.437 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative:Exiting with 0 05-17 19:44:25.437 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: returning 6 bytes 05-17 19:44:25.437 D/JBtlSpp ( 74): After write, status=SUCCESS 05-17 19:44:25.437 D/JBtlSpp ( 74): write: Exiting 05-17 19:44:25.437 D/BluetoothSppPort( 5809): written 6 bytes 05-17 19:44:25.467 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Entered 05-17 19:44:25.467 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: status: 0 context: 24 rxDataLen: 1 05-17 19:44:25.467 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Exiting 05-17 19:44:25.477 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Entered 05-17 19:44:25.477 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: status: 0 context: 24 rxDataLen: 5 05-17 19:44:25.477 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Exiting 05-17 19:44:25.487 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Entered 05-17 19:44:25.487 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: status: 0 context: 24 rxDataLen: 10 05-17 19:44:25.487 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Exiting 05-17 19:44:25.497 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Entered 05-17 19:44:25.497 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: status: 0 context: 24 rxDataLen: 7 05-17 19:44:25.497 D/JBtlSppNative( 74): signal_SPP_EVENT_RX_DATA_IND: Exiting 05-17 19:44:27.930 W/ActivityManager( 74): Activity destroy timeout for HistoryRecord{447e0d48 com.gtosoft.dash/.Dash} 05-17 19:44:29.907 D/dalvikvm( 448): GC freed 78 objects / 3664 bytes in 153ms 05-17 19:44:29.917 D/BluetoothSppService( 74): writeSync called! 05-17 19:44:29.917 D/JBtlSpp ( 74): write: Entered 05-17 19:44:29.917 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: Entered 05-17 19:44:29.927 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: BTL_SPP_WriteSync returned 0 written: 6 total: 0/6 05-17 19:44:29.937 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: Entered 05-17 19:44:29.937 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: status: 0 context:24 txDataLen:6 05-17 19:44:29.937 D/JBtlSppNative( 74): signal_SPP_EVENT_TX_DATA_COMPLETE: Exiting ok 05-17 19:44:29.937 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: written 6 05-17 19:44:29.937 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative:Exiting with 0 05-17 19:44:29.937 D/JBtlSppNative( 74): NativeJBtlSpp_WriteNative: returning 6 bytes 05-17 19:44:29.937 D/JBtlSpp ( 74): After write, status=SUCCESS 05-17 19:44:29.937 D/JBtlSpp ( 74): write: Exiting

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• Help Optimizing MySQL Table (~ 500,000 records) and PHP Code.

  - by Pyrite

  I have a MySQL table that collects player data from various game servers (Urban Terror). The bot that collects the data runs 24/7, and currently the table is up to about 475,000+ records. Because of this, querying this table from PHP has become quite slow. I wonder what I can do on the database side of things to make it as optomized as possible, then I can focus on the application to query the database. The table is as follows: CREATE TABLE IF NOT EXISTS `people` ( `id` bigint(20) unsigned NOT NULL AUTO_INCREMENT, `name` varchar(40) NOT NULL, `ip` int(4) unsigned NOT NULL, `guid` varchar(32) NOT NULL, `server` int(4) unsigned NOT NULL, `date` int(11) NOT NULL, PRIMARY KEY (`id`), UNIQUE KEY `Person` (`name`,`ip`,`guid`), KEY `server` (`server`), KEY `date` (`date`), KEY `PlayerName` (`name`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 COMMENT='People that Play on Servers' AUTO_INCREMENT=475843 ; I'm storying the IPv4 (ip and server) as 4 byte integers, and using the MySQL functions NTOA(), etc to encode and decode, I heard that this way is faster, rather than varchar(15). The guid is a md5sum, 32 char hex. Date is stored as unix timestamp. I have a unique key on name, ip and guid, as to avoid duplicates of the same player. Do I have my keys setup right? Is the way I'm storing data efficient? Here is the code to query this table. You search for a name, ip, or guid, and it grabs the results of the query and cross references other records that match the name, ip, or guid from the results of the first query, and does it for each field. This is kind of hard to explain. But basically, if I search for one player by name, I'll see every other name he has used, every IP he has used and every GUID he has used. <form action="<?php echo $_SERVER['PHP_SELF']; ?>" method="post"> Search: <input type="text" name="query" id="query" /><input type="submit" name="btnSubmit" value="Submit" /> </form> <?php if (!empty($_POST['query'])) { ?> <table cellspacing="1" id="1up_people" class="tablesorter" width="300"> <thead> <tr> <th>ID</th> <th>Player Name</th> <th>Player IP</th> <th>Player GUID</th> <th>Server</th> <th>Date</th> </tr> </thead> <tbody> <?php function super_unique($array) { $result = array_map("unserialize", array_unique(array_map("serialize", $array))); foreach ($result as $key => $value) { if ( is_array($value) ) { $result[$key] = super_unique($value); } } return $result; } if (!empty($_POST['query'])) { $query = trim($_POST['query']); $count = 0; $people = array(); $link = mysql_connect('localhost', 'mysqluser', 'yea right!'); if (!$link) { die('Could not connect: ' . mysql_error()); } mysql_select_db("1up"); $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (name LIKE \"%$query%\" OR INET_NTOA(ip) LIKE \"%$query%\" OR guid LIKE \"%$query%\")"; $result = mysql_query($sql, $link); if (!$result) { die(mysql_error()); } // Now take the initial results and parse each column into its own array while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } // now for each name, ip, guid in results, find additonal records $people2 = array(); foreach ($people AS $person) { $ip = $person['ip']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (ip = \"$ip\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people2[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } $people3 = array(); foreach ($people AS $person) { $guid = $person['guid']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (guid = \"$guid\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people3[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } $people4 = array(); foreach ($people AS $person) { $name = $person['name']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (name = \"$name\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people4[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } // Combine people and people2 into just people $people = array_merge($people, $people2); $people = array_merge($people, $people3); $people = array_merge($people, $people4); $people = super_unique($people); foreach ($people AS $person) { $date = ($person['date']) ? date("M d, Y", $person['date']) : 'Before 8/1/10'; echo "<tr>\n"; echo "<td>".$person['id']."</td>"; echo "<td>".$person['name']."</td>"; echo "<td>".$person['ip']."</td>"; echo "<td>".$person['guid']."</td>"; echo "<td>".$person['server']."</td>"; echo "<td>".$date."</td>"; echo "</tr>\n"; $count++; } // Find Total Records //$result = mysql_query("SELECT id FROM 1up_people", $link); //$total = mysql_num_rows($result); mysql_close($link); } ?> </tbody> </table> <p> <?php echo $count." Records Found for \"".$_POST['query']."\" out of $total"; ?> </p> <?php } $time_stop = microtime(true); print("Done (ran for ".round($time_stop-$time_start)." seconds)."); ?> Any help at all is appreciated! Thank you.

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• Help Optimizing MySQL Table (~ 500,000 records).

  - by Pyrite

  I have a MySQL table that collects player data from various game servers (Urban Terror). The bot that collects the data runs 24/7, and currently the table is up to about 475,000+ records. Because of this, querying this table from PHP has become quite slow. I wonder what I can do on the database side of things to make it as optomized as possible, then I can focus on the application to query the database. The table is as follows: CREATE TABLE IF NOT EXISTS `people` ( `id` bigint(20) unsigned NOT NULL AUTO_INCREMENT, `name` varchar(40) NOT NULL, `ip` int(4) unsigned NOT NULL, `guid` varchar(32) NOT NULL, `server` int(4) unsigned NOT NULL, `date` int(11) NOT NULL, PRIMARY KEY (`id`), UNIQUE KEY `Person` (`name`,`ip`,`guid`), KEY `server` (`server`), KEY `date` (`date`), KEY `PlayerName` (`name`) ) ENGINE=MyISAM DEFAULT CHARSET=latin1 COMMENT='People that Play on Servers' AUTO_INCREMENT=475843 ; I'm storying the IPv4 (ip and server) as 4 byte integers, and using the MySQL functions NTOA(), etc to encode and decode, I heard that this way is faster, rather than varchar(15). The guid is a md5sum, 32 char hex. Date is stored as unix timestamp. I have a unique key on name, ip and guid, as to avoid duplicates of the same player. Do I have my keys setup right? Is the way I'm storing data efficient? Here is the code to query this table. You search for a name, ip, or guid, and it grabs the results of the query and cross references other records that match the name, ip, or guid from the results of the first query, and does it for each field. This is kind of hard to explain. But basically, if I search for one player by name, I'll see every other name he has used, every IP he has used and every GUID he has used. <form action="<?php echo $_SERVER['PHP_SELF']; ?>" method="post"> Search: <input type="text" name="query" id="query" /><input type="submit" name="btnSubmit" value="Submit" /> </form> <?php if (!empty($_POST['query'])) { ?> <table cellspacing="1" id="1up_people" class="tablesorter" width="300"> <thead> <tr> <th>ID</th> <th>Player Name</th> <th>Player IP</th> <th>Player GUID</th> <th>Server</th> <th>Date</th> </tr> </thead> <tbody> <?php function super_unique($array) { $result = array_map("unserialize", array_unique(array_map("serialize", $array))); foreach ($result as $key => $value) { if ( is_array($value) ) { $result[$key] = super_unique($value); } } return $result; } if (!empty($_POST['query'])) { $query = trim($_POST['query']); $count = 0; $people = array(); $link = mysql_connect('localhost', 'mysqluser', 'yea right!'); if (!$link) { die('Could not connect: ' . mysql_error()); } mysql_select_db("1up"); $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (name LIKE \"%$query%\" OR INET_NTOA(ip) LIKE \"%$query%\" OR guid LIKE \"%$query%\")"; $result = mysql_query($sql, $link); if (!$result) { die(mysql_error()); } // Now take the initial results and parse each column into its own array while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } // now for each name, ip, guid in results, find additonal records $people2 = array(); foreach ($people AS $person) { $ip = $person['ip']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (ip = \"$ip\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people2[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } $people3 = array(); foreach ($people AS $person) { $guid = $person['guid']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (guid = \"$guid\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people3[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } $people4 = array(); foreach ($people AS $person) { $name = $person['name']; $sql = "SELECT id, name, INET_NTOA(ip) AS ip, guid, INET_NTOA(server) AS server, date FROM 1up_people WHERE (name = \"$name\")"; $result = mysql_query($sql, $link); while ($row = mysql_fetch_array($result, MYSQL_NUM)) { $name = htmlspecialchars($row[1]); $people4[] = array( 'id' => $row[0], 'name' => $name, 'ip' => $row[2], 'guid' => $row[3], 'server' => $row[4], 'date' => $row[5] ); } } // Combine people and people2 into just people $people = array_merge($people, $people2); $people = array_merge($people, $people3); $people = array_merge($people, $people4); $people = super_unique($people); foreach ($people AS $person) { $date = ($person['date']) ? date("M d, Y", $person['date']) : 'Before 8/1/10'; echo "<tr>\n"; echo "<td>".$person['id']."</td>"; echo "<td>".$person['name']."</td>"; echo "<td>".$person['ip']."</td>"; echo "<td>".$person['guid']."</td>"; echo "<td>".$person['server']."</td>"; echo "<td>".$date."</td>"; echo "</tr>\n"; $count++; } // Find Total Records //$result = mysql_query("SELECT id FROM 1up_people", $link); //$total = mysql_num_rows($result); mysql_close($link); } ?> </tbody> </table> <p> <?php echo $count." Records Found for \"".$_POST['query']."\" out of $total"; ?> </p> <?php } $time_stop = microtime(true); print("Done (ran for ".round($time_stop-$time_start)." seconds)."); ?> Any help at all is appreciated! Thank you.

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• JqGrid addJSONData + ASP.NET 2.0 WS

  - by MilosC

  Dear community ! I am a bit lost. I' ve tried to implement a solution based on JqGrid and tried to use function as datatype. I've setted all by the book i guess, i get WS invoked and get JASON back, I got succes on clientside in ajaf call and i "bind" jqGrid using addJSONData but grid remains empty. I do not have any glue now... other "local" samples on same pages works without a problem (jsonstring ...) My WS method looks like : [WebMethod] [ScriptMethod(ResponseFormat = ResponseFormat.Json)] public string GetGridData() { // Load a list InitSessionVariables(); SA.DB.DenarnaEnota.DenarnaEnotaDB db = new SAOP.SA.DB.DenarnaEnota.DenarnaEnotaDB(); DataSet ds = db.GetLookupForDenarnaEnota(SAOP.FW.DB.RecordStatus.All); // Turn into HTML friendly format GetGridData summaryList = new GetGridData(); summaryList.page = "1"; summaryList.total = "10"; summaryList.records = "160"; int i = 0; foreach (DataRow dr in ds.Tables[0].Rows) { GridRows row = new GridRows(); row.id = dr["DenarnaEnotaID"].ToString(); row.cell = "[" + "\"" + dr["DenarnaEnotaID"].ToString() + "\"" + "," + "\"" + dr["Kratica"].ToString() + "\"" + "," + "\"" + dr["Naziv"].ToString() + "\"" + "," + "\"" + dr["Sifra"].ToString() + "\"" + "]"; summaryList.rows.Add(row); } return JsonConvert.SerializeObject(summaryList); } my ASCX code is this: jQuery(document).ready(function(){ jQuery("#list").jqGrid({ datatype : function (postdata) { jQuery.ajax({ url:'../../AjaxWS/TemeljnicaEdit.asmx/GetGridData', data:'{}', dataType:'json', type: 'POST', contentType: "application/json; charset=utf-8", complete: function(jsondata,stat){ if(stat=="success") { var clearJson = jsondata.responseText; var thegrid = jQuery("#list")[0]; var myjsongrid = eval('('+clearJson+')'); alfs thegrid.addJSONData(myjsongrid.replace(/\\/g,'')); } } } ); }, colNames:['DenarnaEnotaID','Kratica', 'Sifra', 'Naziv'], colModel:[ {name:'DenarnaEnotaID',index:'DenarnaEnotaID', width:100}, {name:'Kratica',index:'Kratica', width:100}, {name:'Sifra',index:'Sifra', width:100}, {name:'Naziv',index:'Naziv', width:100}], rowNum:15, rowList:[15,30,100], pager: jQuery('#pager'), sortname: 'id', // loadtext:"Nalagam zapise...", // viewrecords: true, sortorder: "desc", // caption:"Vrstice", // width:"800", imgpath: "../Scripts/JGrid/themes/basic/images"}); }); from WS i GET JSON like this: {”page”:”1?,”total”:”10?,”records”:”160?,”rows”:[{"id":"18","cell":"["18","BAM","Konvertibilna marka","977"]“},{”id”:”19?,”cell”:”["19","RSD","Srbski dinar","941"]“},{”id”:”20?,”cell”:”["20","AFN","Afgani","971"]“},{”id”:”21?,”cell”:”["21","ALL","Lek","008"]“},{”id”:”22?,”cell”:”["22","DZD","Alžirski dinar","012"]“},{”id”:”23?,”cell”:”["23","AOA","Kvanza","973"]“},{”id”:”24?,”cell”:”["24","XCD","Vzhodnokaribski dolar","951"]“},{”id”:”25?,”cell”:” ……………… ["13","PLN","Poljski zlot","985"]“},{”id”:”14?,”cell”:”["14","SEK","Švedska krona","752"]“},{”id”:”15?,”cell”:”["15","SKK","Slovaška krona","703"]“},{”id”:”16?,”cell”:”["16","USD","Ameriški dolar","840"]“},{”id”:”17?,”cell”:”["17","XXX","Nobena valuta","000"]“},{”id”:”1?,”cell”:”["1","SIT","Slovenski tolar","705"]“}]} i have registered this js : clientSideScripts.RegisterClientScriptFile("prototype.js", CommonFunctions.FixupUrlWithoutSessionID("~/WebUI/Scripts/prototype-1.6.0.2.js")); clientSideScripts.RegisterClientScriptFile("jquery.js", CommonFunctions.FixupUrlWithoutSessionID("~/WebUI/Scripts/JGrid/jquery.js")); clientSideScripts.RegisterClientScriptFile("jquery.jqGrid.js", CommonFunctions.FixupUrlWithoutSessionID("~/WebUI/Scripts/JGrid/jquery.jqGrid.js")); clientSideScripts.RegisterClientScriptFile("jqModal.js", CommonFunctions.FixupUrlWithoutSessionID("~/WebUI/Scripts/JGrid/js/jqModal.js")); clientSideScripts.RegisterClientScriptFile("jqDnR.js", CommonFunctions.FixupUrlWithoutSessionID("~/WebUI/Scripts/JGrid/js/jqDnR.js")); Basical i think it must be something stupid ...but i can figure it out now... Help wanted.

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