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  • Understanding ESXi and Memory Usage

    - by John
    Hi, I am currently testing VMWare ESXi on a test machine. My host machine has 4gigs of ram. I have three guests and each is assigned a memory limit of 1 GB (and only 512 MB reserved). The host summary screen shows a memory capacity of 4082.55 MB and a usage of 2828 MB with two guests running. This seems to make sense, two gigs for each VM plus an overhead for the host. 800MB seems high but that is still reasonable. But on the Resource Allocation Screen I see a memory capacity of 2356 MB and an available capacity of 596 MB. Under the configuration tab, memory link I see a physical total of 4082.5 MB, System of 531.5 MB and VM of 3551.0 MB. I have only allocated my VMs for a gig each, and with two VMs running they are taking up almost two times the amount of ram allocated. Why is this, and why does the Resource Allocation screen short change me so much?

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  • Common filesystem for servers behind a rackspace load balancer

    - by thanos panousis
    Our PHP application consists of a single web server that will receive files from clients and perform a CPU-intensive analysis on them. Right now, analysis of a single user upload can take 3sec to conclude and take 100% CPU. This makes our system capacity amount to 1/3 requests per second. My team's requirement is to increase capacity without a lot of code reengineering. A possible solution would be to set up a load balancer in front of multiple servers running the same app, connecting to a common DB. The problem is that the analysis outputs files on disk. A load balancer would increase capacity, but then files won't be available between servers so consequent client requests may fail. We are hosted on Rackspace, is there a way to configure some sort of "common" storage for all servers, without having to rewrite our file persistance code? Current code relies on simple fopens etc. What are our options?

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  • Server Requirement and Cost for an android Application [duplicate]

    - by CagkanToptas
    This question already has an answer here: How do you do load testing and capacity planning for web sites? 3 answers Can you help me with my capacity planning? 2 answers I am working on a project which is an android application. For my project proposal, I need to calculate what is my server requirements to overcome the traffic I explained below? and if possible, I want to learn what is approximate cost of such server? I am giving the maximum expected values for calculation : -Database will be in mysql (Average service time of DB is 100-110ms in my computer[i5,4GB Ram]) -A request will transfer 150Kb data for each request on average. -Total user count : 1m -Active user count : 50k -Estimated request/sec for 1 active user : 0.06 -Total expected request/second to the server = ~5000 I am expecting this traffic between 20:00-1:00 everyday and then this values will decrease to 1/10 rest of the day. Is there any solution to this? [e.g increasing server capacity in a specific time period everyday to reduce cost]

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  • [Closed] Oracle JDBC connection with Weblogic 10 datasource mapping, giving problem java.sql.SQLExce

    - by gauravkarnatak
    Oracle JDBC connection with Weblogic 10 datasource mapping, giving problem java.sql.SQLException: Closed Connection I am using weblogic 10 JNDI datasource to create JDBC connections, below is my config <?xml version="1.0" encoding="UTF-8"?> <jdbc-data-source xmlns="http://www.bea.com/ns/weblogic/90" xmlns:sec="http://www.bea.com/ns/weblogic/90/security" xmlns:wls="http://www.bea.com/ns/weblogic/90/security/wls" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.bea.com/ns/weblogic/920 http://www.bea.com/ns/weblogic/920.xsd"> <name>XL-Reference-DS</name> <jdbc-driver-params> <url>jdbc:oracle:oci:@abc.XL.COM</url> <driver-name>oracle.jdbc.driver.OracleDriver</driver-name> <properties> <property> <name>user</name> <value>DEV_260908</value> </property> <property> <name>password</name> <value>password</value> </property> <property> <name>dll</name> <value>ocijdbc10</value> </property> <property> <name>protocol</name> <value>oci</value> </property> <property> <name>oracle.jdbc.V8Compatible</name> <value>true</value> </property> <property> <name>baseDriverClass</name> <value>oracle.jdbc.driver.OracleDriver</value> </property> </properties> </jdbc-driver-params> <jdbc-connection-pool-params> <initial-capacity>1</initial-capacity> <max-capacity>100</max-capacity> <capacity-increment>1</capacity-increment> <test-connections-on-reserve>true</test-connections-on-reserve> <test-table-name>SQL SELECT 1 FROM DUAL</test-table-name> </jdbc-connection-pool-params> <jdbc-data-source-params> <jndi-name>ReferenceData</jndi-name> <global-transactions-protocol>OnePhaseCommit</global-transactions-protocol> </jdbc-data-source-params> </jdbc-data-source> When I run a bulk task where there are lots of connections made and closed, sometimes it gives connection closed exception for any of the task in the bulk task. Below is detailed exception' java.sql.SQLException: Closed Connection at oracle.jdbc.driver.DatabaseError.throwSqlException(DatabaseError.java:111) at oracle.jdbc.driver.DatabaseError.throwSqlException(DatabaseError.java:145) at oracle.jdbc.driver.DatabaseError.throwSqlException(DatabaseError.java:207) at oracle.jdbc.driver.OracleStatement.ensureOpen(OracleStatement.java:3512) at oracle.jdbc.driver.OraclePreparedStatement.executeInternal(OraclePreparedStatement.java:3265) at oracle.jdbc.driver.OraclePreparedStatement.executeUpdate(OraclePreparedStatement.java:3367) Any ideas?

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  • Laptop drains of quickly with battery

    - by Shyam
    I am a user since years in ubuntu and I have not come across this problem with ubuntu till date. My battery drains off immediately after I unplug my AC power. The options I tried: 1) checked the battery state with : cat /proc/acpi/battery/BAT0/state present: yes capacity state: ok charging state: charged present rate: 0 mA remaining capacity: 392 mAh present voltage: 12476 mV Initially it was showing charging state: charging after 5mins it started displaying as charged. ! Based on that if I remove my AC Power it shows low battery notification. 2) When I run acpi : acpi -b Battery 0: Unknown, 9% The battery state shows as unknown. But initially when we plug-in to AC adapter acpi -b Battery 0: Charging, 9%, 13:04:00 until charged 3) When the check the same with : upower -i /org/freedesktop/UPower/devices/battery_BAT0 native-path: /sys/devices/LNXSYSTM:00/device:00/PNP0A08:00/device:02/PNP0C09:00/PNP0C0A:00/power_supply/BAT0 vendor: HP power supply: yes updated: Thu Nov 1 16:06:40 2012 (20 seconds ago) has history: yes has statistics: yes battery present: yes rechargeable: yes state: charging energy: 4.2336 Wh energy-empty: 0 Wh energy-full: 33.1128 Wh energy-full-design: 33.1128 Wh energy-rate: 5.6052 W voltage: 12.474 V time to full: 5.2 hours percentage: 12.7854% capacity: 100% technology: lithium-ion Is the power stats output, It says 5hrs to charge completely, If I charge it even more than 5hrs and unplug the AC power, It again cribs stating LOW BATTERY !! The same thing does not happen with Windows7. Any suggestions/ help will be greatly appreciated.

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  • mdadm starts resync on every boot

    - by Anteru
    Since a few days (and I'm positive it started shortly before I updated my server from 13.04-13.10) my mdadm is resyncing on every boot. In the syslog, I get the following output [ 0.809256] md: linear personality registered for level -1 [ 0.811412] md: multipath personality registered for level -4 [ 0.813153] md: raid0 personality registered for level 0 [ 0.815201] md: raid1 personality registered for level 1 [ 1.101517] md: raid6 personality registered for level 6 [ 1.101520] md: raid5 personality registered for level 5 [ 1.101522] md: raid4 personality registered for level 4 [ 1.106825] md: raid10 personality registered for level 10 [ 1.935882] md: bind<sdc1> [ 1.943367] md: bind<sdb1> [ 1.945199] md/raid1:md0: not clean -- starting background reconstruction [ 1.945204] md/raid1:md0: active with 2 out of 2 mirrors [ 1.945225] md0: detected capacity change from 0 to 2000396680192 [ 1.945351] md: resync of RAID array md0 [ 1.945357] md: minimum _guaranteed_ speed: 1000 KB/sec/disk. [ 1.945359] md: using maximum available idle IO bandwidth (but not more than 200000 KB/sec) for resync. [ 1.945362] md: using 128k window, over a total of 1953512383k. [ 2.220468] md0: unknown partition table I'm not sure what's up with that detected capacity change, looking at some old logs, this does have appeared earlier as well without a resync right afterwards. In fact, I let it run yesterday until completion and rebooted, and then it wouldn't resync, but today it does resync again. For instance, yesterday I got: [ 1.872123] md: bind<sdc1> [ 1.950946] md: bind<sdb1> [ 1.952782] md/raid1:md0: active with 2 out of 2 mirrors [ 1.952807] md0: detected capacity change from 0 to 2000396680192 [ 1.954598] md0: unknown partition table So it seems to be a problem that the RAID array does not get marked as clean after every shutdown? How can I troubleshoot this? The disks themselves are both fine, SMART tells me no errors, everything ok.

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  • Big Data Appliance X4-2 Release Announcement

    - by Jean-Pierre Dijcks
    Today we are announcing the release of the 3rd generation Big Data Appliance. Read the Press Release here. Software Focus The focus for this 3rd generation of Big Data Appliance is: Comprehensive and Open - Big Data Appliance now includes all Cloudera Software, including Back-up and Disaster Recovery (BDR), Search, Impala, Navigator as well as the previously included components (like CDH, HBase and Cloudera Manager) and Oracle NoSQL Database (CE or EE). Lower TCO then DIY Hadoop Systems Simplified Operations while providing an open platform for the organization Comprehensive security including the new Audit Vault and Database Firewall software, Apache Sentry and Kerberos configured out-of-the-box Hardware Update A good place to start is to quickly review the hardware differences (no price changes!). On a per node basis the following is a comparison between old and new (X3-2) hardware: Big Data Appliance X3-2 Big Data Appliance X4-2 CPU 2 x 8-Core Intel® Xeon® E5-2660 (2.2 GHz) 2 x 8-Core Intel® Xeon® E5-2650 V2 (2.6 GHz) Memory 64GB 64GB Disk 12 x 3TB High Capacity SAS 12 x 4TB High Capacity SAS InfiniBand 40Gb/sec 40Gb/sec Ethernet 10Gb/sec 10Gb/sec For all the details on the environmentals and other useful information, review the data sheet for Big Data Appliance X4-2. The larger disks give BDA X4-2 33% more capacity over the previous generation while adding faster CPUs. Memory for BDA is expandable to 512 GB per node and can be done on a per-node basis, for example for NameNodes or for HBase region servers, or for NoSQL Database nodes. Software Details More details in terms of software and the current versions (note BDA follows a three monthly update cycle for Cloudera and other software): Big Data Appliance 2.2 Software Stack Big Data Appliance 2.3 Software Stack Linux Oracle Linux 5.8 with UEK 1 Oracle Linux 6.4 with UEK 2 JDK JDK 6 JDK 7 Cloudera CDH CDH 4.3 CDH 4.4 Cloudera Manager CM 4.6 CM 4.7 And like we said at the beginning it is important to understand that all other Cloudera components are now included in the price of Oracle Big Data Appliance. They are fully supported by Oracle and available for all BDA customers. For more information: Big Data Appliance Data Sheet Big Data Connectors Data Sheet Oracle NoSQL Database Data Sheet (CE | EE) Oracle Advanced Analytics Data Sheet

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  • Powershell variables to string

    - by Mike Koerner
    I'm new to powershell. I'm trying to write an error handler to wrap around my script.  Part of the error handler is dumping out some variable settings.  I spent a while trying to do this and couldn't google a complete solution so I thought I'd post something. I want to display the $myinvocation variable. In powershell you can do this PS C:\> $myInvocation for my purpose I want to create a stringbuilder object and append the $myinvocation info.  I tried this $sbOut = new-object System.Text.Stringbuilder $sbOut.appendLine($myinvocation) $sbOut.ToString() This produces                                    Capacity                                MaxCapacity                                     Length                                    --------                                -----------                                     ------                                          86                                 2147483647                                         45 System.Management.Automation.InvocationInfo This is not what I wanted so I tried $sbOut.appendLine(($myinvocation|format-list *)) This produced                                    Capacity                                MaxCapacity                                     Length                                    --------                                -----------                                     ------                                         606                                 2147483647                                        305 Microsoft.PowerShell.Commands.Internal.Format.FormatStartData Microsoft.PowerShell.Commands.Internal.Format.GroupStartData Micros oft.PowerShell.Commands.Internal.Format.FormatEntryData Microsoft.PowerShell.Commands.Internal.Format.GroupEndData Microsoft.Powe rShell.Commands.Internal.Format.FormatEndData Finally I figured out how to produce what I wanted: $sbOut = new-object System.Text.Stringbuilder [void]$sbOut.appendLine(($myinvocation|out-string)) $sbOut.ToString() MyCommand        : $sbOut = new-object System.Text.Stringbuilder                                    [void]$sbOut.appendLine(($myinvocation|out-string))                                      $sbOut.ToString()                    BoundParameters  : {} UnboundArguments : {} ScriptLineNumber : 0 OffsetInLine     : 0 HistoryId        : 13 ScriptName       : Line             : PositionMessage  : InvocationName   : PipelineLength   : 2 PipelinePosition : 1 ExpectingInput   : False CommandOrigin    : Runspace Note the [void] in front of the stringbuilder variable doesn't show the Capacity,MaxCapacity of the stringbuilder object.  The pipe to out-string makes the output a string. It's not pretty but it works.

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  • USB mass storage couldn't get mounted

    - by revo
    It's my android phone SD card which was indicated damaged by android yesterday night, out of the blue! I put it directly to a USB port with a USB SD card holder case, so in that way I can recover it with TestDisk, which I had experienced before on a similar situation. I also noticed that there is a change in file system and capacity: File System : RAW Capacity : 0 (unknown capacity) Also TestDisk doesn't show it on its partitions list. A 2 GB SD card is not that important in price but I've a lot of files and medias which I need them. Used a mini card reader, TestDisk displayed it on its list but a quick search and or a deep search doesn't have any results No partition found or selected for recovery and then I should quit the program. Your help is appreciated. Update #2 lsusb output: Bus 005 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 002 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 004 Device 002: ID 04f3:0234 Elan Microelectronics Corp. Bus 004 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 001 Device 002: ID 058f:6366 Alcor Micro Corp. Multi Flash Reader Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 003 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 009 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 008 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 007 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub Bus 006 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub

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  • apache fails to connect to tomcat (Worker config?)

    - by techventure
    I have a tomcat 6 with follwoing server.xml: <Connector port="8253" maxThreads="150" minSpareThreads="25" maxSpareThreads="75" enableLookups="false" redirectPort="8445" acceptCount="100" debug="0" connectionTimeout="20000" disableUploadTimeout="true" /> <Connector port="8014" protocol="AJP/1.3" redirectPort="8445" /> and in added worker.properties: # Set properties for worker4 (ajp13) worker.worker4.type=ajp13 worker.worker4.host=localhost worker.worker4.port=8014 and i put in httpd.conf: JkMount /myWebApp/* worker4 It is not working a as trying to navigate to www1.myCompany.com/myWebApp gives "Service Temporarily Unavailable". I checked in tomcat catalina.out and it says: INFO: JK: ajp13 listening on /0.0.0.0:8014 UPDATE: i put mod_jk log level to debug and below is the result: [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_set_time_fmt::jk_util.c (458): Pre-processed log time stamp format is '[%a %b %d %H:%M:%S %Y] ' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_open::jk_uri_worker_map.c (770): rule map size is 8 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_add::jk_uri_worker_map.c (720): wildchar rule '/myWebApp/*=worker4' source 'JkMount' was added [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (171): uri map dump after map open: index=0 file='(null)' reject_unsafe=0 reload=60 modified=0 checked=0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 0: size=0 nosize=0 capacity=0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 1: size=8 nosize=0 capacity=8 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (186): NEXT (1) map #3: uri=/myWebApp/* worker=worker4 context=/myWebApp/* source=JkMount type=Wildchar len=6 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_set_time_fmt::jk_util.c (458): Pre-processed log time stamp format is '[%a %b %d %H:%M:%S %Y] ' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] init_jk::mod_jk.c (3123): Setting default connection pool max size to 1 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.list' with value 'worker1,worker2,worker3,worker4' to map. [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.type' with value 'ajp13' to map. [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.host' with value 'localhost' to map. [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.port' with value '8014' to map. [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_resolve_references::jk_map.c (774): Checking for references with prefix worker. with wildcard (recursion 1) [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_shm_calculate_size::jk_shm.c (132): shared memory will contain 4 ajp workers of size 256 and 0 lb workers of size 320 with 0 members of size 320+256 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [error] init_jk::mod_jk.c (3166): Initializing shm:/var/log/httpd/mod_jk.shm.9552 errno=13. Load balancing workers will not function properly. [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'ServerRoot' -> '/etc/httpd' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.list' -> 'worker1,worker2,worker3,worker4' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.port' -> '8009' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.port' -> '8010' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.port' -> '8112' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.port' -> '8014' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] build_worker_map::jk_worker.c (242): creating worker worker4 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] wc_create_worker::jk_worker.c (146): about to create instance worker4 of ajp13 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] wc_create_worker::jk_worker.c (159): about to validate and init worker4 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_validate::jk_ajp_common.c (2512): worker worker4 contact is 'localhost:8014' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2699): setting endpoint options: [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2702): keepalive: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2706): socket timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2710): socket connect timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2714): buffer size: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2718): pool timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2722): ping timeout: 10000 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2726): connect timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2730): reply timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2734): prepost timeout: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2738): recovery options: 0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2742): retries: 2 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2746): max packet size: 8192 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_init::jk_ajp_common.c (2750): retry interval: 100 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] ajp_create_endpoint_cache::jk_ajp_common.c (2562): setting connection pool size to 1 with min 1 and acquire timeout 200 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [info] init_jk::mod_jk.c (3183): mod_jk/1.2.28 initialized [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] wc_get_worker_for_name::jk_worker.c (116): found a worker worker4 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] wc_get_name_for_type::jk_worker.c (293): Found worker type 'ajp13' [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_ext::jk_uri_worker_map.c (512): Checking extension for worker 3: worker4 of type ajp13 (2) [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (171): uri map dump after extension stripping: index=0 file='(null)' reject_unsafe=0 reload=60 modified=0 checked=0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 0: size=0 nosize=0 capacity=0 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 1: size=8 nosize=0 capacity=8 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (186): NEXT (1) map #3: uri=/myWebApp/* worker=worker4 context=/myWebApp/* source=JkMount type=Wildchar len=6 [Wed Jun 13 18:44:26 2012] [9552:3086317328] [debug] uri_worker_map_switch::jk_uri_worker_map.c (482): Switching uri worker map from index 0 to index 1 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_set_time_fmt::jk_util.c (458): Pre-processed log time stamp format is '[%a %b %d %H:%M:%S %Y] ' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_open::jk_uri_worker_map.c (770): rule map size is 8 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_add::jk_uri_worker_map.c (720): wildchar rule '/myWebApp/*=worker4' source 'JkMount' was added [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (171): uri map dump after map open: index=0 file='(null)' reject_unsafe=0 reload=60 modified=0 checked=0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 0: size=0 nosize=0 capacity=0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 1: size=8 nosize=0 capacity=8 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (186): NEXT (1) map #0: uri=/jsp-examples/* worker=worker1 context=/jsp-examples/* source=JkMount type=Wildchar len=15 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (186): NEXT (1) map #3: uri=/myWebApp/* worker=worker4 context=/myWebApp/* source=JkMount type=Wildchar len=6 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_set_time_fmt::jk_util.c (458): Pre-processed log time stamp format is '[%a %b %d %H:%M:%S %Y] ' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] init_jk::mod_jk.c (3123): Setting default connection pool max size to 1 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.list' with value 'worker1,worker2,worker3,worker4' to map. [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.type' with value 'ajp13' to map. [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.host' with value 'localhost' to map. [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_read_property::jk_map.c (491): Adding property 'worker.worker4.port' with value '8014' to map. [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_resolve_references::jk_map.c (774): Checking for references with prefix worker. with wildcard (recursion 1) [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_shm_calculate_size::jk_shm.c (132): shared memory will contain 4 ajp workers of size 256 and 0 lb workers of size 320 with 0 members of size 320+256 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [error] init_jk::mod_jk.c (3166): Initializing shm:/var/log/httpd/mod_jk.shm.9553 errno=13. Load balancing workers will not function properly. [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'ServerRoot' -> '/etc/httpd' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.list' -> 'worker1,worker2,worker3,worker4' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker1.port' -> '8009' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker2.port' -> '8010' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker3.port' -> '8112' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.type' -> 'ajp13' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.host' -> 'localhost' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] jk_map_dump::jk_map.c (589): Dump of map: 'worker.worker4.port' -> '8014' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] build_worker_map::jk_worker.c (242): creating worker worker4 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] wc_create_worker::jk_worker.c (146): about to create instance worker4 of ajp13 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] wc_create_worker::jk_worker.c (159): about to validate and init worker4 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_validate::jk_ajp_common.c (2512): worker worker4 contact is 'localhost:8014' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2699): setting endpoint options: [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2702): keepalive: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2706): socket timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2710): socket connect timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2714): buffer size: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2718): pool timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2722): ping timeout: 10000 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2726): connect timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2730): reply timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2734): prepost timeout: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2738): recovery options: 0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2742): retries: 2 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2746): max packet size: 8192 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_init::jk_ajp_common.c (2750): retry interval: 100 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] ajp_create_endpoint_cache::jk_ajp_common.c (2562): setting connection pool size to 1 with min 1 and acquire timeout 200 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [info] init_jk::mod_jk.c (3183): mod_jk/1.2.28 initialized [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] wc_get_worker_for_name::jk_worker.c (116): found a worker worker4 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] wc_get_name_for_type::jk_worker.c (293): Found worker type 'ajp13' [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_ext::jk_uri_worker_map.c (512): Checking extension for worker 3: worker4 of type ajp13 (2) [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (171): uri map dump after extension stripping: index=0 file='(null)' reject_unsafe=0 reload=60 modified=0 checked=0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 0: size=0 nosize=0 capacity=0 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (176): generation 1: size=8 nosize=0 capacity=8 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_dump::jk_uri_worker_map.c (186): NEXT (1) map #3: uri=/myWebApp/* worker=worker4 context=/myWebApp/* source=JkMount type=Wildchar len=6 [Wed Jun 13 18:44:26 2012] [9553:3086317328] [debug] uri_worker_map_switch::jk_uri_worker_map.c (482): Switching uri worker map from index 0 to index 1 [Wed Jun 13 18:44:26 2012] [9555:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9556:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9557:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9558:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9559:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9560:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9561:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9562:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9563:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9564:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9565:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9567:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9568:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9566:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9569:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:26 2012] [9570:3086317328] [debug] jk_child_init::mod_jk.c (3068): Initialized mod_jk/1.2.28 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] map_uri_to_worker_ext::jk_uri_worker_map.c (1036): Attempting to map URI '/myWebApp/jsp/login.faces' from 8 maps [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] find_match::jk_uri_worker_map.c (850): Attempting to map context URI '/myWebApp/*=worker4' source 'JkMount' [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] find_match::jk_uri_worker_map.c (863): Found a wildchar match '/myWebApp/*=worker4' [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] jk_handler::mod_jk.c (2459): Into handler jakarta-servlet worker=worker4 r->proxyreq=0 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_get_worker_for_name::jk_worker.c (116): found a worker worker4 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_maintain::jk_worker.c (339): Maintaining worker worker1 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_maintain::jk_worker.c (339): Maintaining worker worker2 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_maintain::jk_worker.c (339): Maintaining worker worker3 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_maintain::jk_worker.c (339): Maintaining worker worker4 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] wc_get_name_for_type::jk_worker.c (293): Found worker type 'ajp13' [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] init_ws_service::mod_jk.c (977): Service protocol=HTTP/1.1 method=GET ssl=false host=(null) addr=167.184.214.6 name=www1.myCompany.com.au port=80 auth=(null) user=(null) laddr=10.215.222.78 raddr=167.184.214.6 uri=/myWebApp/jsp/login.faces [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_get_endpoint::jk_ajp_common.c (2977): acquired connection pool slot=0 after 0 retries [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_marshal_into_msgb::jk_ajp_common.c (605): ajp marshaling done [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_service::jk_ajp_common.c (2283): processing worker4 with 2 retries [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_send_request::jk_ajp_common.c (1501): (worker4) all endpoints are disconnected. [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] jk_open_socket::jk_connect.c (452): socket TCP_NODELAY set to On [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] jk_open_socket::jk_connect.c (576): trying to connect socket 18 to 127.0.0.1:8014 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] jk_open_socket::jk_connect.c (594): connect to 127.0.0.1:8014 failed (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] ajp_connect_to_endpoint::jk_ajp_common.c (922): Failed opening socket to (127.0.0.1:8014) (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [error] ajp_send_request::jk_ajp_common.c (1507): (worker4) connecting to backend failed. Tomcat is probably not started or is listening on the wrong port (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] ajp_service::jk_ajp_common.c (2447): (worker4) sending request to tomcat failed (recoverable), because of error during request sending (attempt=1) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_service::jk_ajp_common.c (2304): retry 1, sleeping for 100 ms before retrying [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_send_request::jk_ajp_common.c (1501): (worker4) all endpoints are disconnected. [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] jk_open_socket::jk_connect.c (452): socket TCP_NODELAY set to On [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] jk_open_socket::jk_connect.c (576): trying to connect socket 18 to 127.0.0.1:8014 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] jk_open_socket::jk_connect.c (594): connect to 127.0.0.1:8014 failed (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] ajp_connect_to_endpoint::jk_ajp_common.c (922): Failed opening socket to (127.0.0.1:8014) (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [error] ajp_send_request::jk_ajp_common.c (1507): (worker4) connecting to backend failed. Tomcat is probably not started or is listening on the wrong port (errno=13) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] ajp_service::jk_ajp_common.c (2447): (worker4) sending request to tomcat failed (recoverable), because of error during request sending (attempt=2) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [error] ajp_service::jk_ajp_common.c (2466): (worker4) connecting to tomcat failed. [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_reset_endpoint::jk_ajp_common.c (743): (worker4) resetting endpoint with sd = 4294967295 (socket shutdown) [Wed Jun 13 18:44:54 2012] [9555:3086317328] [debug] ajp_done::jk_ajp_common.c (2905): recycling connection pool slot=0 for worker worker4 [Wed Jun 13 18:44:54 2012] [9555:3086317328] [info] jk_handler::mod_jk.c (2615): Service error=-3 for worker=worker4 The error i get in browser is: Service Temporarily Unavailable Apache/2.2.3 (Red Hat) Server at www1.myCompany.com.au Port 80 can someone please help and explain what is going on and how it can be resolved?

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  • What's New in Database Lifecycle Management in Enterprise Manager 12c Release 3

    - by HariSrinivasan
    Enterprise Manager 12c Release 3 includes improvements and enhancements across every area of the product. This blog provides an overview of the new and enhanced features in the Database Lifecycle Management area. I will deep dive into specific features more in depth in subsequent posts. "What's New?"  In this release, we focused on four things: 1. Lifecycle Management Support for new Database12c - Pluggable Databases 2. Management of long running processes, such as a security patch cycle (Change Activity Planner) 3. Management of large number of systems by · Leveraging new framework capabilities for lifecycle operations, such as the new advanced ‘emcli’ script option · Refining features such as configuration search and compliance 4. Minor improvements and quality fixes to existing features · Rollback support for Single instance databases · Improved "OFFLINE" Patching experience · Faster collection of ORACLE_HOME configurations Lifecycle Management Support for new Database 12c - Pluggable Databases Database 12c introduces Pluggable Databases (PDBs), the brand new addition to help you achieve your consolidation goals. Pluggable databases offer unprecedented consolidation at database level and native lifecycle verbs for creating, plugging and unplugging the databases on a container database (CDB). Enterprise Manager can supplement the capabilities of pluggable databases by offering workflows for migrating, provisioning and cloning them using the software library and the deployment procedures. For example, Enterprise Manager can migrate an existing database to a PDB or clone a PDB by storing a versioned copy in the software library. One can also manage the planned downtime related to patching by  migrating the PDBs to a new CDB. While pluggable databases offer these exciting features, it can also pose configuration management and compliance challenges if not managed properly. Enterprise Manager features like inventory management, topology associations and configuration search can mitigate the sprawl of PDBs and also lock them to predefined golden standards using configuration comparison and compliance rules. Learn More ... Management of Long Running datacenter processes - Change Activity Planner (CAP) Currently, customers resort to cumbersome methods to create, execute, track and monitor change activities within their data center. Some customers use traditional tools such as spreadsheets, project planners and in-house custom built solutions. Customers often have weekly sync up meetings across stake holders to collect status and updates. Some of the change activities, for example the quarterly patch set update (PSU) patch rollouts are not single tasks but processes with multiple tasks. Some of those tasks are performed within Enterprise Manager Cloud Control (for example Patch) and some are performed outside of Enterprise Manager Cloud Control. These tasks often run for a longer period of time and involve multiple people or teams. Enterprise Manger Cloud Control supports core data center operations such as configuration management, compliance management, and automation. Enterprise Manager Cloud Control release 12.1.0.3 leverages these capabilities and introduces the Change Activity Planner (CAP). CAP provides the ability to plan, execute, and track change activities in real time. It covers the typical datacenter activities that are spread over a long period of time, across multiple people and multiple targets (even target types). Here are some examples of Change Activity Process in a datacenter: · Patching large environments (PSU/CPU Patching cycles) · Upgrading large number of database environments · Rolling out Compliance Rules · Database Consolidation to Exadata environments CAP provides user flows for Compliance Officers/Managers (incl. lead administrators) and Operators (DBAs and admins). Managers can create change activity plans for various projects, allocate resources, targets, and groups affected. Upon activation of the plan, tasks are created and automatically assigned to individual administrators based on target ownership. Administrators (DBAs) can identify their tasks and understand the context, schedules, and priorities. They can complete tasks using Enterprise Manager Cloud Control automation features such as patch plans (or in some cases outside Enterprise Manager). Upon completion, compliance is evaluated for validations and updates the status of the tasks and the plans. Learn More about CAP ...  Improved Configuration & Compliance Management of a large number of systems Improved Configuration Comparison:  Get to the configuration comparison results faster for simple ad-hoc comparisons. When performing a 1 to 1 comparison, Enterprise Manager will perform the comparison immediately and take the user directly to the results without having to wait for a job to be submitted and executed. Flattened system comparisons reduce comparison setup time and reduce complexity. In addition to the previously existing topological comparison, users now have an option to compare using a “flattened” methodology. Flattening means to remove duplicate target instances within the systems and remove the hierarchy of member targets. The result are much easier to spot differences particularly for specific use cases like comparing patch levels between complex systems like RAC and Fusion Apps. Improved Configuration Search & Advanced EMCLI Script option for Mass Automation Enterprise manager 12c introduces a new framework level capability to be able to script and stitch together multiple tasks using EMCLI. This powerful capability can be leveraged for lifecycle operations, especially when executing a task over a large number of targets. Specific usages of this include, retrieving a qualified list of targets using Configuration Search and then using the resultset for automation. Another example would be executing a patching operation and then re-executing on targets where it may have failed. This is complemented by other enhancements, such as a better usability for designing reusable configuration searches. IN EM 12c Rel 3, a simplified UI makes building adhoc searches even easier. Searching for missing patches is a common use of configuration search. This required the use of the advanced options which are now clearly defined and easy to use. Perform “Configuration Search” using the EMCLI. Users can find and execute Configuration Searches from the EMCLI which can be extremely useful for building sophisticated automation scripts. For an example, Run the Search named “Oracle Databases on Exadata” which finds all Database targets running on top of Exadata. Further filter the results by refining by options like name, host, etc.. emcli get_targets -config_search="Databases on Exadata" –target_name="exa%“ Use this in powerful mass automation operations using the new emcli script option. For example, to solve the use case of – Finding all DBs running on Exadata and housing E-Biz and Patch them. Create a Python script with emcli functions and invoke it in the new EMCLI script option shell. Invoke the script in the new EMCLI with script option directly: $<path to emcli>/emcli @myPSU_Patch.py Richer compliance content:  Now over 50 Oracle Provided Compliance Standards including new standards for Pluggable Database, Fusion Applications, Oracle Identity Manager, Oracle VM and Internet Directory. 9 Oracle provided Real Time Monitoring Standards containing over 900 Compliance Rules across 500 Facets. These new Real time Compliance Standards covers both Exadata Compute nodes and Linux servers. The result is increased Oracle software coverage and faster time to compliance monitoring on Exadata. Enhancements to Patch Management: Overhauled "OFFLINE" Patching experience: Simplified Patch uploads UI to improve the offline experience of patching. There is now a single step process to get the patches into software library. Customers often maintain local repositories of patches, sometimes called software depots, where they host the patches downloaded from My Oracle Support. In the past, you had to move these patches to your desktop then upload them to the Enterprise Manager's Software library through the Enterprise Manager Cloud Control user interface. You can now use the following EMCLI command to upload multiple patches directly from a remote location within the data center: $emcli upload_patches -location <Path to Patch directory> -from_host <HOSTNAME> The upload process filters all of the new patches, automatically selects the relevant metadata files from the location, and uploads the patches to software library. Other Improvements:  Patch rollback for single instance databases, new option in the Patch Plan to rollback the patches added to the patch plans. Upon execution, the procedure would rollback the patch and the SQL applied to the single instance Databases. Improved and faster configuration collection of Oracle Home targets can enable more reliable automation at higher level functions like Provisioning, Patching or Database as a Service. Just to recap, here is a list of database lifecycle management features:  * Red highlights mark – New or Enhanced in the Release 3. • Discovery, inventory tracking and reporting • Database provisioning including o Migration to Pluggable databases o Plugging and unplugging of pluggable databases o Gold image based cloning o Scaling of RAC nodes •Schema and data change management •End-to-end patch management in online and offline modes, including o Patch advisories in online (connected with My Oracle Support) and offline mode o Patch pre-deployment analysis, deployment and rollback (currently only for single instance databases) o Reporting • Upgrade planning and execution of the upgrade process • Configuration management including • Compliance management with out-of-box content • Change Activity Planner for planning, designing and tracking long running processes For more information on Enterprise Manager’s database lifecycle management capabilities, visit http://www.oracle.com/technetwork/oem/lifecycle-mgmt/index.html

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  • How to indicate reliability when reporting availability of competencies

    - by Jan Doggen
    We have employees with competencies: Pete Welder Carpenter Melissa Carpenter Assume they both work 40 hours/week, and have not yet been assigned work. We need to report the availability of these competencies, expressed in hours. As far as I can see now, we can report this in two ways: Method A. When someone has multiple competencies, count them both. Welder 40 hours Carpenter 80 hours Method B. When someone has multiple competencies, count an equal division of hours for each Welder 20 hours Carpenter 60 hours Method A has our preference: - A good planner will know to plan the least available competency first. If 30 hours of welding is planned, we will be left with 10 welder, 50 carpenter. - Method B has the disadvantage that the planner thinks he cannot plan the job when 30 hours of welding is required. However, if we report this we would like to give an estimate of the reliability of the numbers for each competency, i.e. how much are these over-reported? In my example A, would I say that carpenter is 100% over-reported, or 50%, or maybe another number? How would I calculate this for large numbers of competencies? I'm sure we are not the first ones dealing with this, is there a 'usual' way of doing this in planning? Additionally: - Would there be an even better method than A or B? - Optionally, we also have an preference order of competencies (like: use him/her in this order), Pete could be 1. welder 2. carpenter. Does this introduce new options?

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  • Oracle Announces Oracle Exadata X3 Database In-Memory Machine

    - by jgelhaus
    Fourth Generation Exadata X3 Systems are Ideal for High-End OLTP, Large Data Warehouses, and Database Clouds; Eighth-Rack Configuration Offers New Low-Cost Entry Point ORACLE OPENWORLD, SAN FRANCISCO – October 1, 2012 News Facts During his opening keynote address at Oracle OpenWorld, Oracle CEO, Larry Ellison announced the Oracle Exadata X3 Database In-Memory Machine - the latest generation of its Oracle Exadata Database Machines. The Oracle Exadata X3 Database In-Memory Machine is a key component of the Oracle Cloud. Oracle Exadata X3-2 Database In-Memory Machine and Oracle Exadata X3-8 Database In-Memory Machine can store up to hundreds of Terabytes of compressed user data in Flash and RAM memory, virtually eliminating the performance overhead of reads and writes to slow disk drives, making Exadata X3 systems the ideal database platforms for the varied and unpredictable workloads of cloud computing. In order to realize the highest performance at the lowest cost, the Oracle Exadata X3 Database In-Memory Machine implements a mass memory hierarchy that automatically moves all active data into Flash and RAM memory, while keeping less active data on low-cost disks. With a new Eighth-Rack configuration, the Oracle Exadata X3-2 Database In-Memory Machine delivers a cost-effective entry point for smaller workloads, testing, development and disaster recovery systems, and is a fully redundant system that can be used with mission critical applications. Next-Generation Technologies Deliver Dramatic Performance Improvements Oracle Exadata X3 Database In-Memory Machines use a combination of scale-out servers and storage, InfiniBand networking, smart storage, PCI Flash, smart memory caching, and Hybrid Columnar Compression to deliver extreme performance and availability for all Oracle Database Workloads. Oracle Exadata X3 Database In-Memory Machine systems leverage next-generation technologies to deliver significant performance enhancements, including: Four times the Flash memory capacity of the previous generation; with up to 40 percent faster response times and 100 GB/second data scan rates. Combined with Exadata’s unique Hybrid Columnar Compression capabilities, hundreds of Terabytes of user data can now be managed entirely within Flash; 20 times more capacity for database writes through updated Exadata Smart Flash Cache software. The new Exadata Smart Flash Cache software also runs on previous generation Exadata systems, increasing their capacity for writes tenfold; 33 percent more database CPU cores in the Oracle Exadata X3-2 Database In-Memory Machine, using the latest 8-core Intel® Xeon E5-2600 series of processors; Expanded 10Gb Ethernet connectivity to the data center in the Oracle Exadata X3-2 provides 40 10Gb network ports per rack for connecting users and moving data; Up to 30 percent reduction in power and cooling. Configured for Your Business, Available Today Oracle Exadata X3-2 Database In-Memory Machine systems are available in a Full-Rack, Half-Rack, Quarter-Rack, and the new low-cost Eighth-Rack configuration to satisfy the widest range of applications. Oracle Exadata X3-8 Database In-Memory Machine systems are available in a Full-Rack configuration, and both X3 systems enable multi-rack configurations for virtually unlimited scalability. Oracle Exadata X3-2 and X3-8 Database In-Memory Machines are fully compatible with prior Exadata generations and existing systems can also be upgraded with Oracle Exadata X3-2 servers. Oracle Exadata X3 Database In-Memory Machine systems can be used immediately with any application certified with Oracle Database 11g R2 and Oracle Real Application Clusters, including SAP, Oracle Fusion Applications, Oracle’s PeopleSoft, Oracle’s Siebel CRM, the Oracle E-Business Suite, and thousands of other applications. Supporting Quotes “Forward-looking enterprises are moving towards Cloud Computing architectures,” said Andrew Mendelsohn, senior vice president, Oracle Database Server Technologies. “Oracle Exadata’s unique ability to run any database application on a fully scale-out architecture using a combination of massive memory for extreme performance and low-cost disk for high capacity delivers the ideal solution for Cloud-based database deployments today.” Supporting Resources Oracle Press Release Oracle Exadata Database Machine Oracle Exadata X3-2 Database In-Memory Machine Oracle Exadata X3-8 Database In-Memory Machine Oracle Database 11g Follow Oracle Database via Blog, Facebook and Twitter Oracle OpenWorld 2012 Oracle OpenWorld 2012 Keynotes Like Oracle OpenWorld on Facebook Follow Oracle OpenWorld on Twitter Oracle OpenWorld Blog Oracle OpenWorld on LinkedIn Mark Hurd's keynote with Andy Mendelsohn and Juan Loaiza - - watch for the replay to be available soon at http://www.youtube.com/user/Oracle or http://www.oracle.com/openworld/live/on-demand/index.html

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  • Windows Azure Use Case: Agility

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Agility in this context is defined as the ability to quickly develop and deploy an application. In theory, the speed at which your organization can develop and deploy an application on available hardware is identical to what you could deploy in a distributed environment. But in practice, this is not always the case. Having an option to use a distributed environment can be much faster for the deployment and even the development process. Implementation: When an organization designs code, they are essentially becoming a Software-as-a-Service (SaaS) provider to their own organization. To do that, the IT operations team becomes the Infrastructure-as-a-Service (IaaS) to the development teams. From there, the software is developed and deployed using an Application Lifecycle Management (ALM) process. A simplified view of an ALM process is as follows: Requirements Analysis Design and Development Implementation Testing Deployment to Production Maintenance In an on-premise environment, this often equates to the following process map: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including physical plant, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to on-premise Testing servers. If no server capacity available, more resources procured through standard budgeting and ordering processes. Manual and automated functional, load, security, etc. performed. Deployment to Production Server team involved to select platform and environments with available capacity. If no server capacity available, standard budgeting and procurement process followed. If no server capacity available, systems built, configured and put under standard organizational IT control. Systems configured for proper operating systems, patches, security and virus scans. System maintenance, HA/DR, backups and recovery plans configured and put into place. Maintenance Code changes evaluated and altered according to need. In a distributed computing environment like Windows Azure, the process maps a bit differently: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including budget, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to Azure. Manual and automated functional, load, security, etc. performed. Deployment to Production Code deployed to Azure. Point in time backup and recovery plans configured and put into place.(HA/DR and automated backups already present in Azure fabric) Maintenance Code changes evaluated and altered according to need. This means that several steps can be removed or expedited. It also means that the business function requesting the application can be held directly responsible for the funding of that request, speeding the process further since the IT budgeting process may not be involved in the Azure scenario. An additional benefit is the “Azure Marketplace”, In effect this becomes an app store for Enterprises to select pre-defined code and data applications to mesh or bolt-in to their current code, possibly saving development time. Resources: Whitepaper download- What is ALM?  http://go.microsoft.com/?linkid=9743693  Whitepaper download - ALM and Business Strategy: http://go.microsoft.com/?linkid=9743690  LiveMeeting Recording on ALM and Windows Azure (registration required, but free): http://www.microsoft.com/uk/msdn/visualstudio/contact-us.aspx?sbj=Developing with Windows Azure (ALM perspective) - 10:00-11:00 - 19th Jan 2011

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  • Do I need to be worried about these SMART drive temperatures?

    - by Steve Lorimer
    I have 5 hard drives in a machine sitting in a cupboard. /dev/sda is a 500GB Seagate drive, and is the boot disk. /dev/sd{b,c,d,e} are 2TB drives in a raid6 configuration. smartctl is showing significantly higher temperatures (like ~140 degrees celsius) on the raid drives than the boot drive. Do I need to be worried? /dev/sdb and /dev/sde are new Western Digital Black drives (new=1 week) /dev/sdc and /dev/sdd are 5 year old Hitachi drives /dev/sda [SAT], Temperature_Celsius changed from 40 to 39 /dev/sdc [SAT], Temperature_Celsius changed from 142 to 146 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 142 /dev/sdd [SAT], Temperature_Celsius changed from 142 to 146 /dev/sda [SAT], Airflow_Temperature_Cel changed from 61 to 62 /dev/sda [SAT], Temperature_Celsius changed from 39 to 38 /dev/sde [SAT], Temperature_Celsius changed from 107 to 108 /dev/sdb [SAT], Temperature_Celsius changed from 108 to 109 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 150 /dev/sdc [SAT], Temperature_Celsius changed from 146 to 150 /dev/sda [SAT], Airflow_Temperature_Cel changed from 62 to 61 /dev/sda [SAT], Temperature_Celsius changed from 38 to 39 Update: Adding detailed drive information as per request: /dev/sda =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Seagate Pipeline HD 5900.2 Device Model: ST3500312CS Serial Number: 5VV47HXA LU WWN Device Id: 5 000c50 02aad5ad6 Firmware Version: SC13 User Capacity: 500,107,862,016 bytes [500 GB] Sector Size: 512 bytes logical/physical Rotation Rate: 5900 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 1.5 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdb =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Device Model: WDC WD2003FZEX-00Z4SA0 Serial Number: WD-WMC1F1398726 LU WWN Device Id: 5 0014ee 003b8bd25 Firmware Version: 01.01A01 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Sizes: 512 bytes logical, 4096 bytes physical Rotation Rate: 7200 rpm Device is: Not in smartctl database [for details use: -P showall] ATA Version is: ACS-2 (minor revision not indicated) SATA Version is: SATA 3.0, 6.0 Gb/s (current: 3.0 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdc =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Hitachi Deskstar 7K3000 Device Model: Hitachi HDS723020BLA642 Serial Number: MN1220F30WSTUD LU WWN Device Id: 5 000cca 369cc9f5d Firmware Version: MN6OA580 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Size: 512 bytes logical/physical Rotation Rate: 7200 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 6.0 Gb/s (current: 3.0 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sdd =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Model Family: Hitachi Deskstar 7K3000 Device Model: Hitachi HDS723020BLA642 Serial Number: MN1220F30WST4D LU WWN Device Id: 5 000cca 369cc9f48 Firmware Version: MN6OA580 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Size: 512 bytes logical/physical Rotation Rate: 7200 rpm Device is: In smartctl database [for details use: -P show] ATA Version is: ATA8-ACS T13/1699-D revision 4 SATA Version is: SATA 2.6, 6.0 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled /dev/sde =========================== smartctl 6.0 2012-10-10 r3643 [x86_64-linux-3.9.10-100.fc17.x86_64] (local build) Copyright (C) 2002-12, Bruce Allen, Christian Franke, www.smartmontools.org === START OF INFORMATION SECTION === Device Model: WDC WD2003FZEX-00Z4SA0 Serial Number: WD-WMC1F1483782 LU WWN Device Id: 5 0014ee 3002d235c Firmware Version: 01.01A01 User Capacity: 2,000,398,934,016 bytes [2.00 TB] Sector Sizes: 512 bytes logical, 4096 bytes physical Rotation Rate: 7200 rpm Device is: Not in smartctl database [for details use: -P showall] ATA Version is: ACS-2 (minor revision not indicated) SATA Version is: SATA 3.0, 6.0 Gb/s (current: 1.5 Gb/s) Local Time is: Tue Jun 3 10:54:11 2014 EST SMART support is: Available - device has SMART capability. SMART support is: Enabled

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  • Design by contracts and constructors

    - by devoured elysium
    I am implementing my own ArrayList for school purposes, but to spice up things a bit I'm trying to use C# 4.0 Code Contracts. All was fine until I needed to add Contracts to the constructors. Should I add Contract.Ensures() in the empty parameter constructor? public ArrayList(int capacity) { Contract.Requires(capacity > 0); Contract.Ensures(Size == capacity); _array = new T[capacity]; } public ArrayList() : this(32) { Contract.Ensures(Size == 32); } I'd say yes, each method should have a well defined contract. On the other hand, why put it if it's just delegating work to the "main" constructor? Logicwise, I wouldn't need to. The only point I see where it'd be useful to explicitly define the contract in both constructors is if in the future we have Intelisense support for contracts. Would that happen, it'd be useful to be explicit about which contracts each method has, as that'd appear in Intelisense. Also, are there any books around that go a bit deeper on the principles and usage of Design by Contracts? One thing is having knowledge of the syntax of how to use Contracts in a language (C#, in this case), other is knowing how and when to use it. I read several tutorials and Jon Skeet's C# in Depth article about it, but I'd like to go a bit deeper if possible. Thanks

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  • Python to Java translation

    - by obelix1337
    Hello, i get quite short code of algorithm in python, but i need to translate it to Java. I didnt find any program to do that, so i will really appreciate to help translating it. I learned python a very little to know the idea how algorithm work. The biggest problem is because in python all is object and some things are made really very confuzing like sum(self.flow[(source, vertex)] for vertex, capacity in self.get_edges(source)) and "self.adj" is like hashmap with multiple values which i have no idea how to put all together. Is any better collection for this code in java? code is: [CODE] class FlowNetwork(object): def __init__(self): self.adj, self.flow, = {},{} def add_vertex(self, vertex): self.adj[vertex] = [] def get_edges(self, v): return self.adj[v] def add_edge(self, u,v,w=0): self.adj[u].append((v,w)) self.adj[v].append((u,0)) self.flow[(u,v)] = self.flow[(v,u)] = 0 def find_path(self, source, sink, path): if source == sink: return path for vertex, capacity in self.get_edges(source): residual = capacity - self.flow[(source,vertex)] edge = (source,vertex,residual) if residual > 0 and not edge in path: result = self.find_path(vertex, sink, path + [edge]) if result != None: return result def max_flow(self, source, sink): path = self.find_path(source, sink, []) while path != None: flow = min(r for u,v,r in path) for u,v,_ in path: self.flow[(u,v)] += flow self.flow[(v,u)] -= flow path = self.find_path(source, sink, []) return sum(self.flow[(source, vertex)] for vertex, capacity in self.get_edges(source)) g = FlowNetwork() map(g.add_vertex, ['s','o','p','q','r','t']) g.add_edge('s','o',3) g.add_edge('s','p',3) g.add_edge('o','p',2) g.add_edge('o','q',3) g.add_edge('p','r',2) g.add_edge('r','t',3) g.add_edge('q','r',4) g.add_edge('q','t',2) print g.max_flow('s','t') [/CODE] result of this example is "5". algorithm find max flow in graph(linked list or whatever) from source vertex "s" to destination "t". Many thanx for any idea

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  • 2d Vector with wrong values

    - by Petris Rodrigo Fernandes
    I'm studing STL, then i thought "i'll make a 2d array!" but whatever... a coded this: vector< vector<int> > vetor; vetor.resize(10); vetor[0].resize(10); for(int i = 0; i < vetor.capacity(); i++){ for(int h = 0; h < vetor[0].capacity();h++){ vetor[i][h] = h; } } Until here, ok. But when i try to show the array value a use this: for(int i = 0; i < vetor.capacity(); i++){ cout << "LINE " << i << ": "; for(int h = 0; h < vetor[0].capacity();h++){ cout << vetor[i][h] <<" "; } cout << "\n"; } And the results are really wrong: LINE 0: 4 5 6 7 8 9 6 7 8 9 LINE 1: 0 1 2 3 0 1 2 3 0 1 LINE 2: 0 1 2 3 0 1 2 3 0 1 LINE 3: 0 1 2 3 0 1 2 3 0 1 LINE 4: 0 1 2 3 0 1 2 3 0 1 LINE 5: 0 1 2 3 0 1 2 3 0 1 LINE 6: 0 1 2 3 0 1 2 3 0 1 LINE 7: 0 1 2 3 0 1 2 3 0 1 LINE 8: 0 1 2 3 0 1 2 3 4 5 LINE 9: 0 1 2 3 4 5 6 7 8 9 What's happening with my program? it isn't printing the right values!

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 4

    - by MarkPearl
    Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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  • What kind of scaling method is it, when you add new software to a single server to handle more users? [on hold]

    - by Phil
    I have read about scaling (in terms of terminology and methods). This got me confused about the following: On a single computer, running a web server (say apache), if the system administrator adds a front, caching, reverse-proxy such as Varnish, which in that scenario increase the amount of requests this server is able to handle. My question: Setting up such cache increases the capacity of the server to handle work, hence scales it, but without increasing neither the amount of nodes or the node's capacity. What is the name for this type of scaling?

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  • Efficient algorithm for creating an ideal distribution of groups into containers?

    - by Inshim
    I have groups of students that need to be allocated into classrooms of a fixed capacity (say, 100 chairs in each). Each group must only be allocated to a single classroom, even if it is larger than the capacity (ie there can be an overflow, with students standing up) I need an algorithm to make the allocations with minimum overflows and under-capacity classrooms. A naive algorithm to do this allocation is horrendously slow when having ~200 groups, with a distribution of about half of them being under 20% of the classroom size. Any ideas where I can find at least some good starting point for making this algorithm lightning fast? Thanks!

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  • integrity Constraints on a table.

    - by Dinesh
    See this sample schema Passenger(id PK, Name) Plane(id PK, capacity, type); Flight(id PK, planeId FK(Plane), flightDate, StartLocation, destination) CREATE TABLE Reservation(PassengerId, flightId, PRIMARY KEY (passengerId, flightId), FOREIGN KEY (passengerId) REFERENCES Passenger, FOREIGN KEY (flightId) REFERENCES Flight); I need to define an integrity constraint that enforces the restriction that the number of passengers on a plane cannot exceed the plane’s capacity. I have tried and achieved so far is this. CREATE TABLE Reservation( passengerId INTEGER, flightId INTEGER, PRIMARY KEY (passengerId, flightId), FOREIGN KEY (passengerId) REFERENCES Passenger, FOREIGN KEY (flightId) REFERENCES Flight, Constraint check1 check(Not Exists(select * from Flight s, (select count(*) as totalRes from Reservation group by flightId) t where t.totalRes > s.capacity ) ) ); I am not sure i am doing in right way or not. Any suggestions?

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  • Best Practices - updated: which domain types should be used to run applications

    - by jsavit
    This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (formerly named Logical Domains). This is an updated and enlarged version of the post on this topic originally posted October 2012. One frequent question "what type of domain should I use to run applications?" There used to be a simple answer: "run applications in guest domains in almost all cases", but now there are more things to consider. Enhancements to Oracle VM Server for SPARC and introduction of systems like the current SPARC servers including the T4 and T5 systems, the Oracle SuperCluster T5-8 and Oracle SuperCluster M6-32 provide scale and performance much higher than the original servers that ran domains. Single-CPU performance, I/O capacity, memory sizes, are much larger now, and far more demanding applications are now being hosted in logical domains. The general advice continues to be "use guest domains in almost all cases", meaning, "use virtual I/O rather than physical I/O", unless there is a specific reason to use the other domain types. The sections below will discuss the criteria for choosing between domain types. Review: division of labor and types of domain Oracle VM Server for SPARC offloads management and I/O functionality from the hypervisor to domains (also called virtual machines), providing a modern alternative to older VM architectures that use a "thick", monolithic hypervisor. This permits a simpler hypervisor design, which enhances reliability, and security. It also reduces single points of failure by assigning responsibilities to multiple system components, further improving reliability and security. Oracle VM Server for SPARC defines the following types of domain, each with their own roles: Control domain - management control point for the server, runs the logical domain daemon and constraints engine, and is used to configure domains and manage resources. The control domain is the first domain to boot on a power-up, is always an I/O domain, and is usually a service domain as well. It doesn't have to be, but there's no reason to not leverage it for virtual I/O services. There is one control domain per T-series system, and one per Physical Domain (PDom) on an M5-32 or M6-32 system. M5 and M6 systems can be physically domained, with logical domains within the physical ones. I/O domain - a domain that has been assigned physical I/O devices. The devices may be one more more PCIe root complexes (in which case the domain is also called a root complex domain). The domain has native access to all the devices on the assigned PCIe buses. The devices can be any device type supported by Solaris on the hardware platform. a SR-IOV (Single-Root I/O Virtualization) function. SR-IOV lets a physical device (also called a physical function) or PF) be subdivided into multiple virtual functions (VFs) which can be individually assigned directly to domains. SR-IOV devices currently can be Ethernet or InfiniBand devices. direct I/O ownership of one or more PCI devices residing in a PCIe bus slot. The domain has direct access to the individual devices An I/O domain has native performance and functionality for the devices it owns, unmediated by any virtualization layer. It may also have virtual devices. Service domain - a domain that provides virtual network and disk devices to guest domains. The services are defined by commands that are run in the control domain. It usually is an I/O domain as well, in order for it to have devices to virtualize and serve out. Guest domain - a domain whose devices are all virtual rather than physical: virtual network and disk devices provided by one or more service domains. In common practice, this is where applications are run. Device considerations Consider the following when choosing between virtual devices and physical devices: Virtual devices provide the best flexibility - they can be dynamically added to and removed from a running domain, and you can have a large number of them up to a per-domain device limit. Virtual devices are compatible with live migration - domains that exclusively have virtual devices can be live migrated between servers supporting domains. On the other hand: Physical devices provide the best performance - in fact, native "bare metal" performance. Virtual devices approach physical device throughput and latency, especially with virtual network devices that can now saturate 10GbE links, but physical devices are still faster. Physical I/O devices do not add load to service domains - all the I/O goes directly from the I/O domain to the device, while virtual I/O goes through service domains, which must be provided sufficient CPU and memory capacity. Physical I/O devices can be other than network and disk - we virtualize network, disk, and serial console, but physical devices can be the wide range of attachable certified devices, including things like tape and CDROM/DVD devices. In some cases the lines are now blurred: virtual devices have better performance than previously: starting with Oracle VM Server for SPARC 3.1 there is near-native virtual network performance. There is more flexibility with physical devices than before: SR-IOV devices can now be dynamically reconfigured on domains. Tradeoffs one used to have to make are now relaxed: you can often have the flexibility of virtual I/O with performance that previously required physical I/O. You can have the performance and isolation of SR-IOV with the ability to dynamically reconfigure it, just like with virtual devices. Typical deployment A service domain is generally also an I/O domain: otherwise it wouldn't have access to physical device "backends" to offer to its clients. Similarly, an I/O domain is also typically a service domain in order to leverage the available PCI buses. Control domains must be I/O domains, because they boot up first on the server and require physical I/O. It's typical for the control domain to also be a service domain too so it doesn't "waste" the I/O resources it uses. A simple configuration consists of a control domain that is also the one I/O and service domain, and some number of guest domains using virtual I/O. In production, customers typically use multiple domains with I/O and service roles to eliminate single points of failure, as described in Availability Best Practices - Avoiding Single Points of Failure . Guest domains have virtual disk and virtual devices provisioned from more than one service domain, so failure of a service domain or I/O path or device does not result in an application outage. This also permits "rolling upgrades" in which service domains are upgraded one at a time while their guests continue to operate without disruption. (It should be noted that resiliency to I/O device failures can also be provided by the single control domain, using multi-path I/O) In this type of deployment, control, I/O, and service domains are used for virtualization infrastructure, while applications run in guest domains. Changing application deployment patterns The above model has been widely and successfully used, but more configuration options are available now. Servers got bigger than the original T2000 class machines with 2 I/O buses, so there is more I/O capacity that can be used for applications. Increased server capacity made it attractive to run more vertically-scaled applications, such as databases, with higher resource requirements than the "light" applications originally seen. This made it attractive to run applications in I/O domains so they could get bare-metal native I/O performance. This is leveraged by the Oracle SuperCluster engineered systems mentioned previously. In those engineered systems, I/O domains are used for high performance applications with native I/O performance for disk and network and optimized access to the Infiniband fabric. Another technical enhancement is Single Root I/O Virtualization (SR-IOV), which make it possible to give domains direct connections and native I/O performance for selected I/O devices. Not all I/O domains own PCI complexes, and there are increasingly more I/O domains that are not service domains. They use their I/O connectivity for performance for their own applications. However, there are some limitations and considerations: at this time, a domain using physical I/O cannot be live-migrated to another server. There is also a need to plan for security and introducing unneeded dependencies: if an I/O domain is also a service domain providing virtual I/O to guests, it has the ability to affect the correct operation of its client guest domains. This is even more relevant for the control domain. where the ldm command must be protected from unauthorized (or even mistaken) use that would affect other domains. As a general rule, running applications in the service domain or the control domain should be avoided. For reference, an excellent guide to secure deployment of domains by Stefan Hinker is at Secure Deployment of Oracle VM Server for SPARC. To recap: Guest domains with virtual I/O still provide the greatest operational flexibility, including features like live migration. They should be considered the default domain type to use unless there is a specific requirement that mandates an I/O domain. I/O domains can be used for applications with the highest performance requirements. Single Root I/O Virtualization (SR-IOV) makes this more attractive by giving direct I/O access to more domains, and by permitting dynamic reconfiguration of SR-IOV devices. Today's larger systems provide multiple PCIe buses - for example, 16 buses on the T5-8 - making it possible to configure multiple I/O domains each owning their own bus. Service domains should in general not be used for applications, because compromised security in the domain, or an outage, can affect domains that depend on it. This concern can be mitigated by providing guests' their virtual I/O from more than one service domain, so interruption of service in one service domain does not cause an application outage. The control domain should in general not be used to run applications, for the same reason. Oracle SuperCluster uses the control domain for applications, but it is an exception. It's not a general purpose environment; it's an engineered system with specifically configured applications and optimization for optimal performance. These are recommended "best practices" based on conversations with a number of Oracle architects. Keep in mind that "one size does not fit all", so you should evaluate these practices in the context of your own requirements. Summary Higher capacity servers that run Oracle VM Server for SPARC are attractive for applications with the most demanding resource requirements. New deployment models permit native I/O performance for demanding applications by running them in I/O domains with direct access to their devices. This is leveraged in SPARC SuperCluster, and can be leveraged in T-series servers to provision high-performance applications running in domains. Carefully planned, this can be used to provide peak performance for critical applications. That said, the improved virtual device performance in Oracle VM Server means that the default choice should still be guest domains with virtual I/O.

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  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

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  • Mysql performance problem & Failed DIMM

    - by murdoch
    Hi I have a dedicated mysql database server which has been having some performance problems recently, under normal load the server will be running fine, then suddenly out of the blue the performance will fall off a cliff. The server isn't using the swap file and there is 12GB of RAM in the server, more than enough for its needs. After contacting my hosting comapnies support they have discovered that there is a failed 2GB DIMM in the server and have scheduled to replace it tomorow morning. My question is could a failed DIMM result in the performance problems I am seeing or is this just coincidence? My worry is that they will replace the ram tomorrow but the problems will persist and I will still be lost of explanations so I am just trying to think ahead. The reason I ask is that there is plenty of RAM in the server, more than required and simply missing 2GB should be a problem, so if this failed DIMM is causing these performance problems then the OS must be trying to access the failed DIMM and slowing down as a result. Does that sound like a credible explanation? This is what DELLs omreport program says about the RAM, notice one dimm is "Critical" Memory Information Health : Critical Memory Operating Mode Fail Over State : Inactive Memory Operating Mode Configuration : Optimizer Attributes of Memory Array(s) Attributes : Location Memory Array 1 : System Board or Motherboard Attributes : Use Memory Array 1 : System Memory Attributes : Installed Capacity Memory Array 1 : 12288 MB Attributes : Maximum Capacity Memory Array 1 : 196608 MB Attributes : Slots Available Memory Array 1 : 18 Attributes : Slots Used Memory Array 1 : 6 Attributes : ECC Type Memory Array 1 : Multibit ECC Total of Memory Array(s) Attributes : Total Installed Capacity Value : 12288 MB Attributes : Total Installed Capacity Available to the OS Value : 12004 MB Attributes : Total Maximum Capacity Value : 196608 MB Details of Memory Array 1 Index : 0 Status : Ok Connector Name : DIMM_A1 Type : DDR3-Registered Size : 2048 MB Index : 1 Status : Ok Connector Name : DIMM_A2 Type : DDR3-Registered Size : 2048 MB Index : 2 Status : Ok Connector Name : DIMM_A3 Type : DDR3-Registered Size : 2048 MB Index : 3 Status : Critical Connector Name : DIMM_B1 Type : DDR3-Registered Size : 2048 MB Index : 4 Status : Ok Connector Name : DIMM_B2 Type : DDR3-Registered Size : 2048 MB Index : 5 Status : Ok Connector Name : DIMM_B3 Type : DDR3-Registered Size : 2048 MB the command free -m shows this, the server seems to be using more than 10GB of ram which would suggest it is trying to use the DIMM total used free shared buffers cached Mem: 12004 10766 1238 0 384 4809 -/+ buffers/cache: 5572 6432 Swap: 2047 0 2047 iostat output while problem is occuring avg-cpu: %user %nice %system %iowait %steal %idle 52.82 0.00 11.01 0.00 0.00 36.17 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 47.00 0.00 576.00 0 576 sda1 0.00 0.00 0.00 0 0 sda2 1.00 0.00 32.00 0 32 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 46.00 0.00 544.00 0 544 avg-cpu: %user %nice %system %iowait %steal %idle 53.12 0.00 7.81 0.00 0.00 39.06 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 49.00 0.00 592.00 0 592 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 49.00 0.00 592.00 0 592 avg-cpu: %user %nice %system %iowait %steal %idle 56.09 0.00 7.43 0.37 0.00 36.10 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 232.00 0.00 64520.00 0 64520 sda1 0.00 0.00 0.00 0 0 sda2 159.00 0.00 63728.00 0 63728 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 73.00 0.00 792.00 0 792 avg-cpu: %user %nice %system %iowait %steal %idle 52.18 0.00 9.24 0.06 0.00 38.51 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 49.00 0.00 600.00 0 600 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 49.00 0.00 600.00 0 600 avg-cpu: %user %nice %system %iowait %steal %idle 54.82 0.00 8.64 0.00 0.00 36.55 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 100.00 0.00 2168.00 0 2168 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 100.00 0.00 2168.00 0 2168 avg-cpu: %user %nice %system %iowait %steal %idle 54.78 0.00 6.75 0.00 0.00 38.48 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 84.00 0.00 896.00 0 896 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 84.00 0.00 896.00 0 896 avg-cpu: %user %nice %system %iowait %steal %idle 54.34 0.00 7.31 0.00 0.00 38.35 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 81.00 0.00 840.00 0 840 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 81.00 0.00 840.00 0 840 avg-cpu: %user %nice %system %iowait %steal %idle 55.18 0.00 5.81 0.44 0.00 38.58 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 317.00 0.00 105632.00 0 105632 sda1 0.00 0.00 0.00 0 0 sda2 224.00 0.00 104672.00 0 104672 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 93.00 0.00 960.00 0 960 avg-cpu: %user %nice %system %iowait %steal %idle 55.38 0.00 7.63 0.00 0.00 36.98 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 74.00 0.00 800.00 0 800 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 74.00 0.00 800.00 0 800 avg-cpu: %user %nice %system %iowait %steal %idle 56.43 0.00 7.80 0.00 0.00 35.77 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 72.00 0.00 784.00 0 784 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 72.00 0.00 784.00 0 784 avg-cpu: %user %nice %system %iowait %steal %idle 54.87 0.00 6.49 0.00 0.00 38.64 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 80.20 0.00 855.45 0 864 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 80.20 0.00 855.45 0 864 avg-cpu: %user %nice %system %iowait %steal %idle 57.22 0.00 5.69 0.00 0.00 37.09 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 33.00 0.00 432.00 0 432 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 33.00 0.00 432.00 0 432 avg-cpu: %user %nice %system %iowait %steal %idle 56.03 0.00 7.93 0.00 0.00 36.04 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 41.00 0.00 560.00 0 560 sda1 0.00 0.00 0.00 0 0 sda2 2.00 0.00 88.00 0 88 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 39.00 0.00 472.00 0 472 avg-cpu: %user %nice %system %iowait %steal %idle 55.78 0.00 5.13 0.00 0.00 39.09 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 29.00 0.00 392.00 0 392 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 29.00 0.00 392.00 0 392 avg-cpu: %user %nice %system %iowait %steal %idle 53.68 0.00 8.30 0.06 0.00 37.95 Device: tps Blk_read/s Blk_wrtn/s Blk_read Blk_wrtn sda 78.00 0.00 4280.00 0 4280 sda1 0.00 0.00 0.00 0 0 sda2 0.00 0.00 0.00 0 0 sda3 0.00 0.00 0.00 0 0 sda4 0.00 0.00 0.00 0 0 sda5 78.00 0.00 4280.00 0 4280

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