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  • How and where to implement basic authentication in Kibana 3

    - by Jabb
    I have put my elasticsearch server behind a Apache reverse proxy that provides basic authentication. Authenticating to Apache directly from the browser works fine. However, when I use Kibana 3 to access the server, I receive authentication errors. Obviously because no auth headers are sent along with Kibana's Ajax calls. I added the below to elastic-angular-client.js in the Kibana vendor directory to implement authentication quick and dirty. But for some reason it does not work. $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); What is the best approach and place to implement basic authentication in Kibana? /*! elastic.js - v1.1.1 - 2013-05-24 * https://github.com/fullscale/elastic.js * Copyright (c) 2013 FullScale Labs, LLC; Licensed MIT */ /*jshint browser:true */ /*global angular:true */ 'use strict'; /* Angular.js service wrapping the elastic.js API. This module can simply be injected into your angular controllers. */ angular.module('elasticjs.service', []) .factory('ejsResource', ['$http', function ($http) { return function (config) { var // use existing ejs object if it exists ejs = window.ejs || {}, /* results are returned as a promise */ promiseThen = function (httpPromise, successcb, errorcb) { return httpPromise.then(function (response) { (successcb || angular.noop)(response.data); return response.data; }, function (response) { (errorcb || angular.noop)(response.data); return response.data; }); }; // check if we have a config object // if not, we have the server url so // we convert it to a config object if (config !== Object(config)) { config = {server: config}; } // set url to empty string if it was not specified if (config.server == null) { config.server = ''; } /* implement the elastic.js client interface for angular */ ejs.client = { server: function (s) { if (s == null) { return config.server; } config.server = s; return this; }, post: function (path, data, successcb, errorcb) { $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); console.log($http.defaults.headers); path = config.server + path; var reqConfig = {url: path, data: data, method: 'POST'}; return promiseThen($http(angular.extend(reqConfig, config)), successcb, errorcb); }, get: function (path, data, successcb, errorcb) { $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); path = config.server + path; // no body on get request, data will be request params var reqConfig = {url: path, params: data, method: 'GET'}; return promiseThen($http(angular.extend(reqConfig, config)), successcb, errorcb); }, put: function (path, data, successcb, errorcb) { $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); path = config.server + path; var reqConfig = {url: path, data: data, method: 'PUT'}; return promiseThen($http(angular.extend(reqConfig, config)), successcb, errorcb); }, del: function (path, data, successcb, errorcb) { $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); path = config.server + path; var reqConfig = {url: path, data: data, method: 'DELETE'}; return promiseThen($http(angular.extend(reqConfig, config)), successcb, errorcb); }, head: function (path, data, successcb, errorcb) { $http.defaults.headers.common.Authorization = 'Basic ' + Base64Encode('user:Password'); path = config.server + path; // no body on HEAD request, data will be request params var reqConfig = {url: path, params: data, method: 'HEAD'}; return $http(angular.extend(reqConfig, config)) .then(function (response) { (successcb || angular.noop)(response.headers()); return response.headers(); }, function (response) { (errorcb || angular.noop)(undefined); return undefined; }); } }; return ejs; }; }]); UPDATE 1: I implemented Matts suggestion. However, the server returns a weird response. It seems that the authorization header is not working. Could it have to do with the fact, that I am running Kibana on port 81 and elasticsearch on 8181? OPTIONS /solar_vendor/_search HTTP/1.1 Host: 46.252.46.173:8181 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:25.0) Gecko/20100101 Firefox/25.0 Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8 Accept-Language: de-de,de;q=0.8,en-us;q=0.5,en;q=0.3 Accept-Encoding: gzip, deflate Origin: http://46.252.46.173:81 Access-Control-Request-Method: POST Access-Control-Request-Headers: authorization,content-type Connection: keep-alive Pragma: no-cache Cache-Control: no-cache This is the response HTTP/1.1 401 Authorization Required Date: Fri, 08 Nov 2013 23:47:02 GMT WWW-Authenticate: Basic realm="Username/Password" Vary: Accept-Encoding Content-Encoding: gzip Content-Length: 346 Connection: close Content-Type: text/html; charset=iso-8859-1 UPDATE 2: Updated all instances with the modified headers in these Kibana files root@localhost:/var/www/kibana# grep -r 'ejsResource(' . ./src/app/controllers/dash.js: $scope.ejs = ejsResource({server: config.elasticsearch, headers: {'Access-Control-Request-Headers': 'Accept, Origin, Authorization', 'Authorization': 'Basic XXXXXXXXXXXXXXXXXXXXXXXXXXXXX=='}}); ./src/app/services/querySrv.js: var ejs = ejsResource({server: config.elasticsearch, headers: {'Access-Control-Request-Headers': 'Accept, Origin, Authorization', 'Authorization': 'Basic XXXXXXXXXXXXXXXXXXXXXXXXXXXXX=='}}); ./src/app/services/filterSrv.js: var ejs = ejsResource({server: config.elasticsearch, headers: {'Access-Control-Request-Headers': 'Accept, Origin, Authorization', 'Authorization': 'Basic XXXXXXXXXXXXXXXXXXXXXXXXXXXXX=='}}); ./src/app/services/dashboard.js: var ejs = ejsResource({server: config.elasticsearch, headers: {'Access-Control-Request-Headers': 'Accept, Origin, Authorization', 'Authorization': 'Basic XXXXXXXXXXXXXXXXXXXXXXXXXXXXX=='}}); And modified my vhost conf for the reverse proxy like this <VirtualHost *:8181> ProxyRequests Off ProxyPass / http://127.0.0.1:9200/ ProxyPassReverse / https://127.0.0.1:9200/ <Location /> Order deny,allow Allow from all AuthType Basic AuthName “Username/Password” AuthUserFile /var/www/cake2.2.4/.htpasswd Require valid-user Header always set Access-Control-Allow-Methods "GET, POST, DELETE, OPTIONS, PUT" Header always set Access-Control-Allow-Headers "Content-Type, X-Requested-With, X-HTTP-Method-Override, Origin, Accept, Authorization" Header always set Access-Control-Allow-Credentials "true" Header always set Cache-Control "max-age=0" Header always set Access-Control-Allow-Origin * </Location> ErrorLog ${APACHE_LOG_DIR}/error.log </VirtualHost> Apache sends back the new response headers but the request header still seems to be wrong somewhere. Authentication just doesn't work. Request Headers OPTIONS /solar_vendor/_search HTTP/1.1 Host: 46.252.26.173:8181 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:25.0) Gecko/20100101 Firefox/25.0 Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8 Accept-Language: de-de,de;q=0.8,en-us;q=0.5,en;q=0.3 Accept-Encoding: gzip, deflate Origin: http://46.252.26.173:81 Access-Control-Request-Method: POST Access-Control-Request-Headers: authorization,content-type Connection: keep-alive Pragma: no-cache Cache-Control: no-cache Response Headers HTTP/1.1 401 Authorization Required Date: Sat, 09 Nov 2013 08:48:48 GMT Access-Control-Allow-Methods: GET, POST, DELETE, OPTIONS, PUT Access-Control-Allow-Headers: Content-Type, X-Requested-With, X-HTTP-Method-Override, Origin, Accept, Authorization Access-Control-Allow-Credentials: true Cache-Control: max-age=0 Access-Control-Allow-Origin: * WWW-Authenticate: Basic realm="Username/Password" Vary: Accept-Encoding Content-Encoding: gzip Content-Length: 346 Connection: close Content-Type: text/html; charset=iso-8859-1 SOLUTION: After doing some more research, I found out that this is definitely a configuration issue with regard to CORS. There are quite a few posts available regarding that topic but it appears that in order to solve my problem, it would be necessary to to make some very granular configurations on apache and also make sure that the right stuff is sent from the browser. So I reconsidered the strategy and found a much simpler solution. Just modify the vhost reverse proxy config to move the elastisearch server AND kibana on the same http port. This also adds even better security to Kibana. This is what I did: <VirtualHost *:8181> ProxyRequests Off ProxyPass /bigdatadesk/ http://127.0.0.1:81/bigdatadesk/src/ ProxyPassReverse /bigdatadesk/ http://127.0.0.1:81/bigdatadesk/src/ ProxyPass / http://127.0.0.1:9200/ ProxyPassReverse / https://127.0.0.1:9200/ <Location /> Order deny,allow Allow from all AuthType Basic AuthName “Username/Password” AuthUserFile /var/www/.htpasswd Require valid-user </Location> ErrorLog ${APACHE_LOG_DIR}/error.log </VirtualHost>

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  • How can I use Perl regular expressions to parse XML data?

    - by Luke
    I have a pretty long piece of XML that I want to parse. I want to remove everything except for the subclass-code and city. So that I am left with something like the example below. EXAMPLE TEST SUBCLASS|MIAMI CODE <?xml version="1.0" standalone="no"?> <web-export> <run-date>06/01/2010 <pub-code>TEST <ad-type>TEST <cat-code>Real Estate</cat-code> <class-code>TEST</class-code> <subclass-code>TEST SUBCLASS</subclass-code> <placement-description></placement-description> <position-description>Town House</position-description> <subclass3-code></subclass3-code> <subclass4-code></subclass4-code> <ad-number>0000284708-01</ad-number> <start-date>05/28/2010</start-date> <end-date>06/09/2010</end-date> <line-count>6</line-count> <run-count>13</run-count> <customer-type>Private Party</customer-type> <account-number>100099237</account-number> <account-name>DOE, JOHN</account-name> <addr-1>207 CLARENCE STREET</addr-1> <addr-2> </addr-2> <city>MIAMI</city> <state>FL</state> <postal-code>02910</postal-code> <country>USA</country> <phone-number>4014612880</phone-number> <fax-number></fax-number> <url-addr> </url-addr> <email-addr>[email protected]</email-addr> <pay-flag>N</pay-flag> <ad-description>DEANESTATES2BEDS2BATHSAPPLIANCED</ad-description> <order-source>Import</order-source> <order-status>Live</order-status> <payor-acct>100099237</payor-acct> <agency-flag>N</agency-flag> <rate-note></rate-note> <ad-content> MIAMI&#47;Dean Estates&#58; 2 beds&#44; 2 baths&#46; Applianced&#46; Central air&#46; Carpets&#46; Laundry&#46; 2 decks&#46; Pool&#46; Parking&#46; Close to everything&#46;No smoking&#46; No utilities&#46; &#36;1275 mo&#46; 401&#45;578&#45;1501&#46; </ad-content> </ad-type> </pub-code> </run-date> </web-export> PERL So what I want to do is open an existing file read the contents then use regular expressions to eliminate the unnecessary XML tags. open(READFILE, "FILENAME"); while(<READFILE>) { $_ =~ s/<\?xml version="(.*)" standalone="(.*)"\?>\n.*//g; $_ =~ s/<subclass-code>//g; $_ =~ s/<\/subclass-code>\n.*/|/g; $_ =~ s/(.*)PJ RER Houses /PJ RER Houses/g; $_ =~ s/\G //g; $_ =~ s/<city>//g; $_ =~ s/<\/city>\n.*//g; $_ =~ s/<(\/?)web-export>(.*)\n.*//g; $_ =~ s/<(\/?)run-date>(.*)\n.*//g; $_ =~ s/<(\/?)pub-code>(.*)\n.*//g; $_ =~ s/<(\/?)ad-type>(.*)\n.*//g; $_ =~ s/<(\/?)cat-code>(.*)<(\/?)cat-code>\n.*//g; $_ =~ s/<(\/?)class-code>(.*)<(\/?)class-code>\n.*//g; $_ =~ s/<(\/?)placement-description>(.*)<(\/?)placement-description>\n.*//g; $_ =~ s/<(\/?)position-description>(.*)<(\/?)position-description>\n.*//g; $_ =~ s/<(\/?)subclass3-code>(.*)<(\/?)subclass3-code>\n.*//g; $_ =~ s/<(\/?)subclass4-code>(.*)<(\/?)subclass4-code>\n.*//g; $_ =~ s/<(\/?)ad-number>(.*)<(\/?)ad-number>\n.*//g; $_ =~ s/<(\/?)start-date>(.*)<(\/?)start-date>\n.*//g; $_ =~ s/<(\/?)end-date>(.*)<(\/?)end-date>\n.*//g; $_ =~ s/<(\/?)line-count>(.*)<(\/?)line-count>\n.*//g; $_ =~ s/<(\/?)run-count>(.*)<(\/?)run-count>\n.*//g; $_ =~ s/<(\/?)customer-type>(.*)<(\/?)customer-type>\n.*//g; $_ =~ s/<(\/?)account-number>(.*)<(\/?)account-number>\n.*//g; $_ =~ s/<(\/?)account-name>(.*)<(\/?)account-name>\n.*//g; $_ =~ s/<(\/?)addr-1>(.*)<(\/?)addr-1>\n.*//g; $_ =~ s/<(\/?)addr-2>(.*)<(\/?)addr-2>\n.*//g; $_ =~ s/<(\/?)state>(.*)<(\/?)state>\n.*//g; $_ =~ s/<(\/?)postal-code>(.*)<(\/?)postal-code>\n.*//g; $_ =~ s/<(\/?)country>(.*)<(\/?)country>\n.*//g; $_ =~ s/<(\/?)phone-number>(.*)<(\/?)phone-number>\n.*//g; $_ =~ s/<(\/?)fax-number>(.*)<(\/?)fax-number>\n.*//g; $_ =~ s/<(\/?)url-addr>(.*)<(\/?)url-addr>\n.*//g; $_ =~ s/<(\/?)email-addr>(.*)<(\/?)email-addr>\n.*//g; $_ =~ s/<(\/?)pay-flag>(.*)<(\/?)pay-flag>\n.*//g; $_ =~ s/<(\/?)ad-description>(.*)<(\/?)ad-description>\n.*//g; $_ =~ s/<(\/?)order-source>(.*)<(\/?)order-source>\n.*//g; $_ =~ s/<(\/?)order-status>(.*)<(\/?)order-status>\n.*//g; $_ =~ s/<(\/?)payor-acct>(.*)<(\/?)payor-acct>\n.*//g; $_ =~ s/<(\/?)agency-flag>(.*)<(\/?)agency-flag>\n.*//g; $_ =~ s/<(\/?)rate-note>(.*)<(\/?)rate-note>\n.*//g; $_ =~ s/<ad-content>(.*)\n.*//g; $_ =~ s/\t(.*)\n.*//g; $_ =~ s/<\/ad-content>(.*)\n.*//g; } close( READFILE1 ); Is there an easier way of doing this? I don't want to use any modules. I know that it might make this easier but the file I am reading has a lot of data in it.

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  • Need help making an ODBC MySQL Connection

    - by Andy Moore
    Short Version: How do I connect from PowerShell to an ODBC 5.1 MySQL Driver? I can't seem to find any connection strings that accurately have a "Provider" field for this particular instance. (See bottom of this question for examples/errors) ===== Long Version: I'm not a server guy, and I've been handed the task of setting up PowerGadgets on our network. I have a MySQL server running on a Linux box, that is configured for remote access and has a user defined for remote access as well. On my windows desktop PC, I have PowerGadgets installed. I installed the MySQL ODBC 5.1 connector, and went to Control Panel Data Sources and set up a User DSN connection to the database. The connection, user, and pass seem to be correct because it lists the tables of the database in my windows control panel. Where I'm running into trouble is in 3 places in PowerGadgets: When selecting a data source, I can select "SQL Server". Inputting the servers IP address does not work and I can't get this option to work at all. When selecting a data source, I can select "OleDB". This screen has a wizard on it, that appears to populate all the correct information (including database table names!) for me. "Test Connection" runs great. But if I try to complete the wizard, I get the error "The .NET Framework data provider for OLEDB does not support the MS Ole DB provider for ODBC Drivers." When selecting a data source, I can select "ODBC". This screen does not have a wizard and I cannot figure out a "connection string" that works. Typically it will respond with the error "The field 'Provider' is missing". Googling ODBC connection strings doesn't reveal any examples with a "provider" field and have no idea what to put in here. The connection string (for #2) above contains "SQLOLEDB" as a provider, and upon inputting that value into this connection string I get the same connection error that #2 gets. I believe I can solve my problems by figuring out a connection string for #3 but don't know where to get started. (PowerGadgets also allows for PowerShell support but I believe I will run into the same problem there) == Here's my current PowerShell connection that doesn't work: invoke-sql -connection "Driver={MySQL ODBC 5.1 Driver};Initial Catalog=hq_live;Data Source=HQDB" -sql "Select * FROM accounts" Spits back the error: "Invoke-Sql : An OLE DB Provider was not specified in the ConnectionString. An example would be, 'Provider=SQLOLEDB;'. == Another string that doesn't work: invoke-sql -connection "Provider=MSDASQL.1;Persist Security Info=False;Data Source=HQDB;Initial Catalog=hq_live" -sql "select * from accounts" And the error: The .Net Framework Data Provider for OLEDB (System.Data.OleDb) does not support the Microsoft OLE DB Provider for ODBC Drivers (MSDASQL). Use the .Net Framework Data Provider for ODBC (System.Data.Odbc).

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  • ZFS/Btrfs/LVM2-like storage with advanced features on Linux?

    - by Easter Sunshine
    I have 3 identical internal 7200 RPM SATA hard disk drives on a Linux machine. I'm looking for a storage set-up that will give me all of this: Different data sets (filesystems or subtrees) can have different RAID levels so I can choose performance, space overhead, and risk trade-offs differently for different data sets while having a few number of physical disks (very important data can be 3xRAID1, important data can be 3xRAID5, unimportant reproducible data can be 3xRAID0). If each data set has an explicit size or size limit, then the ability to grow and shrink the size limit (offline if need be) Avoid out-of-kernel modules R/W or read-only COW snapshots. If it's a block-level snapshots, the filesystem should be synced and quiesced during a snapshot. Ability to add physical disks and then grow/redistribute RAID1, RAID5, and RAID0 volumes to take advantage of the new spindle and make sure no spindle is hotter than the rest (e.g., in NetApp, growing a RAID-DP raid group by a few disks will not balance the I/O across them without an explicit redistribution) Not required but nice-to-haves: Transparent compression, per-file or subtree. Even better if, like NetApps, analyzes the data first for compressibility and only compresses compressible data Deduplication that doesn't have huge performance penalties or require obscene amounts of memory (NetApp does scheduled deduplication on weekends, which is good) Resistance to silent data corruption like ZFS (this is not required because I have never seen ZFS report any data corruption on these specific disks) Storage tiering, either automatic (based on caching rules) or user-defined rules (yes, I have all-identical disks now but this will let me add a read/write SSD cache in the future). If it's user-defined rules, these rules should have the ability to promote to SSD on a file level and not a block level. Space-efficient packing of small files I tried ZFS on Linux but the limitations were: Upgrading is additional work because the package is in an external repository and is tied to specific kernel versions; it is not integrated with the package manager Write IOPS does not scale with number of devices in a raidz vdev. Cannot add disks to raidz vdevs Cannot have select data on RAID0 to reduce overhead and improve performance without additional physical disks or giving ZFS a single partition of the disks ext4 on LVM2 looks like an option except I can't tell whether I can shrink, extend, and redistribute onto new spindles RAID-type logical volumes (of course, I can experiment with LVM on a bunch of files). As far as I can tell, it doesn't have any of the nice-to-haves so I was wondering if there is something better out there. I did look at LVM dangers and caveats but then again, no system is perfect.

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  • Mongodb: why is my mongo server using two PID's?

    - by Lucas
    I started my mongo with the following command: [lucas@ecoinstance]~/node/nodetest2$ sudo mongod --dbpath /home/lucas/node/nodetest2/data 2014-06-07T08:46:30.507+0000 [initandlisten] MongoDB starting : pid=6409 port=27017 dbpat h=/home/lucas/node/nodetest2/data 64-bit host=ecoinstance 2014-06-07T08:46:30.508+0000 [initandlisten] db version v2.6.1 2014-06-07T08:46:30.508+0000 [initandlisten] git version: 4b95b086d2374bdcfcdf2249272fb55 2c9c726e8 2014-06-07T08:46:30.508+0000 [initandlisten] build info: Linux build14.nj1.10gen.cc 2.6.3 2-431.3.1.el6.x86_64 #1 SMP Fri Jan 3 21:39:27 UTC 2014 x86_64 BOOST_LIB_VERSION=1_49 2014-06-07T08:46:30.509+0000 [initandlisten] allocator: tcmalloc 2014-06-07T08:46:30.509+0000 [initandlisten] options: { storage: { dbPath: "/home/lucas/n ode/nodetest2/data" } } 2014-06-07T08:46:30.520+0000 [initandlisten] journal dir=/home/lucas/node/nodetest2/data/ journal 2014-06-07T08:46:30.520+0000 [initandlisten] recover : no journal files present, no recov ery needed 2014-06-07T08:46:30.527+0000 [initandlisten] waiting for connections on port 27017 It appears to be working, as I can execute mongo and access the server. However, here are the process running mongo: [lucas@ecoinstance]~/node/testSite$ ps aux | grep mongo root 6540 0.0 0.2 33424 1664 pts/3 S+ 08:52 0:00 sudo mongod --dbpath /ho me/lucas/node/nodetest2/data root 6541 0.6 8.6 522140 52512 pts/3 Sl+ 08:52 0:00 mongod --dbpath /home/lu cas/node/nodetest2/data lucas 6554 0.0 0.1 7836 876 pts/4 S+ 08:52 0:00 grep mongo As you can see, there are two PID's for mongo. Before I ran sudo mongod --dbpath /home/lucas/node/nodetest2/data, there were none (besides the grep of course). How did my command spawn two PID's, and should I be concerned? Any suggestions or tips would be great. Additional Info In addition, I may have other issues that might suggest a cause. I tried running mongo with --fork --logpath /home/lucas..., but it did not work. More information below: [lucas@ecoinstance]~/node/nodetest2$ sudo mongod --dbpath /home/lucas/node/nodetest2/data --fork --logpath /home/lucas/node/nodetest2/data/ about to fork child process, waiting until server is ready for connections. forked process: 6578 ERROR: child process failed, exited with error number 1 [lucas@ecoinstance]~/node/nodetest2$ ls -l data/ total 163852 drwxr-xr-x 2 mongodb nogroup 4096 Jun 7 08:54 journal -rw------- 1 mongodb nogroup 67108864 Jun 7 08:52 local.0 -rw------- 1 mongodb nogroup 16777216 Jun 7 08:52 local.ns -rwxr-xr-x 1 mongodb nogroup 0 Jun 7 08:54 mongod.lock -rw------- 1 mongodb nogroup 67108864 Jun 7 02:08 nodetest1.0 -rw------- 1 mongodb nogroup 16777216 Jun 7 02:08 nodetest1.ns Also, my db path folder is not the original location. It was originally created under the default /var/lib/mongodb/ and moved to my local data folder. This was done after shutting down the server via /etc/init.d/mongod stop. I have a Debian Wheezy server, if it matters.

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  • When using RAID10 + BBWC why is it better to separate PostgreSQL data files from OS and transaction logs than to keep them all on the same array?

    - by Vlad
    I've seen the advice everywhere (including here and here): keep your OS partition, DB data files and DB transaction logs on separate discs/arrays. The general recommendation is to use RAID1 for OS, RAID10 for data (or RAID5 if load is very read-biased) and RAID1 for transaction logs. However, considering that you will need at least 6 or 8 drives to build this setup, wouldn't a RAID10 over 6-8 drives with BBWC perform better? What if the drives are SSDs? I'm talking here about internal server drives, not SAN.

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  • Returning a list from a function in Python

    - by Jasper
    Hi, I'm creating a game for my sister, and I want a function to return a list variable, so I can pass it to another variable. The relevant code is as follows: def startNewGame(): while 1: #Introduction: print print """Hello, You will now be guided through the setup process. There are 7 steps to this. You can cancel setup at any time by typing 'cancelSetup' Thankyou""" #Step 1 (Name): print print """Step 1 of 7: Type in a name for your PotatoHead: """ inputPHName = raw_input('|Enter Name:|') if inputPHName == 'cancelSetup': sys.exit() #Step 2 (Gender): print print """Step 2 of 7: Choose the gender of your PotatoHead: input either 'm' or 'f' """ inputPHGender = raw_input('|Enter Gender:|') if inputPHGender == 'cancelSetup': sys.exit() #Step 3 (Colour): print print """Step 3 of 7: Choose the colour your PotatoHead will be: Only Red, Blue, Green and Yellow are currently supported """ inputPHColour = raw_input('|Enter Colour:|') if inputPHColour == 'cancelSetup': sys.exit() #Step 4 (Favourite Thing): print print """Step 4 of 7: Type your PotatoHead's favourite thing: """ inputPHFavThing = raw_input('|Enter Favourite Thing:|') if inputPHFavThing == 'cancelSetup': sys.exit() # Step 5 (First Toy): print print """Step 5 of 7: Choose a first toy for your PotatoHead: """ inputPHFirstToy = raw_input('|Enter First Toy:|') if inputPHFirstToy == 'cancelSetup': sys.exit() #Step 6 (Check stats): while 1: print print """Step 6 of 7: Check the following details to make sure that they are correct: """ print print """Name:\t\t\t""" + inputPHName + """ Gender:\t\t\t""" + inputPHGender + """ Colour:\t\t\t""" + inputPHColour + """ Favourite Thing:\t""" + inputPHFavThing + """ First Toy:\t\t""" + inputPHFirstToy + """ """ print print "Enter 'y' or 'n'" inputMCheckStats = raw_input('|Is this information correct?|') if inputMCheckStats == 'cancelSetup': sys.exit() elif inputMCheckStats == 'y': break elif inputMCheckStats == 'n': print "Re-enter info: ..." print break else: "The value you entered was incorrect, please re-enter your choice" if inputMCheckStats == 'y': break #Step 7 (Define variables for the creation of the PotatoHead): MFCreatePH = [] print print """Step 7 of 7: Your PotatoHead will now be created... Creating variables... """ MFCreatePH = [inputPHName, inputPHGender, inputPHColour, inputPHFavThing, inputPHFirstToy] time.sleep(1) print "inputPHName" print time.sleep(1) print "inputPHFirstToy" print return MFCreatePH print "Your PotatoHead varibles have been successfully created!" Then it is passed to another function that was imported from another module from potatohead import * ... welcomeMessage() MCreatePH = startGame() myPotatoHead = PotatoHead(MCreatePH) the code for the PotatoHead object is in the potatohead.py module which was imported above, and is as follows: class PotatoHead: #Initialise the PotatoHead object: def __init__(self, data): self.data = data #Takes the data from the start new game function - see main.py #Defines the PotatoHead starting attributes: self.name = data[0] self.gender = data[1] self.colour = data[2] self.favouriteThing = data[3] self.firstToy = data[4] self.age = '0.0' self.education = [self.eduScience, self.eduEnglish, self.eduMaths] = '0.0', '0.0', '0.0' self.fitness = '0.0' self.happiness = '10.0' self.health = '10.0' self.hunger = '0.0' self.tiredness = 'Not in this version' self.toys = [] self.toys.append(self.firstToy) self.time = '0' #Sets data lists for saving, loading and general use: self.phData = (self.name, self.gender, self.colour, self.favouriteThing, self.firstToy) self.phAdvData = (self.name, self.gender, self.colour, self.favouriteThing, self.firstToy, self.age, self.education, self.fitness, self.happiness, self.health, self.hunger, self.tiredness, self.toys) However, when I run the program this error appears: Traceback (most recent call last): File "/Users/Jasper/Documents/Programming/Potato Head Game/Current/main.py", line 158, in <module> myPotatoHead = PotatoHead(MCreatePH) File "/Users/Jasper/Documents/Programming/Potato Head Game/Current/potatohead.py", line 15, in __init__ self.name = data[0] TypeError: 'NoneType' object is unsubscriptable What am i doing wrong? -----EDIT----- The program finishes as so: Step 7 of 7: Your PotatoHead will now be created... Creating variables... inputPHName inputPHFirstToy Then it goes to the Tracback -----EDIT2----- This is the EXACT code I'm running in its entirety: #+--------------------------------------+# #| main.py |# #| A main module for the Potato Head |# #| Game to pull the other modules |# #| together and control through user |# #| input |# #| Author: |# #| Date Created / Modified: |# #| 3/2/10 | 20/2/10 |# #+--------------------------------------+# Tested: No #Import the required modules: import time import random import sys from potatohead import * from toy import * #Start the Game: def welcomeMessage(): print "----- START NEW GAME -----------------------" print "==Print Welcome Message==" print "loading... \t loading... \t loading..." time.sleep(1) print "loading..." time.sleep(1) print "LOADED..." print; print; print; print """Hello, Welcome to the Potato Head Game. In this game you can create a Potato Head, and look after it, like a Virtual Pet. This game is constantly being updated and expanded. Please look out for updates. """ #Choose whether to start a new game or load a previously saved game: def startGame(): while 1: print "--------------------" print """ Choose an option: New_Game or Load_Game """ startGameInput = raw_input('>>> >') if startGameInput == 'New_Game': startNewGame() break elif startGameInput == 'Load_Game': print "This function is not yet supported" print "Try Again" print else: print "You must have mistyped the command: Type either 'New_Game' or 'Load_Game'" print #Set the new game up: def startNewGame(): while 1: #Introduction: print print """Hello, You will now be guided through the setup process. There are 7 steps to this. You can cancel setup at any time by typing 'cancelSetup' Thankyou""" #Step 1 (Name): print print """Step 1 of 7: Type in a name for your PotatoHead: """ inputPHName = raw_input('|Enter Name:|') if inputPHName == 'cancelSetup': sys.exit() #Step 2 (Gender): print print """Step 2 of 7: Choose the gender of your PotatoHead: input either 'm' or 'f' """ inputPHGender = raw_input('|Enter Gender:|') if inputPHGender == 'cancelSetup': sys.exit() #Step 3 (Colour): print print """Step 3 of 7: Choose the colour your PotatoHead will be: Only Red, Blue, Green and Yellow are currently supported """ inputPHColour = raw_input('|Enter Colour:|') if inputPHColour == 'cancelSetup': sys.exit() #Step 4 (Favourite Thing): print print """Step 4 of 7: Type your PotatoHead's favourite thing: """ inputPHFavThing = raw_input('|Enter Favourite Thing:|') if inputPHFavThing == 'cancelSetup': sys.exit() # Step 5 (First Toy): print print """Step 5 of 7: Choose a first toy for your PotatoHead: """ inputPHFirstToy = raw_input('|Enter First Toy:|') if inputPHFirstToy == 'cancelSetup': sys.exit() #Step 6 (Check stats): while 1: print print """Step 6 of 7: Check the following details to make sure that they are correct: """ print print """Name:\t\t\t""" + inputPHName + """ Gender:\t\t\t""" + inputPHGender + """ Colour:\t\t\t""" + inputPHColour + """ Favourite Thing:\t""" + inputPHFavThing + """ First Toy:\t\t""" + inputPHFirstToy + """ """ print print "Enter 'y' or 'n'" inputMCheckStats = raw_input('|Is this information correct?|') if inputMCheckStats == 'cancelSetup': sys.exit() elif inputMCheckStats == 'y': break elif inputMCheckStats == 'n': print "Re-enter info: ..." print break else: "The value you entered was incorrect, please re-enter your choice" if inputMCheckStats == 'y': break #Step 7 (Define variables for the creation of the PotatoHead): MFCreatePH = [] print print """Step 7 of 7: Your PotatoHead will now be created... Creating variables... """ MFCreatePH = [inputPHName, inputPHGender, inputPHColour, inputPHFavThing, inputPHFirstToy] time.sleep(1) print "inputPHName" print time.sleep(1) print "inputPHFirstToy" print return MFCreatePH print "Your PotatoHead varibles have been successfully created!" #Run Program: welcomeMessage() MCreatePH = startGame() myPotatoHead = PotatoHead(MCreatePH) The potatohead.py module is as follows: #+--------------------------------------+# #| potatohead.py |# #| A module for the Potato Head Game |# #| Author: |# #| Date Created / Modified: |# #| 24/1/10 | 24/1/10 |# #+--------------------------------------+# Tested: Yes (24/1/10) #Create the PotatoHead class: class PotatoHead: #Initialise the PotatoHead object: def __init__(self, data): self.data = data #Takes the data from the start new game function - see main.py #Defines the PotatoHead starting attributes: self.name = data[0] self.gender = data[1] self.colour = data[2] self.favouriteThing = data[3] self.firstToy = data[4] self.age = '0.0' self.education = [self.eduScience, self.eduEnglish, self.eduMaths] = '0.0', '0.0', '0.0' self.fitness = '0.0' self.happiness = '10.0' self.health = '10.0' self.hunger = '0.0' self.tiredness = 'Not in this version' self.toys = [] self.toys.append(self.firstToy) self.time = '0' #Sets data lists for saving, loading and general use: self.phData = (self.name, self.gender, self.colour, self.favouriteThing, self.firstToy) self.phAdvData = (self.name, self.gender, self.colour, self.favouriteThing, self.firstToy, self.age, self.education, self.fitness, self.happiness, self.health, self.hunger, self.tiredness, self.toys) #Define the phStats variable, enabling easy display of PotatoHead attributes: def phDefStats(self): self.phStats = """Your Potato Head's Stats are as follows: ---------------------------------------- Name: \t\t""" + self.name + """ Gender: \t\t""" + self.gender + """ Colour: \t\t""" + self.colour + """ Favourite Thing: \t""" + self.favouriteThing + """ First Toy: \t""" + self.firstToy + """ Age: \t\t""" + self.age + """ Education: \t""" + str(float(self.eduScience) + float(self.eduEnglish) + float(self.eduMaths)) + """ -> Science: \t""" + self.eduScience + """ -> English: \t""" + self.eduEnglish + """ -> Maths: \t""" + self.eduMaths + """ Fitness: \t""" + self.fitness + """ Happiness: \t""" + self.happiness + """ Health: \t""" + self.health + """ Hunger: \t""" + self.hunger + """ Tiredness: \t""" + self.tiredness + """ Toys: \t\t""" + str(self.toys) + """ Time: \t\t""" + self.time + """ """ #Change the PotatoHead's favourite thing: def phChangeFavouriteThing(self, newFavouriteThing): self.favouriteThing = newFavouriteThing phChangeFavouriteThingMsg = "Your Potato Head's favourite thing is " + self.favouriteThing + "." #"Feed" the Potato Head i.e. Reduce the 'self.hunger' attribute's value: def phFeed(self): if float(self.hunger) >=3.0: self.hunger = str(float(self.hunger) - 3.0) elif float(self.hunger) < 3.0: self.hunger = '0.0' self.time = str(int(self.time) + 1) #Pass time #"Exercise" the Potato Head if between the ages of 5 and 25: def phExercise(self): if float(self.age) < 5.1 or float(self.age) > 25.1: print "This Potato Head is either too young or too old for this activity!" else: if float(self.fitness) <= 8.0: self.fitness = str(float(self.fitness) + 2.0) elif float(self.fitness) > 8.0: self.fitness = '10.0' self.time = str(int(self.time) + 1) #Pass time #"Teach" the Potato Head: def phTeach(self, subject): if subject == 'Science': if float(self.eduScience) <= 9.0: self.eduScience = str(float(self.eduScience) + 1.0) elif float(self.eduScience) > 9.0 and float(self.eduScience) < 10.0: self.eduScience = '10.0' elif float(self.eduScience) == 10.0: print "Your Potato Head has gained the highest level of qualifications in this subject! It cannot learn any more!" elif subject == 'English': if float(self.eduEnglish) <= 9.0: self.eduEnglish = str(float(self.eduEnglish) + 1.0) elif float(self.eduEnglish) > 9.0 and float(self.eduEnglish) < 10.0: self.eduEnglish = '10.0' elif float(self.eduEnglish) == 10.0: print "Your Potato Head has gained the highest level of qualifications in this subject! It cannot learn any more!" elif subject == 'Maths': if float(self.eduMaths) <= 9.0: self.eduMaths = str(float(self.eduMaths) + 1.0) elif float(self.eduMaths) > 9.0 and float(self.eduMaths) < 10.0: self.eduMaths = '10.0' elif float(self.eduMaths) == 10.0: print "Your Potato Head has gained the highest level of qualifications in this subject! It cannot learn any more!" else: print "That subject is not an option..." print "Please choose either Science, English or Maths" self.time = str(int(self.time) + 1) #Pass time #Increase Health: def phGoToDoctor(self): self.health = '10.0' self.time = str(int(self.time) + 1) #Pass time #Sleep: Age, change stats: #(Time Passes) def phSleep(self): self.time = '0' #Resets time for next 'day' (can do more things next day) #Increase hunger: if float(self.hunger) <= 5.0: self.hunger = str(float(self.hunger) + 5.0) elif float(self.hunger) > 5.0: self.hunger = '10.0' #Lower Fitness: if float(self.fitness) >= 0.5: self.fitness = str(float(self.fitness) - 0.5) elif float(self.fitness) < 0.5: self.fitness = '0.0' #Lower Health: if float(self.health) >= 0.5: self.health = str(float(self.health) - 0.5) elif float(self.health) < 0.5: self.health = '0.0' #Lower Happiness: if float(self.happiness) >= 2.0: self.happiness = str(float(self.happiness) - 2.0) elif float(self.happiness) < 2.0: self.happiness = '0.0' #Increase the Potato Head's age: self.age = str(float(self.age) + 0.1) The game is still under development - There may be parts of modules that aren't complete, but I don't think they're causing the problem

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  • How do I insert data using a DetailsView into an access database without everything breaking?

    - by Steve
    Hey I'm getting the error: Data type mismatch in criteria expression. when I try to submit a DetailsView insert. Code for Default.aspx: (from inside an asp:Content tag) <asp:DetailsView ID="DetailsView1" runat="server" Height="50px" Width="125px" AutoGenerateRows="False" DataKeyNames="user_id" DataSourceID="AccessDataSource1" CellPadding="4" ForeColor="#333333" GridLines="None"> <FooterStyle BackColor="#5D7B9D" Font-Bold="True" ForeColor="White" /> <CommandRowStyle BackColor="#E2DED6" Font-Bold="True" /> <RowStyle BackColor="#F7F6F3" ForeColor="#333333" /> <FieldHeaderStyle BackColor="#E9ECF1" Font-Bold="True" /> <PagerStyle BackColor="#284775" ForeColor="White" HorizontalAlign="Center" /> <Fields> <asp:BoundField DataField="email" HeaderText="email" SortExpression="email" /> <asp:BoundField DataField="password" HeaderText="password" SortExpression="password" /> <asp:BoundField DataField="users_name" HeaderText="users_name" SortExpression="users_name" /> <asp:BoundField DataField="image_path" HeaderText="image_path" SortExpression="image_path" /> <asp:BoundField DataField="mobile" HeaderText="mobile" SortExpression="mobile" /> <asp:BoundField DataField="twitter" HeaderText="twitter" SortExpression="twitter" /> <asp:TemplateField HeaderText="privacy_level_id" SortExpression="privacy_level_id"> <InsertItemTemplate> <asp:DropDownList ID="DropDownList2" runat="server" DataSourceID="AccessDataSource2" DataTextField="privacy_level_name" DataValueField="privacy_level_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource2" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [PrivacyLevels]"></asp:AccessDataSource> </InsertItemTemplate> <ItemTemplate> <asp:Label ID="Label1" runat="server" Text='<%# Bind("date_of_birth") %>'></asp:Label> </ItemTemplate> </asp:TemplateField> <asp:TemplateField HeaderText="course_id" SortExpression="course_id"> <EditItemTemplate> <asp:DropDownList ID="DropDownList3" runat="server" DataSourceID="AccessDataSource3" DataTextField="course_name" DataValueField="course_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource3" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Courses]"> </asp:AccessDataSource> </EditItemTemplate> <InsertItemTemplate> <asp:DropDownList ID="DropDownList22" runat="server" DataSourceID="AccessDataSource22" DataTextField="privacy_level_name" DataValueField="privacy_level_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource22" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [PrivacyLevels]"></asp:AccessDataSource> </InsertItemTemplate> <ItemTemplate> <asp:DropDownList ID="DropDownList3" runat="server" DataSourceID="AccessDataSource3" DataTextField="course_name" DataValueField="course_id" Enabled="False"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource3" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Courses]"></asp:AccessDataSource> </ItemTemplate> </asp:TemplateField> <asp:TemplateField HeaderText="nationality_id" SortExpression="nationality_id"> <EditItemTemplate> <asp:DropDownList ID="DropDownList1" runat="server" DataSourceID="AccessDataSource20" DataTextField="nationality_name" DataValueField="nationality_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource20" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Nationalities]"> </asp:AccessDataSource> </EditItemTemplate> <InsertItemTemplate> <asp:DropDownList ID="DropDownList1" runat="server" DataSourceID="AccessDataSource20" DataTextField="nationality_name" DataValueField="nationality_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource20" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Nationalities]"> </asp:AccessDataSource> </InsertItemTemplate> <ItemTemplate> <asp:DropDownList ID="DropDownList1" runat="server" DataSourceID="AccessDataSource20" DataTextField="nationality_name" DataValueField="nationality_id" Enabled="False"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource20" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Nationalities]"> </asp:AccessDataSource> </ItemTemplate> </asp:TemplateField> <asp:TemplateField HeaderText="residence_id" SortExpression="residence_id"> <EditItemTemplate> <asp:DropDownList ID="DropDownList4" runat="server" DataSourceID="AccessDataSource4" DataTextField="residence_name" DataValueField="residence_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource4" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Residences]"></asp:AccessDataSource> </EditItemTemplate> <InsertItemTemplate> <asp:DropDownList ID="DropDownList4" runat="server" DataSourceID="AccessDataSource4" DataTextField="residence_name" DataValueField="residence_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource4" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Residences]"></asp:AccessDataSource> </InsertItemTemplate> <ItemTemplate> <asp:DropDownList ID="DropDownList4" runat="server" DataSourceID="AccessDataSource4" DataTextField="residence_name" DataValueField="residence_id" Enabled="False"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource4" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Residences]"></asp:AccessDataSource> </ItemTemplate> </asp:TemplateField> <asp:BoundField DataField="course_year" HeaderText="course_year" SortExpression="course_year" /> <asp:TemplateField HeaderText="gender_id" SortExpression="gender_id"> <EditItemTemplate> <asp:DropDownList ID="DropDownList5" runat="server" DataSourceID="AccessDataSource5" DataTextField="gender_name" DataValueField="gender_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource5" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Genders]"></asp:AccessDataSource> </EditItemTemplate> <InsertItemTemplate> <asp:DropDownList ID="DropDownList5" runat="server" DataSourceID="AccessDataSource5" DataTextField="gender_name" DataValueField="gender_id"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource5" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Genders]"></asp:AccessDataSource> </InsertItemTemplate> <ItemTemplate> <asp:DropDownList ID="DropDownList5" runat="server" DataSourceID="AccessDataSource5" DataTextField="gender_name" DataValueField="gender_id" Enabled="False"> </asp:DropDownList> <asp:AccessDataSource ID="AccessDataSource5" runat="server" DataFile="~/App_Data/VisageFinal.mdb" SelectCommand="SELECT * FROM [Genders]"></asp:AccessDataSource> </ItemTemplate> </asp:TemplateField> <asp:CommandField ShowInsertButton="True" InsertText="Create my user!" /> </Fields> <HeaderStyle BackColor="#5D7B9D" Font-Bold="True" ForeColor="White" /> <EditRowStyle BackColor="#999999" /> <AlternatingRowStyle BackColor="White" ForeColor="#284775" /> </asp:DetailsView> <asp:Button ID="Button1" runat="server" Text="Button" /> <asp:AccessDataSource ID="AccessDataSource1" runat="server" DataFile="~/App_Data/VisageFinal.mdb" DeleteCommand="DELETE FROM [Users] WHERE [user_id] = ?" InsertCommand="INSERT INTO [Users] ([email], [password], [users_name], [image_path], [mobile], [twitter], [privacy_level_id], [nationality_id], [course_id], [residence_id], [course_year], [gender_id]) VALUES ('?', '?', '?', '?', '?', '?', ?, ?, ?, ?, ?, ?)" SelectCommand="SELECT * FROM [Users]" UpdateCommand="UPDATE [Users] SET [email] = ?, [password] = ?, [users_name] = ?, [date_of_birth] = ?, [image_path] = ?, [mobile] = ?, [twitter] = ?, [privacy_level_id] = ?, [nationality_id] = ?, [course_id] = ?, [residence_id] = ?, [has_set_privacy_level] = ?, [course_year] = ?, [gender_id] = ? WHERE [user_id] = ?"> <DeleteParameters> <asp:Parameter Name="user_id" Type="Int32" /> </DeleteParameters> <UpdateParameters> <asp:Parameter Name="email" Type="String" /> <asp:Parameter Name="password" Type="String" /> <asp:Parameter Name="users_name" Type="String" /> <asp:Parameter Name="image_path" Type="String" /> <asp:Parameter Name="mobile" Type="String" /> <asp:Parameter Name="twitter" Type="String" /> <asp:Parameter Name="privacy_level_id" Type="Int32" /> <asp:Parameter Name="nationality_id" Type="Int32" /> <asp:Parameter Name="course_id" Type="Int32" /> <asp:Parameter Name="residence_id" Type="Int32" /> <asp:Parameter Name="has_set_privacy_level" Type="Boolean" /> <asp:Parameter Name="course_year" Type="Int32" /> <asp:Parameter Name="gender_id" Type="Int32" /> <asp:Parameter Name="user_id" Type="Int32" /> </UpdateParameters> <InsertParameters> <asp:Parameter Name="email" Type="String" /> <asp:Parameter Name="password" Type="String" /> <asp:Parameter Name="users_name" Type="String" /> <asp:Parameter Name="image_path" Type="String" /> <asp:Parameter Name="mobile" Type="String" /> <asp:Parameter Name="twitter" Type="String" /> <asp:Parameter Name="privacy_level_id" Type="Int32" /> <asp:Parameter Name="nationality_id" Type="Int32" /> <asp:Parameter Name="course_id" Type="Int32" /> <asp:Parameter Name="residence_id" Type="Int32" /> <asp:Parameter Name="course_year" Type="Int32" /> <asp:Parameter Name="gender_id" Type="Int32" /> </InsertParameters> </asp:AccessDataSource> Any ideas what I've broken?

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  • SQL get data out of BEGIN; ...; END; block in python

    - by Claudiu
    I want to run many select queries at once by putting them between BEGIN; END;. I tried the following: cur = connection.cursor() cur.execute(""" BEGIN; SELECT ...; END;""") res = cur.fetchall() However, I get the error: psycopg2.ProgrammingError: no results to fetch How can I actually get data this way? Likewise, if I just have many selects in a row, I only get data back from the latest one. Is there a way to get data out of all of them?

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  • Turning PHP page calling Zend functions procedurally into Zend Framework MVC-help!

    - by Joel
    Hi guys, I posted much of this question, but if didn't include all the Zend stuff because I thought it'd be overkill, but now I'm thinking it's not easy to figure out an OO way of doing this without that code... So with that said, please forgive the verbose code. I'm learning how to use MVC and OO in general, and I have a website that is all in PHP but most of the pages are basic static pages. I have already converted them all to views in Zend Framework, and have the Controller and layout set. All is good there. The one remaining page I have is the main reason I did this...it in fact uses Zend library (for gData connection and pulling info from a Google Calendar and displaying it on the page. I don't know enough about this to know where to begin to refactor the code to fit in the Zend Framework MVC model. Any help would be greatly appreciated!! .phtml view page: <div id="dhtmltooltip" align="left"></div> <script src="../js/tooltip.js" type="text/javascript"> </script> <div id="container"> <div id="conten"> <a name="C4"></a> <?php function get_desc_second_part(&$value) { list(,$val_b) = explode('==',$value); $value = trim($val_b); } function filterEventDetails($contentText) { $data = array(); foreach($contentText as $row) { if(strstr($row, 'When: ')) { ##cleaning "when" string to get date in the format "May 28, 2009"## $data['duration'] = str_replace('When: ','',$row); list($when, ) = explode(' to ',$data['duration']); $data['when'] = substr($when,4); if(strlen($data['when'])>13) $data['when'] = trim(str_replace(strrchr($data['when'], ' '),'',$data['when'])); $data['duration'] = substr($data['duration'], 0, strlen($data['duration'])-4); //trimming time zone identifier (UTC etc.) } if(strstr($row, 'Where: ')) { $data['where'] = str_replace('Where: ','',$row); //pr($row); //$where = strstr($row, 'Where: '); //pr($where); } if(strstr($row, 'Event Description: ')) { $event_desc = str_replace('Event Description: ','',$row); //$event_desc = strstr($row, 'Event Description: '); ## Filtering event description and extracting venue, ticket urls etc from it. //$event_desc = str_replace('Event Description: ','',$contentText[3]); $event_desc_array = explode('|',$event_desc); array_walk($event_desc_array,'get_desc_second_part'); //pr($event_desc_array); $data['venue_url'] = $event_desc_array[0]; $data['details'] = $event_desc_array[1]; $data['tickets_url'] = $event_desc_array[2]; $data['tickets_button'] = $event_desc_array[3]; $data['facebook_url'] = $event_desc_array[4]; $data['facebook_icon'] = $event_desc_array[5]; } } return $data; } // load library require_once 'Zend/Loader.php'; Zend_Loader::loadClass('Zend_Gdata'); Zend_Loader::loadClass('Zend_Gdata_ClientLogin'); Zend_Loader::loadClass('Zend_Gdata_Calendar'); Zend_Loader::loadClass('Zend_Http_Client'); // create authenticated HTTP client for Calendar service $gcal = Zend_Gdata_Calendar::AUTH_SERVICE_NAME; $user = "[email protected]"; $pass = "xxxxxxxx"; $client = Zend_Gdata_ClientLogin::getHttpClient($user, $pass, $gcal); $gcal = new Zend_Gdata_Calendar($client); $query = $gcal->newEventQuery(); $query->setUser('[email protected]'); $secondary=true; $query->setVisibility('private'); $query->setProjection('basic'); $query->setOrderby('starttime'); $query->setSortOrder('ascending'); //$query->setFutureevents('true'); $startDate=date('Y-m-d h:i:s'); $endDate="2015-12-31"; $query->setStartMin($startDate); $query->setStartMax($endDate); $query->setMaxResults(30); try { $feed = $gcal->getCalendarEventFeed($query); } catch (Zend_Gdata_App_Exception $e) { echo "Error: " . $e->getResponse(); } ?> <h1><?php echo $feed->title; ?></h1> <?php echo $feed->totalResults; ?> event(s) found. <table width="90%" border="3" align="center"> <tr> <td width="20%" align="center" valign="middle"><b>;DATE</b></td> <td width="25%" align="center" valign="middle"><b>VENUE</b></td> <td width="20%" align="center" valign="middle"><b>CITY</b></td> <td width="20%" align="center" valign="middle"><b>DETAILS</b></td> <td width="15%" align="center" valign="middle"><b>LINKS</b></td> </tr> <?php if((int)$feed->totalResults>0) { //checking if at least one event is there in this date range foreach ($feed as $event) { //iterating through all events //pr($event);die; $contentText = stripslashes($event->content->text); //striping any escape character $contentText = preg_replace('/\<br \/\>[\n\t\s]{1,}\<br \/\>/','<br />',stripslashes($event->content->text)); //replacing multiple breaks with a single break //die(); $contentText = explode('<br />',$contentText); //splitting data by break tag $eventData = filterEventDetails($contentText); $when = $eventData['when']; $where = $eventData['where']; $duration = $eventData['duration']; $venue_url = $eventData['venue_url']; $details = $eventData['details']; $tickets_url = $eventData['tickets_url']; $tickets_button = $eventData['tickets_button']; $facebook_url = $eventData['facebook_url']; $facebook_icon = $eventData['facebook_icon']; $title = stripslashes($event->title); echo '<tr>'; echo '<td width="20%" align="center" valign="middle" nowrap="nowrap">'; echo $when; echo '</td>'; echo '<td width="20%" align="center" valign="middle">'; if($venue_url!='') { echo '<a href="'.$venue_url.'" target="_blank">'.$title.'</a>'; } else { echo $title; } echo '</td>'; echo '<td width="20%" align="center" valign="middle">'; echo $where; echo '</td>'; echo '<td width="20%" align="center" valign="middle">'; $details = str_replace("\n","<br>",htmlentities($details)); $duration = str_replace("\n","<br>",$duration); $detailed_description = "<b>When</b>: <br>".$duration."<br><br>"; $detailed_description .= "<b>Description</b>: <br>".$details; echo '<a href="javascript:void(0);" onmouseover="ddrivetip(\''.$detailed_description.'\')" onmouseout="hideddrivetip()" onclick="return false">View Details</a>'; echo '</td>'; echo '<td width="20%" valign="middle">'; if(trim($tickets_url) !='' && trim($tickets_button)!='') { echo '<a href="'.$tickets_url.'" target="_blank"><img src="'.$tickets_button.'" border="0" ></a>'; } if(trim($facebook_url) !='' && trim($facebook_icon)!='') { echo '<a href="'.$facebook_url.'" target="_blank"><img src="'.$facebook_icon.'" border="0" ></a>'; } else { echo '......'; } echo '</td>'; echo '</tr>'; } } else { //else show 'no event found' message echo '<tr>'; echo '<td width="100%" align="center" valign="middle" colspan="5">'; echo "No event found"; echo '</td>'; } ?> </table> <h3><a href="#pastevents">Scroll down for a list of past shows.</a></h3> <br /> <a name="pastevents"></a> <ul class="pastShows"> <?php $startDate='2005-01-01'; $endDate=date('Y-m-d'); /*$gcal = Zend_Gdata_Calendar::AUTH_SERVICE_NAME; $user = "[email protected]"; $pass = "silverroof10"; $client = Zend_Gdata_ClientLogin::getHttpClient($user, $pass, $gcal); $gcal = new Zend_Gdata_Calendar($client); $query = $gcal->newEventQuery(); $query->setUser('[email protected]'); $query->setVisibility('private'); $query->setProjection('basic');*/ $query->setOrderby('starttime'); $query->setSortOrder('descending'); $query->setFutureevents('false'); $query->setStartMin($startDate); $query->setStartMax($endDate); $query->setMaxResults(1000); try { $feed = $gcal->getCalendarEventFeed($query); } catch (Zend_Gdata_App_Exception $e) { echo "Error: " . $e->getResponse(); } if((int)$feed->totalResults>0) { //checking if at least one event is there in this date range foreach ($feed as $event) { //iterating through all events $contentText = stripslashes($event->content->text); //striping any escape character $contentText = preg_replace('/\<br \/\>[\n\t\s]{1,}\<br \/\>/','<br />',stripslashes($event->content->text)); //replacing multiple breaks with a single break $contentText = explode('<br />',$contentText); //splitting data by break tag $eventData = filterEventDetails($contentText); $when = $eventData['when']; $where = $eventData['where']; $duration = $eventData['duration']; $title = stripslashes($event->title); echo '<li class="pastShows">' . $when . " - " . $title . ", " . $where . '</li>'; } } ?> </div> </div>

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  • Determine how much can I write into a filehandle; copying data from one FH to the other.

    - by Vi
    How to determine if I can write the given number of bytes to a filehandle (socket actually)? (Alternatively, how to "unread" the data I had read from other filehandle?) I want something like: n = how_much_can_I_write(w_handle); n = read(r_handle, buf, n); assert(n==write(w_handle, buf, n)); Both filehandles (r_handle and w_handle) have received ready status from epoll_wait. I want all data from r_handle to be copied to w_handle without using a "write debt" buffer. In general, how to copy the data from one filehandle to the other simply and reliably?

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  • Is Berkeley DB a NoSQL solution?

    - by Gregory Burd
    Berkeley DB is a library. To use it to store data you must link the library into your application. You can use most programming languages to access the API, the calls across these APIs generally mimic the Berkeley DB C-API which makes perfect sense because Berkeley DB is written in C. The inspiration for Berkeley DB was the DBM library, a part of the earliest versions of UNIX written by AT&T's Ken Thompson in 1979. DBM was a simple key/value hashtable-based storage library. In the early 1990s as BSD UNIX was transitioning from version 4.3 to 4.4 and retrofitting commercial code owned by AT&T with unencumbered code, it was the future founders of Sleepycat Software who wrote libdb (aka Berkeley DB) as the replacement for DBM. The problem it addressed was fast, reliable local key/value storage. At that time databases almost always lived on a single node, even the most sophisticated databases only had simple fail-over two node solutions. If you had a lot of data to store you would choose between the few commercial RDBMS solutions or to write your own custom solution. Berkeley DB took the headache out of the custom approach. These basic market forces inspired other DBM implementations. There was the "New DBM" (ndbm) and the "GNU DBM" (GDBM) and a few others, but the theme was the same. Even today TokyoCabinet calls itself "a modern implementation of DBM" mimicking, and improving on, something first created over thirty years ago. In the mid-1990s, DBM was the name for what you needed if you were looking for fast, reliable local storage. Fast forward to today. What's changed? Systems are connected over fast, very reliable networks. Disks are cheep, fast, and capable of storing huge amounts of data. CPUs continued to follow Moore's Law, processing power that filled a room in 1990 now fits in your pocket. PCs, servers, and other computers proliferated both in business and the personal markets. In addition to the new hardware entire markets, social systems, and new modes of interpersonal communication moved onto the web and started evolving rapidly. These changes cause a massive explosion of data and a need to analyze and understand that data. Taken together this resulted in an entirely different landscape for database storage, new solutions were needed. A number of novel solutions stepped up and eventually a category called NoSQL emerged. The new market forces inspired the CAP theorem and the heated debate of BASE vs. ACID. But in essence this was simply the market looking at what to trade off to meet these new demands. These new database systems shared many qualities in common. There were designed to address massive amounts of data, millions of requests per second, and scale out across multiple systems. The first large-scale and successful solution was Dynamo, Amazon's distributed key/value database. Dynamo essentially took the next logical step and added a twist. Dynamo was to be the database of record, it would be distributed, data would be partitioned across many nodes, and it would tolerate failure by avoiding single points of failure. Amazon did this because they recognized that the majority of the dynamic content they provided to customers visiting their web store front didn't require the services of an RDBMS. The queries were simple, key/value look-ups or simple range queries with only a few queries that required more complex joins. They set about to use relational technology only in places where it was the best solution for the task, places like accounting and order fulfillment, but not in the myriad of other situations. The success of Dynamo, and it's design, inspired the next generation of Non-SQL, distributed database solutions including Cassandra, Riak and Voldemort. The problem their designers set out to solve was, "reliability at massive scale" so the first focal point was distributed database algorithms. Underneath Dynamo there is a local transactional database; either Berkeley DB, Berkeley DB Java Edition, MySQL or an in-memory key/value data structure. Dynamo was an evolution of local key/value storage onto networks. Cassandra, Riak, and Voldemort all faced similar design decisions and one, Voldemort, choose Berkeley DB Java Edition for it's node-local storage. Riak at first was entirely in-memory, but has recently added write-once, append-only log-based on-disk storage similar type of storage as Berkeley DB except that it is based on a hash table which must reside entirely in-memory rather than a btree which can live in-memory or on disk. Berkeley DB evolved too, we added high availability (HA) and a replication manager that makes it easy to setup replica groups. Berkeley DB's replication doesn't partitioned the data, every node keeps an entire copy of the database. For consistency, there is a single node where writes are committed first - a master - then those changes are delivered to the replica nodes as log records. Applications can choose to wait until all nodes are consistent, or fire and forget allowing Berkeley DB to eventually become consistent. Berkeley DB's HA scales-out quite well for read-intensive applications and also effectively eliminates the central point of failure by allowing replica nodes to be elected (using a PAXOS algorithm) to mastership if the master should fail. This implementation covers a wide variety of use cases. MemcacheDB is a server that implements the Memcache network protocol but uses Berkeley DB for storage and HA to replicate the cache state across all the nodes in the cache group. Google Accounts, the user authentication layer for all Google properties, was until recently running Berkeley DB HA. That scaled to a globally distributed system. That said, most NoSQL solutions try to partition (shard) data across nodes in the replication group and some allow writes as well as reads at any node, Berkeley DB HA does not. So, is Berkeley DB a "NoSQL" solution? Not really, but it certainly is a component of many of the existing NoSQL solutions out there. Forgetting all the noise about how NoSQL solutions are complex distributed databases when you boil them down to a single node you still have to store the data to some form of stable local storage. DBMs solved that problem a long time ago. NoSQL has more to do with the layers on top of the DBM; the distributed, sometimes-consistent, partitioned, scale-out storage that manage key/value or document sets and generally have some form of simple HTTP/REST-style network API. Does Berkeley DB do that? Not really. Is Berkeley DB a "NoSQL" solution today? Nope, but it's the most robust solution on which to build such a system. Re-inventing the node-local data storage isn't easy. A lot of people are starting to come to appreciate the sophisticated features found in Berkeley DB, even mimic them in some cases. Could Berkeley DB grow into a NoSQL solution? Absolutely. Our key/value API could be extended over the net using any of a number of existing network protocols such as memcache or HTTP/REST. We could adapt our node-local data partitioning out over replicated nodes. We even have a nice query language and cost-based query optimizer in our BDB XML product that we could reuse were we to build out a document-based NoSQL-style product. XML and JSON are not so different that we couldn't adapt one to work with the other interchangeably. Without too much effort we could add what's missing, we could jump into this No SQL market withing a single product development cycle. Why isn't Berkeley DB already a NoSQL solution? Why aren't we working on it? Why indeed...

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  • Fragmented Log files could be slowing down your database

    - by Fatherjack
    Something that is sometimes forgotten by a lot of DBAs is the fact that database log files get fragmented in the same way that you get fragmentation in a data file. The cause is very different but the effect is the same – too much effort reading and writing data. Data files get fragmented as data is changed through normal system activity, INSERTs, UPDATEs and DELETEs cause fragmentation and most experienced DBAs are monitoring their indexes for fragmentation and dealing with it accordingly. However, you don’t hear about so many working on their log files. How can a log file get fragmented? I’m glad you asked. When you create a database there are at least two files created on the disk storage; an mdf for the data and an ldf for the log file (you can also have ndf files for extra data storage but that’s off topic for now). It is wholly possible to have more than one log file but in most cases there is little point in creating more than one as the log file is written to in a ‘wrap-around’ method (more on that later). When a log file is created at the time that a database is created the file is actually sub divided into a number of virtual log files (VLFs). The number and size of these VLFs depends on the size chosen for the log file. VLFs are also created in the space added to a log file when a log file growth event takes place. Do you have your log files set to auto grow? Then you have potentially been introducing many VLFs into your log file. Let’s get to see how many VLFs we have in a brand new database. USE master GO CREATE DATABASE VLF_Test ON ( NAME = VLF_Test, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test.mdf', SIZE = 100, MAXSIZE = 500, FILEGROWTH = 50 ) LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 5MB, MAXSIZE = 250MB, FILEGROWTH = 5MB ); go USE VLF_Test go DBCC LOGINFO; The results of this are firstly a new database is created with specified files sizes and the the DBCC LOGINFO results are returned to the script editor. The DBCC LOGINFO results have plenty of interesting information in them but lets first note there are 4 rows of information, this relates to the fact that 4 VLFs have been created in the log file. The values in the FileSize column are the sizes of each VLF in bytes, you will see that the last one to be created is slightly larger than the others. So, a 5MB log file has 4 VLFs of roughly 1.25 MB. Lets alter the CREATE DATABASE script to create a log file that’s a bit bigger and see what happens. Alter the code above so that the log file details are replaced by LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 1GB, MAXSIZE = 25GB, FILEGROWTH = 1GB ); With a bigger log file specified we get more VLFs What if we make it bigger again? LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 5GB, MAXSIZE = 250GB, FILEGROWTH = 5GB ); This time we see more VLFs are created within our log file. We now have our 5GB log file comprised of 16 files of 320MB each. In fact these sizes fall into all the ranges that control the VLF creation criteria – what a coincidence! The rules that are followed when a log file is created or has it’s size increased are pretty basic. If the file growth is lower than 64MB then 4 VLFs are created If the growth is between 64MB and 1GB then 8 VLFs are created If the growth is greater than 1GB then 16 VLFs are created. Now the potential for chaos comes if the default values and settings for log file growth are used. By default a database log file gets a 1MB log file with unlimited growth in steps of 10%. The database we just created is 6 MB, let’s add some data and see what happens. USE vlf_test go -- we need somewhere to put the data so, a table is in order IF OBJECT_ID('A_Table') IS NOT NULL DROP TABLE A_Table go CREATE TABLE A_Table ( Col_A int IDENTITY, Col_B CHAR(8000) ) GO -- Let's check the state of the log file -- 4 VLFs found EXECUTE ('DBCC LOGINFO'); go -- We can go ahead and insert some data and then check the state of the log file again INSERT A_Table (col_b) SELECT TOP 500 REPLICATE('a',2000) FROM sys.columns AS sc, sys.columns AS sc2 GO -- insert 500 rows and we get 22 VLFs EXECUTE ('DBCC LOGINFO'); go -- Let's insert more rows INSERT A_Table (col_b) SELECT TOP 2000 REPLICATE('a',2000) FROM sys.columns AS sc, sys.columns AS sc2 GO 10 -- insert 2000 rows, in 10 batches and we suddenly have 107 VLFs EXECUTE ('DBCC LOGINFO'); Well, that escalated quickly! Our log file is split, internally, into 107 fragments after a few thousand inserts. The same happens with any logged transactions, I just chose to illustrate this with INSERTs. Having too many VLFs can cause performance degradation at times of database start up, log backup and log restore operations so it’s well worth keeping a check on this property. How do we prevent excessive VLF creation? Creating the database with larger files and also with larger growth steps and actively choosing to grow your databases rather than leaving it to the Auto Grow event can make sure that the growths are made with a size that is optimal. How do we resolve a situation of a database with too many VLFs? This process needs to be done when the database is under little or no stress so that you don’t affect system users. The steps are: BACKUP LOG YourDBName TO YourBackupDestinationOfChoice Shrink the log file to its smallest possible size DBCC SHRINKFILE(FileNameOfTLogHere, TRUNCATEONLY) * Re-size the log file to the size you want it to, taking in to account your expected needs for the coming months or year. ALTER DATABASE YourDBName MODIFY FILE ( NAME = FileNameOfTLogHere, SIZE = TheSizeYouWantItToBeIn_MB) * – If you don’t know the file name of your log file then run sp_helpfile while you are connected to the database that you want to work on and you will get the details you need. The resize step can take quite a while This is already detailed far better than I can explain it by Kimberley Tripp in her blog 8-Steps-to-better-Transaction-Log-throughput.aspx. The result of this will be a log file with a VLF count according to the bullet list above. Knowing when VLFs are being created By complete coincidence while I have been writing this blog (it’s been quite some time from it’s inception to going live) Jonathan Kehayias from SQLSkills.com has written a great article on how to track database file growth using Event Notifications and Service Broker. I strongly recommend taking a look at it as this is going to catch any sneaky auto grows that take place and let you know about them right away. Hassle free monitoring of VLFs If you are lucky or wise enough to be using SQL Monitor or another monitoring tool that let’s you write your own custom metrics then you can keep an eye on this very easily. There is a custom metric for VLFs (written by Stuart Ainsworth) already on the site and there are some others there are very useful so take a moment or two to look around while you are there. Resources MSDN – http://msdn.microsoft.com/en-us/library/ms179355(v=sql.105).aspx Kimberly Tripp from SQLSkills.com – http://www.sqlskills.com/BLOGS/KIMBERLY/post/8-Steps-to-better-Transaction-Log-throughput.aspx Thomas LaRock at Simple-Talk.com – http://www.simple-talk.com/sql/database-administration/monitoring-sql-server-virtual-log-file-fragmentation/ Disclosure I am a Friend of Red Gate. This means that I am more than likely to say good things about Red Gate DBA and Developer tools. No matter how awesome I make them sound, take the time to compare them with other products before you contact the Red Gate sales team to make your order.

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  • SPARC T4-4 Beats 8-CPU IBM POWER7 on TPC-H @3000GB Benchmark

    - by Brian
    Oracle's SPARC T4-4 server delivered a world record TPC-H @3000GB benchmark result for systems with four processors. This result beats eight processor results from IBM (POWER7) and HP (x86). The SPARC T4-4 server also delivered better performance per core than these eight processor systems from IBM and HP. Comparisons below are based upon system to system comparisons, highlighting Oracle's complete software and hardware solution. This database world record result used Oracle's Sun Storage 2540-M2 arrays (rotating disk) connected to a SPARC T4-4 server running Oracle Solaris 11 and Oracle Database 11g Release 2 demonstrating the power of Oracle's integrated hardware and software solution. The SPARC T4-4 server based configuration achieved a TPC-H scale factor 3000 world record for four processor systems of 205,792 QphH@3000GB with price/performance of $4.10/QphH@3000GB. The SPARC T4-4 server with four SPARC T4 processors (total of 32 cores) is 7% faster than the IBM Power 780 server with eight POWER7 processors (total of 32 cores) on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 36% better in price performance compared to the IBM Power 780 server on the TPC-H @3000GB Benchmark. The SPARC T4-4 server is 29% faster than the IBM Power 780 for data loading. The SPARC T4-4 server is up to 3.4 times faster than the IBM Power 780 server for the Refresh Function. The SPARC T4-4 server with four SPARC T4 processors is 27% faster than the HP ProLiant DL980 G7 server with eight x86 processors on the TPC-H @3000GB benchmark. The SPARC T4-4 server is 52% faster than the HP ProLiant DL980 G7 server for data loading. The SPARC T4-4 server is up to 3.2 times faster than the HP ProLiant DL980 G7 for the Refresh Function. The SPARC T4-4 server achieved a peak IO rate from the Oracle database of 17 GB/sec. This rate was independent of the storage used, as demonstrated by the TPC-H @3000TB benchmark which used twelve Sun Storage 2540-M2 arrays (rotating disk) and the TPC-H @1000TB benchmark which used four Sun Storage F5100 Flash Array devices (flash storage). [*] The SPARC T4-4 server showed linear scaling from TPC-H @1000GB to TPC-H @3000GB. This demonstrates that the SPARC T4-4 server can handle the increasingly larger databases required of DSS systems. [*] The SPARC T4-4 server benchmark results demonstrate a complete solution of building Decision Support Systems including data loading, business questions and refreshing data. Each phase usually has a time constraint and the SPARC T4-4 server shows superior performance during each phase. [*] The TPC believes that comparisons of results published with different scale factors are misleading and discourages such comparisons. Performance Landscape The table lists the leading TPC-H @3000GB results for non-clustered systems. TPC-H @3000GB, Non-Clustered Systems System Processor P/C/T – Memory Composite(QphH) $/perf($/QphH) Power(QppH) Throughput(QthH) Database Available SPARC Enterprise M9000 3.0 GHz SPARC64 VII+ 64/256/256 – 1024 GB 386,478.3 $18.19 316,835.8 471,428.6 Oracle 11g R2 09/22/11 SPARC T4-4 3.0 GHz SPARC T4 4/32/256 – 1024 GB 205,792.0 $4.10 190,325.1 222,515.9 Oracle 11g R2 05/31/12 SPARC Enterprise M9000 2.88 GHz SPARC64 VII 32/128/256 – 512 GB 198,907.5 $15.27 182,350.7 216,967.7 Oracle 11g R2 12/09/10 IBM Power 780 4.1 GHz POWER7 8/32/128 – 1024 GB 192,001.1 $6.37 210,368.4 175,237.4 Sybase 15.4 11/30/11 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64/128 – 512 GB 162,601.7 $2.68 185,297.7 142,685.6 SQL Server 2008 10/13/10 P/C/T = Processors, Cores, Threads QphH = the Composite Metric (bigger is better) $/QphH = the Price/Performance metric in USD (smaller is better) QppH = the Power Numerical Quantity QthH = the Throughput Numerical Quantity The following table lists data load times and refresh function times during the power run. TPC-H @3000GB, Non-Clustered Systems Database Load & Database Refresh System Processor Data Loading(h:m:s) T4Advan RF1(sec) T4Advan RF2(sec) T4Advan SPARC T4-4 3.0 GHz SPARC T4 04:08:29 1.0x 67.1 1.0x 39.5 1.0x IBM Power 780 4.1 GHz POWER7 05:51:50 1.5x 147.3 2.2x 133.2 3.4x HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 08:35:17 2.1x 173.0 2.6x 126.3 3.2x Data Loading = database load time RF1 = power test first refresh transaction RF2 = power test second refresh transaction T4 Advan = the ratio of time to T4 time Complete benchmark results found at the TPC benchmark website http://www.tpc.org. Configuration Summary and Results Hardware Configuration: SPARC T4-4 server 4 x SPARC T4 3.0 GHz processors (total of 32 cores, 128 threads) 1024 GB memory 8 x internal SAS (8 x 300 GB) disk drives External Storage: 12 x Sun Storage 2540-M2 array storage, each with 12 x 15K RPM 300 GB drives, 2 controllers, 2 GB cache Software Configuration: Oracle Solaris 11 11/11 Oracle Database 11g Release 2 Enterprise Edition Audited Results: Database Size: 3000 GB (Scale Factor 3000) TPC-H Composite: 205,792.0 QphH@3000GB Price/performance: $4.10/QphH@3000GB Available: 05/31/2012 Total 3 year Cost: $843,656 TPC-H Power: 190,325.1 TPC-H Throughput: 222,515.9 Database Load Time: 4:08:29 Benchmark Description The TPC-H benchmark is a performance benchmark established by the Transaction Processing Council (TPC) to demonstrate Data Warehousing/Decision Support Systems (DSS). TPC-H measurements are produced for customers to evaluate the performance of various DSS systems. These queries and updates are executed against a standard database under controlled conditions. Performance projections and comparisons between different TPC-H Database sizes (100GB, 300GB, 1000GB, 3000GB, 10000GB, 30000GB and 100000GB) are not allowed by the TPC. TPC-H is a data warehousing-oriented, non-industry-specific benchmark that consists of a large number of complex queries typical of decision support applications. It also includes some insert and delete activity that is intended to simulate loading and purging data from a warehouse. TPC-H measures the combined performance of a particular database manager on a specific computer system. The main performance metric reported by TPC-H is called the TPC-H Composite Query-per-Hour Performance Metric (QphH@SF, where SF is the number of GB of raw data, referred to as the scale factor). QphH@SF is intended to summarize the ability of the system to process queries in both single and multiple user modes. The benchmark requires reporting of price/performance, which is the ratio of the total HW/SW cost plus 3 years maintenance to the QphH. A secondary metric is the storage efficiency, which is the ratio of total configured disk space in GB to the scale factor. Key Points and Best Practices Twelve Sun Storage 2540-M2 arrays were used for the benchmark. Each Sun Storage 2540-M2 array contains 12 15K RPM drives and is connected to a single dual port 8Gb FC HBA using 2 ports. Each Sun Storage 2540-M2 array showed 1.5 GB/sec for sequential read operations and showed linear scaling, achieving 18 GB/sec with twelve Sun Storage 2540-M2 arrays. These were stand alone IO tests. The peak IO rate measured from the Oracle database was 17 GB/sec. Oracle Solaris 11 11/11 required very little system tuning. Some vendors try to make the point that storage ratios are of customer concern. However, storage ratio size has more to do with disk layout and the increasing capacities of disks – so this is not an important metric in which to compare systems. The SPARC T4-4 server and Oracle Solaris efficiently managed the system load of over one thousand Oracle Database parallel processes. Six Sun Storage 2540-M2 arrays were mirrored to another six Sun Storage 2540-M2 arrays on which all of the Oracle database files were placed. IO performance was high and balanced across all the arrays. The TPC-H Refresh Function (RF) simulates periodical refresh portion of Data Warehouse by adding new sales and deleting old sales data. Parallel DML (parallel insert and delete in this case) and database log performance are a key for this function and the SPARC T4-4 server outperformed both the IBM POWER7 server and HP ProLiant DL980 G7 server. (See the RF columns above.) See Also Transaction Processing Performance Council (TPC) Home Page Ideas International Benchmark Page SPARC T4-4 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Sun Storage 2540-M2 Array oracle.com OTN Disclosure Statement TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org. SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads.

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  • Pre-rentrée Oracle Open World 2012 : à vos agendas

    - by Eric Bezille
    A maintenant moins d'un mois de l’événement majeur d'Oracle, qui se tient comme chaque année à San Francisco, fin septembre, début octobre, les spéculations vont bon train sur les annonces qui vont y être dévoilées... Et sans lever le voile, je vous engage à prendre connaissance des sujets des "Key Notes" qui seront tenues par Larry Ellison, Mark Hurd, Thomas Kurian (responsable des développements logiciels) et John Fowler (responsable des développements systèmes) afin de vous donner un avant goût. Stratégie et Roadmaps Oracle Bien entendu, au-delà des séances plénières qui vous donnerons  une vision précise de la stratégie, et pour ceux qui seront sur place, je vous engage à ne pas manquer les séances d'approfondissement qui auront lieu dans la semaine, dont voici quelques morceaux choisis : "Accelerate your Business with the Oracle Hardware Advantage" avec John Fowler, le lundi 1er Octobre, 3:15pm-4:15pm "Why Oracle Softwares Runs Best on Oracle Hardware" , avec Bradley Carlile, le responsable des Benchmarks, le lundi 1er Octobre, 12:15pm-13:15pm "Engineered Systems - from Vision to Game-changing Results", avec Robert Shimp, le lundi 1er Octobre 1:45pm-2:45pm "Database and Application Consolidation on SPARC Supercluster", avec Hugo Rivero, responsable dans les équipes d'intégration matériels et logiciels, le lundi 1er Octobre, 4:45pm-5:45pm "Oracle’s SPARC Server Strategy Update", avec Masood Heydari, responsable des développements serveurs SPARC, le mardi 2 Octobre, 10:15am - 11:15am "Oracle Solaris 11 Strategy, Engineering Insights, and Roadmap", avec Markus Flier, responsable des développements Solaris, le mercredi 3 Octobre, 10:15am - 11:15am "Oracle Virtualization Strategy and Roadmap", avec Wim Coekaerts, responsable des développement Oracle VM et Oracle Linux, le lundi 1er Octobre, 12:15pm-1:15pm "Big Data: The Big Story", avec Jean-Pierre Dijcks, responsable du développement produits Big Data, le lundi 1er Octobre, 3:15pm-4:15pm "Scaling with the Cloud: Strategies for Storage in Cloud Deployments", avec Christine Rogers,  Principal Product Manager, et Chris Wood, Senior Product Specialist, Stockage , le lundi 1er Octobre, 10:45am-11:45am Retours d'expériences et témoignages Si Oracle Open World est l'occasion de partager avec les équipes de développement d'Oracle en direct, c'est aussi l'occasion d'échanger avec des clients et experts qui ont mis en oeuvre  nos technologies pour bénéficier de leurs retours d'expériences, comme par exemple : "Oracle Optimized Solution for Siebel CRM at ACCOR", avec les témoignages d'Eric Wyttynck, directeur IT Multichannel & CRM  et Pascal Massenet, VP Loyalty & CRM systems, sur les bénéfices non seulement métiers, mais également projet et IT, le mercredi 3 Octobre, 1:15pm-2:15pm "Tips from AT&T: Oracle E-Business Suite, Oracle Database, and SPARC Enterprise", avec le retour d'expérience des experts Oracle, le mardi 2 Octobre, 11:45am-12:45pm "Creating a Maximum Availability Architecture with SPARC SuperCluster", avec le témoignage de Carte Wright, Database Engineer à CKI, le mercredi 3 Octobre, 11:45am-12:45pm "Multitenancy: Everybody Talks It, Oracle Walks It with Pillar Axiom Storage", avec le témoignage de Stephen Schleiger, Manager Systems Engineering de Navis, le lundi 1er Octobre, 1:45pm-2:45pm "Oracle Exadata for Database Consolidation: Best Practices", avec le retour d'expérience des experts Oracle ayant participé à la mise en oeuvre d'un grand client du monde bancaire, le lundi 1er Octobre, 4:45pm-5:45pm "Oracle Exadata Customer Panel: Packaged Applications with Oracle Exadata", animé par Tim Shetler, VP Product Management, mardi 2 Octobre, 1:15pm-2:15pm "Big Data: Improving Nearline Data Throughput with the StorageTek SL8500 Modular Library System", avec le témoignage du CTO de CSC, Alan Powers, le jeudi 4 Octobre, 12:45pm-1:45pm "Building an IaaS Platform with SPARC, Oracle Solaris 11, and Oracle VM Server for SPARC", avec le témoignage de Syed Qadri, Lead DBA et Michael Arnold, System Architect d'US Cellular, le mardi 2 Octobre, 10:15am-11:15am "Transform Data Center TCO with Oracle Optimized Servers: A Customer Panel", avec les témoignages notamment d'AT&T et Liberty Global, le mardi 2 Octobre, 11:45am-12:45pm "Data Warehouse and Big Data Customers’ View of the Future", avec The Nielsen Company US, Turkcell, GE Retail Finance, Allianz Managed Operations and Services SE, le lundi 1er Octobre, 4:45pm-5:45pm "Extreme Storage Scale and Efficiency: Lessons from a 100,000-Person Organization", le témoignage de l'IT interne d'Oracle sur la transformation et la migration de l'ensemble de notre infrastructure de stockage, mardi 2 Octobre, 1:15pm-2:15pm Echanges avec les groupes d'utilisateurs et les équipes de développement Oracle Si vous avez prévu d'arriver suffisamment tôt, vous pourrez également échanger dès le dimanche avec les groupes d'utilisateurs, ou tous les soirs avec les équipes de développement Oracle sur des sujets comme : "To Exalogic or Not to Exalogic: An Architectural Journey", avec Todd Sheetz - Manager of DBA and Enterprise Architecture, Veolia Environmental Services, le dimanche 30 Septembre, 2:30pm-3:30pm "Oracle Exalytics and Oracle TimesTen for Exalytics Best Practices", avec Mark Rittman, de Rittman Mead Consulting Ltd, le dimanche 30 Septembre, 10:30am-11:30am "Introduction of Oracle Exadata at Telenet: Bringing BI to Warp Speed", avec Rudy Verlinden & Eric Bartholomeus - Managers IT infrastructure à Telenet, le dimanche 30 Septembre, 1:15pm-2:00pm "The Perfect Marriage: Sun ZFS Storage Appliance with Oracle Exadata", avec Melanie Polston, directeur, Data Management, de Novation et Charles Kim, Managing Director de Viscosity, le dimanche 30 Septembre, 9:00am-10am "Oracle’s Big Data Solutions: NoSQL, Connectors, R, and Appliance Technologies", avec Jean-Pierre Dijcks et les équipes de développement Oracle, le lundi 1er Octobre, 6:15pm-7:00pm Testez et évaluez les solutions Et pour finir, vous pouvez même tester les technologies au travers du Oracle DemoGrounds, (1133 Moscone South pour la partie Systèmes Oracle, OS, et Virtualisation) et des "Hands-on-Labs", comme : "Deploying an IaaS Environment with Oracle VM", le mardi 2 Octobre, 10:15am-11:15am "Virtualize and Deploy Oracle Applications in Minutes with Oracle VM: Hands-on Lab", le mardi 2 Octobre, 11:45am-12:45pm (il est fortement conseillé d'avoir suivi le "Hands-on-Labs" précédent avant d'effectuer ce Lab. "x86 Enterprise Cloud Infrastructure with Oracle VM 3.x and Sun ZFS Storage Appliance", le mercredi 3 Octobre, 5:00pm-6:00pm "StorageTek Tape Analytics: Managing Tape Has Never Been So Simple", le mercredi 3 Octobre, 1:15pm-2:15pm "Oracle’s Pillar Axiom 600 Storage System: Power and Ease", le lundi 1er Octobre, 12:15pm-1:15pm "Enterprise Cloud Infrastructure for SPARC with Oracle Enterprise Manager Ops Center 12c", le lundi 1er Octobre, 1:45pm-2:45pm "Managing Storage in the Cloud", le mardi 2 Octobre, 5:00pm-6:00pm "Learn How to Write MapReduce on Oracle’s Big Data Platform", le lundi 1er Octobre, 12:15pm-1:15pm "Oracle Big Data Analytics and R", le mardi 2 Octobre, 1:15pm-2:15pm "Reduce Risk with Oracle Solaris Access Control to Restrain Users and Isolate Applications", le lundi 1er Octobre, 10:45am-11:45am "Managing Your Data with Built-In Oracle Solaris ZFS Data Services in Release 11", le lundi 1er Octobre, 4:45pm-5:45pm "Virtualizing Your Oracle Solaris 11 Environment", le mardi 2 Octobre, 1:15pm-2:15pm "Large-Scale Installation and Deployment of Oracle Solaris 11", le mercredi 3 Octobre, 3:30pm-4:30pm En conclusion, une semaine très riche en perspective, et qui vous permettra de balayer l'ensemble des sujets au coeur de vos préoccupations, de la stratégie à l'implémentation... Cette semaine doit se préparer, pour tailler votre agenda sur mesure, à travers les plus de 2000 sessions dont je ne vous ai fait qu'un extrait, et dont vous pouvez retrouver l'ensemble en ligne.

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  • Service Broker, not ETL

    - by jamiet
    I have been very quiet on this blog of late and one reason for that is I have been very busy on a client project that I would like to talk about a little here. The client that I have been working for has a website that runs on a distributed architecture utilising a messaging infrastructure for communication between different endpoints. My brief was to build a system that could consume these messages and produce analytical information in near-real-time. More specifically I basically had to deliver a data warehouse however it was the real-time aspect of the project that really intrigued me. This real-time requirement meant that using an Extract transformation, Load (ETL) tool was out of the question and so I had no choice but to write T-SQL code (i.e. stored-procedures) to process the incoming messages and load the data into the data warehouse. This concerned me though – I had no way to control the rate at which data would arrive into the system yet we were going to have end-users querying the system at the same time that those messages were arriving; the potential for contention in such a scenario was pretty high and and was something I wanted to minimise as much as possible. Moreover I did not want the processing of data inside the data warehouse to have any impact on the customer-facing website. As you have probably guessed from the title of this blog post this is where Service Broker stepped in! For those that have not heard of it Service Broker is a queuing technology that has been built into SQL Server since SQL Server 2005. It provides a number of features however the one that was of interest to me was the fact that it facilitates asynchronous data processing which, in layman’s terms, means the ability to process some data without requiring the system that supplied the data having to wait for the response. That was a crucial feature because on this project the customer-facing website (in effect an OLTP system) would be calling one of our stored procedures with each message – we did not want to cause the OLTP system to wait on us every time we processed one of those messages. This asynchronous nature also helps to alleviate the contention problem because the asynchronous processing activity is handled just like any other task in the database engine and hence can wait on another task (such as an end-user query). Service Broker it was then! The stored procedure called by the OLTP system would simply put the message onto a queue and we would use a feature called activation to pick each message off the queue in turn and process it into the warehouse. At the time of writing the system is not yet up to full capacity but so far everything seems to be working OK (touch wood) and crucially our users are seeing data in near-real-time. By near-real-time I am talking about latencies of a few minutes at most and to someone like me who is used to building systems that have overnight latencies that is a huge step forward! So then, am I advocating that you all go out and dump your ETL tools? Of course not, no! What this project has taught me though is that in certain scenarios there may be better ways to implement a data warehouse system then the traditional “load data in overnight” approach that we are all used to. Moreover I have really enjoyed getting to grips with a new technology and even if you don’t want to use Service Broker you might want to consider asynchronous messaging architectures for your BI/data warehousing solutions in the future. This has been a very high level overview of my use of Service Broker and I have deliberately left out much of the minutiae of what has been a very challenging implementation. Nonetheless I hope I have caused you to reflect upon your own approaches to BI and question whether other approaches may be more tenable. All comments and questions gratefully received! Lastly, if you have never used Service Broker before and want to kick the tyres I have provided below a very simple “Service Broker Hello World” script that will create all of the objects required to facilitate Service Broker communications and then send the message “Hello World” from one place to anther! This doesn’t represent a “proper” implementation per se because it doesn’t close down down conversation objects (which you should always do in a real-world scenario) but its enough to demonstrate the capabilities! @Jamiet ----------------------------------------------------------------------------------------------- /*This is a basic Service Broker Hello World app. Have fun! -Jamie */ USE MASTER GO CREATE DATABASE SBTest GO --Turn Service Broker on! ALTER DATABASE SBTest SET ENABLE_BROKER GO USE SBTest GO -- 1) we need to create a message type. Note that our message type is -- very simple and allowed any type of content CREATE MESSAGE TYPE HelloMessage VALIDATION = NONE GO -- 2) Once the message type has been created, we need to create a contract -- that specifies who can send what types of messages CREATE CONTRACT HelloContract (HelloMessage SENT BY INITIATOR) GO --We can query the metadata of the objects we just created SELECT * FROM   sys.service_message_types WHERE name = 'HelloMessage'; SELECT * FROM   sys.service_contracts WHERE name = 'HelloContract'; SELECT * FROM   sys.service_contract_message_usages WHERE  service_contract_id IN (SELECT service_contract_id FROM sys.service_contracts WHERE name = 'HelloContract') AND        message_type_id IN (SELECT message_type_id FROM sys.service_message_types WHERE name = 'HelloMessage'); -- 3) The communication is between two endpoints. Thus, we need two queues to -- hold messages CREATE QUEUE SenderQueue CREATE QUEUE ReceiverQueue GO --more querying metatda SELECT * FROM sys.service_queues WHERE name IN ('SenderQueue','ReceiverQueue'); --we can also select from the queues as if they were tables SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   -- 4) Create the required services and bind them to be above created queues CREATE SERVICE Sender   ON QUEUE SenderQueue CREATE SERVICE Receiver   ON QUEUE ReceiverQueue (HelloContract) GO --more querying metadata SELECT * FROM sys.services WHERE name IN ('Receiver','Sender'); -- 5) At this point, we can begin the conversation between the two services by -- sending messages DECLARE @conversationHandle UNIQUEIDENTIFIER DECLARE @message NVARCHAR(100) BEGIN   BEGIN TRANSACTION;   BEGIN DIALOG @conversationHandle         FROM SERVICE Sender         TO SERVICE 'Receiver'         ON CONTRACT HelloContract WITH ENCRYPTION=OFF   -- Send a message on the conversation   SET @message = N'Hello, World';   SEND  ON CONVERSATION @conversationHandle         MESSAGE TYPE HelloMessage (@message)   COMMIT TRANSACTION END GO --check contents of queues SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   GO -- Receive a message from the queue RECEIVE CONVERT(NVARCHAR(MAX), message_body) AS MESSAGE FROM ReceiverQueue GO --If no messages were received and/or you can't see anything on the queues you may wish to check the following for clues: SELECT * FROM sys.transmission_queue -- Cleanup DROP SERVICE Sender DROP SERVICE Receiver DROP QUEUE SenderQueue DROP QUEUE ReceiverQueue DROP CONTRACT HelloContract DROP MESSAGE TYPE HelloMessage GO USE MASTER GO DROP DATABASE SBTest GO

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  • C# Performance Pitfall – Interop Scenarios Change the Rules

    - by Reed
    C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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  • Oracle Flashback Technologies - Overview

    - by Sridhar_R-Oracle
    Oracle Flashback Technologies - IntroductionIn his May 29th 2014 blog, my colleague Joe Meeks introduced Oracle Maximum Availability Architecture (MAA) and discussed both planned and unplanned outages. Let’s take a closer look at unplanned outages. These can be caused by physical failures (e.g., server, storage, network, file deletion, physical corruption, site failures) or by logical failures – cases where all components and files are physically available, but data is incorrect or corrupt. These logical failures are usually caused by human errors or application logic errors. This blog series focuses on these logical errors – what causes them and how to address and recover from them using Oracle Database Flashback. In this introductory blog post, I’ll provide an overview of the Oracle Database Flashback technologies and will discuss the features in detail in future blog posts. Let’s get started. We are all human beings (unless a machine is reading this), and making mistakes is a part of what we do…often what we do best!  We “fat finger”, we spill drinks on keyboards, unplug the wrong cables, etc.  In addition, many of us, in our lives as DBAs or developers, must have observed, caused, or corrected one or more of the following unpleasant events: Accidentally updated a table with wrong values !! Performed a batch update that went wrong - due to logical errors in the code !! Dropped a table !! How do DBAs typically recover from these types of errors? First, data needs to be restored and recovered to the point-in-time when the error occurred (incomplete or point-in-time recovery).  Moreover, depending on the type of fault, it’s possible that some services – or even the entire database – would have to be taken down during the recovery process.Apart from error conditions, there are other questions that need to be addressed as part of the investigation. For example, what did the data look like in the morning, prior to the error? What were the various changes to the row(s) between two timestamps? Who performed the transaction and how can it be reversed?  Oracle Database includes built-in Flashback technologies, with features that address these challenges and questions, and enable you to perform faster, easier, and convenient recovery from logical corruptions. HistoryFlashback Query, the first Flashback Technology, was introduced in Oracle 9i. It provides a simple, powerful and completely non-disruptive mechanism for data verification and recovery from logical errors, and enables users to view the state of data at a previous point in time.Flashback Technologies were further enhanced in Oracle 10g, to provide fast, easy recovery at the database, table, row, and even at a transaction level.Oracle Database 11g introduced an innovative method to manage and query long-term historical data with Flashback Data Archive. The 11g release also introduced Flashback Transaction, which provides an easy, one-step operation to back out a transaction. Oracle Database versions 11.2.0.2 and beyond further enhanced the performance of these features. Note that all the features listed here work without requiring any kind of restore operation.In addition, Flashback features are fully supported with the new multi-tenant capabilities introduced with Oracle Database 12c, Flashback Features Oracle Flashback Database enables point-in-time-recovery of the entire database without requiring a traditional restore and recovery operation. It rewinds the entire database to a specified point in time in the past by undoing all the changes that were made since that time.Oracle Flashback Table enables an entire table or a set of tables to be recovered to a point in time in the past.Oracle Flashback Drop enables accidentally dropped tables and all dependent objects to be restored.Oracle Flashback Query enables data to be viewed at a point-in-time in the past. This feature can be used to view and reconstruct data that was lost due to unintentional change(s) or deletion(s). This feature can also be used to build self-service error correction into applications, empowering end-users to undo and correct their errors.Oracle Flashback Version Query offers the ability to query the historical changes to data between two points in time or system change numbers (SCN) Oracle Flashback Transaction Query enables changes to be examined at the transaction level. This capability can be used to diagnose problems, perform analysis, audit transactions, and even revert the transaction by undoing SQLOracle Flashback Transaction is a procedure used to back-out a transaction and its dependent transactions.Flashback technologies eliminate the need for a traditional restore and recovery process to fix logical corruptions or make enquiries. Using these technologies, you can recover from the error in the same amount of time it took to generate the error. All the Flashback features can be accessed either via SQL command line (or) via Enterprise Manager.  Most of the Flashback technologies depend on the available UNDO to retrieve older data. The following table describes the various Flashback technologies: their purpose, dependencies and situations where each individual technology can be used.   Example Syntax Error investigation related:The purpose is to investigate what went wrong and what the values were at certain points in timeFlashback Queries  ( select .. as of SCN | Timestamp )   - Helps to see the value of a row/set of rows at a point in timeFlashback Version Queries  ( select .. versions between SCN | Timestamp and SCN | Timestamp)  - Helps determine how the value evolved between certain SCNs or between timestamps Flashback Transaction Queries (select .. XID=)   - Helps to understand how the transaction caused the changes.Error correction related:The purpose is to fix the error and correct the problems,Flashback Table  (flashback table .. to SCN | Timestamp)  - To rewind the table to a particular timestamp or SCN to reverse unwanted updates Flashback Drop (flashback table ..  to before drop )  - To undrop or undelete a table Flashback Database (flashback database to SCN  | Restore Point )  - This is the rewind button for Oracle databases. You can revert the entire database to a particular point in time. It is a fast way to perform a PITR (point-in-time recovery). Flashback Transaction (DBMS_FLASHBACK.TRANSACTION_BACKOUT(XID..))  - To reverse a transaction and its related transactions Advanced use cases Flashback technology is integrated into Oracle Recovery Manager (RMAN) and Oracle Data Guard. So, apart from the basic use cases mentioned above, the following use cases are addressed using Oracle Flashback. Block Media recovery by RMAN - to perform block level recovery Snapshot Standby - where the standby is temporarily converted to a read/write environment for testing, backup, or migration purposes Re-instate old primary in a Data Guard environment – this avoids the need to restore an old backup and perform a recovery to make it a new standby. Guaranteed Restore Points - to bring back the entire database to an older point-in-time in a guaranteed way. and so on..I hope this introductory overview helps you understand how Flashback features can be used to investigate and recover from logical errors.  As mentioned earlier, I will take a deeper-dive into to some of the critical Flashback features in my upcoming blogs and address common use cases.

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  • SQL SERVER – Create a Very First Report with the Report Wizard

    - by Pinal Dave
    This example is from the Beginning SSRS by Kathi Kellenberger. Supporting files are available with a free download from the www.Joes2Pros.com web site. What is the report Wizard? In today’s world automation is all around you. Henry Ford began building his Model T automobiles on a moving assembly line a century ago and changed the world. The moving assembly line allowed Ford to build identical cars quickly and cheaply. Henry Ford said in his autobiography “Any customer can have a car painted any color that he wants so long as it is black.” Today you can buy a car straight from the factory with your choice of several colors and with many options like back up cameras, built-in navigation systems and heated leather seats. The assembly lines now use robots to perform some tasks along with human workers. When you order your new car, if you want something special, not offered by the manufacturer, you will have to find a way to add it later. In computer software, we also have “assembly lines” called wizards. A wizard will ask you a series of questions, often branching to specific questions based on earlier answers, until you get to the end of the wizard. These wizards are used for many things, from something simple like setting up a rule in Outlook to performing administrative tasks on a server. Often, a wizard will get you part of the way to the end result, enough to get much of the tedious work out of the way. Once you get the product from the wizard, if the wizard is not capable of doing something you need, you can tweak the results. Create a Report with the Report Wizard Let’s get started with your first report!  Launch SQL Server Data Tools (SSDT) from the Start menu under SQL Server 2012. Once SSDT is running, click New Project to launch the New Project dialog box. On the left side of the screen expand Business Intelligence and select Reporting Services. Configure the properties as shown in . Be sure to select Report Server Project Wizard as the type of report and to save the project in the C:\Joes2Pros\SSRSCompanionFiles\Chapter3\Project folder. Click OK and wait for the Report Wizard to launch. Click Next on the Welcome screen.  On the Select the Data Source screen, make sure that New data source is selected. Type JProCo as the data source name. Make sure that Microsoft SQL Server is selected in the Type dropdown. Click Edit to configure the connection string on the Connection Properties dialog box. If your SQL Server database server is installed on your local computer, type in localhost for the Server name and select the JProCo database from the Select or enter a database name dropdown. Click OK to dismiss the Connection Properties dialog box. Check Make this a shared data source and click Next. On the Design the Query screen, you can use the query builder to build a query if you wish. Since this post is not meant to teach you T-SQL queries, you will copy all queries from files that have been provided for you. In the C:\Joes2Pros\SSRSCompanionFiles\Chapter3\Resources folder open the sales by employee.sql file. Copy and paste the code from the file into the Query string Text Box. Click Next. On the Select the Report Type screen, choose Tabular and click Next. On the Design the Table screen, you have to figure out the groupings of the report. How do you do this? Well, you often need to know a bit about the data and report requirements. I often draw the report out on paper first to help me determine the groups. In the case of this report, I could group the data several ways. Do I want to see the data grouped by Year and Month? Do I want to see the data grouped by Employee or Category? The only thing I know for sure about this ahead of time is that the TotalSales goes in the Details section. Let’s assume that the CIO asked to see the data grouped first by Year and Month, then by Category. Let’s move the fields to the right-hand side. This is done by selecting Page > Group or Details >, as shown in, and click Next. On the Choose the Table Layout screen, select Stepped and check Include subtotals and Enable drilldown, as shown in. On the Choose the Style screen, choose any color scheme you wish (unlike the Model T) and click Next. I chose the default, Slate. On the Choose the Deployment Location screen, change the Deployment folder to Chapter 3 and click Next. At the Completing the Wizard screen, name your report Employee Sales and click Finish. After clicking Finish, the report and a shared data source will appear in the Solution Explorer and the report will also be visible in Design view. Click the Preview tab at the top. This report expects the user to supply a year which the report will then use as a filter. Type in a year between 2006 and 2013 and click View Report. Click the plus sign next to the Sales Year to expand the report to see the months, then expand again to see the categories and finally the details. You now have the assembly line report completed, and you probably already have some ideas on how to improve the report. Tomorrow’s Post Tomorrow’s blog post will show how to create your own data sources and data sets in SSRS. If you want to learn SSRS in easy to simple words – I strongly recommend you to get Beginning SSRS book from Joes 2 Pros. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Reporting Services, SSRS

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  • Twitter ?? Nashorn ????(??)

    - by Homma
    ???? Nashorn ? Java ??????? Twitter ???????????????????? JavaFX ??????????????? ????? ??? jlaskey ??? Nashorn Blog ????????????? https://blogs.oracle.com/nashorn/entry/nashorn_in_the_twitterverse_continued ???????? ?? Twitter ???????????????????????? JavaFX ??????????????????????????????? Nashorn ?? JavaFX ??????????????JavaFX ???????????????????????????????????????Nashorn ? Java ????????????????????????????????????(JavaFX ?????????????????????)? ?????????????????????????????????????????????? Twitter ????????????????????????? var twitter4j = Packages.twitter4j; var TwitterFactory = twitter4j.TwitterFactory; var Query = twitter4j.Query; function getTrendingData() { var twitter = new TwitterFactory().instance; var query = new Query("nashorn OR nashornjs"); query.since("2012-11-21"); query.count = 100; var data = {}; do { var result = twitter.search(query); var tweets = result.tweets; for each (var tweet in tweets) { var date = tweet.createdAt; var key = (1900 + date.year) + "/" + (1 + date.month) + "/" + date.date; data[key] = (data[key] || 0) + 1; } } while (query = result.nextQuery()); return data; } ??????????????????getTrendingData() ??????????????(??????????Nashorn ???????? OpenJDK ?????? 2012 ? 11 ? 21 ???)??????????????????????????????????? ????JavaFX ? BarChart ??????????? var javafx = Packages.javafx; var Stage = javafx.stage.Stage var Scene = javafx.scene.Scene; var Group = javafx.scene.Group; var Chart = javafx.scene.chart.Chart; var FXCollections = javafx.collections.FXCollections; var ObservableList = javafx.collections.ObservableList; var CategoryAxis = javafx.scene.chart.CategoryAxis; var NumberAxis = javafx.scene.chart.NumberAxis; var BarChart = javafx.scene.chart.BarChart; var XYChart = javafx.scene.chart.XYChart; var Series = javafx.scene.chart.XYChart.Series; var Data = javafx.scene.chart.XYChart.Data; function graph(stage, data) { var root = new Group(); stage.scene = new Scene(root); var dates = Object.keys(data); var xAxis = new CategoryAxis(); xAxis.categories = FXCollections.observableArrayList(dates); var yAxis = new NumberAxis("Tweets", 0.0, 200.0, 50.0); var series = FXCollections.observableArrayList(); for (var date in data) { series.add(new Data(date, data[date])); } var tweets = new Series("Tweets", series); var barChartData = FXCollections.observableArrayList(tweets); var chart = new BarChart(xAxis, yAxis, barChartData, 25.0); root.children.add(chart); } ????????????????????????????????stage.scene = new Scene(root) ? stage.setScene(new Scene(root)) ????????????????????Nashorn ? stage ??????? scene ???????????????????(Dynalink ?????????)Java Beans ???????????????? (setScene()) ???????????????????????????????Nashorn ? FXCollections ??????????????????????????????observableArrayList(dates) ??????????Nashorn ? JavaScript ??? (dates) ? Java ???????????????????????????? JavaScript ?????????????????? Java ????????????????????????????????????????????????????????????? ????????????????????????????????? JavaFX ???????????????????????? JavaFX ??????????????javafx.application.Application ??????????????????????????? JavaFX ????????????????????????????????????????????????? import java.io.IOException; import java.io.InputStream; import java.io.InputStreamReader; import javafx.application.Application; import javafx.stage.Stage; import javax.script.ScriptEngine; import javax.script.ScriptEngineManager; import javax.script.ScriptException; public class TrendingMain extends Application { private static final ScriptEngineManager MANAGER = new ScriptEngineManager(); private final ScriptEngine engine = MANAGER.getEngineByName("nashorn"); private Trending trending; public static void main(String[] args) { launch(args); } @Override public void start(Stage stage) throws Exception { trending = (Trending) load("Trending.js"); trending.start(stage); } @Override public void stop() throws Exception { trending.stop(); } private Object load(String script) throws IOException, ScriptException { try (final InputStream is = TrendingMain.class.getResourceAsStream(script)) { return engine.eval(new InputStreamReader(is, "utf-8")); } } } ???? Nashorn ??????? JSR-223 ? javax.script ????????? private static final ScriptEngineManager MANAGER = new ScriptEngineManager(); private final ScriptEngine engine = MANAGER.getEngineByName("nashorn"); ????????? JavaScript ???????? Nashorn ???????????????????? load ???????????????????????engine ???????????????load ????????????? ???????????????Java ???????????????????????????????????????????????????? Java ????????????????JavaFX ???????? start ????? stop ?????????????????????????????????????? public interface Trending { public void start(Stage stage) throws Exception; public void stop() throws Exception; } ?????????????????????????????? function newTrending() { return new Packages.Trending() { start: function(stage) { var data = getTrendingData(); graph(stage, data); stage.show(); }, stop: function() { } } } newTrending(); ?????? Trending ?????????????????????start ????? stop ??????????????????????????????????? eval ???? Java ??????????????? trending = (Trending) load("Trending.js"); ????????????????Trending.js ??????? getTrendingData ???????????? newTrending ????????????????????? Java ?????????newTrending ????????? eval ????????? Trending ????????????????????????????????????????????????????????? trending.start(stage); ???????? ???? Nashorn ????????? http://www.myexpospace.com/JavaOne2012/SessionFiles/CON5251_PDF_5251_0001.pdf ???????? Dynalink ??????? https://github.com/szegedi/dynalink ????????

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  • Gnome 3 gdm fails to start after preupgrade from fedora 14 to 15

    - by digital illusion
    I'm not able to boot fedora 15 in runlevel 5. After all services start, when the login screen should appear, gdm just show a mouse waiting cursor and keeps restarting itself. From /var/log/gdm/\:0-greeter.log Gtk-Message: Failed to load module "pk-gtk-module" /usr/bin/gnome-session: symbol lookup error: /usr/lib/gtk-3.0/modules/libatk-bridge.so: undefined symbol: atk_plug_get_type /usr/libexec/gnome-setting-daemon: symbol lookup error: /usr/lib/gtk-3.0modules/libatk-bridge.so: undefined symbol: atk_plug_get_type Where should atk_plug_get_type be defined? Edit: Here a better description of the error (system-config-network-gui:2643): Gnome-WARNING **: Accessibility: failed to find module 'libgail-gnome' which is needed to make this application accessible /usr/bin/python: symbol lookup error: /usr/lib/gtk-2.0/modules/libatk-bridge.so: undefined symbol: atk_plug_get_type Why there are still references to gtk2? Did preupgrade fail? Attaching upgrade log... it seems gdm was not added, but it is present in the users and groups list. May 26 11:25:52 sysimage sendmail[1076]: alias database /etc/aliases rebuilt by root May 26 11:25:52 sysimage sendmail[1076]: /etc/aliases: 77 aliases, longest 23 bytes, 795 bytes total May 26 11:46:09 sysimage useradd[1793]: failed adding user 'dbus', data deleted May 26 11:53:37 sysimage systemd-machine-id-setup[2443]: Initializing machine ID from D-Bus machine ID. May 26 11:55:28 sysimage useradd[2835]: failed adding user 'apache', data deleted May 26 11:55:38 sysimage useradd[2842]: failed adding user 'haldaemon', data deleted May 26 11:55:43 sysimage useradd[2848]: failed adding user 'smolt', data deleted May 26 11:57:32 sysimage sendmail[3032]: alias database /etc/aliases rebuilt by root May 26 11:57:32 sysimage sendmail[3032]: /etc/aliases: 77 aliases, longest 23 bytes, 795 bytes total May 26 11:57:46 sysimage groupadd[3066]: group added to /etc/group: name=cgred, GID=482 May 26 11:57:47 sysimage groupadd[3066]: group added to /etc/gshadow: name=cgred May 26 11:57:47 sysimage groupadd[3066]: new group: name=cgred, GID=482 May 26 11:58:42 sysimage useradd[3086]: failed adding user 'ntp', data deleted May 26 12:00:13 sysimage dbus: avc: received policyload notice (seqno=2) May 26 12:15:08 sysimage useradd[4950]: failed adding user 'gdm', data deleted May 26 12:24:39 sysimage dbus: avc: received policyload notice (seqno=3) May 26 12:25:24 sysimage useradd[5522]: failed adding user 'mysql', data deleted May 26 12:25:37 sysimage useradd[5533]: failed adding user 'rpcuser', data deleted May 26 12:26:31 sysimage useradd[5592]: failed adding user 'tcpdump', data deleted Any suggestions before I revert installation to F14?

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  • Tomcat6 getting crashed at regular intervals installed in Ubuntu

    - by Milesh Rout
    I have installed Tomcat6 in Ubuntu OS and when I run my web application the server gets crashed at regular intervals. I have tried a lot but not getting the solution. I have increased the memory upto 2048mb but still getting such error. Following is the error I am getting. Any help would be really appreciated. org.apache.tomcat.util.http.Parameters processParametersINFO: Invalid chunk starting at byte [312] and ending at byte [312] with a value of [null] ignoredException in thread "Timer-1" Exception in thread "com.mchange.v2.async.ThreadPoolAsynchronousRunner$PoolThread-#0" Exception in thread "com.mchange.v2.async.ThreadPoolAsynchronousRunner$PoolThread-#2" Exception in thread "com.mchange.v2.async.ThreadPoolAsynchronousRunner$PoolThread-#1" Exception in thread "Timer-2" Exception in thread "http-8080-4" Exception in thread "http-8080-8" Exception in thread "http-8080-17" Exception in thread "org.hibernate.cache.StandardQueryCache.data" Exception in thread "org.hibernate.cache.UpdateTimestampsCache.data" Exception in thread "org.hibernate.cache.StandardQueryCache.data" Exception in thread "org.hibernate.cache.StandardQueryCache.data" Exception in thread "org.hibernate.cache.UpdateTimestampsCache.data" Exception in thread "org.hibernate.cache.StandardQueryCache.data" Exception in thread "org.hibernate.cache.StandardQueryCache.data" Exception in thread "org.hibernate.cache.UpdateTimestampsCache.data" Exception in thread "com.safenet.usermgmt.User.data" Exception in thread "http-8080-7" Exception in thread "http-8080-12" Exception in thread "http-8080-16" Exception in thread "http-8080-14" Exception in thread "http-8080-13" Exception in thread "http-8080-15" Exception in thread "http-8080-6" OpenJDK Client VM warning: Exception java.lang.OutOfMemoryError occurred dispatching signal SIGTERM to handler- the VM may need to be forcibly terminated

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  • Slowdown upon router/modem setup change

    - by Ollie Saunders
    I’ve been using a Belkin FSD7632-4 modem router to connect to my TalkTalk provided ADSL internet connection for some time and been pretty happy with it. Recently, however, the connection has been failing and I decided to get a ASUS RT-N16 instead, which is also a much more capable router generally. The ASUS RT-N16 doesn’t come with a modem built-in so I purchased as Zoom modem as well. I’ve set them both up and am using them to post this message. But I’m a bit miffed to find that I get a significantly and consistently slower downstream rate from the new configuration than with the old Belkin. Belkin modem router: downstream: 3.45 mbps upstream: 0.73 mbps ASUS router + Zoom modem: downstream: 2.71 mbps upstream: 0.66 mbps Any ideas why this is? The really weird thing about this is that the Zoom supports ADSL2 and ADSL2+ but I don’t think the old Belkin does. At first I thought it might be due to the Zoom modem being limited to PPPoE instead of PPPoA, which my ISP supports, but then I tried using PPPoE with the Belkin and that still gave a high speed. I’m using VC-Mux encapsulation with both. VPI of 0 and VCI of 38. I pulled this data off the Zoom: Mode: ADSL2 Line Coding: Trellis On Status: No Defect Link Power State: L0 Downstream Upstream SNR Margin (dB): 12.3 11.8 Attenuation (dB): 43.0 24.9 Output Power (dBm): 12.9 0.0 Attainable Rate (Kbps): 3936 844 Rate (Kbps): 3194 840 MSGc (number of bytes in overhead channel message): 59 10 B (number of bytes in Mux Data Frame): 99 14 M (number of Mux Data Frames in FEC Data Frame): 2 16 T (Mux Data Frames over sync bytes): 1 8 R (number of check bytes in FEC Data Frame): 8 8 S (ratio of FEC over PMD Data Frame length): 1.9833 9.0594 L (number of bits in PMD Data Frame): 839 219 D (interleaver depth): 32 2 Delay (msec): 15 4 Super Frames: 15808 14078 Super Frame Errors: 0 4294967232 RS Words: 513778 111753 RS Correctable Errors: 126 4294967238 RS Uncorrectable Errors: 0 N/A HEC Errors: 0 4294967279 OCD Errors: 0 0 LCD Errors: 0 0 Total Cells: 1920175 237597 Data Cells: 205993 392 Bit Errors: 0 0 Total ES: 0 0 Total SES: 0 0 Total UAS: 34 0

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  • Using Truecrypt to secure mySQL database, any pitfalls?

    - by Saul
    The objective is to secure my database data from server theft, i.e. the server is at a business office location with normal premises lock and burglar alarm, but because the data is personal healthcare data I want to ensure that if the server was stolen the data would be unavailable as encrypted. I'm exploring installing mySQL on a mounted Truecrypt encrypted volume. It all works fine, and when I power off, or just cruelly pull the plug the encrypted drive disappears. This seems a load easier than encrypting data to the database, and I understand that if there is a security hole in the web app , or a user gets physical access to a plugged in server the data is compromised, but as a sanity check , is there any good reason not to do this? @James I'm thinking in a theft scenario, its not going to be powered down nicely and so is likely to crash any DB transactions running. But then if someone steals the server I'm going to need to rely on my off site backup anyway. @tomjedrz, its kind of all sensitive, individual personal and address details linked to medical referrals/records. Would be as bad in our field as losing credit card data, but means that almost everything in the database would need encryption... so figured better to run the whole DB in an encrypted partition. If encrypt data in the tables there's got to be a key somewhere on the server I'm presuming, which seems more of a risk if the box walks. At the moment the app is configured to drop a dump of data (weekly full and then deltas only hourly using rdiff) into a directory also on the Truecrypt disk. I have an off site box running WS_FTP Pro scheduled to connect by FTPs and synch down the backup, again into a Truecrypt mounted partition.

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  • MySQL : table organisation for very large sets with high update frequency

    - by Remiz
    I'm facing a dilemma in the choice of my MySQL schema application. So before I start here is a picture extremely simplified of my database : Schema here : http://i43.tinypic.com/2wp5lxz.png In one sentence : for each customer, the application harvest text data and attached tags to each data collected. As approximation of the usage of each table, here is what I expect : customer : ~5000, shouldn't grow fast data : 5 millions per customer, could double or triple for big customers. tag : ~1000, quite fixed size data_tag : hundred of millions per customer easily. Each data can be tagged a lot. The harvesting process is permanent, that means that around every 15 minutes new data come and are tagged, that require a very constant index refreshing. A lot of my queries are a SELECT COUNT of DATA between specific DATES and tagged with a specific TAG on a specific CUSTOMER (very rarely it will involve several customers). Here is the situation, you can imagine with this kind of volume of data I'm facing a challenge in term of data organization and indexing. Again, it's a very minimalistic and simplified version of my structure. My question is, is it better: to stick with this model and to manage crazy index optimization ? (which involves potentially having billions of rows in the data_tag table) change the schema and use one data table and one data_tag table per customer ? (which involves having 5000 tables on my database) I'm running all of this on a MySQL 5.0 dedicated server (quad-core, 8Go of ram) replicated. I only use InnoDB, I also have another server that run Sphinx. So knowing all of this, I can't wait to hear your opinion about this. Thanks.

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