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  • Getting Started With XML Indexes

    XML Indexes make a huge difference to the speed of XML queries, as Seth Delconte explains; and demonstrates by running queries against half a million XML employee records. The execution time of a query is reduced from two seconds to being too quick to measure, purely by creating the right type of secondary index for the query. Schedule Azure backupsRed Gate’s Cloud Services makes it simple to create and schedule backups of your SQL Azure databases to Azure blob storage or Amazon S3. Try it for free today.

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  • 11g ???:Active Data Guard

    - by JaneZhang(???)
    ?Oracle 11g??,????(physical Standby)???redo???,???????,???mount??11g??,???redo???,????????read-only??,????Active Data Guard ???Active Data Guard,?????????????????,??????????????   Active Data Guard???????????,??,????????????,????????,????redo??,????????????,??????????? Oracle Active Data Guard ?Oracle Database Enterprise Edition?????,??????????????   ????Active Data Guard, ??????? read-only ????,???? ALTER DATABASE RECOVER MANAGED STANDBY DATABASE????????????:??????COMPATIBLE ????????11.0.0?  ???????Active Data Guard,???V$DATABASE????"READ ONLY WITH APPLY':      SQL> SELECT open_mode FROM V$DATABASE;      OPEN_MODE      --------------------      READ ONLY WITH APPLY   ????????????,???????real-time apply:   SQL>ALTER DATABASE RECOVER MANAGED STANDBY DATABASE USING CURRENT LOGFILE; ?????????read-only????????:    • Issue SELECT statements, including queries that require multiple sorts that leverage TEMP segments    • Use ALTER SESSION and ALTER SYSTEM statements    • Use SET ROLE    • Call stored procedures    • Use database links (dblinks) to write to remote databases    • Use stored procedures to call remote procedures via dblinks    • Use SET TRANSACTION READ ONLY for transaction level read consistency    • Issue complex queries (such as grouping SET queries and WITH CLAUSE queries) ??????????read-only????????:    • Any DMLs (excluding simple SELECT statements) or DDLs    • Query accessing local sequences    • DMLs to local temporary tables    ?????Active Data Guard ??: • ????????????????? • ???Oracle Real Application Clusters (Oracle RAC) ,?????? • RAC???RAC??    Oracle Data Guard ?????,,????????:    * ?????????????????:     http://docs.oracle.com/cd/B28359_01/server.111/b28294/create_ps.htm   * ???Oracle Real Application Clusters (Oracle RAC) ,??????:     http://www.oracle.com/technetwork/database/features/availability/maa-wp-10g-racprimarysingleinstance-131970.pdf   * RAC ???RAC ??:     http://www.oracle.com/technetwork/database/features/availability/maa-wp-10g-racprimaryracphysicalsta-131940.pdf  ??Active Data Guard???????,?????:    http://www.oracle.com/technetwork/database/features/availability/maa-wp-11gr1-activedataguard-1-128199.pdf     ??Oracle Maximum Availability Architecture Best Practices?????,???:   http://www.oracle.com/goto/maa

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  • Computer specs for a large database

    - by SpeksETC
    What sort of computer specs (CPU, RAM, disk speed) should I use for running queries on a database of 200+ million records? The queries are for a research project, so there is only one "user" and only one query will be running at a time. I tried it on my own laptop with SQL Server with an i3 processor, 2GB RAM, 5400 RPM disk and a simple query didn't finish even after 8+ hours. I have an option to connect a SSD via eSata and upgrade to 4GB RAM, but not sure if this will be enough... Thanks! Edit: The database is about 25 GB and the indexes are not setup properly. When I tried to add an index, I let it run for about 8 hours and it still hadn't finished so I gave up. Should I have more patience :)? In general, the queries will run once in a while and its ok even if it takes a couple hours to complete.... Also, the queries will produce probably about 10 million records which I need to process using Stata/Matlab and I'm concerned that my current laptop is not strong enough, but unsure of the bottleneck....

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  • Network connection to Firebird 2.1 became slow after upgrading to Ubuntu 10.04

    - by lyle
    We've got a setup that we're using for different clients : a program connecting to a Firebird server on a local network. So far we mostly used 32bit processors running Ubuntu LTS (recently upgraded to 10.04). Now we introduced servers running on 64bit processors, running Ubuntu 10.04 64bit. Suddenly some queries run slower than they used to. In short: running the query locally works fine on both 64bit and 32bit servers, but when running the same queries over the network the 64bit server is suddenly much slower. We did a few checks with both local and remote connections to both 64bit and 32bit servers, using identical databases and identical queries, running in Flamerobin. Running the query locally takes a negligible amount of time: 0.008s on the 64bit server, 0.014s on the 32bit servers. So the servers themselves are running fine. Running the queries over the network, the 64bit server suddenly needs up to 0.160s to respond, while the 32bit server responds in 0.055s. So the older servers are twice as fast over the network, in spite of the newer servers being twice as fast if run locally. Apart from that the setup is identical. All servers are running the same installation of Ubuntu 10.04, same version of Firebird and so on, the only difference is that some are 64 and some 32bit. Any idea?? I tried to google it, but I couldn't find any complains that Firebird 64bit is slower than Firebird 32bit, except that the Firebird 2.1 change log mentions that there's a new network API which is twice as fast, as soon as the drivers are updated to use it. So I could imagine that the 64bit driver is still using the old API, but that's a bit of a stretch, I guess. Thanx in advance for any replies! :)

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  • Logging hurts MySQL performance - but, why?

    - by jimbo
    I'm quite surprised that I can't see an answer to this anywhere on the site already, nor in the MySQL documentation (section 5.2 seems to have logging otherwise well covered!) If I enable binlogs, I see a small performance hit (subjectively), which is to be expected with a little extra IO -- but when I enable a general query log, I see an enormous performance hit (double the time to run queries, or worse), way in excess of what I see with binlogs. Of course I'm now logging every SELECT as well as every UPDATE/INSERT, but, other daemons record their every request (Apache, Exim) without grinding to a halt. Am I just seeing the effects of being close to a performance "tipping point" when it comes to IO, or is there something fundamentally difficult about logging queries that causes this to happen? I'd love to be able to log all queries to make development easier, but I can't justify the kind of hardware it feels like we'd need to get performance back up with general query logging on. I do, of course, log slow queries, and there's negligible improvement in general usage if I disable this. (All of this is on Ubuntu 10.04 LTS, MySQLd 5.1.49, but research suggests this is a fairly universal issue)

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  • High Load mysql on Debian server stops every day. Why?

    - by Oleg Abrazhaev
    I have Debian server with 32 gb memory. And there is apache2, memcached and nginx on this server. Memory load always on maximum. Only 500m free. Most memory leak do MySql. Apache only 70 clients configured, other services small memory usage. When mysql use all memory it stops. And nothing works, need mysql reboot. Mysql configured use maximum 24 gb memory. I have hight weight InnoDB bases. (400000 rows, 30 gb). And on server multithread daemon, that makes many inserts in this tables, thats why InnoDB. There is my mysql config. [mysqld] # # * Basic Settings # default-time-zone = "+04:00" user = mysql pid-file = /var/run/mysqld/mysqld.pid socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp language = /usr/share/mysql/english skip-external-locking default-time-zone='Europe/Moscow' # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. # # * Fine Tuning # #low_priority_updates = 1 concurrent_insert = ALWAYS wait_timeout = 600 interactive_timeout = 600 #normal key_buffer_size = 2024M #key_buffer_size = 1512M #70% hot cache key_cache_division_limit= 70 #16-32 max_allowed_packet = 32M #1-16M thread_stack = 8M #40-50 thread_cache_size = 50 #orderby groupby sort sort_buffer_size = 64M #same myisam_sort_buffer_size = 400M #temp table creates when group_by tmp_table_size = 3000M #tables in memory max_heap_table_size = 3000M #on disk open_files_limit = 10000 table_cache = 10000 join_buffer_size = 5M # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #myisam_use_mmap = 1 max_connections = 200 thread_concurrency = 8 # # * Query Cache Configuration # #more ignored query_cache_limit = 50M query_cache_size = 210M #on query cache query_cache_type = 1 # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. #log = /var/log/mysql/mysql.log # # Error logging goes to syslog. This is a Debian improvement :) # # Here you can see queries with especially long duration log_slow_queries = /var/log/mysql/mysql-slow.log long_query_time = 1 log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log server-id = 1 log-bin = /var/lib/mysql/mysql-bin #replicate-do-db = gate log-bin-index = /var/lib/mysql/mysql-bin.index log-error = /var/lib/mysql/mysql-bin.err relay-log = /var/lib/mysql/relay-bin relay-log-info-file = /var/lib/mysql/relay-bin.info relay-log-index = /var/lib/mysql/relay-bin.index binlog_do_db = 24avia expire_logs_days = 10 max_binlog_size = 100M read_buffer_size = 4024288 innodb_buffer_pool_size = 5000M innodb_flush_log_at_trx_commit = 2 innodb_thread_concurrency = 8 table_definition_cache = 2000 group_concat_max_len = 16M #binlog_do_db = gate #binlog_ignore_db = include_database_name # # * BerkeleyDB # # Using BerkeleyDB is now discouraged as its support will cease in 5.1.12. #skip-bdb # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # You might want to disable InnoDB to shrink the mysqld process by circa 100MB. #skip-innodb # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 500M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 32M key_buffer_size = 512M # # * NDB Cluster # # See /usr/share/doc/mysql-server-*/README.Debian for more information. # # The following configuration is read by the NDB Data Nodes (ndbd processes) # not from the NDB Management Nodes (ndb_mgmd processes). # # [MYSQL_CLUSTER] # ndb-connectstring=127.0.0.1 # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ Please, help me make it stable. Memory used /etc/mysql # free total used free shared buffers cached Mem: 32930800 32766424 164376 0 139208 23829196 -/+ buffers/cache: 8798020 24132780 Swap: 33553328 44660 33508668 Maybe my problem not in memory, but MySQL stops every day. As you can see, cache memory free 24 gb. Thank to Michael Hampton? for correction. Load overage on server 3.5. Maybe hdd or another problem? Maybe my config not optimal for 30gb InnoDB ? I'm already try mysqltuner and tunung-primer.sh , but they marked all green. Mysqltuner output mysqltuner >> MySQLTuner 1.0.1 - Major Hayden <[email protected]> >> Bug reports, feature requests, and downloads at http://mysqltuner.com/ >> Run with '--help' for additional options and output filtering -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.5.24-9-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: -Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 112G (Tables: 1528) [--] Data in InnoDB tables: 39G (Tables: 340) [--] Data in PERFORMANCE_SCHEMA tables: 0B (Tables: 17) [!!] Total fragmented tables: 344 -------- Performance Metrics ------------------------------------------------- [--] Up for: 8h 18m 33s (14M q [478.333 qps], 259K conn, TX: 9B, RX: 5B) [--] Reads / Writes: 84% / 16% [--] Total buffers: 10.5G global + 81.1M per thread (200 max threads) [OK] Maximum possible memory usage: 26.3G (83% of installed RAM) [OK] Slow queries: 1% (259K/14M) [!!] Highest connection usage: 100% (201/200) [OK] Key buffer size / total MyISAM indexes: 1.5G/5.6G [OK] Key buffer hit rate: 100.0% (6B cached / 1M reads) [OK] Query cache efficiency: 74.3% (8M cached / 11M selects) [OK] Query cache prunes per day: 0 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 247K sorts) [!!] Joins performed without indexes: 106025 [!!] Temporary tables created on disk: 49% (351K on disk / 715K total) [OK] Thread cache hit rate: 99% (249 created / 259K connections) [!!] Table cache hit rate: 15% (2K open / 13K opened) [OK] Open file limit used: 15% (3K/20K) [OK] Table locks acquired immediately: 99% (4M immediate / 4M locks) [!!] InnoDB data size / buffer pool: 39.4G/5.9G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Reduce or eliminate persistent connections to reduce connection usage Adjust your join queries to always utilize indexes Temporary table size is already large - reduce result set size Reduce your SELECT DISTINCT queries without LIMIT clauses Increase table_cache gradually to avoid file descriptor limits Variables to adjust: max_connections (> 200) wait_timeout (< 600) interactive_timeout (< 600) join_buffer_size (> 5.0M, or always use indexes with joins) table_cache (> 10000) innodb_buffer_pool_size (>= 39G) Mysql primer output -- MYSQL PERFORMANCE TUNING PRIMER -- - By: Matthew Montgomery - MySQL Version 5.5.24-9-log x86_64 Uptime = 0 days 8 hrs 20 min 50 sec Avg. qps = 478 Total Questions = 14369568 Threads Connected = 16 Warning: Server has not been running for at least 48hrs. It may not be safe to use these recommendations To find out more information on how each of these runtime variables effects performance visit: http://dev.mysql.com/doc/refman/5.5/en/server-system-variables.html Visit http://www.mysql.com/products/enterprise/advisors.html for info about MySQL's Enterprise Monitoring and Advisory Service SLOW QUERIES The slow query log is enabled. Current long_query_time = 1.000000 sec. You have 260626 out of 14369701 that take longer than 1.000000 sec. to complete Your long_query_time seems to be fine BINARY UPDATE LOG The binary update log is enabled Binlog sync is not enabled, you could loose binlog records during a server crash WORKER THREADS Current thread_cache_size = 50 Current threads_cached = 45 Current threads_per_sec = 0 Historic threads_per_sec = 0 Your thread_cache_size is fine MAX CONNECTIONS Current max_connections = 200 Current threads_connected = 11 Historic max_used_connections = 201 The number of used connections is 100% of the configured maximum. You should raise max_connections INNODB STATUS Current InnoDB index space = 214 M Current InnoDB data space = 39.40 G Current InnoDB buffer pool free = 0 % Current innodb_buffer_pool_size = 5.85 G Depending on how much space your innodb indexes take up it may be safe to increase this value to up to 2 / 3 of total system memory MEMORY USAGE Max Memory Ever Allocated : 23.46 G Configured Max Per-thread Buffers : 15.84 G Configured Max Global Buffers : 7.54 G Configured Max Memory Limit : 23.39 G Physical Memory : 31.40 G Max memory limit seem to be within acceptable norms KEY BUFFER Current MyISAM index space = 5.61 G Current key_buffer_size = 1.47 G Key cache miss rate is 1 : 5578 Key buffer free ratio = 77 % Your key_buffer_size seems to be fine QUERY CACHE Query cache is enabled Current query_cache_size = 200 M Current query_cache_used = 101 M Current query_cache_limit = 50 M Current Query cache Memory fill ratio = 50.59 % Current query_cache_min_res_unit = 4 K MySQL won't cache query results that are larger than query_cache_limit in size SORT OPERATIONS Current sort_buffer_size = 64 M Current read_rnd_buffer_size = 256 K Sort buffer seems to be fine JOINS Current join_buffer_size = 5.00 M You have had 106606 queries where a join could not use an index properly You have had 8 joins without keys that check for key usage after each row join_buffer_size >= 4 M This is not advised You should enable "log-queries-not-using-indexes" Then look for non indexed joins in the slow query log. OPEN FILES LIMIT Current open_files_limit = 20210 files The open_files_limit should typically be set to at least 2x-3x that of table_cache if you have heavy MyISAM usage. Your open_files_limit value seems to be fine TABLE CACHE Current table_open_cache = 10000 tables Current table_definition_cache = 2000 tables You have a total of 1910 tables You have 2151 open tables. The table_cache value seems to be fine TEMP TABLES Current max_heap_table_size = 2.92 G Current tmp_table_size = 2.92 G Of 366426 temp tables, 49% were created on disk Perhaps you should increase your tmp_table_size and/or max_heap_table_size to reduce the number of disk-based temporary tables Note! BLOB and TEXT columns are not allow in memory tables. If you are using these columns raising these values might not impact your ratio of on disk temp tables. TABLE SCANS Current read_buffer_size = 3 M Current table scan ratio = 2846 : 1 read_buffer_size seems to be fine TABLE LOCKING Current Lock Wait ratio = 1 : 185 You may benefit from selective use of InnoDB. If you have long running SELECT's against MyISAM tables and perform frequent updates consider setting 'low_priority_updates=1'

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  • Replicated MongoDB server slower than simple shards

    - by displayName
    I tried to compare the performance of a sharded configuration against a sharded and replicated configuration. The sharded configuration consists of 8 shards each running on three different machines thereby constituting a total of 24 shards. All 8 of these shards run in the same partition on each machine. The sharded and replicated version is 8 shards again just like plain sharding, and all 8 mongods run on the same partition in each machine. But apart from this, each of these three machine now run additional 16 threads on another partition which serve as the secondary for the 8 mongods running on other machines. This is the way I prepared a sharded and replicated configuration with data chunks having replication factor of 3. Important point to note is that once the data has been loaded, it is not modified. So after primary and secondaries have synchronized then it doesn't matter which one i read from. To run the queries, I use an entirely different machine (let's call it config) which runs mongos and this machine's only purpose is to receive queries and run them on the cluster. Contrary to my expectations, plain sharding of 8 threads on each machine (total = 3 * 8 = 24) is performing better for queries than the sharded + replicated configuration. I have a script written to perform the query. So in order to time the scripts, I use time ./testScript and see the result. I tried changing the reading preference for replicated cluster by logging to mongo of config and run db.getMongo().setReadPref('secondary') and then exit the shell and run the queries like time ./testScript. The questions are: Where am i going wrong in the replication? Why is it slower than its plain sharding version? Does the db.getMongo().ReadPref('secondary') persist when i leave the shell and try to perform the query? All the four machines are running Linux and i have already increased the ulimit -n to 2048 from initial value of 1024 to allow more connections. The collections are properly distributed and all the mongods have equal number of chunks. Goes without saying that indices in both configurations are the same.

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  • MySQL query, 2 similar servers, 2 minute difference in execution times

    - by mr12086
    I had a similar question on stack overflow, but it seems to be more server/mysql setup related than coding. The queries below all execute instantly on our development server where as they can take upto 2 minutes 20 seconds. The query execution time seems to be affected by home ambiguous the LIKE string's are. If they closely match a country that has few matches it will take less time, and if you use something like 'ge' for germany - it will take longer to execute. But this doesn't always work out like that, at times its quite erratic. Sending data appears to be the culprit but why and what does that mean. Also memory on production looks to be quite low (free memory)? Production: Intel Quad Xeon E3-1220 3.1GHz 4GB DDR3 2x 1TB SATA in RAID1 Network speed 100Mb Ubuntu Development Intel Core i3-2100, 2C/4T, 3.10GHz 500 GB SATA - No RAID 4GB DDR3 UPDATE 2 : mysqltuner output: [prod] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.61-0ubuntu0.10.04.1 [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 103M (Tables: 180) [--] Data in InnoDB tables: 491M (Tables: 19) [!!] Total fragmented tables: 38 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 77d 4h 6m 1s (53M q [7.968 qps], 14M conn, TX: 87B, RX: 12B) [--] Reads / Writes: 98% / 2% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (12K/53M) [OK] Highest usage of available connections: 22% (34/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/10.6M [OK] Key buffer hit rate: 98.7% (162M cached / 2M reads) [OK] Query cache efficiency: 20.7% (7M cached / 36M selects) [!!] Query cache prunes per day: 3934 [OK] Sorts requiring temporary tables: 1% (3K temp sorts / 230K sorts) [!!] Joins performed without indexes: 71068 [OK] Temporary tables created on disk: 24% (3M on disk / 13M total) [OK] Thread cache hit rate: 99% (690 created / 14M connections) [!!] Table cache hit rate: 0% (64 open / 85M opened) [OK] Open file limit used: 12% (128/1K) [OK] Table locks acquired immediately: 99% (16M immediate / 16M locks) [!!] InnoDB data size / buffer pool: 491.9M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 16M) join_buffer_size (> 128.0K, or always use indexes with joins) table_cache (> 64) innodb_buffer_pool_size (>= 491M) [dev] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.62-0ubuntu0.11.10.1 [!!] Switch to 64-bit OS - MySQL cannot currently use all of your RAM -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 185M (Tables: 632) [--] Data in InnoDB tables: 967M (Tables: 38) [!!] Total fragmented tables: 73 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 1d 2h 26m 9s (5K q [0.058 qps], 1K conn, TX: 4M, RX: 1M) [--] Reads / Writes: 99% / 1% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (0/5K) [OK] Highest usage of available connections: 1% (2/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/18.6M [OK] Key buffer hit rate: 99.9% (60K cached / 36 reads) [OK] Query cache efficiency: 44.5% (1K cached / 2K selects) [OK] Query cache prunes per day: 0 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 44 sorts) [OK] Temporary tables created on disk: 24% (162 on disk / 666 total) [OK] Thread cache hit rate: 99% (2 created / 1K connections) [!!] Table cache hit rate: 1% (64 open / 4K opened) [OK] Open file limit used: 8% (88/1K) [OK] Table locks acquired immediately: 100% (1K immediate / 1K locks) [!!] InnoDB data size / buffer pool: 967.7M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: table_cache (> 64) innodb_buffer_pool_size (>= 967M) UPDATE 1: When testing the queries listed here there is usually no more than one other query taking place, and usually none. Because production is actually handling apache requests that development gets very few of as it's only myself and 1 other who accesses it - could the 4GB of RAM be getting exhausted by using the single machine for both apache and mysql server? Production: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 24872 MB in 2.00 seconds = 12450.72 MB/sec Timing buffered disk reads: 368 MB in 3.00 seconds = 122.49 MB/sec sudo hdparm -tT /dev/sdb /dev/sdb: Timing cached reads: 24786 MB in 2.00 seconds = 12407.22 MB/sec Timing buffered disk reads: 350 MB in 3.00 seconds = 116.53 MB/sec Server version(mysql + ubuntu versions): 5.1.61-0ubuntu0.10.04.1 Development: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 10632 MB in 2.00 seconds = 5319.40 MB/sec Timing buffered disk reads: 400 MB in 3.01 seconds = 132.85 MB/sec Server version(mysql + ubuntu versions): 5.1.62-0ubuntu0.11.10.1 ORIGINAL DATA : This query is NOT the query in question but is related so ill post it. SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' And the explain plan for the above query is, run on both dev and production produce the same plan. +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | 1 | SIMPLE | p2 | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index | | 1 | SIMPLE | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | const | 796 | Using where | | 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using index | | 1 | SIMPLE | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 1 | SIMPLE | f2 | ref | form_project_id | form_project_id | 4 | const | 15 | Using where | | 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ This query takes 2 minutes ~20 seconds to execute. The query that is ACTUALLY being run on the server is this one: SELECT COUNT(*) AS num_results FROM (SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' GROUP BY f.form_question_has_answer_id;) dctrn_count_query; With explain plans (again same on dev and production): +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | 1 | PRIMARY | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | | 2 | DERIVED | p2 | const | PRIMARY | PRIMARY | 4 | | 1 | Using index | | 2 | DERIVED | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | | 797 | Using where | | 2 | DERIVED | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id,project_company_has_user_garbage_collection | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 2 | DERIVED | f2 | ref | form_project_id | form_project_id | 4 | | 15 | Using where | | 2 | DERIVED | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | | 2 | DERIVED | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_user_id | 1 | Using where; Using index | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ On the production server the information I have is as follows. Upon execution: +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (2 min 14.28 sec) Show profile: +--------------------------------+------------+ | Status | Duration | +--------------------------------+------------+ | starting | 0.000016 | | checking query cache for query | 0.000057 | | Opening tables | 0.004388 | | System lock | 0.000003 | | Table lock | 0.000036 | | init | 0.000030 | | optimizing | 0.000016 | | statistics | 0.000111 | | preparing | 0.000022 | | executing | 0.000004 | | Sorting result | 0.000002 | | Sending data | 136.213836 | | end | 0.000007 | | query end | 0.000002 | | freeing items | 0.004273 | | storing result in query cache | 0.000010 | | logging slow query | 0.000001 | | logging slow query | 0.000002 | | cleaning up | 0.000002 | +--------------------------------+------------+ On development the results are as follows. +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (0.08 sec) Again the profile for this query: +--------------------------------+----------+ | Status | Duration | +--------------------------------+----------+ | starting | 0.000022 | | checking query cache for query | 0.000148 | | Opening tables | 0.000025 | | System lock | 0.000008 | | Table lock | 0.000101 | | optimizing | 0.000035 | | statistics | 0.001019 | | preparing | 0.000047 | | executing | 0.000008 | | Sorting result | 0.000005 | | Sending data | 0.086565 | | init | 0.000015 | | optimizing | 0.000006 | | executing | 0.000020 | | end | 0.000004 | | query end | 0.000004 | | freeing items | 0.000028 | | storing result in query cache | 0.000005 | | removing tmp table | 0.000008 | | closing tables | 0.000008 | | logging slow query | 0.000002 | | cleaning up | 0.000005 | +--------------------------------+----------+ If i remove user and/or project innerjoins the query is reduced to 30s. Last bit of information I have: Mysqlserver and Apache are on the same box, there is only one box for production. Production output from top: before & after. top - 15:43:25 up 78 days, 12:11, 4 users, load average: 1.42, 0.99, 0.78 Tasks: 162 total, 2 running, 160 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 50.4%sy, 0.0%ni, 49.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3772580k used, 265288k free, 243704k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207944k cached top - 15:44:31 up 78 days, 12:13, 4 users, load average: 1.94, 1.23, 0.87 Tasks: 160 total, 2 running, 157 sleeping, 0 stopped, 1 zombie Cpu(s): 0.2%us, 50.6%sy, 0.0%ni, 49.3%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3834300k used, 203568k free, 243736k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207804k cached But this isn't a good representation of production's normal status so here is a grab of it from today outside of executing the queries. top - 11:04:58 up 79 days, 7:33, 4 users, load average: 0.39, 0.58, 0.76 Tasks: 156 total, 1 running, 155 sleeping, 0 stopped, 0 zombie Cpu(s): 3.3%us, 2.8%sy, 0.0%ni, 93.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3676136k used, 361732k free, 271480k buffers Swap: 3905528k total, 268736k used, 3636792k free, 1063432k cached Development: This one doesn't change during or after. top - 15:47:07 up 110 days, 22:11, 7 users, load average: 0.17, 0.07, 0.06 Tasks: 210 total, 2 running, 208 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 0.2%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4111972k total, 1821100k used, 2290872k free, 238860k buffers Swap: 4183036k total, 66472k used, 4116564k free, 921072k cached

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  • IPtables - Accept Arbitrary Packets

    - by Asad Moeen
    I've achieved a lot on blocking attacks on GameServers but I'm stuck on something. I've blocked major requests of game-server which it aceepts in the form "\xff\xff\xff\xff" which can be followed by the actual queries like get status or get info to make something like "\xff\xff\xff\xff getstatus " but I see other queries if sent to the game-server will cause it to reply with a "disconnect" packet with the same rate as input so if the input rate is high then the high output of "disconnect" might give lag to the server. Hence I want to block all queries except the ones actual clients use which I suppose are in the form "\xff\xff\xff\xff" or .... so, I tried using this rule : -A INPUT -p udp -m udp -m u32 ! --u32 0x1c=0xffffffff -j ACCEPT -A INPUT -p udp -m udp -m recent --set --name Total --rsource -A INPUT -p udp -m udp -m recent --update --seconds 1 --hitcount 20 --name Total --rsource -j DROP Now where the rule does accept the clients but it only blocks requests in the form "\xff\xff\xff\xff getstatus " ( by which GameServer replies with status ) and not just "getstatus " ( by which GameServer replies with disconnect packet ). So I suppose the accept rule is accepting the simple "string" as well. I actually want it to also block the non-(\xff) queries. So how do I modify the rule?

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  • Inheritance Mapping Strategies with Entity Framework Code First CTP5: Part 3 – Table per Concrete Type (TPC) and Choosing Strategy Guidelines

    - by mortezam
    This is the third (and last) post in a series that explains different approaches to map an inheritance hierarchy with EF Code First. I've described these strategies in previous posts: Part 1 – Table per Hierarchy (TPH) Part 2 – Table per Type (TPT)In today’s blog post I am going to discuss Table per Concrete Type (TPC) which completes the inheritance mapping strategies supported by EF Code First. At the end of this post I will provide some guidelines to choose an inheritance strategy mainly based on what we've learned in this series. TPC and Entity Framework in the Past Table per Concrete type is somehow the simplest approach suggested, yet using TPC with EF is one of those concepts that has not been covered very well so far and I've seen in some resources that it was even discouraged. The reason for that is just because Entity Data Model Designer in VS2010 doesn't support TPC (even though the EF runtime does). That basically means if you are following EF's Database-First or Model-First approaches then configuring TPC requires manually writing XML in the EDMX file which is not considered to be a fun practice. Well, no more. You'll see that with Code First, creating TPC is perfectly possible with fluent API just like other strategies and you don't need to avoid TPC due to the lack of designer support as you would probably do in other EF approaches. Table per Concrete Type (TPC)In Table per Concrete type (aka Table per Concrete class) we use exactly one table for each (nonabstract) class. All properties of a class, including inherited properties, can be mapped to columns of this table, as shown in the following figure: As you can see, the SQL schema is not aware of the inheritance; effectively, we’ve mapped two unrelated tables to a more expressive class structure. If the base class was concrete, then an additional table would be needed to hold instances of that class. I have to emphasize that there is no relationship between the database tables, except for the fact that they share some similar columns. TPC Implementation in Code First Just like the TPT implementation, we need to specify a separate table for each of the subclasses. We also need to tell Code First that we want all of the inherited properties to be mapped as part of this table. In CTP5, there is a new helper method on EntityMappingConfiguration class called MapInheritedProperties that exactly does this for us. Here is the complete object model as well as the fluent API to create a TPC mapping: public abstract class BillingDetail {     public int BillingDetailId { get; set; }     public string Owner { get; set; }     public string Number { get; set; } }          public class BankAccount : BillingDetail {     public string BankName { get; set; }     public string Swift { get; set; } }          public class CreditCard : BillingDetail {     public int CardType { get; set; }     public string ExpiryMonth { get; set; }     public string ExpiryYear { get; set; } }      public class InheritanceMappingContext : DbContext {     public DbSet<BillingDetail> BillingDetails { get; set; }              protected override void OnModelCreating(ModelBuilder modelBuilder)     {         modelBuilder.Entity<BankAccount>().Map(m =>         {             m.MapInheritedProperties();             m.ToTable("BankAccounts");         });         modelBuilder.Entity<CreditCard>().Map(m =>         {             m.MapInheritedProperties();             m.ToTable("CreditCards");         });                 } } The Importance of EntityMappingConfiguration ClassAs a side note, it worth mentioning that EntityMappingConfiguration class turns out to be a key type for inheritance mapping in Code First. Here is an snapshot of this class: namespace System.Data.Entity.ModelConfiguration.Configuration.Mapping {     public class EntityMappingConfiguration<TEntityType> where TEntityType : class     {         public ValueConditionConfiguration Requires(string discriminator);         public void ToTable(string tableName);         public void MapInheritedProperties();     } } As you have seen so far, we used its Requires method to customize TPH. We also used its ToTable method to create a TPT and now we are using its MapInheritedProperties along with ToTable method to create our TPC mapping. TPC Configuration is Not Done Yet!We are not quite done with our TPC configuration and there is more into this story even though the fluent API we saw perfectly created a TPC mapping for us in the database. To see why, let's start working with our object model. For example, the following code creates two new objects of BankAccount and CreditCard types and tries to add them to the database: using (var context = new InheritanceMappingContext()) {     BankAccount bankAccount = new BankAccount();     CreditCard creditCard = new CreditCard() { CardType = 1 };                      context.BillingDetails.Add(bankAccount);     context.BillingDetails.Add(creditCard);     context.SaveChanges(); } Running this code throws an InvalidOperationException with this message: The changes to the database were committed successfully, but an error occurred while updating the object context. The ObjectContext might be in an inconsistent state. Inner exception message: AcceptChanges cannot continue because the object's key values conflict with another object in the ObjectStateManager. Make sure that the key values are unique before calling AcceptChanges. The reason we got this exception is because DbContext.SaveChanges() internally invokes SaveChanges method of its internal ObjectContext. ObjectContext's SaveChanges method on its turn by default calls AcceptAllChanges after it has performed the database modifications. AcceptAllChanges method merely iterates over all entries in ObjectStateManager and invokes AcceptChanges on each of them. Since the entities are in Added state, AcceptChanges method replaces their temporary EntityKey with a regular EntityKey based on the primary key values (i.e. BillingDetailId) that come back from the database and that's where the problem occurs since both the entities have been assigned the same value for their primary key by the database (i.e. on both BillingDetailId = 1) and the problem is that ObjectStateManager cannot track objects of the same type (i.e. BillingDetail) with the same EntityKey value hence it throws. If you take a closer look at the TPC's SQL schema above, you'll see why the database generated the same values for the primary keys: the BillingDetailId column in both BankAccounts and CreditCards table has been marked as identity. How to Solve The Identity Problem in TPC As you saw, using SQL Server’s int identity columns doesn't work very well together with TPC since there will be duplicate entity keys when inserting in subclasses tables with all having the same identity seed. Therefore, to solve this, either a spread seed (where each table has its own initial seed value) will be needed, or a mechanism other than SQL Server’s int identity should be used. Some other RDBMSes have other mechanisms allowing a sequence (identity) to be shared by multiple tables, and something similar can be achieved with GUID keys in SQL Server. While using GUID keys, or int identity keys with different starting seeds will solve the problem but yet another solution would be to completely switch off identity on the primary key property. As a result, we need to take the responsibility of providing unique keys when inserting records to the database. We will go with this solution since it works regardless of which database engine is used. Switching Off Identity in Code First We can switch off identity simply by placing DatabaseGenerated attribute on the primary key property and pass DatabaseGenerationOption.None to its constructor. DatabaseGenerated attribute is a new data annotation which has been added to System.ComponentModel.DataAnnotations namespace in CTP5: public abstract class BillingDetail {     [DatabaseGenerated(DatabaseGenerationOption.None)]     public int BillingDetailId { get; set; }     public string Owner { get; set; }     public string Number { get; set; } } As always, we can achieve the same result by using fluent API, if you prefer that: modelBuilder.Entity<BillingDetail>()             .Property(p => p.BillingDetailId)             .HasDatabaseGenerationOption(DatabaseGenerationOption.None); Working With The Object Model Our TPC mapping is ready and we can try adding new records to the database. But, like I said, now we need to take care of providing unique keys when creating new objects: using (var context = new InheritanceMappingContext()) {     BankAccount bankAccount = new BankAccount()      {          BillingDetailId = 1                          };     CreditCard creditCard = new CreditCard()      {          BillingDetailId = 2,         CardType = 1     };                      context.BillingDetails.Add(bankAccount);     context.BillingDetails.Add(creditCard);     context.SaveChanges(); } Polymorphic Associations with TPC is Problematic The main problem with this approach is that it doesn’t support Polymorphic Associations very well. After all, in the database, associations are represented as foreign key relationships and in TPC, the subclasses are all mapped to different tables so a polymorphic association to their base class (abstract BillingDetail in our example) cannot be represented as a simple foreign key relationship. For example, consider the the domain model we introduced here where User has a polymorphic association with BillingDetail. This would be problematic in our TPC Schema, because if User has a many-to-one relationship with BillingDetail, the Users table would need a single foreign key column, which would have to refer both concrete subclass tables. This isn’t possible with regular foreign key constraints. Schema Evolution with TPC is Complex A further conceptual problem with this mapping strategy is that several different columns, of different tables, share exactly the same semantics. This makes schema evolution more complex. For example, a change to a base class property results in changes to multiple columns. It also makes it much more difficult to implement database integrity constraints that apply to all subclasses. Generated SQLLet's examine SQL output for polymorphic queries in TPC mapping. For example, consider this polymorphic query for all BillingDetails and the resulting SQL statements that being executed in the database: var query = from b in context.BillingDetails select b; Just like the SQL query generated by TPT mapping, the CASE statements that you see in the beginning of the query is merely to ensure columns that are irrelevant for a particular row have NULL values in the returning flattened table. (e.g. BankName for a row that represents a CreditCard type). TPC's SQL Queries are Union Based As you can see in the above screenshot, the first SELECT uses a FROM-clause subquery (which is selected with a red rectangle) to retrieve all instances of BillingDetails from all concrete class tables. The tables are combined with a UNION operator, and a literal (in this case, 0 and 1) is inserted into the intermediate result; (look at the lines highlighted in yellow.) EF reads this to instantiate the correct class given the data from a particular row. A union requires that the queries that are combined, project over the same columns; hence, EF has to pad and fill up nonexistent columns with NULL. This query will really perform well since here we can let the database optimizer find the best execution plan to combine rows from several tables. There is also no Joins involved so it has a better performance than the SQL queries generated by TPT where a Join is required between the base and subclasses tables. Choosing Strategy GuidelinesBefore we get into this discussion, I want to emphasize that there is no one single "best strategy fits all scenarios" exists. As you saw, each of the approaches have their own advantages and drawbacks. Here are some rules of thumb to identify the best strategy in a particular scenario: If you don’t require polymorphic associations or queries, lean toward TPC—in other words, if you never or rarely query for BillingDetails and you have no class that has an association to BillingDetail base class. I recommend TPC (only) for the top level of your class hierarchy, where polymorphism isn’t usually required, and when modification of the base class in the future is unlikely. If you do require polymorphic associations or queries, and subclasses declare relatively few properties (particularly if the main difference between subclasses is in their behavior), lean toward TPH. Your goal is to minimize the number of nullable columns and to convince yourself (and your DBA) that a denormalized schema won’t create problems in the long run. If you do require polymorphic associations or queries, and subclasses declare many properties (subclasses differ mainly by the data they hold), lean toward TPT. Or, depending on the width and depth of your inheritance hierarchy and the possible cost of joins versus unions, use TPC. By default, choose TPH only for simple problems. For more complex cases (or when you’re overruled by a data modeler insisting on the importance of nullability constraints and normalization), you should consider the TPT strategy. But at that point, ask yourself whether it may not be better to remodel inheritance as delegation in the object model (delegation is a way of making composition as powerful for reuse as inheritance). Complex inheritance is often best avoided for all sorts of reasons unrelated to persistence or ORM. EF acts as a buffer between the domain and relational models, but that doesn’t mean you can ignore persistence concerns when designing your classes. SummaryIn this series, we focused on one of the main structural aspect of the object/relational paradigm mismatch which is inheritance and discussed how EF solve this problem as an ORM solution. We learned about the three well-known inheritance mapping strategies and their implementations in EF Code First. Hopefully it gives you a better insight about the mapping of inheritance hierarchies as well as choosing the best strategy for your particular scenario. Happy New Year and Happy Code-Firsting! References ADO.NET team blog Java Persistence with Hibernate book a { color: #5A99FF; } a:visited { color: #5A99FF; } .title { padding-bottom: 5px; font-family: Segoe UI; font-size: 11pt; font-weight: bold; padding-top: 15px; } .code, .typeName { font-family: consolas; } .typeName { color: #2b91af; } .padTop5 { padding-top: 5px; } .padTop10 { padding-top: 10px; } .exception { background-color: #f0f0f0; font-style: italic; padding-bottom: 5px; padding-left: 5px; padding-top: 5px; padding-right: 5px; }

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Troubleshooting High-CPU Utilization for SQL Server

    - by Susantha Bathige
    The objective of this FAQ is to outline the basic steps in troubleshooting high CPU utilization on  a server hosting a SQL Server instance. The first and the most common step if you suspect high CPU utilization (or are alerted for it) is to login to the physical server and check the Windows Task Manager. The Performance tab will show the high utilization as shown below: Next, we need to determine which process is responsible for the high CPU consumption. The Processes tab of the Task Manager will show this information: Note that to see all processes you should select Show processes from all user. In this case, SQL Server (sqlserver.exe) is consuming 99% of the CPU (a normal benchmark for max CPU utilization is about 50-60%). Next we examine the scheduler data. Scheduler is a component of SQLOS which evenly distributes load amongst CPUs. The query below returns the important columns for CPU troubleshooting. Note – if your server is under severe stress and you are unable to login to SSMS, you can use another machine’s SSMS to login to the server through DAC – Dedicated Administrator Connection (see http://msdn.microsoft.com/en-us/library/ms189595.aspx for details on using DAC) SELECT scheduler_id ,cpu_id ,status ,runnable_tasks_count ,active_workers_count ,load_factor ,yield_count FROM sys.dm_os_schedulers WHERE scheduler_id See below for the BOL definitions for the above columns. scheduler_id – ID of the scheduler. All schedulers that are used to run regular queries have ID numbers less than 1048576. Those schedulers that have IDs greater than or equal to 1048576 are used internally by SQL Server, such as the dedicated administrator connection scheduler. cpu_id – ID of the CPU with which this scheduler is associated. status – Indicates the status of the scheduler. runnable_tasks_count – Number of workers, with tasks assigned to them that are waiting to be scheduled on the runnable queue. active_workers_count – Number of workers that are active. An active worker is never preemptive, must have an associated task, and is either running, runnable, or suspended. current_tasks_count - Number of current tasks that are associated with this scheduler. load_factor – Internal value that indicates the perceived load on this scheduler. yield_count – Internal value that is used to indicate progress on this scheduler.                                                                 Now to interpret the above data. There are four schedulers and each assigned to a different CPU. All the CPUs are ready to accept user queries as they all are ONLINE. There are 294 active tasks in the output as per the current_tasks_count column. This count indicates how many activities currently associated with the schedulers. When a  task is complete, this number is decremented. The 294 is quite a high figure and indicates all four schedulers are extremely busy. When a task is enqueued, the load_factor  value is incremented. This value is used to determine whether a new task should be put on this scheduler or another scheduler. The new task will be allocated to less loaded scheduler by SQLOS. The very high value of this column indicates all the schedulers have a high load. There are 268 runnable tasks which mean all these tasks are assigned a worker and waiting to be scheduled on the runnable queue.   The next step is  to identify which queries are demanding a lot of CPU time. The below query is useful for this purpose (note, in its current form,  it only shows the top 10 records). SELECT TOP 10 st.text  ,st.dbid  ,st.objectid  ,qs.total_worker_time  ,qs.last_worker_time  ,qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC This query as total_worker_time as the measure of CPU load and is in descending order of the  total_worker_time to show the most expensive queries and their plans at the top:      Note the BOL definitions for the important columns: total_worker_time - Total amount of CPU time, in microseconds, that was consumed by executions of this plan since it was compiled. last_worker_time - CPU time, in microseconds, that was consumed the last time the plan was executed.   I re-ran the same query again after few seconds and was returned the below output. After few seconds the SP dbo.TestProc1 is shown in fourth place and once again the last_worker_time is the highest. This means the procedure TestProc1 consumes a CPU time continuously each time it executes.      In this case, the primary cause for high CPU utilization was a stored procedure. You can view the execution plan by clicking on query_plan column to investigate why this is causing a high CPU load. I have used SQL Server 2008 (SP1) to test all the queries used in this article.

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  • New Replication, Optimizer and High Availability features in MySQL 5.6.5!

    - by Rob Young
    As the Product Manager for the MySQL database it is always great to announce when the MySQL Engineering team delivers another great product release.  As a field DBA and developer it is even better when that release contains improvements and innovation that I know will help those currently using MySQL for apps that range from modest intranet sites to the most highly trafficked web sites on the web.  That said, it is my pleasure to take my hat off to MySQL Engineering for today's release of the MySQL 5.6.5 Development Milestone Release ("DMR"). The new highlighted features in MySQL 5.6.5 are discussed here: New Self-Healing Replication ClustersThe 5.6.5 DMR improves MySQL Replication by adding Global Transaction Ids and automated utilities for self-healing Replication clusters.  Prior to 5.6.5 this has been somewhat of a pain point for MySQL users with most developing custom solutions or looking to costly, complex third-party solutions for these capabilities.  With 5.6.5 these shackles are all but removed by a solution that is included with the GPL version of the database and supporting GPL tools.  You can learn all about the details of the great, problem solving Replication features in MySQL 5.6 in Mat Keep's Developer Zone article.  New Replication Administration and Failover UtilitiesAs mentioned above, the new Replication features, Global Transaction Ids specifically, are now supported by a set of automated GPL utilities that leverage the new GTIDs to provide administration and manual or auto failover to the most up to date slave (that is the default, but user configurable if needed) in the event of a master failure. The new utilities, along with links to Engineering related blogs, are discussed in detail in the DevZone Article noted above. Better Query Optimization and ThroughputThe MySQL Optimizer team continues to amaze with the latest round of improvements in 5.6.5. Along with much refactoring of the legacy code base, the Optimizer team has improved complex query optimization and throughput by adding these functional improvements: Subquery Optimizations - Subqueries are now included in the Optimizer path for runtime optimization.  Better throughput of nested queries enables application developers to simplify and consolidate multiple queries and result sets into a single unit or work. Optimizer now uses CURRENT_TIMESTAMP as default for DATETIME columns - For simplification, this eliminates the need for application developers to assign this value when a column of this type is blank by default. Optimizations for Range based queries - Optimizer now uses ready statistics vs Index based scans for queries with multiple range values. Optimizations for queries using filesort and ORDER BY.  Optimization criteria/decision on execution method is done now at optimization vs parsing stage. Print EXPLAIN in JSON format for hierarchical readability and Enterprise tool consumption. You can learn the details about these new features as well all of the Optimizer based improvements in MySQL 5.6 by following the Optimizer team blog. You can download and try the MySQL 5.6.5 DMR here. (look under "Development Releases")  Please let us know what you think!  The new HA utilities for Replication Administration and Failover are available as part of the MySQL Workbench Community Edition, which you can download here .Also New in MySQL LabsAs has become our tradition when announcing DMRs we also like to provide "Early Access" development features to the MySQL Community via the MySQL Labs.  Today is no exception as we are also releasing the following to Labs for you to download, try and let us know your thoughts on where we need to improve:InnoDB Online OperationsMySQL 5.6 now provides Online ADD Index, FK Drop and Online Column RENAME.  These operations are non-blocking and will continue to evolve in future DMRs.  You can learn the grainy details by following John Russell's blog.InnoDB data access via Memcached API ("NotOnlySQL") - Improved refresh of an earlier feature releaseSimilar to Cluster 7.2, MySQL 5.6 provides direct NotOnlySQL access to InnoDB data via the familiar Memcached API. This provides the ultimate in flexibility for developers who need fast, simple key/value access and complex query support commingled within their applications.Improved Transactional Performance, ScaleThe InnoDB Engineering team has once again under promised and over delivered in the area of improved performance and scale.  These improvements are also included in the aggregated Spring 2012 labs release:InnoDB CPU cache performance improvements for modern, multi-core/CPU systems show great promise with internal tests showing:    2x throughput improvement for read only activity 6x throughput improvement for SELECT range Read/Write benchmarks are in progress More details on the above are available here. You can download all of the above in an aggregated "InnoDB 2012 Spring Labs Release" binary from the MySQL Labs. You can also learn more about these improvements and about related fixes to mysys mutex and hash sort by checking out the InnoDB team blog.MySQL 5.6.5 is another installment in what we believe will be the best release of the MySQL database ever.  It also serves as a shining example of how the MySQL Engineering team at Oracle leads in MySQL innovation.You can get the overall Oracle message on the MySQL 5.6.5 DMR and Early Access labs features here. As always, thanks for your continued support of MySQL, the #1 open source database on the planet!

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  • MySQL Connect 9 Days Away – Optimizer Sessions

    - by Bertrand Matthelié
    72 1024x768 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Following my previous blog post focusing on InnoDB talks at MySQL Connect, let us review today the sessions focusing on the MySQL Optimizer: Saturday, 11.30 am, Room Golden Gate 6: MySQL Optimizer Overview—Olav Sanstå, Oracle The goal of MySQL optimizer is to take a SQL query as input and produce an optimal execution plan for the query. This session presents an overview of the main phases of the MySQL optimizer and the primary optimizations done to the query. These optimizations are based on a combination of logical transformations and cost-based decisions. Examples of optimization strategies the presentation covers are the main query transformations, the join optimizer, the data access selection strategies, and the range optimizer. For the cost-based optimizations, an overview of the cost model and the data used for doing the cost estimations is included. Saturday, 1.00 pm, Room Golden Gate 6: Overview of New Optimizer Features in MySQL 5.6—Manyi Lu, Oracle Many optimizer features have been added into MySQL 5.6. This session provides an introduction to these great features. Multirange read, index condition pushdown, and batched key access will yield huge performance improvements on large data volumes. Structured explain, explain for update/delete/insert, and optimizer tracing will help users analyze and speed up queries. And last but not least, the session covers subquery optimizations in Release 5.6. Saturday, 7.00 pm, Room Golden Gate 4: BoF: Query Optimizations: What Is New and What Is Coming? This BoF presents common techniques for query optimization, covers what is new in MySQL 5.6, and provides a discussion forum in which attendees can tell the MySQL optimizer team which optimizations they would like to see in the future. Sunday, 1.15 pm, Room Golden Gate 8: Query Performance Comparison of MySQL 5.5 and MySQL 5.6—Øystein Grøvlen, Oracle MySQL Release 5.6 contains several improvements in the query optimizer that create improved performance for complex queries. This presentation looks at how MySQL 5.6 improves the performance of many of the queries in the DBT-3 benchmark. Based on the observed improvements, the presentation discusses what makes the specific queries perform better in Release 5.6. It describes the relevant new optimization techniques and gives examples of the types of queries that will benefit from these techniques. Sunday, 4.15 pm, Room Golden Gate 4: Powerful EXPLAIN in MySQL 5.6—Evgeny Potemkin, Oracle The EXPLAIN command of MySQL has long been a very useful tool for understanding how MySQL will execute a query. Release 5.6 of the MySQL database offers several new additions that give more-detailed information about the query plan and make it easier to understand at the same time. This presentation gives an overview of new EXPLAIN features: structured EXPLAIN in JSON format, EXPLAIN for INSERT/UPDATE/DELETE, and optimizer tracing. Examples in the session give insights into how you can take advantage of the new features. They show how these features supplement and relate to each other and to classical EXPLAIN and how and why the MySQL server chooses a particular query plan. You can check out the full program here as well as in the September edition of the MySQL newsletter. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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  • Some notes on Reflector 7

    - by CliveT
    Both Bart and I have blogged about some of the changes that we (and other members of the team) have made to .NET Reflector for version 7, including the new tabbed browsing model, the inclusion of Jason Haley's PowerCommands add-in and some improvements to decompilation such as handling iterator blocks. The intention of this blog post is to cover all of the main new features in one place, and to describe the three new editions of .NET Reflector 7. If you'd simply like to try out the latest version of the beta for yourself you can do so here. Three new editions .NET Reflector 7 will come in three new editions: .NET Reflector .NET Reflector VS .NET Reflector VSPro The first edition is just the standalone Windows application. The latter two editions include the Windows application, but also add the power of Reflector into Visual Studio so that you can save time switching tools and quickly get to the bottom of a debugging issue that involves third-party code. Let's take a look at some of the new features in each edition. Tabbed browsing .NET Reflector now has a tabbed browsing model, in which the individual tabs have independent histories. You can open a new tab to view the selected object by using CTRL+CLICK. I've found this really useful when I'm investigating a particular piece of code but then want to focus on some other methods that I find along the way. For version 7, we wanted to implement the basic idea of tabs to see whether it is something that users will find helpful. If it is something that enhances productivity, we will add more tab-based features in a future version. PowerCommands add-in We have also included Jason Haley's PowerCommands add-in as part of version 7. This add-in provides a number of useful commands, including support for opening .xap files and extracting the constituent assemblies, and a query editor that allows C# queries to be written and executed against the Reflector object model . All of the PowerCommands features can be turned on from the options menu. We will be really interested to see what people are finding useful for further integration into the main tool in the future. My personal favourite part of the PowerCommands add-in is the query editor. You can set up as many of your own queries as you like, but we provide 25 to get you started. These do useful things like listing all extension methods in a given assembly, and displaying other lower-level information, such as the number of times that a given method uses the box IL instruction. These queries can be extracted and then executed from the 'Run Query' context menu within the assembly explorer. Moreover, the queries can be loaded, modified, and saved using the built-in editor, allowing very specific user customization and sharing of queries. The PowerCommands add-in contains many other useful utilities. For example, you can open an item using an external application, work with enumeration bit flags, or generate assembly binding redirect files. You can see Bart's earlier post for a more complete list. .NET Reflector VS .NET Reflector VS adds a brand new Reflector object browser into Visual Studio to save you time opening .NET Reflector separately and browsing for an object. A 'Decompile and Explore' option is also added to the context menu of references in the Solution Explorer, so you don't need to leave Visual Studio to look through decompiled code. We've also added some simple navigation features to allow you to move through the decompiled code as quickly and easily as you can in .NET Reflector. When this is selected, the add-in decompiles the given assembly, Once the decompilation has finished, a clone of the Reflector assembly explorer can be used inside Visual Studio. When Reflector generates the source code, it records the location information. You can therefore navigate from the source file to other decompiled source using the 'Go To Definition' context menu item. This then takes you to the definition in another decompiled assembly. .NET Reflector VSPro .NET Reflector VSPro builds on the features in .NET Reflector VS to add the ability to debug any source code you decompile. When you decompile with .NET Reflector VSPro, a matching .pdb is generated, so you can use Visual Studio to debug the source code as if it were part of the project. You can now use all the standard debugging techniques that you are used to in the Visual Studio debugger, and step through decompiled code as if it were your own. Again, you can select assemblies for decompilation. They are then decompiled. And then you can debug as if they were one of your own source code files. The future of .NET Reflector As I have mentioned throughout this post, most of the new features in version 7 are exploratory steps and we will be watching feedback closely. Although we don't want to speculate now about any other new features or bugs that will or won't be fixed in the next few versions of .NET Reflector, Bart has mentioned in a previous post that there are lots of improvements we intend to make. We plan to do this with great care and without taking anything away from the simplicity of the core product. User experience is something that we pride ourselves on at Red Gate, and it is clear that Reflector is still a long way off our usual standards. We plan for the next few versions of Reflector to be worked on by some of our top usability specialists who have been involved with our other market-leading products such as the ANTS Profilers and SQL Compare. I re-iterate the need for the really great simple mode in .NET Reflector to remain intact regardless of any other improvements we are planning to make. I really hope that you enjoy using some of the new features in version 7 and that Reflector continues to be your favourite .NET development tool for a long time to come.

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  • Just quick: How do you call a mutator from within a constructor in the same class?

    - by Blockhead
    For a homework assignment the instructions state (within Undergrad class): You do NOT need to include a default constructor, but you must write a full parameterized constructor (it takes 4 arguments) -- this constructor calls the parent class parameterized constructor and the mutator for year level. Because Undergrad extends Student, then Student is my parent class, right? I just can't quite figure out how I'm to use my year level mutator (which is just the simplest of methods) to assign my "year" attribute. public void setYear(int inYear) { year = inYear; } public Student(String inName, String inID, int inCredits) { name = inName; id = inID; credits = inCredits; } public Undergrad(String inName, String inID, int inCredits,int inYear) { super(inName, inID, inCredits); year = inYear; } I keep missing assignments because I spend too much time on these small specific points of the homework so just asking for a little help. I swear it's the wording that throws me off on these assignments almost as often as just learning the material itself.

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  • Postgres 9.0 locking up, 100% CPU

    - by Jake
    We are having a problem where our Postgres 9.0 server occasionally locks up and kills our webapp. Restarting Postgres fixes the problem. Here's what I've been able to observe: First, usage of one CPU jumps to 100% for a few minutes Disk operations drop to ~0 during this time Database operations drop to 0 (blocks and tuples per sec) Logs show during this time: WARNING: worker took too long to start; cancelled WARNING: worker took too long to start; cancelled No Queries in logs (only those over 200ms are logged) No unusually long-running queries logged before or during Then the second CPU jumps to 100% The number of postgres processes jumps from the usual 8-10 to ~20 Matched by a spike in Postgres Blocks per second (about twice normal) Logs show LOG: could not accept SSL connection: EOF detected Queries are running but slow Restarting postgres returns everything to normal Setup: Server: Amazon EC2 Large Ubuntu 10.04.2 LTS Postgres 9.0.3 Dedicated DB server Does anyone have any idea what's causing this? Or any suggestions about what else I should be checking out?

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  • How can I access a method of the consumer class inside a method created at runtime in a method of th

    - by xxxxxxx
    I define a method inside a parametrized role that needs to create a new class at run time using Moose::Meta::Class->create and apply that exact parametrized role to it. I am also making a new method for that role using $new_class->meta->add_method( some_name => sub { my ($self) = @_; ... }) inside the sub {...} I want to access a method of the consumer class and use it for something, I have tried using $self->get_method, it didn't work, how do I do this? Please notice that the $self inside the sub above is MooseX::Role::Parameterized::Meta::Role::Parameterizable I also have another question, if I do this: my $object = Moose::Meta::Class->create( "some_type", ); Why isn't $object of type some_type and it's some ugly MooseX::Role::Parameterized::Meta::Role::Parameterizable and how do I get to the object of type some_type?

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  • How can I grant read-only access to my SQL Server 2008 database?

    - by Adrian Grigore
    Hi, I'm trying to grant read-only access (in other words: select queries only) to a user account on my SQL Server 2008 R2 database. Which rights do I have to grant to the user to make this work? I've tried several kinds of combinations of permissions on the server and the database itself, but in all cases the user could still run update queries or he could not run any queries (not even select) at all. The error message I always got was The server principal "foo" is not able to access the database "bar" under the current security context. Thanks for your help, Adrian

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  • Caching DNS server (bind9.2) CPU usage is so so so high.

    - by Gk
    Hi, I have a caching-only dns server which get ~3k queries per second. Here is specs: Xeon dual-core 2,8GHz 4GB of RAM Centos 5x (kernel 2.6.18-164.15.1.el5PAE) bind 9.4.2 rndc status: recursive clients: 666/4900/5000 About 300 new queries (not in cache) per second. Bind always uses 100% on one core on single-thread config. After I recompiled it to multi-thread, it uses nearly 200% on two core :( No iowait, only sys and user. I searched around but didn't see any info about how bind use CPU. Why does it become bottleneck? One more thing, here is RAM usage: cat /proc/meminfo MemTotal: 4147876 kB MemFree: 1863972 kB Buffers: 143632 kB Cached: 372792 kB SwapCached: 0 kB Active: 1916804 kB Inactive: 276056 kB I've set max-cache-size to 0 to make sure bind can use as much RAM as it want, but it always stop at ~2GB. Since every second we got not cached queries so theoretically RAM must be exhausted but it wasn't. Do you have any idea? TIA, -Gk

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  • Linq2SQL vs NHibernate performance (have I gone mad?)

    - by HeavyWave
    I have written the following tests to compare performance of Linq2SQL and NHibernate and I find results to be somewhat strange. Mappings are straight forward and identical for both. Both are running against a live DB. Although I'm not deleting Campaigns in case of Linq, but that shouldn't affect performance by more than 10 ms. Linq: [Test] public void Test1000ReadsWritesToAgentStateLinqPrecompiled() { Stopwatch sw = new Stopwatch(); Stopwatch swIn = new Stopwatch(); sw.Start(); for (int i = 0; i < 1000; i++) { swIn.Reset(); swIn.Start(); ReadWriteAndDeleteAgentStateWithLinqPrecompiled(); swIn.Stop(); Console.WriteLine("Run ReadWriteAndDeleteAgentState: " + swIn.ElapsedMilliseconds + " ms"); } sw.Stop(); Console.WriteLine("Total Time: " + sw.ElapsedMilliseconds + " ms"); Console.WriteLine("Average time to execute queries: " + sw.ElapsedMilliseconds / 1000 + " ms"); } private static readonly Func<AgentDesktop3DataContext, int, EntityModel.CampaignDetail> GetCampaignById = CompiledQuery.Compile<AgentDesktop3DataContext, int, EntityModel.CampaignDetail>( (ctx, sessionId) => (from cd in ctx.CampaignDetails join a in ctx.AgentCampaigns on cd.CampaignDetailId equals a.CampaignDetailId where a.AgentStateId == sessionId select cd).FirstOrDefault()); private void ReadWriteAndDeleteAgentStateWithLinqPrecompiled() { int id = 0; using (var ctx = new AgentDesktop3DataContext()) { EntityModel.AgentState agentState = new EntityModel.AgentState(); var campaign = new EntityModel.CampaignDetail { CampaignName = "Test" }; var campaignDisposition = new EntityModel.CampaignDisposition { Code = "123" }; campaignDisposition.Description = "abc"; campaign.CampaignDispositions.Add(campaignDisposition); agentState.CallState = 3; campaign.AgentCampaigns.Add(new AgentCampaign { AgentState = agentState }); ctx.CampaignDetails.InsertOnSubmit(campaign); ctx.AgentStates.InsertOnSubmit(agentState); ctx.SubmitChanges(); id = agentState.AgentStateId; } using (var ctx = new AgentDesktop3DataContext()) { var dbAgentState = ctx.GetAgentStateById(id); Assert.IsNotNull(dbAgentState); Assert.AreEqual(dbAgentState.CallState, 3); var campaignDetails = GetCampaignById(ctx, id); Assert.AreEqual(campaignDetails.CampaignDispositions[0].Description, "abc"); } using (var ctx = new AgentDesktop3DataContext()) { ctx.DeleteSessionById(id); } } NHibernate (the loop is the same): private void ReadWriteAndDeleteAgentState() { var id = WriteAgentState().Id; StartNewTransaction(); var dbAgentState = agentStateRepository.Get(id); Assert.IsNotNull(dbAgentState); Assert.AreEqual(dbAgentState.CallState, 3); Assert.AreEqual(dbAgentState.Campaigns[0].Dispositions[0].Description, "abc"); var campaignId = dbAgentState.Campaigns[0].Id; agentStateRepository.Delete(dbAgentState); NHibernateSession.Current.Transaction.Commit(); Cleanup(campaignId); NHibernateSession.Current.BeginTransaction(); } Results: NHibernate: Total Time: 9469 ms Average time to execute 13 queries: 9 ms Linq: Total Time: 127200 ms Average time to execute 13 queries: 127 ms Linq lost by 13.5 times! Event with precompiled queries (both read queries are precompiled). This can't be right, although I expected NHibernate to be faster, this is just too big of a difference, considering mappings are identical and NHibernate actually executes more queries against the DB.

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  • How to automatically insert a class notation using eclipse templates?

    - by João Paulo G. Piccinini
    Does anybody know how to insert a "@RunWith anotation" above the class signature, using eclipse templates? Ex.: @RunWith(Parameterized.class) public class MyClassTest { ... @Parameters public static Collection<Object[]> parameters() { List<Object[]> list = new ArrayList<Object[]>(); list.add(new Object[] { "mind!", "find!" }); list.add(new Object[] { "misunderstood", "understood" }); return list; } ... } __ Template: // TODO: move this '@RunWith(Parameterized.class)' to class anotation @Parameters public static Collection<Object[]> parameters() { ${type:elemType(collection)}<Object[]> parametersList = new ${type:elemType(collection)}<Object[]>(); ${cursor}// TODO: populate collection return parametersList; } __ Thanks for the help!

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  • Oracle: show parameters on error

    - by llappall
    When Oracle logs a parameterized SQL query failing, it shows "?" in place of the parameters, i.e. the query before replacing parameters. For example, "SELECT * FROM table where col like '?'" SQL state [99999]; error code [29902]; ORA-29902: error in executing ODCIIndexStart() routine ORA-20000: Oracle Text error: DRG-50901: text query parser syntax error on line 1, column 48 Is there a way to change logging so it shows the parameter values? The information above is absolutely useless unless I can see what the actual parsing problem was. In general, is there a way to set logs in Oracle to show parameters in parameterized query errors?

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  • master-slave-slave replication: master will become bottleneck for writes

    - by JMW
    hi, the mysql database has arround 2TB of data. i have a master-slave-slave replication running. the application that uses the database does read (SELECT) queries just on one of the 2 slaves and write (DELETE/INSERT/UPDATE) queries on the master. the application does way more reads, than writes. if we have a problem with the read (SELECT) queries, we can just add another slave database and tell the application, that there is another salve. so it scales well... Currently, the master is running arround 40% disk io due to the writes. So i'm thinking about how to scale the the database in the future. Because one day the master will be overloaded. What could be a solution there? maybe mysql cluster? if so, are there any pitfalls or limitations in switching the database to ndb? thanks a lot in advance... :)

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  • In SQL Server merge replication, how does reinitializing work?

    - by Craig Shearer
    I have set up a pull subscription to a merge publication in SQL Server. I use parameterized row filters on some tables. This works fine with the initial synchronization - just the rows using the filter arrive in the replicated (client) database. However, at some later point I'd like to be able to synchronize the replicated database again from the server and have new rows that match the parameterized row filters appear on the client database. The doucmentation seems to indicate that I can call Reinitialize() to do this. However, when I do try this and Synchronize again, I get an error saying that the script 'snapshot.pre' cannot be applied to the database. I've inspected the script and can see why - it's trying to drop some functions are used by the tables in the database. It would appear that for Reinitialize() to work it requires that the database be blank. Am I misunderstanding something here? Is there a way to make this work?

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