[B! sql] n-segaã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

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sqlã«é–¢ã™ã‚‹n-segaã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (84)

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è«–ç†å‰Šé™¤ Casual Talks #1 ã§ã€Œè«–ç†å‰Šé™¤ã—ãªã„ã€ã¨ã„ã†è©±ã‚’ã—ã¾ã—ãŸ - moroã®ãƒ–ãƒã‚°
äº’ã„ã®å‰è·ã§ã®å…ˆè¼©å¾Œè¼©ã§ã‚ã‚‹ @kenchan ã¨ä¼ç”»ã—ãŸè«–ç†å‰Šé™¤ Casual Talks #1ã§ã€ã€Œè«–ç†å‰Šé™¤ã—ãªã„ã€ã¨ã„ã†è©±ã‚’ã—ã¦ãã¾ã—ãŸã€‚ è©±ã™å†…å®¹ãŒå„è©±è€…ã§é¢ç™½ã„ã»ã©ã‹ã¶ã£ã¦ã„ãŸã®ã§ãªã‹ãªã‹å¤§å¤‰ã§ã—ãŸãŒã€æ™®æ®µã‹ã‚‰è¨€ã£ã¦ã„ã‚‹ã€Œè«–ç†å‰Šé™¤ã™ã‚‹ãªã€ã€Œå‰Šé™¤ã˜ã‚ƒãªã„ã‹ã‚‰ã¡ã‚ƒã‚“ã¨æ©Ÿèƒ½ã‚’è¨è¨ˆã—ã¾ã—ã‚‡ã†ã€ã¨ã„ã†å†…å®¹ã‚’è©±ã—ã¦ãã¾ã—ãŸã€‚ ä»–ã®æ–¹ã®è©±ã‚‚ã€ã‹ã¶ã£ã¦ã„ã‚‹ã‚ˆã†ã§æ–°ã—ã„è¦–ç‚¹ã‚‚ã‚ã£ã¦ã€ã„ã¡å‚åŠ è€…ã¨ã—ã¦ã‚‚ãŸã„ã¸ã‚“å‹‰å¼·ã«ãªã‚Šã¾ã—ãŸã€‚
n-sega 2015/09/01
database

sql
ãƒªãƒ³ã‚¯
SQLã‚¢ãƒ³ãƒãƒ‘ã‚¿ãƒ¼ãƒ³ å¹»ã®ç¬¬26ç« ã€Œã¨ã‚Šã‚ãˆãšå‰Šé™¤ãƒ•ãƒ©ã‚°ã€
SQLã‚¢ãƒ³ãƒãƒ‘ã‚¿ãƒ¼ãƒ³ 26ç« ã€Œã¨ã‚Šã‚ãˆãšå‰Šé™¤ãƒ•ãƒ©ã‚°ã€ 2015/08/31 @ GMO Yours #ronsakucasual https://atnd.org/events/68902Read less
n-sega 2015/09/01
database

sql
ãƒªãƒ³ã‚¯
Postgres vs Mongo
This table shows us which companies the experts have worked at and in which capacity, however the addresses refer to the company rather then the expert or their specialty, this violates 3NF. Put simply, this can be rem embered as "Everything must provide a fact about the key, the whole key, and nothing but the key, so help me Codd". (Codd being the scientist who coined these forms.) Now at this poi
n-sega 2015/08/30
postgresql

mongodb

sql

nosql
ãƒªãƒ³ã‚¯
Breaking the SQL Barrier: Google BigQuery User-Defined Functions- Google Developers Blog
Share Facebook Twitter LinkedIn Mail Posted by, Thomas Park, Senior Software Engineer, Google BigQuery Many types of computations can be difficult or impossible to express in SQL. Loops, complex conditionals, and non-trivial string parsing or transf ormations are all common examples. What can you do when you need to perform these operations but your data lives in a SQL-based Big data tool? Is it po
n-sega 2015/08/26
google

sql

bigquery
ãƒªãƒ³ã‚¯
Tuning SQL LIKE using indexes
The SQL LIKE operator very often causes unexpected performance behavior because some search terms prevent efficient index usage. That means that there are search terms that can be indexed very well, but others can not. It is the position of the wild card characters that makes all the difference. The following example uses the % wild card in the middle of the search term: SELECT first_name, last_na
n-sega 2015/08/20
sql

tuning

performance

database
ãƒªãƒ³ã‚¯
SQL unleashed: 7 SQL mistakes to avoid
SQL is a convenient way to manage and query your data, but badly written queries can tie up your database. Here are seven common SQL traps and how to avoid them. Database developers have it tough. Whether they use SQL Server, Oracle, DB2, MySQL, PostgreSQL, or SQLite, the challenges are similar. Itâ€™s too easy to write queries that perform badly, that waste system resources, or that donâ€™t take adva
n-sega 2015/08/20
sql

tuning

performance

database
ãƒªãƒ³ã‚¯
SQL Database Performance Tuning for Developers | ToptalÂ®
n-sega 2015/08/20
sql

tuning

performance
ãƒªãƒ³ã‚¯
Performance Tuning for SQL Server
Youâ€™re a developer, DBA, or sysadmin stuck with long running queries in SQL Server, and you need to do SQL Server performance tuning. I can help! Iâ€™m a consultant, and I do this for a living. I donâ€™t keep anything secret â€“ Iâ€™ll tell you how you can get started, or if you prefer, you can hire me for help, whicheverâ€™s easier. Here are the basic steps: Measure how fast the server is going now. Perfor
n-sega 2015/08/20
sql

sqlserver
ãƒªãƒ³ã‚¯
SQL Tutorial For Beginners | 1Keydata
SQL (Structured Query Language) is a computer language aimed to store, manipulate, and query data stored in relational databases. The first incarnation of SQL appeared in 1974, when a group in IBM developed the first prototype of a relational database. The first commercial relational database was released by Relational Software (later becoming Oracle). Standards for SQL exist. However, the SQL tha
n-sega 2015/08/20
database

sql
ãƒªãƒ³ã‚¯
ã€ŒSQLãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹è©³è§£ã€ã¨ã„ã†æœ¬ã‚’ç¿»è¨³ã—ã¾ã—ãŸ | b.l0g.jp
ã€ŒSQLãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹è©³è§£ã€ã¨ã„ã†æœ¬ã‚’ç¿»è¨³ã—ã¾ã—ãŸ 2015-04-07 é¡Œã®é€šã‚Šã€ã€ŒSQLãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹è©³è§£ã€(åŽŸæ–‡ã‚¿ã‚¤ãƒˆãƒ«SQL Performance Explained)ã¨ã„ã†æœ¬ã‚’ç¿»è¨³ã—ã¾ã—ãŸã€‚PDFç‰ˆã¨å°åˆ·ç‰ˆãŒä¸Šè¨˜ã‚µã‚¤ãƒˆã‹ã‚‰è³¼å…¥ã§ãã¾ã™ã€‚ (è¿½è¨˜ 2017å¹´9æœˆã‹ã‚‰ã€æ¸‹è°·ã®BOOK LAB TOKYOã•ã‚“ã§ã‚‚å°åˆ·ç‰ˆã‚’è²©å£²ã—ã¦ã„ãŸã ã„ã¦ã„ã¾ã™ã€‚è¼¸é€ã‚³ã‚¹ãƒˆã®é–¢ä¿‚ã§ã€ã‚µã‚¤ãƒˆã‹ã‚‰è³¼å…¥ã™ã‚‹ã‚ˆã‚Šè‹¥å¹²å®‰ããªã£ã¦ã„ã¾ã™) ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«ãŠã„ã¦ã€SQLã¨ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ãŒã©ã®ã‚ˆã†ã«é–¢é€£ã—ã€ã©ã®ã‚ˆã†ã«ã™ã‚Œã°SQLã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚’è‰¯ãã§ãã‚‹ã®ã‹ã‚’è§£èª¬ã—ãŸæœ¬ã§ã™ã€‚ç‰¹å®šã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹è£½å“ã«ç„¦ç‚¹ã‚’å½“ã¦ãŸæœ¬ã¯å¤šæ•°ã‚ã‚Šã¾ã™ãŒã€ã“ã®æœ¬ã§ã¯Oracle Databaseã€PostgreSQLã€MySQLã€SQL Serverã®4ã¤ã®ãƒ¡ã‚¸ãƒ£ãƒ¼ãªãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹è£½å“ã‚’åŒæ™‚ã«æ‰±ã£ã¦ã„ã¦ã€ãã‚Œãžã‚Œã®ã‚¯
n-sega 2015/04/08
sql

performance

database

book
ãƒªãƒ³ã‚¯
æ–°è‘—ãŒå‡ºã¾ã™ï¼šã€ŽSQLå®Ÿè·µå…¥é–€ã€ - ãƒŸãƒƒã‚¯ã®ãƒ–ãƒã‚°
4æœˆä¸æ—¬ã“ã‚ã«ãªã‚Šã¾ã™ãŒã€æ–°è‘—ãŒå‡ºã¾ã™ã€‚SQLã®ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚’ä¸»é¡Œã«ã—ãŸæœ¬ã§ã€å®Ÿè¡Œè¨ˆç”»ã‚’èªã‚€ã“ã¨ã§ã€ãªãœã“ã®SQLã¯é…ã„ã®ã‹ã€ã‚ã‚‹ã„ã¯é€Ÿã„ã®ã‹ã‚’ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã®å†…éƒ¨å‹•ä½œã¾ã§æŠŠæ¡ã—ã¦ç†è§£ã—ã‚ˆã†ã€ã¨ã„ã†è¶£æ—¨ã§ã™ã€‚ ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã¨ã„ã†ã®ã¯ã€SQLã¨ã„ã†è‡ªç„¶è¨€èªžã‚’æ¨¡ã—ãŸã‚¤ãƒ³ã‚¿ãƒ•ã‚§ãƒ¼ã‚¹ã«ã‚ˆã£ã¦ã€ä½Žæ¬¡ã®ãƒ¬ã‚¤ãƒ¤ãƒ¼ã‚’éš è”½ã™ã‚‹æ„å›³ã§ä½œã‚‰ã‚ŒãŸãƒŸãƒ‰ãƒ«ã‚¦ã‚§ã‚¢ãªã®ã§ã€æœ¬å½“ã¯å®Ÿè¡Œè¨ˆç”»ãªã©ã¨ã„ã†æ‰‹ç¶šãƒ¬ãƒ™ãƒ«ã®ä¸–ç•Œã‚’ãƒ¦ãƒ¼ã‚¶ãŒè¦—ãè¦‹ã‚‹ã®ã¯ã€æœ¬æœ«è»¢å€’ãªã¨ã“ã‚ã‚‚ã‚ã‚Šã¾ã™ã€‚ãŸã ãã†ã¯ã„ã£ã¦ã‚‚ã€ç¾å®Ÿã«SQLãŒé…ã‹ã£ãŸã‚‰åŽŸå› ã‚’è§£æžã›ã–ã‚‹ã‚’ãˆãªã„ã‚ã‘ã ã—ã€å¤§ä½“æœ¬å½“ã«ãƒ–ãƒ©ãƒƒã‚¯ãƒœãƒƒã‚¯ã‚¹ã«ã—ãŸã„ãªã‚‰ã€ãªã‚“ã§ã©ã®DBMSã‚‚å®Ÿè¡Œè¨ˆç”»ã‚’è¦‹ã‚‰ã‚Œã‚‹æ‰‹æ®µãªã‚“ã‹ç”¨æ„ã—ã¦ã‚‹ã‚“ã§ã—ã‚‡ã†ãä¸æ€è°ã§ã™ãã€ã¨ã„ã†ç†æƒ³ã¨ç¾å®Ÿã®ç‹é–“ã§æ‚©ã‚€ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã®æ–¹ã€…ã«å°‘ã—ã§ã‚‚ãƒ™ã‚¿ãƒ¼ãªè§£ã«è¾¿ã‚Šã¤ã‘ã‚‹ã‚¢ãƒ—ãƒãƒ¼ãƒã‚’æç¤ºã§ãã‚Œã°ã€ã¨è€ƒãˆã¦ãŠã‚Šã¾ã™ã€‚ ä»¥ä¸‹ã¾ãˆãŒãã¨ç« ç«‹ã¦ã§ã™ã€‚
n-sega 2015/03/29
sql

database
ãƒªãƒ³ã‚¯
Modern SQL in PostgreSQL
SQL has gone out of fashion latelyâ€”partly due to the NoSQL movement, but mostly because SQL is often still used like 20 years ago. As a matter of fact, the SQL standard continued to evolve during the past decades resulting in the current release of 2016. In this session, we will go through the most important additions since the widely known SQL-92. We will cover common table expressions and window
n-sega 2015/02/10
postgresql

sql
ãƒªãƒ³ã‚¯
PostgreSQLã§å„ãƒ†ãƒ¼ãƒ–ãƒ«ã®ç·ã‚µã‚¤ã‚ºã¨å¹³å‡ã‚µã‚¤ã‚ºã‚’çŸ¥ã‚‹ - Qiita
DBã‚’ä½¿ã£ã¦ã„ã‚‹æ™‚ã€ã©ã®ãƒ†ãƒ¼ãƒ–ãƒ«ãŒã©ã®ãã‚‰ã„å®¹é‡ã‚’é£Ÿã£ã¦ã„ã‚‹ã‹çŸ¥ã‚ŠãŸã„ã“ã¨ãŒã‚ã‚‹ã¨æ€ã†ã€‚ ã¾ãŸä»Šå¾Œã®ã‚µã‚¤ã‚ºå¢—åŠ ã‚’è¦‹ç©ã‚‚ã‚ŠãŸã„ã¨ãã€ã‚ã‚‹ãƒ†ãƒ¼ãƒ–ãƒ«ã®1è¡Œã‚ãŸã‚Šã®å¹³å‡ãƒã‚¤ãƒˆã‚µã‚¤ã‚ºã‚‚çŸ¥ã‚ŠãŸã„ã¯ãšï¼ PostgreSQLã§è¦‹ã‚‹ã¹ãã¨ã“ã‚ pg_classã®ãƒ†ãƒ¼ãƒ–ãƒ«ã® relpagesãŒãƒ–ãƒãƒƒã‚¯æ•° reltuplesãŒè¡Œæ•° ã‚’è¡¨ã™ã‚‰ã—ã„ã€‚ ã“ã‚Œã‚‰ã¯å®Ÿéš›ã«ã¯ãƒ—ãƒ©ãƒ³ãƒŠãŒç”¨ã„ã‚‹æŽ¨æ¸¬å€¤ã€‚ANALYZEã‚³ãƒžãƒ³ãƒ‰ã‚’æ‰“ã¤ã¨ã“ã‚Œã‚‰ã®çµ±è¨ˆæƒ…å ±ãŒæ›´æ–°ã•ã‚Œã‚‹ã®ã§ã€ANALYZEç›´å¾Œã«ã‚„ã‚‹ã»ã†ãŒæ£ç¢ºã€‚ã¾ãå¤§æŠµã€æ¦‚ç®—ãŒçŸ¥ã‚ŠãŸã„ã ã‘ãªã®ã§ã‚ã¾ã‚Šæ°—ã«ã™ã‚‹å¿…è¦ãªã„ã‹ã‚‚ã—ã‚Œãªã„ãŒã€‚ ãƒ–ãƒãƒƒã‚¯ã‚µã‚¤ã‚ºã¯8K(SHOW block_size;ã§ç¢ºèªå¯èƒ½)ãªã®ã§ relpages / 128Mbytesã®ã‚µã‚¤ã‚ºã‚’å é ˜ã—ã¦ã„ã‚‹ã¨ã„ã†ã“ã¨ã€‚ å¹³å‡ã‚µã‚¤ã‚ºã¯ã€ãƒã‚¤ãƒˆæ•°ã§çŸ¥ã‚ŠãŸã„ã®ã§relpages * 8192 / reltuplesã™ã‚Œã°è‰¯ã„ã€‚0å‰²
n-sega 2015/01/01
postgresql

sql
ãƒªãƒ³ã‚¯
[PostgreSQL]Explain Analyzeã§ã€å¤šé‡JOINã—ãŸSQLã‚’ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ã™ã‚‹ Â· DQNEOæ—¥è¨˜
Sec Scanã®ãªã„SQLã‚’ã©ã†ã‚„ã£ã¦é«˜é€ŸåŒ–ã™ã‚‹ã®ã‹ æœ¬å½“ã«é›£ã—ã„ã®ã¯ã“ã“ã‹ã‚‰ã€‚ ä¾‹ãˆã°ã€Explain Analyzeã®çµæžœãŒä¸‹è¨˜ã®ã‚ˆã†ãªã‚‚ã®ã ã£ãŸã‚‰ã€ã©ã†ã—ã¾ã™ã‹ï¼Ÿ ã©ã“ã«ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ãŒã‚ã‚‹ã‹ã€ã‚ã‹ã‚Šã¾ã™ã‹ï¼Ÿ QUERY PLAN ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Sort (cost=1568.27..1568.51 rows=96 width=260) (actual time=822.175..822.259 rows=
n-sega 2014/12/25
sql

performance

tuning

postgresql
ãƒªãƒ³ã‚¯
ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªã®åˆ†æž â€” Let's Postgres
NTT ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã‚»ãƒ³ã‚¿ æ¿åž£ è²´è£• ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒª (æ™‚é–“ã®ã‹ã‹ã‚‹SQL) ã‚’ç™ºè¦‹ã™ã‚‹ã¾ã§ã®æ‰‹é †ã‚’è§£èª¬ã—ã¾ã™ã€‚ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªåˆ†æžã¨æ”¹å–„ã¯ä»¥ä¸‹ã®æµã‚Œã§è¡Œã†ã“ã¨ã«ãªã‚Šã¾ã™ã€‚ã“ã®è¨˜äº‹ã§ã¯ä¸»ã« 1. ã®ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªã®ç‰¹å®šæ–¹æ³•ã«ã¤ã„ã¦è§£èª¬ã—ã¾ã™ã€‚2.ã«ã¤ã„ã¦ã¯ã€Žã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªã®æ”¹å–„ã€ã‚’å‚è€ƒã«ã—ã¦ãã ã•ã„ã€‚ ã©ã®SQLãŒé…ã„ã®ã‹ã‚’è¦‹ã¤ã‘ã‚‹ã€‚ ãã®SQLãŒãªãœæ™‚é–“ãŒã‹ã‹ã‚‹ã®ã‹ã‚’åˆ¤æ–ã™ã‚‹ã€‚ è¨å®šãƒ‘ãƒ©ãƒ¡ãƒ¼ã‚¿ã€SQLã€ã‚¹ã‚ãƒ¼ãƒžãªã©ã‚’æ”¹å–„ã™ã‚‹ã€‚ ç€ç›®ã—ãŸSQLã®æ€§èƒ½ã‚’å†æ¸¬å®šã—ã€2. ã‹ã‚‰ç¹°ã‚Šè¿”ã™ã€‚ ç€ç›®ã—ãŸSQLã®ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°ãŒå®Œäº†ã—ãŸã‚‰ã€ä»–ã®ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã‚’æŽ¢ã™ãŸã‚ 1. ã‹ã‚‰ç¹°ã‚Šè¿”ã™ã€‚ ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªã®è¦‹ã¤ã‘æ–¹ ã‚¹ãƒãƒ¼ã‚¯ã‚¨ãƒªã‚’è¦‹ã¤ã‘ã‚‹ã«ã¯ã€å¤§ããåˆ†ã‘ã¦çµ±è¨ˆæƒ…å ±ãƒ“ãƒ¥ãƒ¼ã‚’ä½¿ã†æ–¹æ³•ã¨ã€ã‚µãƒ¼ãƒãƒã‚°ã‚’ä½¿ã†æ–¹æ³•ã®2ã¤ãŒã‚ã‚Šã¾ã™ã€‚çµ±è¨ˆæƒ…å ±ãƒ“ãƒ¥ãƒ¼ã‚’ä½¿ã†æ–¹æ³•ã¯ PostgreSQL 8.4 ä»¥é™ã§ã—ã‹åˆ©ç”¨ã§ãã¾ã›ã‚“ãŒ
n-sega 2014/08/14
postgresql

performance

sql

tuning
ãƒªãƒ³ã‚¯
ã€ŒRDBMSè§£å‰–å¦ã€ã®ã¾ã¨ã‚ï¼ˆå‰åŠï¼‰: Akito's ITæŠ€è¡“ ãƒ¡ãƒ¢
n-sega 2014/07/19
rdbms

sql
ãƒªãƒ³ã‚¯
SQL vs NoSQL: what about other issues than ACID and scalibility? - Ask Use The Index, Luke!
n-sega 2014/07/17
sql

rdbms

nosql
ãƒªãƒ³ã‚¯
SQL Fiddle - Online SQL Compiler for learning & practice
During Phase 1, only users who are logged in can access the AI chat feature. SQL Fiddle is free to use and ad-free! Want to help us? It takes 10 seconds Step 1: Like & Share our EFE Bulk Extensions videos Step 2: Like & Share our EFE Bulk Insert videos Thank During Phase 1, only users who are logged in can access the AI Editor feature. SQL Fiddle is free to use and ad-free! Want to help us? It tak
n-sega 2014/07/17
database

sql

study
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n-sega 2014/07/14
database

sql
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n-sega 2014/07/05
sql

visualization
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