[B! PostgreSQL] tom__boã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

tom__bo id:tom__bo

PostgreSQLã«é–¢ã™ã‚‹tom__boã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (100)

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PostgreSQL ã®è¦šãˆæ›¸ãã®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹
PostgreSQL ã®å†…éƒ¨æ§‹é€ ã®è§£èª¬ åŸºæœ¬ãƒ‡ãƒ¼ã‚¿åž‹ã¨ã‚¿ãƒ—ãƒ«ã®æ‰±ã„ ãƒ†ãƒ¼ãƒ–ãƒ«ã¨ãƒ–ãƒãƒƒã‚¯ã®ãƒ‡ãƒ¼ã‚¿æ§‹é€ ãƒ¡ãƒ¢ãƒªç®¡ç†é–¢æ•°ã®è§£èª¬ æŽ’ä»–åˆ¶å¾¡ã®æ¦‚è¦ ãƒ—ãƒ©ãƒ³ãƒ„ãƒªãƒ¼ã®æ¦‚è¦ ãƒ—ãƒ©ãƒ³æœ€é©åŒ–ã®è§£èª¬ ã‚¯ã‚¨ãƒªãƒ¼å®Ÿè¡Œã®è§£èª¬ ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ & MVCC & ã‚¹ãƒŠãƒƒãƒ—ã‚·ãƒ§ãƒƒãƒˆã®ä»•çµ„ã¿ ã‚¨ã‚¯ã‚¹ãƒ†ãƒ³ã‚·ãƒ§ãƒ³ã®é–‹ç™ºæ–¹æ³• ã‚¨ã‚¯ã‚¹ãƒ†ãƒ³ã‚·ãƒ§ãƒ³ã®ä½œæˆæ–¹æ³•(Makefileã€ãƒ†ã‚¹ãƒˆã€ãƒªã‚°ãƒ¬ãƒƒã‚·ãƒ§ãƒ³) é›†åˆã‚’è¿”ã™ãƒ¦ãƒ¼ã‚¶ãƒ¼å®šç¾©é–¢æ•°ã®æ›¸ãæ–¹ ãƒãƒƒã‚¯ã‚°ãƒ©ã‚¦ãƒ³ãƒ‰ãƒ¯ãƒ¼ã‚«ãƒ¼(Background Worker)ã®ä½¿ã„æ–¹ å¤–éƒ¨ãƒ‡ãƒ¼ã‚¿ãƒ©ãƒƒãƒ‘ãƒ¼(Foreign Data Wrapper)ã‚’ä½œæˆã™ã‚‹ ã‚«ã‚¹ã‚¿ãƒ ã‚¹ã‚ãƒ£ãƒ³(Custom Scan)ã‚’ä½œæˆã™ã‚‹ ç‹¬è‡ªã®æ‰‹ç¶šãè¨€èªžã‚’ä½œæˆã™ã‚‹ ç‹¬è‡ªã®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ã‚’ä½œæˆã™ã‚‹ ã‚³ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ã‚¹ã‚¿ã‚¤ãƒ«
tom__bo 2018/03/28
postgresql
ãƒªãƒ³ã‚¯
GitBook
Forget building your own custom docs platform. With GitBook you get beautiful documentation for your users, and a branch-based Git workflow for your team.
tom__bo 2017/11/29
postgresql

internals
ãƒªãƒ³ã‚¯
é€²æ—ï¼‰SSD-to-GPU ãƒ€ã‚¤ãƒ¬ã‚¯ãƒˆSQLå®Ÿè¡Œæ©Ÿèƒ½ - KaiGaiã®ä¿ºãƒ¡ãƒ¢
ã“ã“æš«ããƒ–ãƒã‚°ã§ã¾ã¨ã‚ã¦ã„ãªã‹ã£ãŸã€SSD-to-GPUãƒ€ã‚¤ãƒ¬ã‚¯ãƒˆSQLå®Ÿè¡Œæ©Ÿèƒ½ã®é€²æ—ã«ã¤ã„ã¦ã€‚ ã“ã®æ©Ÿèƒ½ã‚’ã‹ã„ã¤ã¾ã‚“ã§è¨€ã†ã¨ã€NVMe-SSDã«æ ¼ç´ã•ã‚Œã¦ã„ã‚‹PostgreSQLã®ãƒ‡ãƒ¼ã‚¿ãƒ–ãƒãƒƒã‚¯ã‚’GPU RAMã«ç›´æŽ¥è»¢é€ã—ã€ãã“ã§SQLã®WHEREå¥/JOIN/GROUP BYã‚’å®Ÿè¡Œã™ã‚‹ã“ã¨ã§è¦‹ã‹ã‘ä¸Šã®I/Oé‡ã‚’å‰Šæ¸›ã™ã‚‹ã¨ã„ã†ä»£ç‰©ã§ã‚ã‚‹ã€‚ NVIDIAã®Tesla/Quadro GPUãŒå¯¾å¿œã™ã‚‹GPUDirect RDMAæ©Ÿèƒ½ã‚’ä½¿ã„ã€SSD<=>GPUé–“ã®ãƒ‡ãƒ¼ã‚¿è»¢é€ã‚’ä»²ä»‹ã™ã‚‹Linux kernel moduleã‚’ä½¿ãˆã°ã€CPU/RAMã«ãƒ‡ãƒ¼ã‚¿ã‚’ãƒãƒ¼ãƒ‰ã™ã‚‹å‰ã«GPUä¸Šã§ã®å‡¦ç†ã‚’è¡Œã†ã“ã¨ãŒã§ãã‚‹ã€‚ ã—ã°ã‚‰ãå‰ã‹ã‚‰Scanç³»ã®å‡¦ç†ã«ã¯å¯¾å¿œã—ã¦ã„ãŸãŒã€JOIN/GROUP BYã¸ã®å¯¾å¿œã‚’åŠ ãˆã€ã•ã‚‰ã«PostgreSQL v9.6ã®CPUä¸¦åˆ—ã«ã‚‚è¿½å¾“ã—ãŸã¨ã„ã†ã“ã¨ã§ã€ç°¡å˜ãªãƒ™ãƒ³ãƒãƒžãƒ¼ã‚¯ãªã‚‰å–ã‚Œã‚‹
tom__bo 2017/10/10
GPU

PostgreSQL
ãƒªãƒ³ã‚¯
PostgreSQL performance on EXT4 and XFS | PostgreSQL Addict
In case you haven't noticed, the schedule for pgconf.eu 2015 was published a few days ago. One of my talks is called PostgreSQL Performance on EXT4, XFS, F2FS, BTRFS and ZFS and aims to compare PostgreSQL performance of modern Linux file systems (and also impact of various tuning options like write barriers, discard etc.). It's not an entirely new talk - it's a reworked (and significantly improved
tom__bo 2017/09/22
performance

postgresql
ãƒªãƒ³ã‚¯
ç¬¬25å›žã€€MySQLã®å…¬å¼Dockerã‚¤ãƒ¡ãƒ¼ã‚¸ã®ã”ç´¹ä»‹ã€PostgreSQL9.6.4ã¨PostgreSQL10ãƒ™ãƒ¼ã‚¿3ãƒªãƒªãƒ¼ã‚¹ | gihyo.jp
OSSãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å–ã‚Šå–ã‚Šæ™‚å ± ç¬¬25å›žMySQLã®å…¬å¼Dockerã‚¤ãƒ¡ãƒ¼ã‚¸ã®ã”ç´¹ä»‹â â ã€PostgreSQL9.6.4ã¨PostgreSQL10ãƒ™ãƒ¼ã‚¿3ãƒªãƒªãƒ¼ã‚¹ MySQLã®å…¬å¼Dockerã‚¤ãƒ¡ãƒ¼ã‚¸ã‚’ã”ç´¹ä»‹ã—ã¾ã™ã€‚PostgreSQLã¯ã‚»ã‚ãƒ¥ãƒªãƒ†ã‚£ã‚¢ãƒƒãƒ—ãƒ‡ãƒ¼ãƒˆã§ã‚ã‚‹PostgreSQL9.6.4ã¨ã€æ¬¡æœŸãƒ¡ã‚¸ãƒ£ãƒ¼ãƒªãƒªãƒ¼ã‚¹ã«å‘ã‘ãŸPostgreSQL 10ãƒ™ãƒ¼ã‚¿3ãŒãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã¾ã—ãŸã€‚ ï¼»MySQLï¼½2017å¹´8æœˆã®ä¸»ãªå‡ºæ¥äº‹ 7æœˆã«ã‚³ãƒŸãƒ¥ãƒ‹ãƒ†ã‚£ç‰ˆã®ç¾è¡Œè£½å“ã¯ã»ã¼å…¨ã¦ã®è£½å“ã§ãƒžã‚¤ãƒŠãƒ¼ãƒªãƒªãƒ¼ã‚¹ãŒè¡Œã‚ã‚ŒãŸãŸã‚ã€8æœˆã¯Pythonç”¨æŽ¥ç¶šéƒ¨å“Connector/Python 2.1.7ã¨.Netç”¨ã®Connector/Net 6.10.3ãƒªãƒªãƒ¼ã‚¹å€™è£œç‰ˆï¼ˆRCï¼‰ã®ã¿ã®ãƒªãƒªãƒ¼ã‚¹ã¨ãªã‚Šã¾ã—ãŸã€‚ãªãŠConnector/Net 6.10ã¯Entity Framework ï¼ˆâ EFâ ï¼‰â Core 1.1å¯¾å¿œã‚’
tom__bo 2017/09/09
PostgreSQL

MySQL
ãƒªãƒ³ã‚¯
PostgreSQLã¨MySQLã€ä½¿ã†ãªã‚‰ã©ã£ã¡ï¼Ÿ ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å°‚é–€å®¶ãŒ8ã¤ã®è¦–ç‚¹ã§å¾¹åº•æ¯”è¼ƒï¼ï½œãƒã‚¤ã‚¯ãƒ©ã‚¹è»¢è·ãƒ»æ±‚äººæƒ…å ±ã‚µã‚¤ãƒˆ AMBIï¼ˆã‚¢ãƒ³ãƒ“ï¼‰
PostgreSQLã¨MySQLã€ä½¿ã†ãªã‚‰ã©ã£ã¡ï¼ŸÂ ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å°‚é–€å®¶ãŒ8ã¤ã®è¦–ç‚¹ã§å¾¹åº•æ¯”è¼ƒï¼ ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã¨ã—ã¦ã‚ˆãæ¯”è¼ƒã•ã‚Œã‚‹PostgreSQLã¨MySQLã€‚ã©ã‚“ãªé•·æ‰€ãƒ»çŸæ‰€ãŒã‚ã‚‹ã®ã§ã—ã‚‡ã†ï¼ŸÂ ãã‚Œãžã‚Œã®å°‚é–€å®¶ã«ã‚ˆã‚‹å¯¾è«‡ã§æ˜Žã‚‰ã‹ã«ã—ã¾ã™ã€‚ ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã¨ã—ã¦åƒã„ã¦ã„ã‚‹ã¨å¿…ãšç›´é¢ã™ã‚‹æ‚©ã¿ã€‚ãã‚Œã¯ã€ã€Œã©ã®ãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãƒ»ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ï¼ˆä»¥ä¸‹ã€RDBï¼‰ã‚’é¸ã¶ã®ãŒæœ€å–„ãªã®ã‹ï¼Ÿã€ã§ã™ã€‚ RDBã”ã¨ã«é•·æ‰€ã¨çŸæ‰€ã¯ç•°ãªã£ã¦ã„ã¾ã™ã€‚ãã®ãŸã‚è‡ªç¤¾ã‚µãƒ¼ãƒ“ã‚¹ã«ãƒžãƒƒãƒã—ãªã„RDBã‚’é¸ã‚“ã§ã—ã¾ã†ã¨ã€ãã‚ŒãŒãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã¨ãªã‚Šé–‹ç™ºãƒ»é‹ç”¨ã«ãƒˆãƒ©ãƒ–ãƒ«ãŒç”Ÿã˜ã‚‹ã‚±ãƒ¼ã‚¹ã¯å°‘ãªãã‚ã‚Šã¾ã›ã‚“ã€‚ ãªã‹ã§ã‚‚ã‚ˆãæ¯”è¼ƒæ¤œè¨Žã•ã‚Œã‚‹ã®ãŒã€PostgreSQLã¨MySQLã€‚ã¨ã‚‚ã«ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹RDBã®ãƒ‡ãƒ•ã‚¡ã‚¯ãƒˆã‚¹ã‚¿ãƒ³ãƒ€ãƒ¼ãƒ‰ã§ã‚ã‚Šã€é«˜ã„æ€§èƒ½ã¨æ•°å¤šãã®æ©Ÿèƒ½ã‚’æŒã£ã¦ã„ã¾ã™ã€‚ ã§ã¯ã€ä¸¡è€…ã¯å…·ä½“çš„ã«ã©ã®ã‚ˆã†ãªé•·æ‰€ãƒ»çŸæ‰€ãŒã‚ã‚‹ã®ã§ã—ã‚‡ã†ã‹ã€‚ã
tom__bo 2017/09/05
postgresql

MySQL

DB

RDB
ãƒªãƒ³ã‚¯
http://www.interdb.jp/pg/
tom__bo 2017/07/09
postgresql
ãƒªãƒ³ã‚¯
When Boring is Awesome: Building a scalable time-series database on PostgreSQL
PostgreSQL, but faster. Built for lightning-fast ingest and querying of time-based data. Timeseries and analytics
tom__bo 2017/04/05
PostgreSQL
ãƒªãƒ³ã‚¯
RethinkDBã¨PostgreSQLã®æ¯”è¼ƒ:ç§ã®å€‹äººçš„ãªçµŒé¨“ã‚ˆã‚Š â€“ å‰ç·¨ | POSTD
å°Žå…¥ æœ€åˆã¯ RethinkDBç¤¾ã®æ¥å‹™åœæ¢ ã¨ RethinkDBã®ãƒ©ã‚¤ã‚»ãƒ³ã‚¹ã®çŠ¶æ³ï¼ˆç§ã®ä»•äº‹ã®ã‚ã‚‹éƒ¨åˆ†ã‚’é˜»å®³ã™ã‚‹ã‚‚ã®ï¼‰ ãŒç™ºç«¯ã¨ãªã‚Šã€ Hacker Newsã§ã®ã“ã®ãƒ‡ã‚£ã‚¹ã‚«ãƒƒã‚·ãƒ§ãƒ³ ã«è§¦ç™ºã•ã‚ŒãŸã“ã¨ã§ã€RethinkDBã®ä»£ã‚ã‚Šã«PostgreSQLã‚’ä½¿ã„SageMathCloud(SMC)ã®ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã¨ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚³ãƒ³ãƒãƒ¼ãƒãƒ³ãƒˆã‚’å…¨é¢çš„ã«æ›¸ãç›´ã™ãŸã‚ã«ã€2ã‚«æœˆé–“å¿…æ»ã«åƒãã¾ã—ãŸã€‚2015å¹´3æœˆã‹ã‚‰RethinkDBã‚’è‘›è—¤ã—ãªãŒã‚‰ã‚‚å¤§ã„ã«ä½¿ç”¨ã—ã¦ã„ã¾ã—ãŸãŒã€PostgreSQLã‚‚åŒæ§˜ã«æ´»ç”¨ã—ã¦ã„ã¾ã™ã€‚æœ¬ç•ªãƒ‡ãƒ¼ã‚¿ã‚’ä½¿ã„ä¸¡ã‚·ã‚¹ãƒ†ãƒ ã§åŒã˜ã‚¯ã‚¨ãƒªã‚’å…¨ã¦æ›¸ãç›´ã—ã¦ã„ã‚‹ã®ã§ã€ç§ã¯è‡ªåˆ†ã®ä½¿ã„æ–¹ã®ã‚±ãƒ¼ã‚¹ï¼ˆSMCã®ã‚µã‚¤ãƒˆï¼‰ã‚’æ¯”è¼ƒã™ã‚‹ã®ã«ã¡ã‚‡ã†ã©è‰¯ã„ç«‹å ´ã«ã„ã‚‹ã‚ã‘ã§ã™ã€‚ ã“ã‚Œã‹ã‚‰è©±ã™ã®ã¯ç§ã®çµŒé¨“ã§ã™ã€‚â€ãƒ™ãƒ³ãƒãƒžãƒ¼ã‚¯â€ã‚„å†ç¾å¯èƒ½ãªãƒãƒ¼ãƒ‰ãƒ‡ãƒ¼ã‚¿ãªã©ã‚’å«ã¾ãªã„å€‹äººçš„ãªæ¯”è¼ƒã§ã™ã€‚è¨€ã†ãªã‚Œã°ã€ä¼‘æ†©æ‰€ã«ã„ã‚‹æ™‚ã«è©±
tom__bo 2017/03/31
RethinkDB

postgresql

DB
ãƒªãƒ³ã‚¯
Data EgretDeep dive into postgres stats: Introduction - Data Egret
This bl ogpost is all about postgres activity stats. Stats are the very important since they allow us to understand whatâ€™s going on with the system. With that in mind, stats also have some weak points and thatâ€™s what I would like to discuss here. In these blog series I will try to explain how to use stats effectively and how to detect and solve probl ems with their help. I will start with an overvie
tom__bo 2017/02/27
postgresql
ãƒªãƒ³ã‚¯
https://dalibo.org/_media/understanding_explain.pdf
tom__bo 2016/07/22
postgresql

explain
ãƒªãƒ³ã‚¯
ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã‚’æ´»ç”¨ã—ã‚ˆã†(2) â€” Let's Postgres
NTT ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã‚»ãƒ³ã‚¿ ç¬ åŽŸ è¾°ä» ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã‚’å–å¾—ã—ã¦ã¿ã‚ˆã† ã§ã¯ã€å®Ÿéš›ã«ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã‚’å–å¾—ã—ã¦ã¿ã¾ã—ã‚‡ã†ã€‚ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã¯ã€PostgreSQLã®ãƒ†ãƒ¼ãƒ–ãƒ«ã‚„ãƒ“ãƒ¥ãƒ¼ã®å½¢ã§æä¾›ã•ã‚Œã¦ã„ã¾ã™ã€‚pg_stat_* ã¨ã„ã†åç§°ã®ãƒ†ãƒ¼ãƒ–ãƒ«/ãƒ“ãƒ¥ãƒ¼ãŒãã‚Œã‚‰ã«å½“ãŸã‚Šã¾ã™ã€‚ãã®ãŸã‚ã€å–å¾—ã«ã¯SQLã‚’ç”¨ã„ã¾ã™ã€‚ãªãŠã€psqlã®\dã‚³ãƒžãƒ³ãƒ‰ãªã©ã§pg_stat_*ã®ãƒ“ãƒ¥ãƒ¼å®šç¾©ã‚’è¦‹ã¦ã¿ã‚‹ã¨ã€pg_stat_get_*() é–¢æ•°ã§å„ç¨®æƒ…å ±ãŒå–å¾—ã•ã‚Œã¦ã„ã‚‹ã“ã¨ãŒåˆ†ã‹ã‚‹ã¨æ€ã„ã¾ã™ã€‚ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã‚’ç›´æŽ¥å–å¾—ã™ã‚‹ã«ã¯é–¢æ•°ã‚’ä½¿ã†ã®ã§ã™ãŒã€ãã‚Œã‚’ãƒ“ãƒ¥ãƒ¼çµŒç”±ã§ãƒ¦ãƒ¼ã‚¶ãŒé–²è¦§ã§ãã‚‹ã‚ˆã†ã«ãªã£ã¦ã„ã¾ã™ã€‚æœ¬é …ã§ã¯ã€pg_stat_*ã§æä¾›ã•ã‚Œã¦ã„ã‚‹ãƒ“ãƒ¥ãƒ¼ã‚’èªã¿è§£ã„ã¦ã„ãã“ã¨ã«ã—ã¾ã™ã€‚ ãã‚Œã§ã¯ã€å‰ãƒšãƒ¼ã‚¸ã®å†’é ã§ç´¹ä»‹ã—ãŸæƒ…å ±ã«ã¤ã„ã¦å…·ä½“çš„ã«è§£èª¬ã—ã¦ã„ãã¾ã™ã€‚ä¸‹è¨˜ã¯ç¨¼å‹•çµ±è¨ˆæƒ…å ±ã®ä¸ã§ã‚‚å¤šç”¨ã•ã‚Œã‚‹æƒ…å ±ã§ã™ã®ã§ã€è¦šãˆã¦ãŠãã¨
tom__bo 2016/07/19
postgresql

tuning
ãƒªãƒ³ã‚¯
ã‚¢ã‚¤ãƒ•ãƒ« ç”³è¾¼ã¿å…¥ãƒ
è³ƒè²¸ä½å®…ä½ã¾ã„ã€ç‹¬èº«ã®æ–¹ã€æ‰€å¾—ã‚‚ä½Žé¡ã¨ã„ã†çŠ¶æ…‹ã§ã‚‚å¹´åŽã®ï¼“åˆ†ã®ï¼‘ã‚ˆã‚Šå°‘ãªã„é‡‘é¡ã‚’å¸Œæœ›ã™ã‚‹ãªã‚‰ã°ã€å¯©æŸ»ã§OKã¨ãªã‚‹ã“ã¨ã‚‚æœŸå¾…ã•ã‚Œã‚‹ã¨è¨€ã£ã¦ã‚ˆã„ã¨æ€ã„ã¾ã™ã€‚ é•·ã„äººç”Ÿã®ä¸ã«ãŠã„ã¦ã¯ã€ã©ã‚“ãªäººã§ã‚‚æ€ã„ãŒã‘ãšã€å¾…ã£ãŸãªã—ã§ã‚ãƒ£ãƒƒã‚·ãƒ¥ãŒå…¥ç”¨ã«ãªã‚‹ã“ã¨ãŒã‚ã‚‹ã§ã—ã‚‡ã†ã€‚ã“ã†ã„ã£ãŸæ™‚ã«ã¯ã€å³æ—¥èžè³‡ã«å¯¾å¿œã—ã¦ã„ã‚‹ã‚ãƒ£ãƒƒã‚·ãƒ³ã‚°ãŒéžå¸¸ã«å½¹ã«ç«‹ã¤ã¨æ€ã„ã¾ã™ã€‚ ã€ŒéŠ€è¡Œã§ç”³è«‹ã™ã‚‹ã‚«ãƒ¼ãƒ‰ãƒãƒ¼ãƒ³ã€ã¯ãŸã¾ãŸä¿¡è²©ç³»ã®è²¸ä»˜ã‚µãƒ¼ãƒ“ã‚¹ã¨ã„ã†ã®ã¯ã€å®Ÿéš›ã®ã¨ã“ã‚å¯©æŸ»ã«æ™‚é–“ã‚’ã‹ã‘ã‚‹ã®ã§ã¯ãªã„ã‹ï¼Ÿï¼½ã¨å¿ƒé…ã—ã¦ã„ã‚‹ã‹ã‚‚ã—ã‚Œã¾ã›ã‚“ãŒã€ã“ã“æœ€è¿‘ã§ã¯å³æ—¥èžè³‡ã‚’å®Ÿæ–½ã—ã¦ã„ã‚‹é‡‘èžæ¥è€…ã‚‚æ¬¡ç¬¬ã«å¤šããªã£ã¦ã„ã‚‹ã¨ã®ã“ã¨ã§ã™ã€‚ ã©ã‚“ãªå†…å®¹ã®ãƒãƒ¼ãƒ³ã‚’çµ„ã‚€ã¨ã—ã¾ã—ã¦ã‚‚ã€ä¸‡ãŒä¸€ã‚ãƒ£ãƒƒã‚·ãƒ³ã‚°ã«ã‚ˆã£ã¦ãŠé‡‘ã‚’å€Ÿã‚Šã¦ã„ã‚‹çŠ¶æ³ãªã‚‰ã€ãƒãƒ¼ãƒ³åˆ©ç”¨ã«ã‚ˆã‚‹å€Ÿå…¥é‡‘ã¯ç¸®æ¸›ã•ã‚Œã‚‹ã“ã¨ã¯è€ƒãˆã‚‰ã‚Œã‚‹ã§ã—ã‚‡ã†ã€‚ çµ¦æ–™æ—¥ãŒæ¥ã‚‹ã¾ã§ã€æ•°æ—¥é–“åŠ©ã‘ã¦è²°ãˆã‚‹ã®ãŒã‚ãƒ£ãƒƒã‚·ãƒ³ã‚°ã§ã¯ãªã„ã§ã—ã‚‡ã†ã‹ï¼Ÿç·Šæ€¥ã®æ™‚ã
tom__bo 2016/06/24
postgresql
ãƒªãƒ³ã‚¯
Introducing pg_query: Parse PostgreSQL queries in Ruby Â· pganalyze
tom__bo 2016/06/24
parse query

postgresql
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Query Parsing - PostgreSQL wiki
There are quite a few use cases where it'd be of great help if you could access the query tree Postgres uses internally for processing queries. For example, when you need to do non-trivial operations on queries, like: Filtering out queries containing specific tables Reformatting & pretty-printing query strings Modifying or removing parts of the query string, e.g. rename a column The Postgres docum
tom__bo 2016/06/24
query parse

postgresql
ãƒªãƒ³ã‚¯
postgres_fdwã§ç•°ãƒãƒ¼ã‚¸ãƒ§ãƒ³æŽ¥ç¶š/å¤–éƒ¨è¡¨ã®ã‚«ã‚¹ã‚±ãƒ¼ãƒ‰ - æ—¥ã€…ã®è¨˜éŒ² åˆ¥é¤¨
PostgreSQL 9.6/9.5ã®postgres_fdwã®å·®ç•°ã‚’èª¿ã¹ã¦ã„ã¦ã€ãµã¨æ°—ã«ãªã£ãŸã“ã¨ã‚’èª¿ã¹ã¦ã¿ãŸã€‚ ç•°ãƒãƒ¼ã‚¸ãƒ§ãƒ³é–“ã§FDW PostgreSQL 9.6/9.5ã®postgres_fdwã®å·®ç•°ã‚’èª¿ã¹ã¦ã„ã¦ã€ãµã¨æ°—ã«ãªã£ãŸã®ã ã‘ã©ã€ç•°ãªã‚‹ãƒãƒ¼ã‚¸ãƒ§ãƒ³é–“ã‚’postgres_fdwã§æŽ¥ç¶šã£ã¦ã§ããŸã£ã‘ã€‚ ã¨ã„ã†ã“ã¨ã§ã‚„ã£ã¦ã¿ãŸã€‚ ãƒãƒ¼ã‚«ãƒ«ã‚µãƒ¼ãƒãŒ9.6ã€ãƒªãƒ¢ãƒ¼ãƒˆã‚µãƒ¼ãƒãŒ9.5ã®å ´åˆã€‚ bench=# EXPLAIN ANALYZE VERBOSE SELECT AVG(a.data1), AVG(a.data2) FROM table_a a JOIN table_b b ON (a.id = b.id) WHERE a.data1 = 10000 ; QUERY PLAN ------------------------------------------------------
tom__bo 2016/06/14
postgresql

fdw
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pg_upgrade | Let's POSTGRES
NTT ã‚ªãƒ¼ãƒ—ãƒ³ã‚½ãƒ¼ã‚¹ã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã‚»ãƒ³ã‚¿ ç¬ åŽŸ è¾°ä» ã¯ã˜ã‚ã« PostgreSQLã§ã¯ã€å®šæœŸçš„ãªãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚¢ãƒƒãƒ—ãŒè¡Œã‚ã‚Œã¾ã™ã€‚ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚¢ãƒƒãƒ—ã«ã¯2ç¨®é¡žã‚ã‚Šã€ãƒãƒ¼ã‚¸ãƒ§ãƒ³å (x.y.z) ã® x ã¾ãŸã¯ y ãŒå¤‰åŒ–ã™ã‚‹ãƒ¡ã‚¸ãƒ£ãƒ¼ãƒªãƒªãƒ¼ã‚¹ (8.3 â†’ 8.4) ã¨ã€z ãŒå¤‰åŒ–ã™ã‚‹ãƒžã‚¤ãƒŠãƒ¼ãƒªãƒªãƒ¼ã‚¹ (8.3.6 â†’ 8.3.7) ã§ã™ã€‚ãƒ¡ã‚¸ãƒ£ãƒ¼ãƒãƒ¼ã‚¸ãƒ§ãƒ³ãŒã‚¢ãƒƒãƒ—ã™ã‚‹ã¨DBã‚¯ãƒ©ã‚¹ã‚¿ã®äº’æ›æ€§ãŒãªããªã‚‹ãŸã‚ã€pg_dumpç‰ã«ã‚ˆã‚‹ãƒ€ãƒ³ãƒ—ã‚’è¡Œã„ã€æ–°ç‰ˆã®DBã‚¯ãƒ©ã‚¹ã‚¿ã«ãƒ‡ãƒ¼ã‚¿ã‚’ãƒªã‚¹ãƒˆã‚¢ã™ã‚‹å‡¦ç†ãŒå¿…è¦ã§ã™ã€‚ ã“ã®ãƒ€ãƒ³ãƒ—ã®å–å¾—ã¨ãƒªã‚¹ãƒˆã‚¢ã¯ã€éžå¸¸ã«å¤§ããªãƒ‡ãƒ¼ã‚¿ã‚’æŒã¤ã‚·ã‚¹ãƒ†ãƒ ã§ã¯é•·æ™‚é–“ã‹ã‹ã‚‹ãŸã‚åŽ„ä»‹ã§ã—ãŸã€‚ã“ã®ä½œæ¥ãŒé¢å€’ã§ã€å¤ã„ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚’ä½¿ã„ç¶šã‘ã¦ã„ã‚‹æ–¹ã‚‚å¤šã„ã®ã§ã¯ãªã„ã§ã—ã‚‡ã†ã‹ï¼Ÿã“ã®ã‚ˆã†ãªãƒ€ãƒ³ãƒ—ã‚„ãƒªã‚¹ãƒˆã‚¢å‡¦ç†ã‚’ä¸è¦ã«ã—ã€ä½¿ç”¨ä¸ã®DBã‚¯ãƒ©ã‚¹ã‚¿ã‚’ãã®ã¾ã¾æ–°ã—ã„ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã®PostgreSQLã§ã‚‚ä½¿ã„ç¶šã‘ã‚‰ã‚Œã‚‹ã‚ˆ
tom__bo 2016/05/31
postgresql

pg_upgrade
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PostgreSQL Scalability: Towards Millions TPS - Alexander Korotkov's blog
PostgreSQL scalability on multicore and multisocket machines became a subject of optimization long time ago once such machines became widely used. This blog post shows brief history of vertical scalability improvements between versions 8.0 and 8.4. PostgreSQL 9.2 had very noticeable scalability improvement. Thanks to fast path locking and other optimizations it becomes possible to achieve more tha
tom__bo 2016/05/28
PostgreSQL

performance
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Chef ã§ PostgreSQL 9.3 ã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ« - æš‡äººã˜ã‚ƒãªã„
postgresql cookbook ã‚’ä½¿ã£ã¦ Chef ã§ PostgreSQL 9.3 ã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ãŸéš›ã®ãƒ¡ãƒ¢ã§ã™ã€‚ OS: Ubuntu 12.04 (Debian ã§ã‚‚ä½¿ãˆãã†ã§ã™ãŒæœªæ¤œè¨¼ã§ã™) Cookbook: postgresql 3.3.4 Cookbook ã¯ã‚ªãƒ•ã‚£ã‚·ãƒ£ãƒ«ã®ã‚‚ã®ã‚’ä½¿ã„ã¾ã—ãŸã€‚ãƒ‡ãƒ•ã‚©ãƒ«ãƒˆã§ã¯ PostgreSQL 9.1 ãŒã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã•ã‚Œã¾ã™ã€‚ Chef Cookbook: postgresql - Opscode Community ã¾ãšã¯ attributes ã€‚ enable_pgdg_apt ã‚’æœ‰åŠ¹ã«ã™ã‚‹ã“ã¨ã§ PostgreSQL ã® APT ãƒªãƒã‚¸ãƒˆãƒªãŒä½¿ç”¨ã§ãã‚‹ã‚ˆã†ã«ãªã‚Šã¾ã™ã€‚ ãƒ•ã‚¡ã‚¤ãƒ«ã‚„ãƒ‡ã‚£ãƒ¬ã‚¯ãƒˆãƒªåã‚’æŒ‡å®šã—ç›´ã—ã¦ã„ã‚‹ã®ãŒæ°—æŒã¡æ‚ªã„ã®ã§ã™ãŒã€Cookbook ãƒ‡ãƒ•ã‚©ãƒ«ãƒˆã® 9.1 ã®ãƒ‘ã‚¹ã«ãªã£ã¦ã—ã¾ã†ã®ã§ä»•æ–¹ãªã... attribu
tom__bo 2016/05/20
chef

postgresql
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æœ¬å½“ã¯æ€–ã„PostgreSQLæ€§èƒ½æ¸¬å®š
ã“ã®è¨˜äº‹ã¯ï¼ŒPostgreSQL Advent Calendar 2012ã®12æœˆ25æ—¥åˆ†ã®è¨˜äº‹ã§ã™(æ›¸ãäººãŒã„ãªã•ãã†ãªã®ã§å‹æ‰‹ã«)ã€‚ PostgreSQLã®æ€§èƒ½æ¸¬å®šã«çµ¡ã‚ã¤ã¤ï¼Œãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚·ã‚¹ãƒ†ãƒ ã®æ€§èƒ½æ¸¬å®šã«é–¢ã™ã‚‹æ§˜ã€…ãªç½ ã«ã¤ã„ã¦ï¼Œ å‚¾å‘ã¨å¯¾ç–ã‚’æ›¸ã„ã¦ã¿ã‚ˆã†ã¨æ€ã„ã¾ã™ã€‚ ã“ã®è¨˜äº‹ã®ãã£ã‹ã‘ã¨ãªã£ãŸã®ãŒï¼Œ æ°¸å®‰ã•ã‚“ã®PostgreSQL Advent Calendar 2012ï¼ˆå…¨éƒ¨ä¿ºï¼‰ ã®ï¼ŒPostgreSQL Deep Dive: ãƒ‡ãƒ¼ã‚¿ãƒ–ãƒãƒƒã‚¯ã‚µã‚¤ã‚ºã®å¤‰æ›´ã¨åˆ†æžç³»ã‚¯ã‚¨ãƒªã¸ã®æ€§èƒ½å½±éŸ¿ï¼ˆSSDç·¨ï¼‰ ã¨ã„ã†è¨˜äº‹ã§ã™ã€‚ ã¿ã‚“ãªå¤§å¥½ãSSDã®ä¸Šã§ï¼ŒDWHç³»ã®ãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã‚’å‹•ã‹ã—ãŸå ´åˆã®æ€§èƒ½ã«ã¤ã„ã¦ï¼Œ DBã®ãƒ–ãƒãƒƒã‚¯ã‚µã‚¤ã‚ºãŒä¸Žãˆã‚‹å½±éŸ¿ã‚’æ¸¬å®šã—ãŸè¨˜äº‹ã§ã™ã€‚ ä»Šå›žã¯ï¼Œã“ã®è¨˜äº‹ã¸ã®ãƒ„ãƒƒã‚³ãƒŸã¨ã„ã†å½¢ã§æ€§èƒ½æ¸¬å®šã®ç½ ã‚’ç´¹ä»‹ã—ã¦ã‚†ãã“ã¨ã«ã—ã¾ã™ã€‚ â€» å¿µã®ãŸã‚ã«æ–ã£ã¦ãŠãã¾ã™ãŒï¼Œå½“è©²è¨˜äº‹ã‚’è²¶ã‚ã‚‹æ„å›³ãŒã‚ã‚‹ã‚
tom__bo 2016/03/15
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postgresql
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