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Compile SQL to type-safe code
You write SQL queries You run sqlc to generate code that presents type-safe interfaces to those queries You write application code calling the methods sqlc generated. Seriously, it's that easy. You don't have to write any boilerplate SQL querying code ever again. See the current list of supported programming languages and databases. Schema updates and poorly-written queries often bring down produc
BlazingSQL is Now Open Source
BlazingSQL, the GPU-accelerated SQL engine of the RAPIDS ecosystem, is now 100% open-source licensed under Apache 2.0! Check out the code on our Github page. BlazingSQL is not a database, which is why we changed our original name of BlazingDB to BlazingSQL. It is a SQL engine that processes (almost) any data you want. Working within RAPIDS has been game-changing. There are now over 100 developers
TeamSQL - Cross-platform SQL Client Built for Collaboration
Looking for an Amazon Redshift client? TeamSQL has retired and is not available for download anymore. You can The world's first and the only query and management tool built for Amazon Redshift. Get DataRow for Amazon Redshift Hello, TeamSQL has been a great platform to experiment with modern UI and powerful features to help you manage your popular databases with collaborative features. Over two ye
SQL Indexing and Tuning e-Book for developers: Use The Index, Luke covers Oracle, MySQL, PostgreSQL, SQL Server, ...
A site explaining SQL indexing to developers—no crap about administration. SQL indexing is the most effective tuning method—yet it is often neglected during development. Use The Index, Luke explains SQL indexing from grounds up and doesn’t stop at ORM tools like Hibernate. Use The Index, Luke is the free web-edition of my book SQL Performance Explained (from Є9.95). Be sure to subscribe my free ne
gstore_fdw: GPUメモリをSQLã§èªã¿æ›¸ãã€ãã—ã¦â€¦ã€‚ - KaiGaiã®ä¿ºãƒ¡ãƒ¢
昨年ã€PGconf.ASIAã§ç™ºè¡¨ã—ãŸPL/CUDAã«ã‚ˆã‚‹å‰µè–¬ãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã®é«˜é€ŸåŒ–実験ã®ãƒ†ãƒ¼ãƒžã§ã‚ã‚‹ãŒã€ kaigai.hatenablog.com 実測ã—ãŸãƒ™ãƒ³ãƒãƒžãƒ¼ã‚¯ã‚’見るã¨ã€å¥‡å¦™ãªå‚¾å‘ãŒè¦‹ã¦ã¨ã‚Œã‚‹ã€‚ ã“ã®ãƒ¯ãƒ¼ã‚¯ãƒãƒ¼ãƒ‰ã«ãŠã‘る計算é‡ã¯ã€ŒQã®è¡Œæ•°Ã—Dã®è¡Œæ•°ã€ã§ã‚ã‚‹ã®ã§ã€Dã®è¡Œæ•°ãŒåŒã˜1000万行ã§ã‚ã‚‹ãªã‚‰ã°ã€Qã®è¡Œæ•°ãŒ1000ã®ã‚±ãƒ¼ã‚¹ï¼ˆ22.6s）ã«æ¯”ã¹ã€Qã®è¡Œæ•°ãŒ10ã®ã‚±ãƒ¼ã‚¹ï¼ˆ13.4s）ã®å®Ÿè¡Œæ™‚é–“ã¯ã‚‚ã£ã¨é¡•è‘—ã«çŸæ™‚é–“ã§ãªã‘ã‚Œã°ãªã‚‰ãªã„。 計算é‡ãŒ1/100ãªã®ã«ã€å®Ÿè¡Œæ™‚é–“ã¯åŠåˆ†å¼±ã«ã—ã‹ãªã£ã¦ã„ãªã„。 実ã¯ã“ã‚Œã¯ã€åŒ–åˆç‰©åŒå¿—ã®é¡žä¼¼åº¦ã‚’計算ã™ã‚‹ãŸã‚ã®æ™‚é–“ã ã‘ã§ãªãã€PL/CUDA関数ã«ä¸Žãˆã‚‹å¼•æ•°ã‚’セットアップã™ã‚‹ãŸã‚ã®æ™‚é–“ã«12秒程度をè¦ã—ã¦ãŠã‚Šã€ã‚¢ãƒ ダールã®æ³•å‰‡ã‚’引用ã™ã‚‹ã¾ã§ã‚‚ãªãã€é¡žä¼¼åº¦ã®è¨ˆç®—を高速化ã™ã‚‹ã ã‘ã§ã¯å‡¦ç†é€Ÿåº¦ã¯ã“れ以上伸ã³ãªã„ã®ã§ã‚る。 PL/CUDA関数ã®å¼•æ•°ã¨ã—ã¦è¡Œåˆ—
10 Cool SQL Optimisations That do not Depend on the Cost Model
Java, SQL and jOOQ. Best Practices and Lessons Learned from Writing Awesome Java and SQL Code. Get some hands-on insight on what's behind developing jOOQ. Cost Based Optimisation is the de-facto standard way to optimise SQL queries in most modern databases. It is the reason why it is really really hard to implement a complex, hand-written algorithm in a 3GL (third generation programming language)
Franchise: a sql notebook
No sign up, no install. Chart with a single click. Compare queries side by side. Download your work and share it with anyone. SQL without the Ceremony No sign up, no install. Start playing with your data quickly and securely. If your data is in a CSV, JSON, or XLSX file, loading it is as simple as dropping the file into Franchise. We run a version of the SQLite engine in your browser, so all proce
Apache Kafkaã«å¯¾å¿œã—ãŸSQLエンジン「KSQLã€ãƒªãƒªãƒ¼ã‚¹ã€ã‚¹ãƒˆãƒªãƒ¼ãƒ データをSQLã§ç¶™ç¶šçš„ã«å‡¦ç†ã€‚ConfluentãŒã‚ªãƒ¼ãƒ—ンソースã§
Apache Kafkaを用ã„ãŸãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ データ処ç†ã®å•†ç”¨ã‚µãƒ¼ãƒ“スをæä¾›ã—ã¦ã„ã‚‹Confluentã¯ã€Apache Kafkaã«å¯¾å¿œã—ãŸã‚ªãƒ¼ãƒ—ンソースã®SQLエンジン「KSQLã€ã®ãƒ‡ãƒ™ãƒãƒƒãƒ‘ープレビューをリリースã—ã¾ã—ãŸã€‚ Apache Kafkaã¯ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã«å„ªã‚Œã€å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’リアルタイムã«å‡¦ç†ã§ãるソフトウェアã§ã™ã€‚ã•ã¾ã–ã¾ãªã‚¢ãƒ—リケーションã‹ã‚‰é€ã‚‰ã‚Œã¦ãã‚‹ãƒã‚°ã‚„大é‡ã®ã‚»ãƒ³ã‚µãƒ¼ãªã©ã‹ã‚‰ç”Ÿæˆã•ã‚Œã‚‹ãƒ‡ãƒ¼ã‚¿ãªã©ã€ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«é€ä¿¡ã•ã‚Œã¦ãるストリームデータをã„ã£ãŸã‚“Kafkaã§å—ã‘æ¢ã‚ã€ãれをã¾ã¨ã‚ã¦Hadoopãªã©ã®åˆ†æžã‚¨ãƒ³ã‚¸ãƒ³ã«æ¸¡ã—ã¦ãƒ‡ãƒ¼ã‚¿ã®åˆ†æžã‚’è¡Œã†ã€ã¨ã„ã£ãŸå½¢ã§ä½¿ã‚ã‚Œã¾ã™ã€‚ KSQLã¯ã€ã“ã®Kafkaã«å¯¾å¿œã—ãŸSQLエンジン。ã“ã‚Œã«ã‚ˆã‚ŠJavaã‚„Pythonã§è¤‡é›‘ãªå‡¦ç†ã‚’記述ã—ãªãã¨ã‚‚ã€ã‚¹ãƒˆãƒªãƒ¼ãƒ データを柔軟ã«åŠ å·¥ã§ãるよã†ã«ãªã‚Šã¾ã™ã€‚ SQLã¨KSQLã®é•ã„ã¨ã¯ï¼Ÿ 一般的
自然言語ã‹ã‚‰SQLクエリを機械å¦ç¿’ã§ç”Ÿæˆã€æ¥å‹™ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ãŒè¨€è‘‰ã§æ¤œç´¢ã§ãるよã†ã«ã€‚セールスフォース・ドットコムãŒAIã®ç ”究æˆæžœã‚’公開
自然言語ã‹ã‚‰SQLクエリを機械å¦ç¿’ã§ç”Ÿæˆã€æ¥å‹™ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ãŒè¨€è‘‰ã§æ¤œç´¢ã§ãるよã†ã«ã€‚セールスフォース・ドットコムãŒAIã®ç ”究æˆæžœã‚’公開 セールスフォース・ドットコムã®äººå·¥çŸ¥èƒ½ç ”究部門ã§ã‚ã‚‹Salesforce Researchã¯ã€è‡ªç„¶è¨€èªžã«ã‚ˆã‚‹è³ªå•ã¨ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‚¹ã‚ーマã®æƒ…å ±ã‚’åŸºã«ã€è³ªå•ã«å¯¾å¿œã™ã‚‹SQLクエリを機械å¦ç¿’ã§ç”Ÿæˆã™ã‚‹ç ”究æˆæžœã‚’公開ã—ã¾ã—ãŸã€‚ ã“ã‚Œã«ã‚ˆã£ã¦ãƒ“ジãƒã‚¹ãƒ‘ーソンãŒSQL言語をå¦ã¶ã“ã¨ãªãã€æ¥å‹™ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã‹ã‚‰å¿…è¦ãªæƒ…å ±ã‚’è‡ªç„¶è¨€èªžã§æ¤œç´¢ã§ãã‚‹ã“ã¨ãŒæœŸå¾…ã§ãã¾ã™ã€‚ 自然言語を解æžã—ã¦SQLã‚¯ã‚¨ãƒªã‚’ç”Ÿæˆ ä¸‹è¨˜ã®å›³ã¯ã€å…¬é–‹ã•ã‚ŒãŸç ”究æˆæžœã®æ¦‚è¦ã‚’示ã—ãŸã‚‚ã®ã§ã™ã€‚ 図ã®å·¦ä¸Šã€ŒHow many engine types did Val Musetti use？ã€ãŒè‡ªç„¶è¨€èªžã®å•ã„ã¨ãªã‚Šã€ã€ŒEntrant / Constructor / Chassis / Engine / No / D
Introducing KSQL: Streaming SQL for Apache Kafka | Confluent
What does it even mean to query streaming data, and how does this compare to a SQL database? Well, it’s actually quite different to a SQL database. Most databases are used for doing on-demand lookups and modifications to stored data. KSQL doesn’t do lookups (yet), what it does do is continuous transformations— that is, stream processing. For example, imagine that I have a stream of clicks from use
We need tool support for keyset pagination
Did you know pagination with offset is very troublesome but easy to avoid? offset instructs the databases skip the first N results of a query. However, the database must still fetch these rows from the disk and bring them in order before it can send the following ones. This is not an implementation problem, it’s the way offset is designed: …the rows are first sorted according to the <order by clau
スケールアウトã™ã‚‹SQLシステム(2017/08/22 19:00〜)
最近増ãˆã¦ã„るプãƒã‚°ãƒ©ãƒ ã«ã‚ˆã‚‹åž‚直分割を必è¦ã¨ã—ãªã„ スケールã™ã‚‹SQLシステムã«ã¤ã„ã¦å¾—æ„ãªæ–¹ã« 話ã—ã¦ã„ãŸã ã“ã†ã¨æ€ã„ã¾ã™ã€‚ タイムテーブル 18:55～ ä¼šå ´èª¬æ˜Ž ä¼šå ´ã®æ³¨æ„ãªã© 19:00～ PostgreSQLã§ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆ by sawada_masahikoã•ã‚“ 19:30～ MariaDB ã®DBエンジンã€ColumnStore,InnoDB,Mroonga + Spiderã§ã‚¹ã‚±ãƒ¼ãƒ«ã‚¢ã‚¦ãƒˆ by æ ªå¼ä¼šç¤¾ã‚¤ãƒ³ã‚µã‚¤ãƒˆãƒ†ã‚¯ãƒŽãƒã‚¸ãƒ¼ã•ã‚“ ãã®å¯ç”¨æ€§ã‚’検証 20:00～ 普通ã®ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ãŒã€ŒCloud Spannerã€ä½¿ã£ã¦ã¿ãŸ by æ ªå¼ä¼šç¤¾ã‚·ãƒªã‚¢ãƒ«ã‚²ãƒ¼ãƒ ズ è’井ã•ã‚“ MySQLã¨ã®å·®ç•°ã‚’ä¸å¿ƒã«è§£èª¬ 20:30～21:00 10年使ã‚ã‚Œã¦ã„るスケールシステムMySQL CLusterã«ã¤ã„㦠by 日本オラクル 梶山ã•ã‚“ 21:00～21：30 懇親会 21：30～ 希望者ã§
What’s New in SQL:2016
In December 2016, ISO released a new version of the international SQL standard (ISO/IEC 9075:2016). It supersedes the previous version from 2011. This article is a brief overview of the new features being introduced into the SQL language. Strictly speaking, this article covers the additions to part 2 of the standard (SQL/Foundation), i.e. the most commonly used part. This article also shows the av
State of SQL Antipatterns in 2017
2017/07/10 SQLアンãƒãƒ‘ターンNight Part2 https://connpass.com/event/59946/
ãªãœã€SQLã¯é‡ãŸããªã‚‹ã®ã‹ï¼Ÿâ”€â”€ã€ŽSQLパフォーマンス詳解ã€ã®ç¿»è¨³è€…ãŒæ•™ãˆã‚‹åŽŸå› ã¨å¯¾ç–｜ãƒã‚¤ã‚¯ãƒ©ã‚¹è»¢è·ãƒ»æ±‚äººæƒ…å ±ã‚µã‚¤ãƒˆ AMBI（アンビ）
ãªãœã€SQLã¯é‡ãŸããªã‚‹ã®ã‹ï¼Ÿâ”€â”€ã€ŽSQLパフォーマンス詳解ã€ã®ç¿»è¨³è€…ãŒæ•™ãˆã‚‹åŽŸå› ã¨å¯¾ç– 『SQLパフォーマンス詳解ã€ã®ç¿»è¨³è€…ã®æ¾æµ¦éš¼äººã•ã‚“ã«ã€8ã¤ã®ã€ŒSQLãŒé‡ãŸããªã‚‹åŽŸå› ã¨ãã®å¯¾ç–ã€ã‚’èžãã¾ã—ãŸã€‚システムã®ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã«ãªã‚‹ã‚ˆã†ãªã€Œå•é¡Œã®ã‚ã‚‹SQLã€ã‚’回é¿ã™ã‚‹ãƒŽã‚¦ãƒã‚¦ã‚’å¦ã³ã¾ã—ょã†ã€‚ データã®æ“作や定義をã™ã‚‹è¨€èªžã€ŒSQLã€ã¯ã€ã©ã®ã‚ˆã†ãªé ˜åŸŸã‚’æ‹…ã†ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã«ã¨ã£ã¦ã‚‚必修科目ã§ã™ã€‚ã—ã‹ã—ã€ãã®ä»•æ§˜ã‚’ãã¡ã‚“ã¨ç†è§£ã—ã€ãƒ‘フォーマンスã«å„ªã‚ŒãŸSQLを書ã‘ã‚‹æ–¹ã¯ãã‚Œã»ã©å¤šãã‚ã‚Šã¾ã›ã‚“。å•é¡Œã®ã‚ã‚‹SQLを書ã„ã¦ã—ã¾ã„ã€çŸ¥ã‚‰ã¬é–“ã«ãã‚ŒãŒã‚·ã‚¹ãƒ†ãƒ ã®ãƒœãƒˆãƒ«ãƒãƒƒã‚¯ã«ãªã£ã¦ã—ã¾ã†äº‹æ…‹ã¯ã‚ˆã発生ã—ã¾ã™ã€‚ ã§ã¯ã€ã©ã†ã™ã‚Œã°ãã†ã—ãŸäº‹æ…‹ã‚’回é¿ã§ãã‚‹ã®ã§ã—ょã†ã‹ï¼Ÿ ãã®ãƒŽã‚¦ãƒã‚¦ã‚’å¦ã¶ãŸã‚ã€ä»Šå›žã¯ã€ŽSQLパフォーマンス詳解ã€ã®ç¿»è¨³è€…ã§ã‚ã‚Šã€è‡ªèº«ã‚‚エンジニアã§ã‚‚ã‚ã‚‹æ¾æµ¦éš¼äººï¼ˆã¾ã¤ã†ã‚‰ãƒ»ã¯ã‚„ã¨ï¼@dblmkt）ã•ã‚“ã«8ã¤
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GitHub - BlazingDB/blazingsql: BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
Why does SUM(...) on an empty recordset return NULL instead of 0?
GitHub - HVF/franchise: 🟠a notebook sql client. what you get when have a lot of sequels.
https://jp.techcrunch.com/2017/08/30/20170829salesforce-is-using-ai-to-democratize-sql-so-anyone-can-query-databases-in-natural-language/
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