Sqlime - Online SQLite playgroundSqlime is an online SQLite playground for debugging and sharing SQL snippets.
時点tã«ãŠã‘る連続ã§çµæžœxãŒå‡ºãŸå›žæ•°(çµæžœyãŒå‡ºãŸã‚‰å›žæ•°ã¯ãƒªã‚»ãƒƒãƒˆã•ã‚Œã‚‹)を出ã™SQLを書ã„㟠- カンムテックブãƒã‚°
カンムã§COOã‚’ã—ã¦ã„ã¾ã™ã€achikuã§ã™ã€‚ ニッãƒã™ãŽã¦èª°ã«è©±ã—ã¦ã‚‚「？ã€ã¨ãªã‚‹ãŒã€ã¨ã«ã‹ãç†è§£ã§ãã¦å¬‰ã—ã‹ã£ãŸSQLã®è©±ã‚’ã™ã‚‹ã€‚ 誰ã‹ã«ã“ã®æ„Ÿå‹•ã‚’ä¼ãˆãŸã„ã®ã§ã‚³ãƒ¼ãƒ’ーカップã«å‘ã‹ã£ã¦ã‚¯ã‚¨ãƒªã®èª¬æ˜Žã—ã¦ã„る— _achiku (@_achiku) February 21, 2021 話ã—ã‚’ç°¡å˜ã«ã™ã‚‹ç‚ºã«ã‚³ã‚¤ãƒ³ãƒˆã‚¹ã‚’用ã„ãŸä¾‹é¡Œã§èª¬æ˜Žã™ã‚‹ã€‚ å•é¡Œ 複数回ã®ã‚³ã‚¤ãƒ³ãƒˆã‚¹ã®çµæžœ(試行IDã€è£ãŒå‡ºãŸã‹è¡¨ãŒå‡ºãŸã‹ã€ãƒˆã‚¹ã—ãŸæ™‚é–“)を記録ã—ãŸãƒ‡ãƒ¼ã‚¿ãŒã‚る。ã“ã®ãƒ‡ãƒ¼ã‚¿ã‚’用ã„ã¦è©¦è¡Œå›žæ•°t回目ã«ãŠã„ã¦ä½•å›žé€£ç¶šã§è¡¨ãŒå‡ºãŸã‹ã‚’出力ã—ãŸã„。ãªãŠã€ä¸€åº¦è£ãŒå‡ºãŸã‚‰é€£ç¶šã§è¡¨ãŒå‡ºãŸå›žæ•°ã¯0ã«ãƒªã‚»ãƒƒãƒˆã•ã‚Œã‚‹ã€‚ å•é¡Œã‚’表ã§è¡¨ç¾ã™ã‚‹ 最終形ã‹ã‚‰ã‚¤ãƒ¡ãƒ¼ã‚¸ã™ã‚‹ã¨ã€å¤§ä½“以下ã®ã‚ˆã†ãªäº‹ãŒã—ãŸã„。試行回数t回目ã«ãŠã„ã¦é€£ç¶šã§head=trueã§ã‚る回数を出ã™ã€‚ã¨ã«ã‹ã時系列ã«ä¸¦ã¹ãŸéš›ã«æ™‚点tã«ãŠã‘る連続表ãŒå‡ºãŸå›žæ•°ãŒæ¬²ã—ã„。 consecu
BigQuery SQL ã§ãƒ¬ã‚¤ãƒˆãƒ¬ãƒ¼ã‚·ãƒ³ã‚° - Qiita
# 以é™ã¯ã‚³ãƒ¡ãƒ³ãƒˆãªã®ã§ã“れ㯠valid 㪠pnm フォーマットã§ã™ã€‚ æ‹¡å¼µå pgm ã§ä¿å˜ã™ã‚Œã°ã€Windows ã®å ´åˆã¯ IfranViewã€macOS ã®å ´åˆã¯ Preview.app ã§è¡¨ç¤ºã§ãã¾ã™ã€‚ ã“れ㧠BigQuery ã§ç”»åƒã‚’出力ã§ãã‚‹ã“ã¨ãŒç¢ºèªã§ãã¾ã—ãŸã€‚ BigQuery ã«ã‚ˆã‚‹ãƒ¬ã‚¤ãƒˆãƒ¬ãƒ¼ã‚·ãƒ³ã‚° ã¨ã„ã†ã‚ã‘ã§ã€BigQueryã§ãƒ¬ã‚¤ãƒˆãƒ¬ãƒ¼ã‚·ãƒ³ã‚°ã‚’ã‚„ã£ã¦ã¿ã¾ã—ょã†ã€‚ 実際ã®SQLコードã¯ä»¥ä¸‹ã®ã‚ˆã†ã«ãªã‚Šã¾ã™ã€‚ -- Vec3ã®ãƒ‰ãƒƒãƒˆç© CREATE TEMPORARY FUNCTION DOT (a STRUCT<x FLOAT64, y FLOAT64, z FLOAT64>, b STRUCT<x FLOAT64, y FLOAT64, z FLOAT64>) AS ( a.x*b.x + a.y*b.y + a.z*b.z ) ; -- ç·šå½¢çµåˆ aP +
SQL Notebook
Open source app for casual data exploration in SQL Import your data from CSV, Excel, Microsoft SQL Server, PostgreSQL, and MySQL. Then use a Jupyter-style notebook interface for exploratory queries, and write stored procedures for reusable logic. SQL Notebook is powered by an extended SQLite engine, supporting both standard SQL queries and SQL Notebook-specific commands and functions. Download SQL
The JSON1 Extension | SQLite
1. Overview By default, SQLite supports thirty functions and two operators for dealing with JSON values. There are also two table-valued functions that can be used to decompose a JSON string. There are twenty-six scalar functions and operators: json(json) jsonb(json) json_array(value1,value2,...) jsonb_array(value1,value2,...) json_array_length(json) json_array_length(json,path) json_error_positio
Modern SQL in PostgreSQL
SQL has gone out of fashion lately—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
SQLを生æˆã™ã‚‹Common Lispライブラリ「SxQLã€ã‚’作りã¾ã—㟠- 八発白ä¸
何ã‹ä½œã£ãŸã¨ãã«ã—ã‹æ›´æ–°ã—ãªã„ブãƒã‚°ãŒã€æœ€è¿‘ã§ã¯ä½•ã‹ä½œã£ã¦ã‚‚「ã¾ã‚ã“ã®ç¨‹åº¦ã¯ãƒ–ãƒã‚°æ›¸ãã»ã©ã§ã‚‚ãªã„ã‹ã€ã¨æ€ã£ã¦ã€æ›´æ–°ã‚‚ç„¡ã„よã†ãªæ„Ÿã˜ã«ãªã£ã¦ã„ã¾ã™ã€‚ 今回もãã†ã‚„ã£ã¦ã‚¹ãƒ«ãƒ¼ã—よã†ã¨æ€ã£ãŸã®ã§ã™ãŒå¦»ã«ã€Œãƒ–ãƒã‚°ã§ç´¹ä»‹ã—ãŸã‚‰ã„ã„ã®ã«ã€ã¨è¨€ã‚ã‚Œã¦ã—ã¾ã„ã€å¦»ã¨éŽã”ã™ä¼‘日を潰ã—ã¦ä½œã£ãŸãƒ©ã‚¤ãƒ–ラリã¨ã—ã¦ã¯ã€ã‚‚ã†ã“ã‚Œã¯æ›¸ã‹ã–ã‚‹ã‚’å¾—ãªã„ã‚ã‘ã§ã€è»½ã紹介ã—ã¦ãŠã“ã†ã¨æ€ã„ã¾ã™ã€‚ Common Lispã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å‘¨è¾º Common Lispã®ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å‘¨ã‚Šã§ã¯ã“ã‚Œã¨ã„ã£ãŸå¥½ã‚€ãƒ©ã‚¤ãƒ–ラリも無ãã€æ‹™ä½œã®CL-DBIã§ã‚ˆã†ã‚„ã土å°ãŒã§ããŸã¨ã„ã†çŠ¶æ…‹ã§ã™ã€‚ ãŸã ã€ä¾ç„¶SQLã‚’æ–‡å—列ã§æ›¸ãå¿…è¦ãŒã‚る。もã¡ã‚ã‚“ãã‚Œã§å›°ã‚‰ãªã„ケースも多ã„ã®ã§ã™ãŒã€WHEREå¥ã‚„ORDER BYå¥ã ã‘ãŒç•°ãªã‚‹ã‚¯ã‚¨ãƒªã‚’複数回投ã’ãŸã„ã¨ã„ã£ãŸã¨ãã«ã¯ãƒ—ãƒã‚°ãƒ©ãƒ ã‹ã‚‰ç”Ÿæˆã§ãã‚‹ã»ã†ãŒå¥½ã¾ã—ã„。 Perlã«ã¯SQL::Makerã¨ã„ã†ãƒ©ã‚¤ãƒ–ラリã§ã€
Grass on SQL - still deeper
Overview ã¡ã‚‡ã£ã¨è‰æ¤ãˆã¨ãã¾ã™ã型言語 Grass ã‚’SQLã§å®Ÿè£…ã—ã¾ã—ãŸã¨ã„ã†è©±. Grassã¯Î»è¨ˆç®—をベースã«ã—ãŸé–¢æ•°åž‹ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°è¨€èªžã§ã™.å…¬å¼ãƒšãƒ¼ã‚¸ã®ä»•æ§˜ã‚’å…ƒã«SQL(PostgreSQL)ã§å®Ÿè£…ã—ã¾ã—ãŸ. ä»–Grassã«ã¤ã„ã¦ã¯ä¸Šè¨˜ã®å…¬å¼ãƒšãƒ¼ã‚¸ã¨ã‹ã“ã“ら辺をå‚ç…§. プãƒã‚°ãƒ©ãƒŸãƒ³ã‚°è¨€èªž/Grass - プãƒã‚°ãƒ©ãƒŸãƒ³ã‚°ã‚¹ãƒ¬ã¾ã¨ã‚ in VIP ã†ã¯ï½—ï½—ï½— Mosh 㧠Grass 実装ã—ãŸï½—ï½—ï½—ï½— - Higepon’s blog - Mona OS and Mosh Example SELECT run_grass('wwWWwv wwwwWWWwwWwwWWWWWWwwwwWwwv wWWwwwWwwwwWwwwwwwWwwwwwwwww'); run_grass ----------- ww (1 row) SELECT run_grass('wWWWwwwwWWW
「SQLインジェクション対ç–ã€ã§Google検索ã—ã¦ä¸Šä½15記事を検証ã—㟠- ockeghem's blog
ã“ã®ã‚¨ãƒ³ãƒˆãƒªã§ã¯ã€ãƒãƒƒãƒˆä¸Šã§ã€ŒSQLインジェクション対ç–ã€ã§Google検索ã—ãŸçµæžœã®ä¸Šä½15エントリを検証ã—ãŸçµæžœã‚’å ±å‘Šã—ã¾ã™ã€‚ SQLインジェクション脆弱性ã®å¯¾ç–ã¯ã€æ—¢ã«ã€Œå®‰å…¨ãªSQLã®å‘¼ã³å‡ºã—æ–¹ã€ã«ãƒ•ã‚¡ã‚¤ãƒŠãƒ«ã‚¢ãƒ³ã‚µãƒ¼ï¼ˆå¾Œè¿°ï¼‰ã‚’示ã—ã¦ã„ã¾ã™ãŒã€ã¾ã ã“ã®æ–‡æ›¸ã‚’知らãªã„人ãŒå¤šã„ã ã‚ã†ã“ã¨ã¨ã€ã‚„や上級者å‘ã‘ã®æ–‡æ›¸ã§ã‚ã‚‹ã“ã¨ã‹ã‚‰ã€ã¾ã å分ã«å®Ÿè·µã•ã‚Œã¦ã¯ã„ãªã„ã¨æ€ã„ã¾ã™ã€‚ ã“ã®çŠ¶æ³ã§ã€ã‚»ã‚ュリティã®ã“ã¨ã‚’よã知らãªã„人ãŒSQLインジェクション対ç–ã—よã†ã¨ã—ãŸå ´åˆã®è¡Œå‹•ã‚’予測ã—ã¦ã¿ã‚‹ã¨ã€ã‹ãªã‚Šã®å‰²åˆã®äººãŒGoogleç‰ã§æ¤œç´¢ã—ã¦å¯¾å‡¦æ–¹æ³•ã‚’調ã¹ã‚‹ã¨æ€ã‚ã‚Œã¾ã™ã€‚ãã“ã§ã€ä»¥ä¸‹ã®URLã§SQLインジェクション対ç–方法を検索ã—ãŸçµæžœã®ä¸Šä½ã®ã‚¨ãƒ³ãƒˆãƒªã‚’検証ã—ã¦ã¿ã‚ˆã†ã¨æ€ã„ç«‹ã¡ã¾ã—ãŸã€‚ http://www.google.co.jp/search?q=SQLã‚¤ãƒ³ã‚¸ã‚§ã‚¯ã‚·ãƒ§ãƒ³å¯¾ç– ã©ã“ã¾ã§èª¿ã¹ã‚‹ã‹ã§ã™ãŒã€ä»¥å‰NH
Sql2Dot
Sql2Dot is a tiny parser written in java to transform sql into dot for visualizing data structures. It parses some very basic sql which we use in PostgreSQL. Here is an example of sql (borrowed from lain) that Sql2Dot likes to parse. Source and class files can be found in this sql2dot.jar file Usage: java -jar sql2dot.jar <files> <files> - list of sql files Sql2Dot sends its output to the same loc
SQLã®æœªæ¥ - ミックã®ãƒ–ãƒã‚°
先週ã®åœŸæ›œã«ãƒ“ズアイユã•ã‚“ã€å‚井ã•ã‚“ã¨ã‚‚ã«ã€æ…¶æ‡‰å¤§å¦æ—¥å‰ã‚ャンパスã¸å‡ºã‹ã‘ã¦ãã¾ã—ãŸã€‚目的ã¯ã€é 山元é“準教授ã®ç ”究室ã¸ãŠé‚ªé”ã—ã¦SuperSQL ã¨ã„ã†æ–°è¨€èªžã®ãŠè©±ã‚’èžãã“ã¨ã€‚6時間超ã«ã‚ãŸã£ã¦é 山先生自らプレゼンã¨QA ã¾ã§ã—ã¦ã„ãŸã ãã¨ã„ã†éžå¸¸ã«è´…æ²¢ãªæ™‚é–“ã§ã—ãŸã€‚ SuperSQL ã¯ã€åå‰ã‹ã‚‰é€£æƒ³ã™ã‚‹ã‚ˆã†ãª SQL ã®æ‹¡å¼µè¨€èªžã§ã¯ã‚ã‚Šã¾ã›ã‚“。ã“ã‚Œã¯é 山先生も強調ã—ã¦ã„ãŸã®ã§ã™ãŒã€ç§ã®ç†è§£ã—ãŸç¯„囲ã§è¡¨ç¾ã™ã‚‹ã¨ã€ã“れ㯠HTMLã€LATEXã€Ajax ãªã©ã€Œè¡¨ç¤ºã€ã‚’ã¤ã‹ã•ã©ã‚‹ãƒ—レゼンテーション・レイヤー㨠SQL ã¨ã„ã†ãƒŸãƒ‰ãƒ«ãƒ»ãƒ¬ã‚¤ãƒ¤ãƒ¼ã‚’ラップã™ã‚‹è¨€èªžã§ã™ã€‚ ã‚‚ã¨ã‚‚ã¨ã€æ´å²çš„ã«ã¯ SQL ã¯ãƒ—レゼンテーションをæ„è˜ã—ãªã„言語ã¨ã—ã¦é–‹ç™ºã•ã‚Œã¾ã—ãŸã€‚ãã®ç›®çš„ã¯ã‚ãã¾ã§æ¬²ã—ã„データを検索ã™ã‚‹ã“ã¨ã§ã‚ã£ã¦ã€è¦‹ã›æ–¹ã¯ä¸Šä½ãƒ¬ã‚¤ãƒ¤ãƒ¼ã®ä»•äº‹ãªã®ã§è‡ªåˆ†ã¯é–¢çŸ¥ã—ãªã„ã€ã¨ã„ã†åˆ†æ¥ã®æ–¹é‡ã«åŸºã¥ã„ã¦ã„ã¾ã™ã€‚ã“ã‚Œã¯
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Stupid Coding Tricks: The T-SQL Mandelbrot 2008-11-19
Feature Articles Most Recent Articles Classic WTF: Documentation by Sticky Note Space for Queries Lowering the Rent Floor Testing the Juniors README NPath Complexity Structure is Structure A Date This Weekend? CodeSOD Most Recent Articles Zero Competence One Month A Little Extra Padding Ready Xor Not A Set of Mistakes While This Works Enterprise Code Coverage Building Blocks Error'd Most Recent Ar
(普通ã®) å†å¸° CTE ã‚’ hierarchyid 㧠- ãã‚‹ãる～
SQL Server 2008 ã«å®Ÿè£…ã•ã‚Œã¦ã„ã‚‹ hierarchyid åž‹ã¯ã€çµŒè·¯åˆ—挙モデルをベースã«ã—ãŸåž‹ãªã®ã§ã€å†å¸° CTE ã‚’ç½®ãæ›ãˆã‚‹ã“ã¨ãŒã§ãる。 例ãˆã°ã€ SQL Server 2005ã§å†å¸°ã‚¯ã‚¨ãƒª - taediumã®æ—¥è¨˜ ã®å†å¸° CTE ã‚’ hierarchyid ã§å®Ÿç¾ã—ã¦ã¿ã‚‹ã€‚ 使用ã™ã‚‹ãƒ†ãƒ¼ãƒ–ル CREATE TABLE [dbo].[Classes]( [id] [hierarchyid] NOT NULL, [name] [nvarchar](50) NOT NULL, CONSTRAINT [PK_Classes] PRIMARY KEY CLUSTERED ( [id] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS
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H2k6風 データベース型オーディオプレーヤ Lutea(仮)
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