GitHub - pingcap/tidb: TiDB - the open-source, cloud-native, distributed SQL database designed for modern applications.
Distributed Transactions: TiDB uses a two-phase commit protocol to ensure ACID compliance, providing strong consistency. Transactions span multiple nodes, and TiDB's distributed nature ensures data correctness even in the presence of network partitions or node failures. Horizontal and Vertical Scalability: TiDB can be scaled horizontally by adding more nodes or vertically by increasing resources o
The last decade of database research and its blindingly bright future. or Database Research: A love song. · Stanford DAWN
The last decade of database research and its blindingly bright future. or Database Research: A love song. by Michael Cafarella and Chris Ré 11 Apr 2018 To go by Twitter and many hallway conversations, the database research community has been unsettled lately in a way that we have never seen before. Many people are unhappy with the review process, many types of useful work seem to be more difficult
Data cleaning is a machine learning problem that needs data systems help! – ACM SIGMOD Blog
Data cleaning is a machine learning problem that needs data systems help! When dealing with real-world data, dirty data is the norm rather than the exception. We continuously need to predict correct values, impute missing ones, and find links between various data artefacts such as schemas and records. We need to stop treating data cleaning as a piecemeal exercise (resolving different types of erro
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開発者å‘ã‘ã®SQLインデックス解説サイトã€ç®¡ç†ã«ã¤ã„ã¦ã®é–“é•ã„ãªã„知è˜ã‚’æä¾›ã—ã¾ã™ã€‚ インデックスã¯é–‹ç™ºæ™‚ã«ã¯å¿˜ã‚Œã‚‰ã‚ŒãŒã¡ã§ã‚る一方ã§ã€éžå¸¸ã«åŠ¹æžœçš„ãªSQLã®ãƒãƒ¥ãƒ¼ãƒ‹ãƒ³ã‚°æ–¹æ³•ã§ã™ã€‚Use The Index, Lukeã§ã¯ã€Hibernateãªã©ã®ORMツールã®è§£èª¬ã«ã¨ã©ã¾ã‚‰ãšã€SQLã®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ã«ã¤ã„ã¦åŸºç¤Žã‹ã‚‰èª¬æ˜Žã—ã¾ã™ã€‚ Use The Index, Lukeã¯SQLパフォーマンス詳解ã®Web上ã®ç„¡æ–™ç‰ˆã§ã™ã€‚サイトを気ã«å…¥ã£ã¦é ‚ã‘ãŸã‚‰ã€ãœã²æ›¸ç±ã‚‚購入ã—ã¦ã¿ã¦ä¸‹ã•ã„。ã¾ãŸã€ã“ã®ã‚µã‚¤ãƒˆã®é‹å–¶ã‚’サãƒãƒ¼ãƒˆã™ã‚‹æ§˜ã€…ãªã‚°ãƒƒã‚ºã‚‚販売ã—ã¦ã„ã¾ã™ã€‚ MySQLã€Oracleã€SQL Serverãªã©ã«ãŠã‘ã‚‹SQLã®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹Use The Index, Lukeã§ã¯ã€ãƒ™ãƒ³ãƒ€ã«ã¨ã‚‰ã‚ã‚Œãªã„インデックスã®èª¬æ˜Žã‚’心ãŒã‘ã¦ã„ã¾ã™ã€‚製å“特有ã®äº‹æŸ„ã«ã¤ã„ã¦ã¯ã€ä»¥ä¸‹ã®ã‚ˆã†ãªè¡¨ç¤ºã‚’ã—ã¦ã„ã¾ã™ã€‚ Db2 (LUW)U
奥野幹也『ç†è«–ã‹ã‚‰å¦ã¶ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å®Ÿè·µå…¥é–€ã€ã¯ã©ã“ãŒãƒ€ãƒ¡ãªã®ã‹ - 檜山æ£å¹¸ã®ã‚マイラ飼育記 (ã¯ã¦ãªBlog)
言ã„訳ã‹ã‚‰å§‹ã‚ã¾ã™ã€‚ã“ã®è¨˜äº‹ã‚’（途ä¸ã¾ã§ã§ã‚‚）èªã‚“ã 人ã¯ã€æ¬¡ã®ã‚ˆã†ã«è¨€ã„ãŸããªã‚‹ã§ã—ょã†ã€‚ 『ç†è«–ã‹ã‚‰å¦ã¶ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹å®Ÿè·µå…¥é–€ã€ã¯è‰¯ã„本ãªã®ã‹æ‚ªã„本ãªã®ã‹ã€ã„ã£ãŸã„ã©ã£ã¡ãªã‚“ã よ?! ã“ã®æœ¬ã¯é–“é•ã„や説明ä¸è¶³ãŒã‚ã‚Šã€èª¤èªã•ã‚Œã‚„ã™ã„表ç¾ã‚‚多ãã€ãã®ç‚¹ã§ã¯æ®‹å¿µãªæœ¬ã§ã™ã€‚ã—ã‹ã—ã€é¢ç™½ã„アイディアã€ã™ã‚‹ã©ã„観察もå«ã¾ã‚Œã¦ã„ã¦ã€è¡Œé–“を補ã„æ·±èªã¿ã™ã‚Œã°ã€å¤šãã®ç¤ºå”†ã‚’得られる本ã§ã‚‚ã‚ã‚Šã¾ã™ã€‚ よã£ã¦ã€ã€Œè‰¯ã„ï¼æ‚ªã„ã€ã®äºŒæŠžã§ã¯ç”ãˆã‚‰ã‚Œã¾ã›ã‚“。良ã„点ã¨æ‚ªã„点ã®ä¸¡æ–¹ã‚’ã€ã§ãã‚‹ã ã‘客観的ã«è¨˜è¿°ã™ã‚‹ã—ã‹ãªã„ã®ã§ã™ã€‚ãれをã—ãŸçµæžœã€é•·ã„記事ã¨ãªã‚Šã¾ã—ãŸã€‚ 内容： ã“ã¨ã®ç™ºç«¯ï¼š zhanponã•ã‚“ã®æ‰¹åˆ¤ 奥野本æ“è·ã¨å¥¥é‡Žæœ¬æ‰¹åˆ¤ 僕ã®æ“è·ãƒ»æ‰¹åˆ¤ã®æ–¹é‡ zhanponã•ã‚“ã®æŒ‡æ‘˜ã®å†æ¤œè¨Ž 1. è«–ç†çš„ãªçŸ›ç›¾ã¨ãƒ‡ãƒ¼ã‚¿ã®ä¸æ•´åˆã‚’æ··åŒã—ã¦ã„ã‚‹ 2. 命題論ç†ã®é™ç•Œã«ã¤ã„ã¦ã®èª¬æ˜ŽãŒãŠã‹ã—ã„ 3. å¤å…¸è«–ç†ã®å®šç¾©ã‚’é–“é•ãˆã¦ã„ã‚‹ 4.
列指å‘データベースã®ãƒšãƒ¼ã‚¸ã®ãƒ‡ãƒ¼ã‚¿æ§‹é€ - ablog
行指å‘データベースã¯è¡Œå˜ä½ã§ãƒšãƒ¼ã‚¸(Oracle Database ã§ã„ã†ãƒ‡ãƒ¼ã‚¿ãƒ–ãƒãƒƒã‚¯)ã«ãƒ‡ãƒ¼ã‚¿ã‚’æ ¼ç´ã—ã¦ã„ã‚‹ã®ã«å¯¾ã—ã¦ã€åˆ—指å‘データベースã¯åˆ—ã”ã¨ã«ãƒšãƒ¼ã‚¸ã«æ ¼ç´ã—ã¦ã„る。クエリ実行時ã«çµæžœã‚»ãƒƒãƒˆã‚’è¿”ã™éš›ã«åˆ—別ã«ãƒãƒ©ãƒãƒ©ã®ãƒšãƒ¼ã‚¸ã«æ ¼ç´ã•ã‚Œã¦ã„るデータをã©ã†ã‚„ã£ã¦ã‚¿ãƒ—ル(レコード)ã«å¾©å…ƒã—ã¦ã„ã‚‹*1ã®ã‹ã¨æ€ã£ãŸãŒã‚„ã¯ã‚Šè¡ŒIDã®ã‚ˆã†ãªã‚‚ã®ã‚’æŒã£ã¦ã„るよã†ã 。 è¡ŒID 㯠C-Store ã§ã¯ pidã€MonetDB ã§ã¯ BAT(Binary Association Tables) ã® oid ã¨å‘¼ã°ã‚Œã¦ã„る。 The Design and Implementation of Modern Column-Oriented Database Systems NSM(N-ary Storage Model): 行方å‘ã§ãƒ–ãƒãƒƒã‚¯ï¼ˆãƒšãƒ¼ã‚¸ï¼‰ã«ãƒ‡ãƒ¼ã‚¿ã‚’æ ¼ç´ã™ã‚‹æ–¹å¼ DSM(Decomposition
MDM - Wikipedia
通常マスターデータã¯å€‹ã€…ã®æƒ…å ±ç®¡ç†ã‚¢ãƒ—リケーション内ã§å®šç¾©ã•ã‚Œã‚‹ãŒã€ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿ãŒé©åˆ‡ã«ç®¡ç†ã•ã‚Œã¦ã„ãªã„å ´åˆã‚„ã€è¤‡æ•°ã®æƒ…å ±ç®¡ç†ã‚·ã‚¹ãƒ†ãƒ ã§åŒã˜ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿ã‚’使用ã™ã‚‹å ´åˆã«ã¯ã€ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿é–“ã®æ•´åˆæ€§ãŒä¿ãŸã‚Œãªã„ã€ã¾ãŸã¯é‡è¤‡ãŒå˜åœ¨ã™ã‚‹ã¨ã„ã†äº‹æ…‹ãŒç™ºç”Ÿã—ã†ã‚‹ã€‚マスターデータã®é‡è¤‡ã‚„ä¸æ•´åˆã¯ã€ãã®ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿ã¨é–¢é€£ã™ã‚‹ãƒ‡ãƒ¼ã‚¿ãŒæ¤œç´¢ãƒ»åŒå®šã§ããªããªã‚‹ã€ã¨ã„ã£ãŸä¸éƒ½åˆã‚’生むãŸã‚ã€ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿è‡ªä½“を管ç†ã™ã‚‹å¿…è¦ã‹ã‚‰MDMã¨ã„ã†æ¦‚念ãŒç”Ÿã¾ã‚Œã¦ã„る。 MDM ã¯ã€ãƒ¡ã‚¤ãƒ³ãƒ•ãƒ¬ãƒ¼ãƒ 時代ã‹ã‚‰ç¶šãå¤ã„課題ã§ã‚ã‚Šã€ã‚·ã‚¹ãƒ†ãƒ 開発ã®åº¦ã«ãã®ã‚¢ãƒ—リケーションã«ãŠã„ã¦æ•´åˆæ€§ã‚’ã¨ã‚Šå“質をä¿ã¤ä»•çµ„ã¿ã‚’実装ã—ã¦ããŸã€‚æƒ…å ±ã‚·ã‚¹ãƒ†ãƒ ã«ãŠã‘るパッケージソフトウェアã®é©ç”¨ãŒæ‹¡å¤§ã™ã‚‹ã“ã¨ã§ã€ã‚¢ãƒ—リケーションå´ã§ã®ãƒžã‚¹ã‚¿ãƒ¼ãƒ‡ãƒ¼ã‚¿ç®¡ç†ãŒå›°é›£ã«ãªã£ã¦ããŸã“ã¨ã‹ã‚‰ã€MDMã‚’è¡Œã†ãŸã‚ã®ãƒ‘ッケージソフトウェア製å“も開発ã•ã‚Œã¦ããŸã€‚ 以下ã§è¡Œã†
Laboratory for Web Algorithmics
Introduction to LAW The Laboratory for Web Algorithmics (LAW) was established in 2002 at the Dipartimento di Scienze dell'Informazione (now merged in the Computer Science Department) of the Università degli studi di Milano. Research at LAW concerns all algorithmic aspects of the study of the web and of social networks. More in detail… High-performance web crawling UbiCrawler is a scalable, fault-t
カーãƒã‚®ãƒ¼ãƒ¡ãƒãƒ³ã®DBã«é–¢ã™ã‚‹è¬›ç¾©ãŒé¢ç™½ã„ã®ã§ãŠã™ã™ã‚ - ã ã„ãŸã„よãã‚ã‹ã‚‰ãªã„ブãƒã‚°
ã“ã“ã«æ›¸ãã“ã¨ã«ã‚ˆã£ã¦é€”ä¸ã§ã‚„ã‚られãªãã™ã‚‹ãƒ¡ã‚½ãƒƒãƒ‰ã§ã™ã€‚ ãƒãƒƒã‚«ãƒ¼ãƒ‹ãƒ¥ãƒ¼ã‚¹ã‚’眺ã‚ã¦ã„ãŸã‚‰ä»¥ä¸‹ã®ã‚ˆã†ãªCS系講義動画ã®ã¾ã¨ã‚リãƒã‚¸ãƒˆãƒªãŒæµã‚Œã¦ã„ã¾ã—ãŸã€‚ GitHub - Developer-Y/cs-video-courses: List of Computer Science courses with video lectures. ã¸ãƒ¼ã£ã¨æ€ã„ãªãŒã‚‰ä½•å€‹ã‹ãƒãƒã£ã¦ã¿ãŸã¨ã“ã‚以下ã«å‡ºãã‚ã—ã¾ã—ãŸã€‚ 15721.courses.cs.cmu.edu 英語ãŒï¼ˆè‡ªåˆ†ã«ã¨ã£ã¦ï¼‰èžãå–ã‚Šã‚„ã™ãã€å‹•ç”»ã®å“質（画質やスライドãŒã¡ã‚ƒã‚“ã¨è¦‹ãˆã‚‹ã‹ã©ã†ã‹ã¨ã„ã£ãŸéƒ¨åˆ†ï¼‰ã‚‚良ã„ã‚‚ã®ã§ã‹ã¤èˆˆå‘³ã®ã‚る内容ã§å‡ºæ¥ã‚Œã°ã‚¹ãƒ©ã‚¤ãƒ‰ã‚‚ãŠã—ゃれã§ãƒ»ãƒ»ãƒ»ã¨ãªã‚‹ã¨ãªã‹ãªã‹å°‘ãªã„ã§ã™ãŒã€ã“ã‚Œã¯ã‹ãªã‚Šè¦‹ã‚„ã™ã„ã§ã™ã€‚ スライドも概念図ãŒé »ç¹ã«ç™»å ´ã—ãŸã‚Šã—ã¦ã€ã“ã‚Œã ã‘ã§ã‚‚èžãå–ã‚Œãªã‹ã£ãŸéƒ¨åˆ†ãªã©ã‚’ã‹ãªã‚Šè£œå®Œã§ãã¾ã™ã€‚ スケジュールページ
Data lake - Wikipedia
Example of a database that can be used by a data lake (in this case structured data) A data lake is a system or repository of data stored in its natural/raw format,[1] usually object blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc.,[2] and transformed data used for tasks such as reporting, visualization, advance
Big News In Databases: Fall 2016
Big News In DatabasesThere’s been a lot of big news in 2016, also when it comes to databases. Let’s have a look at the really BIG news. MySQL and MariaDB Become ModernFor a long time, MySQL and MariaDB were mostly limited to the functionality of SQL-92. Now, both of them have decided to move forward by supporting the WITH and OVER clauses in their next major release (MySQL 8.0, MariaDB 10.2). The
Open sourcing the Microsoft JDBC Driver and Maven support
We are excited to announce the open sourcing of the Microsoft JDBC Driver for SQL Server! By open sourcing the driver, we hope to get quicker feedback from the community, release on a faster cadence, and develop new features based on the scenarios Java developers need to support. Please check out the announcement video. Open sourcing the driver includes: Java source code on GitHub under MIT licens
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マイクãƒã‚½ãƒ•ãƒˆã¯ãƒ‹ãƒ¥ãƒ¼ãƒ¨ãƒ¼ã‚¯ã§é–‹å‚¬ä¸ã®ã‚¤ãƒ™ãƒ³ãƒˆã€ŒConnect();// 2016ã€ã§ã€ã€ŒSQL Server on Linuxã€ãƒ‘ブリックプレビュー版ã®ãƒªãƒªãƒ¼ã‚¹ã‚’発表ã—ã¾ã—ãŸã€‚ Scott Guthrie announces #SQLServer public preview on #Linux live at Connect(); https://t.co/brSzFs0vEf #MSFTConnect pic.twitter.com/uj8E25N7in — Microsoft SQL Server (@SQLServer) 2016å¹´11月16æ—¥ SQL Server on Linuxã¯ã€ä»Šå¹´ã®3月ã«åŒç¤¾ãŒé–‹ç™ºã—ã¦ã„ã‚‹ã“ã¨ã‚’åˆã‚ã¦æ˜Žã‚‰ã‹ã«ã—ã¾ã—ãŸã€‚「SQL Server v.Nextã€ã¨å‘¼ã°ã‚Œã‚‹æ¬¡æœŸç‰ˆSQL Serverをターゲットã«ã—ã¦ãŠã‚Šã€2017å¹´ä¸ç›¤ã«ãƒªãƒªãƒ¼ã‚¹äºˆå®šã¨ã•ã‚Œã¦ã„
RethinkDB is shutting down - RethinkDB
Today I have sad news to share. After more than seven years of development, the company behind RethinkDB is shutting down. We worked very hard to make RethinkDB successful, but in spite of all our efforts we were ultimately unable to build a sustainable business. There is a lot of information to unpack – over the next few months, I’ll write about lessons learned so the startup community can benefi
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https://dl.acm.org/doi/book/10.1145/3226595
The Case for Automatic Database Administration using Deep Reinforcement Learning
GitHub - achiku/planter: Generate PlantUML ER diagram textual description from PostgreSQL tables
https://techcrunch.com/2017/08/29/salesforce-is-using-ai-to-democratize-sql-so-anyone-can-query-databases-in-natural-language/
SOFA: An Extensible Logical Optimizer for UDF-heavy Dataflows
Time-series-database-world
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