Introducing Chaos to C*
by Christos Kalantzis, Minh Do, Homajeet Cheema, and Roman Vasilyev One of the practices that sets Netflix apart from most companies is the belief that you can only know how good your software stack is by trying to making it fail. We’ve blogged about Chaos Monkey and how it helps identify deficiencies in your software stack. Netflix, has implemented Chaos Monkey on our mid-tier stateless systems,
Apache Cassandraã¨Amazon DynamoDBã®æ¯”較 | DevelopersIO
2012/1/23 updated Apache Cassandraã¨ã¯ï¼Ÿ Apache Cassandraã¯ã€2007å¹´ã«Amazonã«ã‚ˆã£ã¦ç™ºè¡¨ã•ã‚ŒãŸDynamoã«é–¢ã™ã‚‹è«–æ–‡ã‹ã‚‰ã‚¤ãƒ³ã‚¹ãƒ‘イアã•ã‚Œã¦é–‹ç™ºã•ã‚ŒãŸNoSQL分散データベースã§ã™ã€‚2008å¹´ã«Facebook社ã«ã‚ˆã‚Šã‚ªãƒ¼ãƒ—ンソースã¨ã—ã¦å…¬é–‹ã•ã‚Œã¾ã—ãŸã€‚スケーラビリティã¨é«˜å¯ç”¨æ€§ã‚’求ã‚ã¦ã„ã‚‹æ–¹ã«ã¯é©ã—ã¦ã„ã¾ã™ã€‚ç·šå½¢ã®æ‹¡å¼µæ€§ã¨ãƒ•ã‚©ãƒ¼ãƒ«ãƒˆãƒˆãƒ¬ãƒ©ãƒ³ãƒˆã‚’å‚™ãˆã¦ã„ã¦ã€ã‚¯ãƒ©ã‚¦ãƒ‰ã‚„オンプレミス上ã§æ§‹ç¯‰ã™ã‚‹ã“ã¨ãŒã§ãã€ãƒŸãƒƒã‚·ãƒ§ãƒ³ã‚¯ãƒªãƒ†ã‚£ã‚«ãƒ«ãªãƒ‡ãƒ¼ã‚¿ã‚’ä¿ç®¡ã™ã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚Cassandraã¯ã€è¤‡æ•°ã®ãƒ‡ãƒ¼ã‚¿ã‚»ãƒ³ã‚¿ãƒ¼ã§ã®ç¨¼åƒã‚’サãƒãƒ¼ãƒˆã—ã¦ã„ã¦ã€ä½Žã„レイテンシーã§ã‚„ã‚Šå–ã‚Šã‚’è¡Œã†äº‹ãŒå‡ºæ¥ã¾ã™ã€‚万ãŒä¸€ã®ç½å®³æ™‚ã«ã‚‚安心ã§ã™ã€‚ Amazon DynamoDBã¨ã¯ï¼Ÿ Amazon DynamoDBã¯ã€ã‚·ãƒ¼ãƒ レスã«æ‹¡å¼µãŒã§ãã€é«˜é€Ÿã§äºˆæ¸¬å¯èƒ½ãªãƒ‘フォーマンスをæä¾›
Cassandra入門ã¨ã€ã•ã‚‰ã«è©³ã—ã知るãŸã‚ã®ãƒªã‚½ãƒ¼ã‚¹é›†
クラウド時代ã®æ–°ã—ã„データベースã¨ã—ã¦ã€éžãƒªãƒ¬ãƒ¼ã‚·ãƒ§ãƒŠãƒ«ãªæ§‹é€ ã‚’æŒã¤NoSQLデータベースãŒè©±é¡Œã«ãªã£ã¦ã„ã¾ã™ï¼ˆNoSQLï¼Not Only SQL。命åã®çµŒç·¯ã¯ã“ã¡ã‚‰ï¼‰ã€‚ãã®NoSQLã®ä¸ã§ã€ã‚‚ã£ã¨ã‚‚注目ã•ã‚Œã¦ã„るデータベースã®1ã¤ãŒApacheã®Cassandraã§ã™ã€‚ Cassandraã¯ã€Facebookã§å¤§è¦æ¨¡ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã®ãŸã‚ã«é–‹ç™ºã•ã‚Œã€ãã®å¾Œã‚ªãƒ¼ãƒ—ンソースã¨ãªã‚Šã€ç¾åœ¨ã§ã¯Apache Software Foundationã®ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã¨ã—ã¦é–‹ç™ºã•ã‚Œã¦ã„ã¾ã™ã€‚ ç¾åœ¨ã€Cassandraã¯Facebookã‚„Diggãªã©ã§ä½¿ã‚ã‚Œã¦ã„ã‚‹ã€ã‚‚ã—ãã¯ä½¿ã†ã“ã¨ãŒæ¤œè¨Žã•ã‚Œã¦ã„ã‚‹ã¨ã•ã‚Œã€Twitterã§ã‚‚（ツイートデータã®æ ¼ç´ã«ã¯ä½¿ã‚ã‚Œãªã„よã†ã§ã™ãŒã€ãれ以外ã®ç”¨é€”ã§ï¼‰åˆ©ç”¨ã•ã‚Œã¦ã„ã¾ã™ã€‚ Twitterã¨DiggãŒNoSQLã®ã€ŒCassandraã€ã‚’é¸ã¶ç†ç”± TwitterãŒã€Cassandr
NoSQL at Netflix
This is Yury Izrailevsky, Director of Cloud and Systems Infrastructure here at Netflix. As Netflix moved into the cloud, we needed to find the appropriate mechanisms to persist and query data within our highly distributed infrastructure. Our goal is to build fast, fault tolerant systems at Internet scale. We realized that in order to achieve this goal, we needed to move beyond the constraints of t
Hector – a Java Cassandra client | PrettyPrint.me
UPDATE: I added a downloads section, so you may simply download the jar and sources if you’re not into git or maven. UPDATE 2: I added license clarification; the license it MIT, which is the most permissive license I know of and basically lets you do anything with the software: use it commercially or uncommercially, copy it, fork it (but I’ll be happy to accept patches and committers) and whatnot.
Digg Not Likely to Give Up on Cassandra – Old GigaOm
Cassandra was a tragic figure in Greek myth. She could hear the future and thus was able to foretell what was coming next (usually death and destruction). It’s no surprise that no one wanted her hanging around. It’s ironic that an open-source NoSQL software of the same name has often found itself amidst controversy. Today, Cassandra was blamed for scaling (and availability) problems at Digg, which
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GitHub - riptano/brisk: DataStax Brisk Distribution
Cassandra Range Query Using CompositeType
Getting started using CQL | DataStax Cassandra 1.2 Documentation
[CASSANDRA-2597] inconsistent implementation of 'cumulative distribution function' for Exponential Distribution - ASF JIRA
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