Spanner: Always-on, virtually unlimited scale databaseBuild intelligent apps with a single database that brings together relational, graph, key value, and search. No maintenance windows mean uninterrupted mission-critical apps.
Mesos, Omega, Borg: A Survey : umbrant
Google recently unveiled one of their crown jewels of system infrastructure: Borg, their cluster scheduler. This prompted me to re-read the Mesos and Omega papers, which deal with the same topic. I thought it'd be interested to do a compare and contrast of these systems. Mesos gets credit for the groundbreaking idea of two-level scheduling, Omega improved upon this with an analogy from databases,
Google on Latency Tolerant Systems: Making a Predictable Whole Out of Unpredictable Parts  - High Scalability -
In Taming The Long Latency Tail we covered Luiz Barroso’s exploration of the long tail latency (some operations are really slow) problems generated by large fanout architectures (a request is composed of potentially thousands of other requests). You may have noticed there weren’t a lot of solutions. That’s where a talk I attended, Achieving Rapid Response Times in Large Online Services (slide deck
SpannerãŠå‹‰å¼·ãƒ¡ãƒ¢ - スティルãƒã‚¦ã‚¹ã®æ›¸åº«ã®æ›¸åº«
SpannerãŠå‹‰å¼·ãƒ¡ãƒ¢ã§ã™ã€‚ã‹ãªã‚Šä¹…々ã®æŠ€è¡“系エントリã 。。 æœèµ·ãã¦Twitterã¿ã¦ãŸã‚‰@ichiro_satoh先生ã®ã“ã‚“ãªã¤ã¶ã‚„ããŒã€‚ ç¾æ™‚点ã§ã¯Google Spannerã®ä¸€ç•ªè©³ã—ã„資料ã‹ã‚‚。berlinbuzzwords.de/sites/berlinbu…— ICHIRO SATOHã•ã‚“ (@ichiro_satoh) 6月 6, 2012 。。やã£ã±ã‚ŠGoogleã®ã‚¤ãƒ³ãƒ•ãƒ©æƒ…å ±ã¯å¦ä¼šç™ºè¡¨ã§æµã‚Œã¦ãるケースãŒå¤šã„ãªãã¨æ€ã„ã¤ã¤ã€å…ˆæ—¥å…¬é–‹ã•ã‚ŒãŸF1（Googleè¦æ¨¡ã§ã‚¹ã‚±ãƒ¼ãƒ«ã™ã‚‹RDB。AdWords用ã«ä½¿ã‚ã‚Œã¦ã‚‹ï¼‰ã§ã‚‚SpannerãŒé‡è¦ãªã‚«ã‚®ã‚’æ¡ã£ã¦ã„ã‚‹ã®ã§ã€ã¤ã„カッã¨ãªã£ã¦ã‚¹ãƒ©ã‚¤ãƒ‰ã®è¦ç‚¹ã‚’訳ã—ã¦ã¿ã¾ã—ãŸã€‚ 原文ã¯ã“ã‚Œã§ã™ï¼šBuilding Spanner - Better clocks → stronger semantics（セッションã®ãƒ“デオ） 一行ã«è¦ç´„ã™ã‚‹ã¨ã€
Google Research Publication: Paxos Made Live – An Engineering Perspective
Paxos Made Live &ndash An Engineering Perspective Tushar Chandra, Robert Griesemer, and Joshua Redstone Abstract We describe our experience building a fault-tolerant data-base using the Paxos consensus algorithm. Despite the existing literature in the field, building such a database proved to be non-trivial. We describe selected algorithmic and engineering problems encountered, and the solutions
1
ランã‚ング
ランã‚ング
メンテナンス
リリースã€éšœå®³æƒ…å ±ãªã©ã®ã‚µãƒ¼ãƒ“スã®ãŠçŸ¥ã‚‰ã›
最新ã®äººæ°—エントリーã®é…ä¿¡
j次ã®ãƒ–ックマーク
kå‰ã®ãƒ–ックマーク
lã‚ã¨ã§èªã‚€
eコメント一覧を開ã
oページを開ã
Large-scale Incremental Processing Using Distributed Transactions and Notifications
Google Spannerã¾ã¨ã‚
Think Like a {Vertex, Column, Parallel Collection}
Google Code University - Google Code
Dapper, a Large-Scale Distributed Systems Tracing Infrastructure
{{#tags}}- {{label}}
{{/tags}}