GitHub - aws/clock-bound: Used to generate and compare bounded timestamps.
ClockBound allows you to generate and compare bounded timestamps that include accumulated error as reported from the local chronyd process. On every request, ClockBound uses two pieces of information: the current time and the associated absolute error range, which is also known as the clock error bound. This means that the “true†time of a ClockBound timestamp is within a set range. Using ClockBou
DDSketch: A fast and fully-mergeable quantile sketch with relative-error guarantees
Summary statistics such as the mean and variance are easily maintained for large, distributed data streams, but order statistics (i.e., sample quantiles) can only be approximately summarized. There is extensive literature on maintaining quantile sketches where the emphasis has been on bounding the rank error of the sketch while using little memory. Unfortunately, rank error guarantees do not precl
Scaling Strongly Consistent Replication
Strong consistency replication helps keep application logic simple and provides significant benefits for correctness and manageability. Unfortunately, the adoption of strongly-consistent replication protocols has been curbed due to their limited scalability and performance. To alleviate the leader bottleneck in strongly-consistent replication protocols, we introduce Pig, an in-protocol communicati
Keeping CALM: When Distributed Consistency is Easy
A key concern in modern distributed systems is to avoid the cost of coordination while maintaining consistent semantics. Until recently, there was no answer to the question of when coordination is actually required. In this paper we present an informal introduction to the CALM Theorem, which answers this question precisely by moving up from traditional storage consistency to consider properties of
分散ã‚ューã¨ã„ã†åã®è‹¦ã—ã¿ - Software Transactional Memo
TL;DR 分散システムã«ãŠã„ã¦ã‚ューを導入ã™ã‚‹å ´åˆã€æœ¬å½“ã«ã‚ューãŒå¿…è¦ãªã®ã‹å†è€ƒã™ã¹ã。ãã“ãŒåœ°ç„ã®å…¥ã‚Šå£ã ã‹ã‚‰ã€‚ システムã®æŠ½è±¡ コンピュータã®ä¸–ç•Œã¯ã€æœ¬æ¥ã¯0ã¨1ã®ä¿¡å·ã®ç¾…列ãŒé£›ã³äº¤ã†ç„¡æ©Ÿè³ªãªã‚‚ã®ã§ã‚る。ã§ã‚‚人類ã¯ä¿¡å·ã ã‘ã§ã™ã¹ã¦ã‚’語らãšã€æ§˜ã€…ãªå–©ãˆã‚’定義ã—ã¦ããŸã€‚ãã‚Œã¯ãƒ‡ã‚¹ã‚¯ãƒˆãƒƒãƒ—・ウィンドウ・マウスカーソルã¨ã„ã£ãŸã‚°ãƒ©ãƒ•ã‚£ã‚«ãƒ«ãªè¡¨ç¾ã«ç•™ã¾ã‚‰ãšã€ãƒ‘ケットやカプセル化ã¨ã„ã£ãŸç”¨èªžã«ãƒãƒƒã‚¯ãƒ»ã‚ュー・リスト・木ãªã©ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã‚„ãƒ‡ãƒ¼ã‚¿æ§‹é€ ã®ä¸–ç•Œã«ã‚‚自然ã«æº¶ã‘込んã§ã„る。ã“れらã¯ã™ã¹ã¦äººé–“ã®ç†è§£ã‚’助ã‘ã‚‹ãŸã‚ã®å–©ãˆè©±ã«éŽãŽãšã€ã“ã®å–©ãˆã“ããŒäººé–“ã®ã‚ˆã‚Šç›´æ„Ÿçš„ãªç†è§£ã‚’ã‚‚ãŸã‚‰ã™ä¸€æ–¹ã§ã€ç™ºæƒ³ã®åˆ¶ç´„を生ã¿å‡ºã—ã¦ããŸã€‚ 人間ãŒå¤§ããªã‚·ã‚¹ãƒ†ãƒ を作るã¨ãも何らã‹ã®å–©ãˆã‚’用ã„ã¦ã‚·ã‚¹ãƒ†ãƒ 全体を整ç†ã™ã‚‹ã€‚アーã‚テクãƒãƒ£ã®ã€Œãƒãƒ³ãƒçµµã€ã‚’æã„ã¦æƒ…å ±å…±æœ‰ã‚’ã™ã‚‹ã®ã¯ä¼æ¥ã«å‹¤ã‚ã¦ã„ã‚Œã°çµŒé¨“ã—ãŸäººã‚‚多ã„ã ã‚ã†ã€‚パワーãƒã‚¤ãƒ³
分散ãƒãƒƒã‚¯ã¨ã„ã†åã®éŽã¡ - Software Transactional Memo
 TL;DR; 「分散ãƒãƒƒã‚¯ã€ãŒåˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã®è¨è¨ˆå›³ã«ç™»å ´ã—ãŸæ™‚ ã ã„ãŸã„ãã®è¨è¨ˆã¯é–“é•ã£ã¦ã„ã¦æœ¬å½“ã«å¿…è¦ãªã‚‚ã®ã¯ãƒˆãƒ©ãƒ³ã‚¶ã‚¯ã‚·ãƒ§ãƒ³ã 並行システムを実装ã™ã‚‹éš›ã«ãƒãƒƒã‚¯ã‚’用ã„ã‚‹ã®ã¯ã¨ã¦ã‚‚自然ãªã“ã¨ã 。 僕も普段ã¯ãƒãƒƒã‚¯ãƒ•ãƒªãƒ¼ç³»ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã«è©³ã—ã„ã¨è¨€ã‚ã‚ŒãŒã¡ã ãŒçŸ¥è˜é‡ã§ã„ã£ãŸã‚‰å®Ÿã¯ãƒãƒƒã‚¯ç³»ã®æ–¹ãŒå¤šãè“„ãˆã¦ã„ã‚‹ã‹ã‚‚知れãªã„。 分散システムã¯ä¸¦è¡Œã‚·ã‚¹ãƒ†ãƒ ã§ã‚ã‚‹ã“ã¨ãŒå¤šã„ã®ã§ã€ãã®ä¸ã«ãƒãƒƒã‚¯ãŒç™»å ´ã™ã‚‹ã®ã¯ã¨ã¦ã‚‚自然ãªç™ºæƒ³ã§ã‚る。 よã「分散ã€ã€Œä¸¦è¡Œã€ã€Œä¸¦åˆ—ã€ã®è¨€è‘‰ã®å®šç¾©ãŒã”ã£ã¡ã‚ƒã«ãªã£ã¦ã„るケースãŒã‚ã‚Šã€ã“ã®è¨˜äº‹ã®ä¸»é¡Œã«ã—ãŸã„ã‚ã‘ã§ã¯ãªã„ã®ã§æ·±ãã¯è¨€åŠã—ãªã„ãŒã€åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã¯ç’°å¢ƒãªã©ã®è¦å› ã§çªå¦‚ã¨ã—ã¦å‚åŠ è€…ãŒéŸ³ä¿¡ä¸é€šã«ãªã£ãŸã‚Šå¾©æ´»ã—ãŸã‚Šã™ã‚‹ç‚¹ã§ä¸¦è¡Œã‚·ã‚¹ãƒ†ãƒ ã¨å¤§ããç•°ãªã‚‹ã€‚ 並行システムã¨åŒã˜ãƒŽãƒªã§åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã‚’è¨è¨ˆã—よã†ã¨ã—ãŸéš›ã«é™¥ã‚‹é »å‡ºã®éŽã¡ãŒã€Œåˆ†æ•£ãƒãƒƒã‚¯ã€ã§ã‚る。ãã®ã‚¢ã‚¤ãƒ‡ã‚¢ã¯ã¨ã¦ã‚‚ç°¡å˜ã§
PRINCIPLES OF CHAOS ENGINEERING - Principles of chaos engineering
PRINCIPLES OF CHAOS ENGINEERING Last Update: 2019 March (changes) Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production. Advances in large-scale, distributed software systems are changing the game for software engineering. As an industry, we are quick to adopt practices that increase
分散深層å¦ç¿’ @ NIPS'17
NIPS2017èªã¿ä¼šã§ã®ç™ºè¡¨è³‡æ–™ã§ã™ã€‚DL at Supercomputer Scale Workshop ã‚’é¡Œæã«ã€2017 å¹´ã®åˆ†æ•£æ·±å±¤å¦ç¿’ã®é€²å±•ã«ã¤ã„ã¦ã¾ã¨ã‚ã¾ã—ãŸã€‚ NIPS2017èªã¿ä¼š@PFN - connpass https://connpass.com/event/76552/
SyncFree - Home
Global-scale applications, such as virtual wallets, advertising platforms, social networks, online games, or collaboration networks, require consistency across distributed data items. As networked users, objects, devices, and sensors proliferate, the consistency issue is increasingly acute for the software industry. Both sides of the classical alternative, requiring to choose between consistency a
Eventual Consistencyã¾ã§ã®ä¸€è²«æ€§å›³è§£å¤§å…¨ - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? TL;DR; Eventual Consistencyã¨ã‹è¨€ã„ãªãŒã‚‰ã©ã†ã›ã‚‚ã£ã¨ã¾ã¨ã‚‚ãªä¸€è²«æ€§å®Ÿè£…ã—ã¦ã‚‹ã“ã¨ã¯ã‚ˆãã‚ã‚‹ã‚“ã ã‹ã‚‰ã¿ã‚“ãªé©åˆ‡ãªåå‰ã‚’使ãŠã†ãœã€‚ ãªãœã“ã®è¨˜äº‹ã‚’書ãã®ã‹ NoSQLã®æ–‡è„ˆã«ãŠã„ã¦ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã¨ã®ãƒˆãƒ¬ãƒ¼ãƒ‰ã‚ªãƒ•ã§Eventual Consistencyã¨ã„ã†ç”¨èªžã¯çµæ§‹ãªé »åº¦ã§å‡ºã¦ãる。 ACIDã«å¯¾æŠ—ã—ã¦BASE(Basicaly Avalilable, Soft state, Eventual consistency)ãªã‚“ã¦è¨€è‘‰ãŒå‡ºã¦ããŸã‚Šã€CAP定ç†ã®ä¸ã®Aã¨Pã ã¨è¨€ã£ã¦ã¿ãŸã‚Šã€åˆ†æ•£ã‚·ã‚¹ãƒ†ãƒ ã®ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リテ
OLTP Database, MySQL And PostgreSQL Managed Database - Amazon Aurora - AWS
Amazon Aurora Unparalleled high performance and availability at global scale for PostgreSQL, MySQL, and DSQL Aurora has 5x the throughput of MySQL and 3x of PostgreSQL with full PostgreSQL and MySQL compatibility. Aurora also offers DSQL, the fastest distributed SQL database that is PostgreSQL-compatible. Aurora is designed for up to 99.999% multi-Region availability. With Aurora DSQL, Aurora prov
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GitHub - oceanbase/oceanbase: OceanBase is an enterprise distributed relational database with high availability, high performance, horizontal scalability, and compatibility with SQL standards.
GitHub - icecc/icecream: Distributed compiler with a central scheduler to share build load
GitHub - vmware/concord-bft: Concord byzantine fault tolerant state machine replication library
GitHub - apple/foundationdb: FoundationDB - the open source, distributed, transactional key-value store
GitHub - ray-project/ray: Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
GitHub - etcd-io/zetcd: Serve the Apache Zookeeper API but back it with an etcd cluster
GitHub - baidu/bigflow: Baidu Bigflow is an interface that allows for writing distributed computing programs and provides lots of simple, flexible, powerful APIs. Using Bigflow, you can easily handle data of any scale. Bigflow processes 4P+ data inside Ba
GitHub - microsoft/rDSN: Robust Distributed System Nucleus (rDSN) is an open framework for quickly building and managing high performance and robust distributed systems.
2017 Jim Gray Award Talk: Coordination Avoidance in Distributed Databases
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