イベントストリームKafkaã¨ãƒ¯ãƒ¼ã‚¯ãƒ•ãƒãƒ¼ã‚¨ãƒ³ã‚¸ãƒ³Zeebe
Spring Bootã«ã‚ˆã‚‹APIãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰æ§‹ç¯‰å®Ÿè·µã‚¬ã‚¤ãƒ‰ 第2版 何åƒäººã‚‚ã®é–‹ç™ºè€…ãŒã€InfoQã®ãƒŸãƒ‹ãƒ–ック「Practical Guide to Building an API Back End with Spring Bootã€ã‹ã‚‰ã€Spring Bootを使ã£ãŸREST API構築ã®åŸºç¤Žã‚’å¦ã‚“ã 。ã“ã®æœ¬ã§ã¯ã€å‡ºç‰ˆæ™‚ã«æ–°ã—ãリリースã•ã‚ŒãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã‚ã‚‹ Spring Boot 2 を使用ã—ã¦ã„る。ã—ã‹ã—ã€Spring Boot3ãŒæœ€è¿‘リリースã•ã‚Œã€é‡è¦ãªå¤‰...
GitHub - redpanda-data/console: Redpanda Console is a developer-friendly UI for managing your Kafka/Redpanda workloads. Console gives you a simple, interactive approach for gaining visibility into your topics, masking data, managing consumer groups, and e
Message viewer: Explore your topics' messages in our message viewer through ad-hoc queries and dynamic filters. Find any message you want using JavaScript functions to filter messages. Supported encodings are: JSON, Avro, Protobuf, CBOR, XML, MessagePack, Text and Binary (hex view). The used encoding (except Protobuf and CBOR) is recognized automatically. Consumer groups: List all your active cons
Kafkaを利用ã—ãŸã‚¸ãƒ§ãƒ–ã‚ューライブラリ「Decatonã€ã®æ´»ç”¨äº‹ä¾‹
先日 LINE ãŒé–‹ç™ºã™ã‚‹ãƒ©ã‚¤ãƒ–ラリ Decaton ㌠OSS ã¨ã—ã¦å…¬é–‹ã•ã‚Œã¾ã—ãŸã€‚ Decaton 㯠Kafka を利用ã—ãŸã‚¸ãƒ§ãƒ–ã‚ューライブラリã§ã€LINE 社内ã§å¹…広ã利用ã•ã‚Œã¦ã„ã¾ã™ã€‚ GitHub - line/decaton: High throughput asynchronous task processing on Apache Kafka 今回ã®è¨˜äº‹ã§ã¯ã€LINE 㧠Decaton ãŒã©ã®ã‚ˆã†ã«åˆ©ç”¨ã•ã‚Œã¦ã„ã‚‹ã‹ã€å®Ÿéš›ã«åˆ©ç”¨ã•ã‚Œã¦ã„るプãƒãƒ€ã‚¯ãƒˆã®å®Ÿä¾‹ã‚’交ãˆã¦ç´¹ä»‹ã—ã¾ã™ã€‚ Decaton ã¨ã¯? Decaton 㯠LINE 社内ã§éžåŒæœŸå‡¦ç†ã‚’è¡Œã†éš›ã®ã‚¸ãƒ§ãƒ–ã‚ューã¨ã—ã¦åˆ©ç”¨ã•ã‚Œã¦ã„るライブラリã§ã€ãƒ‡ãƒ¼ã‚¿ã‚¹ãƒˆã‚¢ã¨ã—㦠Kafka を利用ã—ã¦ã„ã¾ã™ã€‚ Kafka ã«ã¯ã€ã‚¹ãƒˆãƒªãƒ¼ãƒ 処ç†ã‚’扱ã†å…¬å¼ã®ãƒ©ã‚¤ãƒ–ラリã¨ã—㦠Kafka Streams ãŒã‚ã‚Šã¾ã™ã€‚ã—ã‹ã—ã€Kafka
Building A Relational Database Using Kafka
In a previous post, I showed how Kafka can be used as the persistent storage for an embedded key-value store, called KCache. Once you have a key-value store, it can be used as the basis for other models such as documents, graphs, and even SQL. For example, CockroachDB is a SQL layer built on top of the RocksDB key-value store and YugaByteDB is both a document and SQL layer built on top of RocksDB.
マイクãƒã‚µãƒ¼ãƒ“スã¨ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã®ãªãœ [概è¦ç·¨] - 赤帽エンジニアブãƒã‚°
レッドãƒãƒƒãƒˆã§ã‚¤ãƒ³ãƒ†ã‚°ãƒ¬ãƒ¼ã‚·ãƒ§ãƒ³ã®ãŸã‚ã®ãƒŸãƒ‰ãƒ«ã‚¦ã‚§ã‚¢ã®ãƒ†ã‚¯ãƒ‹ã‚«ãƒ«ã‚µãƒãƒ¼ãƒˆã‚’担当ã—ã¦ã„る山下ã§ã™ã€‚ 最近ã¯ãƒžã‚¤ã‚¯ãƒã‚µãƒ¼ãƒ“スã§ã‚·ã‚¹ãƒ†ãƒ を開発ã—ã¦ã„ã‚‹ã¨ã„ã†è©±ã‚‚よãèžãよã†ã«ãªã£ã¦ãã¾ã—ãŸã€‚ã§ã¯ãã“ã§ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã€ãã—ã¦Kafkaを使ã£ã¦ã¾ã™ã§ã—ょã†ã‹ï¼Ÿãƒžã‚¤ã‚¯ãƒã‚µãƒ¼ãƒ“スã§ã¯ä½•æ•…ã‹RESTã°ã‹ã‚ŠãŒä¸–ã®ä¸ã«æ³¨ç›®ã•ã‚Œã¦ã—ã¾ã†ã“ã¨ã‚‚多ã„ãŸã‚ã«ã€ä»Šå›žã¯ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°æŽ¨ã—ã®å†…容ã«ã—ã¦ã„ã¾ã™ã€‚ マイクãƒã‚µãƒ¼ãƒ“スã§ã¯ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã‚’用ã„ãŸã‚³ãƒžãƒ³ãƒ‰ã‚„イベントã“ãä¸å¿ƒã§ã‚ã£ã¦ä¸å¯æ¬ ã§ã™ã€‚マイクãƒã‚µãƒ¼ãƒ“スã®ä¸ã§ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã¯ã©ã®ã‚ˆã†ã«åˆ©ç”¨ã•ã‚Œã€ãã—ã¦ãªãœå¿…è¦ãªã®ã§ã—ょã†ã‹ã€‚今回ã¯ã€Œãƒžã‚¤ã‚¯ãƒã‚µãƒ¼ãƒ“スã¨ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã®ãªãœ [概è¦ç·¨]ã€ã¨é¡Œã—ã¦ãれを概観ã—ã¦ã„ãã¾ã™ã€‚ Kafkaã®ç°¡å˜ãªãŠã•ã‚‰ã„ ã©ã“ã§ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°ã¯åˆ©ç”¨ã•ã‚Œã‚‹ã®ã‹ï¼Ÿ RESTã¯ãŠæ‰‹è»½ãªè§£æ±ºç–？ ãªãœãƒžã‚¤ã‚¯ãƒã‚µãƒ¼ãƒ“スã«ãƒ¡ãƒƒã‚»ãƒ¼ã‚¸ãƒ³ã‚°(Kafka)ãŒå¿…
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KIP-500: Replace ZooKeeper with a Self-Managed Metadata Quorum - Apache Kafka - Apache Software Foundation
KIP-500: Replace ZooKeeper with a Self-Managed Metadata Quorum StatusCurrent state: Accepted Discussion thread:Â here JIRA: KAFKA-9119 - Getting issue details... STATUS Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast). MotivationCurrently, Kafka uses ZooKeeper to store its metadata about partitions and brokers, and to elect a bro
３週間ã§å‡ºæ¥ãŸEvent Sourcingã§CQRSãªã‚¢ãƒ¼ã‚テクãƒãƒ£ä¸Šã§ã®HBaseã®upgrade - kubell Creator's Note
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Open sourcing Brooklin: Near real-time data streaming at scale
Open Source Open sourcing Brooklin: Near real-time data streaming at scale Editor's note: This blog has been updated. Brooklin—a distributed service for streaming data in near real-time and at scale—has been running in production at LinkedIn since 2016, powering thousands of data streams and over 2 trillion messages per day. Today, we are pleased to announce the open-sourcing of Brooklin and that
俺ã®ä¸ã§ä»ŠKafkaãŒå®Œå…¨ã«ç†±ã„
Hosting Casual Talks #5 ã§ä»Šå¾Œã®è©±ã‚’ã—ã¾ã—ãŸã€‚
Google Cloud Platform and Confluent partner to deliver a managed Apache Kafka service | Google Cloud Blog
Google Cloud Platform and Confluent partner to deliver a managed Apache Kafka service One of the most common requests we get from customers migrating to GCP is whether we’ll offer a managed version of Apache Kafka. This comes as no surprise, as Kafka has become a leading open-source solution for event streaming and is increasingly the primary messaging platform for event-driven organizations
Apache Kafka 0.11 ã® Exactly Once Semantics
This document discusses exactly once semantics in Apache Kafka 0.11. It provides an overview of how Kafka achieved exactly once delivery between producers and consumers. Key points include: - Kafka 0.11 introduced exactly once semantics with changes to support transactions and deduplication. - Producers can write in a transactional fashion and receive acknowledgments of committed writes from broke
Kafka Replication Deep Dive | Folioscope
ã“ã®è¨˜äº‹ã¯ Distributed computing Advent Calendar 2017 20 日目ã®è¨˜äº‹ã§ã™ã€‚ Kafka ã®ãƒ¬ãƒ—リケーションã¯ã€é«˜å¯ç”¨æ€§ã¨é«˜ä¿¡é ¼æ€§ã‚’実ç¾ã™ã‚‹ãŸã‚ã®ã€é‡è¦ãªæ©Ÿèƒ½ã® 1 ã¤ã§ã™ã€‚ ã“ã®è¨˜äº‹ã§ã¯ã€Kafka ã®ãƒ¬ãƒ—リケーションã®ä»•çµ„ã¿ã«ã¤ã„ã¦ç´¹ä»‹ã—ã¾ã™ã€‚ レプリケーションã®åŸºç¤Ž Kafka ã®ãƒ‡ãƒ¼ã‚¿ã‚¹ãƒˆãƒªãƒ¼ãƒ ã®æœ€å°å˜ä½ã¯ãƒ‘ーティションã§ã™ã€‚ã¾ãŸãƒ¬ãƒ—リケーションもパーティションå˜ä½ã§è¡Œã‚ã‚Œã¾ã™ã€‚ Kafka ã®ãƒ¬ãƒ—リケーションã®æƒ…å ±ã¯ã€ZooKeeper 上ã«ä¿å˜ã•ã‚Œã¦ã„ã¾ã™ã€‚ レプリカã®é…ç½®æƒ…å ±ã¯ã€${prefix}/brokers/topics/${topic} ã« JSON ã§ä¿å˜ã•ã‚Œã¾ã™ã€‚ { "version": 1, "partitions": { "0": [0, 1], "1": [1, 2] } } トピック作æˆæ™‚ã«ã¯ãƒ¬ãƒ—リカ数を指定ã—
Apache KafkaãŒã¤ã„ã«ãƒãƒ¼ã‚¸ãƒ§ãƒ³1.0ã«åˆ°é”ã€ã‚ªãƒ¼ãƒ—ンソース化ã‹ã‚‰ç´„7年。大é‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’高速ã«åŽé›†ã§ãるメッセージ処ç†ã‚·ã‚¹ãƒ†ãƒ
大é‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’高速ã«åŽé›†ã§ãるメッセージ処ç†ã‚·ã‚¹ãƒ†ãƒ ã¨ã—ã¦çŸ¥ã‚‰ã‚Œã‚‹ã€ŒApaceh Kafkaã€ãŒã€æ£å¼ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã¨ãªã‚‹ã€ŒApache Kafka 1.0ã€ã«11月1日付ã‘ã§åˆ°é”ã—ãŸã“ã¨ãŒã€Kafkaã®ä¸»è¦ãªé–‹ç™ºå…ƒã§ã‚ã‚‹Confluentã‹ã‚‰ç™ºè¡¨ã•ã‚Œã¾ã—ãŸã€‚ Apache Kafkaã¯ã‚¹ã‚±ãƒ¼ãƒ©ãƒ“リティã«å„ªã‚Œã€å¤§é‡ã®ãƒ‡ãƒ¼ã‚¿ã‚’リアルタイムã«å‡¦ç†ã™ã‚‹æ©Ÿèƒ½ã‚’å‚™ãˆãŸã‚½ãƒ•ãƒˆã‚¦ã‚§ã‚¢ã§ã™ã€‚ ã•ã¾ã–ã¾ãªã‚¢ãƒ—リケーションやシステムã‹ã‚‰é€ã‚‰ã‚Œã¦ãã‚‹ãƒã‚°ã‚„大é‡ã®ã‚»ãƒ³ã‚µãƒ¼ãªã©ã‹ã‚‰ç”Ÿæˆã•ã‚Œã‚‹ãƒ‡ãƒ¼ã‚¿ãªã©ã€ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ ã«é€ä¿¡ã•ã‚Œã¦ãるストリームデータをã„ã£ãŸã‚“Kafkaã§å—ã‘æ¢ã‚ã€ãれをã¾ã¨ã‚ã¦Hadoopãªã©ã®åˆ†æžã‚¨ãƒ³ã‚¸ãƒ³ã«æ¸¡ã—ã¦ãƒ‡ãƒ¼ã‚¿ã®åˆ†æžã‚’è¡Œã†ã€ã¨ã„ã£ãŸå½¢ã§ä½¿ã‚ã‚Œã¾ã™ã€‚ ã¾ãŸã€ãã®å称ã¯ã€Œå¤‰èº«ã€ãªã©ã§çŸ¥ã‚‰ã‚Œã‚‹ä½œå®¶ã®ãƒ•ãƒ©ãƒ³ãƒ„・カフカã«ã¡ãªã‚“ã ã‚‚ã®ã¨ã•ã‚Œã¦ã„ã¾ã™ã€‚ ãƒãƒ¼ã‚¸ãƒ§ãƒ³1.0ã§ã¯ã€Stream APIã®å¼·åŒ–ã€Jav
Apache Kafka Goes 1.0
It has been seven years since we first set out to create the distributed streaming platform we know now as Apache Kafka®. Born initially as a highly scalable messaging system, Apache Kafka has evolved over the years into a full-fledged distributed streaming platform for publishing and subscribing, storing, and processing streaming data at scale and in real-time. Since we first open-sourced Apache
イベントアーã‚テクãƒãƒ£ã‚’é¸æŠžã™ã‚‹
Spring Bootã«ã‚ˆã‚‹APIãƒãƒƒã‚¯ã‚¨ãƒ³ãƒ‰æ§‹ç¯‰å®Ÿè·µã‚¬ã‚¤ãƒ‰ 第2版 何åƒäººã‚‚ã®é–‹ç™ºè€…ãŒã€InfoQã®ãƒŸãƒ‹ãƒ–ック「Practical Guide to Building an API Back End with Spring Bootã€ã‹ã‚‰ã€Spring Bootを使ã£ãŸREST API構築ã®åŸºç¤Žã‚’å¦ã‚“ã 。ã“ã®æœ¬ã§ã¯ã€å‡ºç‰ˆæ™‚ã«æ–°ã—ãリリースã•ã‚ŒãŸãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã‚ã‚‹ Spring Boot 2 を使用ã—ã¦ã„る。ã—ã‹ã—ã€Spring Boot3ãŒæœ€è¿‘リリースã•ã‚Œã€é‡è¦ãªå¤‰...
内部データパイプラインã¸ã®Kafka Streamsã®é©ç”¨ - LINE ENGINEERING
! This post is also available in the following languages. 英語, 韓国語 By Kawamura Yuto | 2016.08.19 2021.01.08LINEã§ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã¨ã—ã¦åƒã„ã¦ã„ã¾ã™ã€‚Apache Kafkaã€Apache Hbaseãªã©ã®OSS技術をベースã«LINEã®ä¸æ ¸çš„ãªãƒ‡ãƒ¼ã‚¿ãƒ‘イプラインã¨ã‚¹ãƒˆãƒ¬ãƒ¼ã‚¸ã‚’開発・é‹å–¶ã—ã¦ã„ã¾ã™ã€‚ Kafka Streamsã®ã”紹介 ã“ã‚“ã«ã¡ã¯ã€‚LINEã§ã‚µãƒ¼ãƒé–‹ç™ºã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã¨ã—ã¦åƒã„ã¦ã„ã‚‹Yuto Kawamuraã§ã™ã€‚主ã«HBaseã€Kafkaã¨ã„ã£ãŸLINEã®ä¸æ ¸çš„ãªã‚¹ãƒˆãƒ¬ãƒ¼ã‚¸ã‚’開発・é‹å–¶ã—ã¦ã„ã¾ã™ã€‚ 昨年下期ã‹ã‚‰ã¯ã€IMF(Internal Message Flowã¾ãŸã¯Fund)ã¨å‘¼ã°ã‚Œã‚‹æ–°è¦ãƒ—ãƒã‚¸ã‚§ã‚¯ãƒˆã‚‚担当ã—ã¦ã„ã¾ã™ã€‚ã“ã®IMFプãƒã‚¸ã‚§ã‚¯ãƒˆã®ç›®çš„ã¯å¤§ãã2ã¤ã‚ã‚Šã¾ã™ã€‚ 内部シ
LinkedInã®Kafkaã«é–¢ã™ã‚‹è«–文をèªã‚“ã§ã¿ãŸï¼ˆï¼‘） - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? 0. 本投稿ã«ã¤ã„㦠LinkedInã®Kafkaã«ã¤ã„ã¦æ›¸ã‹ã‚ŒãŸè«–文をèªã‚“ã ã®ã§ã€æ¦‚è¦ã ã‘記録ã™ã‚‹ã€‚ 論文リンク http://sites.computer.org/debull/A12june/pipeline.pdf 1. Introduction LinkedInã§ã¯ã€ã‚³ãƒã‚¯ã‚·ãƒ§ãƒ³äºˆæ¸¬ã€ã‚¸ãƒ§ãƒ–ã®ãƒžãƒƒãƒãƒ³ã‚°ã€è¡¨ç¤ºã™ã‚‹åºƒå‘Šã®æœ€é©åŒ–をユーザーã®è¡Œå‹•å±¥æ´ã‹ã‚‰æ©Ÿæ¢°å¦ç¿’を利用ã—ã¦ãƒ¢ãƒ‡ãƒªãƒ³ã‚°ã—ã¦ã„る。 ユーザーã®ã‚½ãƒ¼ã‚·ãƒ£ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã«é–¢é€£ã®ã‚るニュースフィードをactivity drivenã«æŠ•ç¨¿ã—ã¦ã„ã‚‹ 1.1 Previous Syst
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Introducing kmql
GitHub - zendesk/delivery_boy: A simple way to publish messages to Kafka from Ruby applications
Apache Kafka® Tutorials and Recipes by Confluent
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