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Presto ã«ãŠã‘ã‚‹ Service Discovery ã®å‹•ä½œåŽŸç†
Presto ã‚’é‹ç”¨ã—ã¦ã„る㨠“No worker nodes available†ã¨ã„ã†ã‚¨ãƒ©ãƒ¼ã«éé‡ã™ã‚‹ã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ã“れ㯠coordinator ㌠planning ã‚’ã™ã‚‹éš›ã« active 㪠worker nodes ãŒå˜åœ¨ã—ãªã„ã¨èµ·ãるエラーãªã‚“ã§ã™ãŒã€worker nodes ã«å•é¡Œã§ã¯ãªã service discovery ãŒä¸Šæ‰‹ã機能ã—ã¦ã„ãªãã¦èµ·ãã‚‹ã“ã¨ãŒã‚ã‚Šã¾ã™ã€‚ worker nodes ãŒç•°å¸¸ãªã®ã‹ service discovery ãŒä¸Šæ‰‹ã機能ã—ã¦ã„ãªã„ã®ã‹ã‚’切り分ã‘ã‚‹ã«ã¯ã€Presto ãŒã©ã®ã‚ˆã†ã« service discovery を実ç¾ã—ã¦ã„ã‚‹ã‹ã‚’ç†è§£ã—ã¦ã„ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã™ãŒã€ã‚ˆãã‚ã‹ã£ã¦ãªã‹ã£ãŸã®ã§èª¿ã¹ã¦ã¿ã¾ã—ãŸã€‚ 環境㯠Amazon Elastic MapReduce (EMR) ã§ã¯ã˜ã‚ã‚‹ Presto 入門ã¨åŒã˜ãã€Presto 0
Presto Infrastructure at Lyft
OverviewEarly in 2017 we started exploring Presto for OLAP use cases and we realized the potential of this amazing query engine. It started as an adhoc querying tool for data engineers and analysts to run SQL in a faster way to prototype their queries, when compared to Apache Hive. A lot of internal dashboards were powered by AWS-Redshift back then and it had data storage and compute coupled toget
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爆速クエリエンジンâ€Prestoâ€ã‚’使ã„ãŸããªã‚‹è©±
Prestoã®å°Žå…¥ãƒ¡ãƒªãƒƒãƒˆã®ã»ã‹ã€HiveQLã‹ã‚‰Prestoã¸ã®æ›¸ãæ›ãˆTipsを紹介ã—ã¾ã™Read less
Treasure Data Update 2015 - Presto - Qiita
Treasure Dataã§ã¯fluentd, å„種SDK, Data Connectorãªã©ã§åŽé›†ã•ã‚ŒãŸãƒ‡ãƒ¼ã‚¿ã«å¯¾ã—ã¦ã€Hive, Prestoã«ã‚ˆã‚‹åˆ†æ•£SQLクエリãŒå®Ÿè¡Œã§ãã¾ã™ã€‚特ã«Prestoã¯ã“ã®1å¹´ã§å¤§ãã進化ã—ã¾ã—ãŸã®ã§ã€ã“ã“ã§ãã®å†…容ã«ã¤ã„ã¦ç´¹ä»‹ã—ã¦ã„ããŸã„ã¨æ€ã„ã¾ã™ã€‚ Prestoクエリã®åˆ©ç”¨é‡ã¯å¢—ãˆç¶šã‘ã¦ã„ã¦ã€2015å¹´12月ç¾åœ¨ã€Treasure Dataã®åˆ©ç”¨çµ±è¨ˆã§ã¯ã€ １日ã‚ãŸã‚Š5万クエリ (月æ›ç®—ã§150万クエリ) １日ã‚ãŸã‚Š10å…† (10 trillion) レコード を処ç†ã—ã¦ã„ã¾ã™ã€‚2015å¹´ã®å§‹ã¾ã‚Šã®æ™‚点ã§ã¯ã€1æ—¥ã‚ãŸã‚ŠãŠã‚ˆã5000クエリã€1兆レコードã¨ã„ã†æ•°å—ã§ã—ãŸã®ã§ã€ã“ã®ï¼‘å¹´ã§ã»ã¼10å€ã«ãªã£ãŸè¨ˆç®—ã«ãªã‚Šã¾ã™ã€‚昨年末ã®Prestoサービスã®é–‹å§‹ã«ã‚ãŸã‚Šã€CTOã®å¤ªç”°ã¨ç›¸è«‡ã—ã¦10å€ã‚¹ã‚±ãƒ¼ãƒ«ã§ãるよã†ã«æº–備をã—ã¦ã„ãŸã®ã§ã™ãŒã€æƒ³å®šã—ã¦ã„ãŸã‚ˆã‚Šæ—©ãã“
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Presto is a fast, distributed SQL query engine that allows for ad-hoc queries against data sources like Cassandra, Hive, Kafka and others. It uses a pluggable connector architecture that allows it to connect to different data sources. Presto's query execution is distributed across worker nodes and queries are compiled to Java bytecode for efficient execution. Some limitations of Presto include its
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This document summarizes a presentation about Presto, an open source distributed SQL query engine. It discusses Presto's distributed and plug-in architecture, query planning process, and cluster configuration options. For architecture, it explains that Presto uses coordinators, workers, and connectors to distribute queries across data sources. For query planning, it shows how SQL queries are conve
Presto+MySQLã§åˆ†æ•£SQL
This document discusses Presto, an open source distributed SQL query engine for interactive analysis of large datasets. It describes Presto's architecture including its coordinator, connectors, workers and storage plugins. Presto allows querying of multiple data sources simultaneously through its connector plugins for systems like Hive, Cassandra, PostgreSQL and others. Queries are executed in a p
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