Google BigQuery Benchmark — DoIT International :: Helping businesses adopt, manage and enhance cloud solutions from Google and Zendesk
By Vadim Solovey, Google Developer Expert.Recently, I came across an interesting benchmark of BigData systems based on "A Comparison of Approaches to Large-Scale Data Analysis" by Pavlo et al. (SIGMOD 2009). Based on the benchmark methodology, the APMLab guys from Berkeley University developed an open-source software that allows anyone to run this benchmark using public cloud (AWS in this case).Th
Apache Hadoop YARN: Avoiding 6 Time-Consuming "Gotchas" | Cloudera Developer Blog
For the inaugural episode of Women Leaders in Technology on The AI Forecast, we welcomed Kari Briski – Vice President AI Software Product Management at NVIDIA. Kari shared the stories and strategies that inform her leadership style (like GSD or “getting stuff doneâ€), what it means to trust your instinct, and the advice she gives to young women embarking on a career in technology and to women furth
SQL on Hadoop 比較検証 ã€2014月11æ—¥ã«ãŠã‘る検証レãƒãƒ¼ãƒˆã€‘
Impala Meetup 2014/10/31 @Tokyo 講演資料 ã€æ³¨æ„äº‹é …ã€‘ 本資料ã§ç´¹ä»‹ã—ã¦ã„る検証çµæžœã¯2014年当時ã®ã‚‚ã®ã§ã™ã€‚当該ソフトウェアã¯æˆé•·ã‚„改善ãŒæ—©ãã€ç¾æ™‚点ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã§ã¯å¤§ããç•°ãªã‚‹æ©Ÿèƒ½ã‚„性能ã¨ãªã£ã¦ã„ã¾ã™ã€‚ SQL on Hadoopã®æœ€æ–°æƒ…å ±ã«åŸºã¥ãサービスやシステムインテグレーションã«ã”興味をãŠæŒã¡ã®æ–¹ã¯ã€NTTデータ 基盤システム事æ¥æœ¬éƒ¨ OSSプãƒãƒ•ã‚§ãƒƒã‚·ãƒ§ãƒŠãƒ«ã‚µãƒ¼ãƒ“ス（電åメール： hadoop [AT] kits.nttdata.co.jp） ã«ã”相談ãã ã•ã„。Read less
Cloudera Impalaをサービスã«çµ„ã¿è¾¼ã‚€ã¨ãã«è‹¦åŠ´ã—ãŸè©±
1. Cloudera Impalaをサービス㫠組ã¿è¾¼ã‚€æ™‚ã«è‹¦åŠ´ã—ãŸè©± 2014年年10⽉月31⽇日 æ ªå¼ä¼šç¤¾ã‚»ãƒ©ãƒ³ RD戦略略室 é ˆâ½¥ç”°å¹¸æ†² @sudabon Copyright © CELLâ–²NT Corp. All right Reserved. h t t p : / / w w w . x d a t a . j p / 2. ⾃自⼰己紹介 é ˆâ½¥ç”°å¹¸æ†²ï¼ˆ@sudabon) æ ªå¼ä¼šç¤¾ã‚»ãƒ©ãƒ³ RD戦略略室 室⻑⾧長 çµŒæ´ lï¬ 1997〜～2004 NEC ä¸å¤®ç ”究所 / ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã®ç ”究 lï¬ 2005〜～2006 BIGLOBE / BtoBサービスã®é–‹ç™º SNIP lï¬ 2012/8〜～ ç¾è· Hadoopæ´ï¼šç´„2å¹´ï¦ŽåŠ å¥½ããªHadoopエコシステム：Hive 2 Copyright © CELLâ–²NT Corp. All right Reserved. h t t p
Impala 2.0 Update #impalajp
5. 5 What is Impala? • MPP SQL query engine for Hadoop environment • wriTen in naLve code for maximum hardware efficiency • open-Ââ€source! • hTp://impala.io/ • Supported by Cloudera, Amazon, and MapR • History • 2012/10 Public Beta released • 2013/04 Impala 1.0 released • current version: Impala 2.0 6. 6 Impala is easy to use • create tables as virtual views over data stored in HDFS / HBase • sche
Cloudera Blog
We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Background The generative AI landscape is evolving […] Read blog post
War of the Hadoop SQL engines. And the winner is ...? - Sonra
War of the Hadoop SQL engines. And the winner is …? You may have wondered why we were quiet over the last couple of weeks? Well, we locked ourselves into the basement and did some research and a couple of projects and PoCs on Hadoop, Big Data, and distributed processing frameworks in general. We were also looking at Clickstream data and Web Analytics solutions. Over the next couple of weeks we wil
MPP on Hadoop, Redshift, BigQuery - Go ahead!
Twitterã§ã€Œæ—©ã今æµè¡Œã®MPPã®å¤§ã¾ã‹ãªä½¿ã„æ–¹ã®é•ã„書ã‘よï¼ã€ã¨ã„ã†ãƒ—レッシャーãŒåŠç«¯ãªã„ã®ã§ã¦ãã¨ã†ã«æ›¸ãã¾ã™ï¼Žã“ã®è¨˜äº‹ã¯ä¿ºã®çµŒé¨“ã¨å‹‰å¼·ä¼šãªã©ã§ãƒ¦ãƒ¼ã‚¶ã‹ã‚‰èžã„ãŸè©±ã‚’ã‚‚ã¨ã«æ›¸ã„ã¦ã„ã‚‹ã®ã§ï¼Œã™ã¹ã¦ãŒä¿ºã®çµŒé¨“ã§ã¯ã‚ã‚Šã¾ã›ã‚“(特ã«BigQuery)．å„社ã®SAã®äººã¨ã‹ã«èžã‘ã°ï¼Œã‚‚ã£ã¨è‰¯ã„アプãƒãƒ¼ãƒã¨ã‹è©³ç´°ã‚’æ•™ãˆã¦ãれるã‹ã‚‚ã—ã‚Œã¾ã›ã‚“． オンプレミスã®å•†ç”¨MPPã¯ä½¿ã£ãŸã“ã¨ãªã„ã®ã§ãƒŽãƒ¼ã‚³ãƒ¡ãƒ³ãƒˆã§ã™ï¼Ž MPP on Hadoopã§PrestoãŒãƒ¡ã‚¤ãƒ³ãªã®ã¯ä»Šä¸€ç•ªä½¿ã£ã¦ã„ã‚‹ã‹ã‚‰ã§ï¼ŒImpalaãªã©ä»–ã®MPP on Hadoopçš„ãªã‚‚ã®ã‚‚ä¼¼ãŸã‚ˆã†ãªæ„Ÿã˜ã‹ãªã¨æ€ã£ã¦ã„ã¾ã™ï¼Ž ã‚‚ã¡ã‚ん実装ã®é•ã„ãªã©ãŒã‚ã‚‹ã®ã§ï¼Œãã®è¾ºã¯é©å®œè‡ªåˆ†ã§è£œé–“ã—ã¦ãã ã•ã„． å‰æ アプリケーションを開発ã—ã¦ã„ã¦ï¼Œãã®ãŸã‚ã®è§£æžåŸºç›¤ã‚’一ã‹ã‚‰ä½œã‚‹ï¼Ž ç°¡å˜ãªã¾ã¨ã‚ データを貯ã‚る所ãŒä½œã‚Œã‚‹ã®ã§ã‚ã‚Œã°ï¼Œãã“ã«ç›´æŽ¥ã‚¯ã‚¨ãƒªã‚’投ã’られるPre
米デルã€Oracle 12c用垂直統åˆã‚·ã‚¹ãƒ†ãƒ ã€MySQL用アプライアンスã€Cloudera用インメモリアプライアンスãªã©ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ç‰¹åŒ–ã®åž‚ç›´çµ±åˆã‚·ã‚¹ãƒ†ãƒ を相次ã„ã§ç™ºè¡¨
米デルã€Oracle 12c用垂直統åˆã‚·ã‚¹ãƒ†ãƒ ã€MySQL用アプライアンスã€Cloudera用インメモリアプライアンスãªã©ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ç‰¹åŒ–ã®åž‚ç›´çµ±åˆã‚·ã‚¹ãƒ†ãƒ を相次ã„ã§ç™ºè¡¨ 「デルã¯ã‚¢ãƒ—ライアンス群ã¸ã®æä¾›ã¸ã¨æ€¥é€Ÿã«ç§»è¡Œã—ã¦ãŠã‚Šã€ãŠå®¢æ§˜ã¯å¤§è¦æ¨¡ãªã‚¨ãƒ³ã‚¿ãƒ¼ãƒ—ライズアプリケーションã®ç®¡ç†ã‚„é‹ç”¨ã®ã‚·ãƒ³ãƒ—ル化ã«ã‚ˆã‚‹ä¾¡å€¤ã‚’å—ã‘られるよã†ã«ãªã‚Šã¾ã™ã€ï¼ˆ6月24日付ã‘プレスリリースã‹ã‚‰ï¼‰ 米デルã¯ãƒ•ãƒãƒªãƒ€ã§ã®åŒç¤¾ã®ã‚¤ãƒ™ãƒ³ãƒˆã€ŒDell User Forumã€ã«ãŠã„ã¦ã€ãƒ‡ãƒ¼ã‚¿ãƒ™ãƒ¼ã‚¹ã«å€‹åˆ¥ã«ç‰¹åŒ–ã—ãŸåž‚ç›´çµ±åˆã‚·ã‚¹ãƒ†ãƒ やアプライアンスを相次ã„ã§ç™ºè¡¨ã€‚ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ—ãƒ©ã‚¤ã‚ºå¸‚å ´ã«ãŠã„ã¦ã¯ã‚¢ãƒ—ライアンス戦略ã«æ³¨åŠ›ã—ã¦ã„ãã“ã¨ã‚’明らã‹ã«ã—ã¾ã—ãŸã€‚ 発表ã•ã‚ŒãŸä¸»ãªã‚·ã‚¹ãƒ†ãƒ ã¯ä»¥ä¸‹ã®é€šã‚Šã€‚ Dell Integrated System for Oracle 12c Database フルラックã«ã€ŒDell PowerEdge Se
Cloudera Blog
We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Background The generative AI landscape is evolving […] Read blog post
Building a Hadoop Data Warehouse with Impala
This talk was held at the 11th meeting on April 7 2014 by Marcel Kornacker. Impala (impala.io) raises the bar for SQL query performance on Apache Hadoop. With Impala, you can query Hadoop data – including SELECT, JOIN, and aggregate functions – in real time to do BI-style analysis. As a result, Impala makes a Hadoop-based enterprise data hub function like an enterprise data warehouse for native Bi
impalaã®ãƒ¡ãƒ¢ãƒªç®¡ç† - Qiita
#Cgroupã¨ã¯ï¼Ÿ cgroup(control group) Control Groupã€Linux Containerã®ç´¹ä»‹ Control Groups (cgroups) cgroupsã¨ã—ã°ã‚‰ã一緒ã«éŽã”ã—ã¦ã¿ãŸ Performance Prediction and Optimization using Linux/cgroups Redhat カスタマーãƒãƒ¼ã‚¿ãƒ«ï¼š3.7. memory memory.limit_in_bytes ユーザーメモリーã®æœ€å¤§å€¤ (ファイルã‚ャッシュをå«ã‚€) ã‚’è¨å®šã—ã¾ã™ã€‚å˜ä½ãŒæŒ‡å®šã•ã‚Œã¦ã„ãªã„å ´åˆã€ãã®å€¤ã¯ãƒã‚¤ãƒˆå˜ä½ã¨è§£é‡ˆã•ã‚Œã¾ã™ãŒã€ã‚ˆã‚Šå¤§ããªå˜ä½ã‚’示ã™ã‚µãƒ•ã‚£ãƒƒã‚¯ã‚¹ã‚’使用ã™ã‚‹ã“ã¨ãŒå¯èƒ½ã§ã™ (ã‚ãƒãƒã‚¤ãƒˆã«ã¯ k ã¾ãŸã¯ Kã€ãƒ¡ã‚¬ãƒã‚¤ãƒˆã«ã¯ m ã¾ãŸã¯ Mã€ã‚®ã‚¬ãƒã‚¤ãƒˆã«ã¯ g ã¾ãŸã¯ G)。 root cgroup を制é™ã™ã‚‹ã®ã«ã¯ã€memory.l
What are the main differences between Facebook, Presto, and Amplab Shark?
Answer (1 of 2): 1. Primary Use Case: While both are intended for analytics, Shark's primary use case is providing SQL to an (extremely fast) in-memory database, with support also for on-disk (or abstract) data sources. Presto is designed to be a fast SQL engine for the latter, and does not have ...
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
Inside Yellow Pages' SQL-on-Hadoop Journey
2138cn太阳集团-首页
stripe/herringbone · GitHub - Tools for working with parquet, impala, and hive
Under Construction | Home
Apache Hadoop Distribution | MapR
Hitoshi Harada on Twitter: "ã•ã¦ãã‚ãã‚種明ã‹ã—ã‚’ã—ã¦ãŠãã¨ã€Impalaã¨Hawqã®ã‚¹ãƒ”ードã®å·®ã¯ã‚ªãƒ—ティマイザやパーティショニングã ã‘ã§ã¯ãªã„ã®ã§ã™ã€‚Impalaã¯ç¾çŠ¶JNI経由ã§HDFSã«ã‚¢ã‚¯ã‚»ã‚¹ã—ã¾ã™ãŒã€Hawqã¯C++ã§ProtocolBufferã‚’å–‹ã‚‹ã®ã§ãã®ã¸ã‚“ã«ç”±æ¥ã™ã‚‹ã¨ã“ã‚も大ãã„ã§ã™"
Data into results » Big data benchmark : Impala vs Hawq vs Hive
{{#tags}}- {{label}}
{{/tags}}