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テクノロジー https://www.docstoc.com/docs/12426408/HBase-at-Hadoop-World-NYC
Send an email to desktop-announce-subscribe@cloudera.com to stay current with Cloudera Desktop. Read our Company Blog Post about the product release. Cloudera Desktop is a graphical user interface for the many tools required to operate and develop for Hadoop. These tools have been collected into a desktop environment and delivered as a web application that simplifies cluster administration and job
Support We're always trying to improve our distribution for Hadoop. If you have trouble finding information you need on the following pages, check out our community support. We also offer commercial support for Hadoop. The Cloudera Distribution for Hadoop Getting Support Overview of the Configurator Installing the Configurator RPM Browsing your Yum Repositories Installing your Hadoop Cluster Form
It’s hard to believe it’s been 15 years since the global financial crisis of 2007/2008. While this might be a blast from the past we’d rather leave in the proverbial rear-view mirror, in March of 2023 we were back to the future with the collapse of Silicon Valley Bank (SVB), the largest US bank to […] Read blog post
As Google rolls out GFS2 - a major update to the custom-built file system underpinning its online infrastructure - the company's former infrastructure don sees no reason why the open source world can't follow suit. Famously, Christophe Bisciglia taught a course at the University of Washington meant to educate rising computer scientists in Google's epic data juggling ways, and earlier this year, he
Hadoop World: NYC. October 2nd, 2009 To support the growing, world wide Apache Hadoop community, we are happy to announce Hadoop World: NYC 2009 to be held in New York City on October 2nd, 2009. The above companies have already signed up to sponsor Hadoop World: NYC 2009. If you are interested in sponsoring the event, there are still great opportunities available. For more info, contact hadoopworl
はじめまして。今年の5月に入社した勝間@さがすチームです。 入社してからは、なかなか大変なことも多いですが、最近はお酒好きが集まって月曜から飲み合う 「勝間会」なるものも発足して、仕事面でも仕事以外の面でも密度の高い毎日を過ごしています! さて、僕は「さがす」チーム所属ということで、普段はレシピを「さがす」ユーザの満足度を上げるために、 クックパッドの検索まわりについて、いろいろな開発を行っています。 一方で、ユーザの「さがす欲求」について深く知るために、大規模なデータ解析を行い、欲求の分析を行う機会も増えてきました。 ところが、クックパッドのログは膨大な数があるので、一口のデータ解析と言っても通常のバッチ処理だと間に合わないため、 分散処理環境の必要性が高まってきました。 そこで、まずは手軽に試せる分散処理の王道ということで、最近ではHadoopを使ったデータ解析環境を整備しています。
Hadoop World: NYC. October 2nd, 2009 To support the growing, world wide Apache Hadoop community, we are happy to announce Hadoop World: NYC 2009 to be held in New York City on October 2nd, 2009. The above companies have already signed up to sponsor Hadoop World: NYC 2009. If you are interested in sponsoring the event, there are still great opportunities available. For more info, contact hadoopworl
前回、JavaScriptでMap Reduceのコードが書けるHadoop Streamingについて紹介しました。 標準入出力さえサポートされてあれば、任意のコードでMap Reduuceの処理が書ける、というものでしたが、エンジニアはそもそも面倒くさがり。コードも書くのも面倒です。 と、いうわけで、今回はもうコードすら書かずにSQLライクでMap ReduceできるHiveというプロダクトについて、まとめたいと思います。 Hive Hiveとは、簡単に言うとHadoop上で動作するRDBのようなものです。 HDFSなどの分散ファイルシステム上に存在するデータに対して、HiveQLというSQLライクな言語で操作できます。 で、面白いのがHiveQLの操作は基本的にMap Reduceのラッパーになっていること。 要するに、SELECT文実行すると裏でMap&Reduceのタスクが走り出
Introduction In a typical Hadoop MapReduce job, input files are read from HDFS. Data are usually compressed to reduce the file sizes. After decompression, serialized bytes are transformed into Java objects before being passed to a user-defined map() function. Conversely, output records are serialized, compressed, and eventually pushed back to HDFS. This seemingly simple, two-way process is in fact
It’s hard to believe it’s been 15 years since the global financial crisis of 2007/2008. While this might be a blast from the past we’d rather leave in the proverbial rear-view mirror, in March of 2023 we were back to the future with the collapse of Silicon Valley Bank (SVB), the largest US bank to […] Read blog post
It’s hard to believe it’s been 15 years since the global financial crisis of 2007/2008. While this might be a blast from the past we’d rather leave in the proverbial rear-view mirror, in March of 2023 we were back to the future with the collapse of Silicon Valley Bank (SVB), the largest US bank to […] Read blog post
Many of LinkedIn’s products are critically dependent on computationally intensive data mining algorithms. Examples of these include some modules like People You May Know, Viewers of This Profile Also Viewed, and much of the Job matching functionality that we give to people who post jobs on the site. To support these data-intensive products we have begun to move many of the largest offline processi
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Facebookにログインして、友達や家族と写真や近況をシェアしましょう。
Within the rules for the 2009 Gray sort, our 500 GB sort set a new record for the minute sort and the 100 TB sort set a new record of 0.578 TB/minute. The 1 PB sort ran after the 2009 deadline, but improves the speed to 1.03 TB/minute. The 62 second terabyte sort would have set a new record, but the terabyte benchmark that we won last year has been retired. (Clearly the minute sort and terabyte so
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