November 2017
Intermediate to advanced
328 pages
6h 51m
Japanese
Content preview from 入門 PySpark ―PythonとJupyterで活用するSpark 2エコシステム
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2
章 耐障害性分散データセット
17
2
章
耐 障 害 性 分 散 デ ー タ セ ット
耐障害性分散データセット（Resilient Distributed Dataset = RDD）は、JVMのイミュータブルな
オブジェクトの分散コレクションであり、演算処理を高速に行えます。そして RDDは、Apache Spark
を支えるバックボーンです。
その名が示すとおり、RDDは分散配置されています。RDDは何らかのキーに基づいてチャンクに分
割され、エクゼキュータノードに分散配置されます。そうすることによって、RDDに対する演算処理は
非常に高速に処理できるようになります。また、「1章 Spark を理解する」ですでに述べたとおり、RDD
はそれぞれのチャンクに対して適用されたすべての変換を追跡（記録）することによって、処理を高速
化するとともに、何か問題が生じて一部のデータが失われた場合にフォールバックを行います。すなわ
ち、そういった場合には失われたデータを再計算できるのです。このデータリネージは、データの損失
に対する防衛線の一つでもあり、データのレプリケーションを補完するものです。
本章で取り上げる話題は次のとおりです。
●
RDD の内部動作
●
RDD の生成
●
グローバルスコープとローカルスコープ
●
変換
●
アクション
2.1
RDD
の内部動作
RDDの処理は並列に行われます。これは、Sparkを使うことの最大の利点です。それぞれの変換は
並列に行われるので、速度が大幅に向上することにな
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.