August 2015
Intermediate to advanced
312 pages
7h 28m
Japanese
Content preview from 初めてのSpark
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274
付録 C Spark/MapReduce の機械学習ライブラリ比較検証
せることで、ユーザーのアイテムに対する評価を予測した予測値の行列（ユーザー×アイテム）を
算出します。予測値の行列からおすすめ商品を抽出するところはアイテムベースと同様です。
C.3.3
2
のアルムのい
この
2
つのアルゴリズムの特徴的な違いは、アイテムベースが逐次的なアルゴリズムであるの
に対し、
ALS
では繰り返し計算を必要とする点です。繰り返し計算は、計算過程で大量の中間デー
タを必要としますが、
MapReduce
が
1
回の処理ごとに中間データを
HDFS
に出力するのに対し
て、
Spark
は可能な限り中間データをメモリ上に保持して再利用するため、中間データへのアクセ
ス効率は、
Spark
が
MapReduce
より優れています。そのため、今回の検証観点から見ると、繰り
返し計算を必要とする
ALS
は
Spark
向きのアルゴリズムといえます。
C.4
比較法
本検証では、実行時間とレコメンド精度の
2
点を比較観点として検証します。
実行時間は、同じスペックの環境上で同じデータを入力として与えた際の実時間を測定して比較
します。使用した環境、データについて、
C-1
と
C-2
にまとめます。
C-1
ハードウェア
AWS EC2
サーバー数
13
台（
Master
×
2,Slave
×
10,Client
×
1
）
EC2
インスタンス
r3.2xlarge
CPU 8 Core
メモリ
61GiB
ストレージ
160GB
OS CentOS ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.