January 2020
Beginner to intermediate
728 pages
10h 26m
Japanese
Content preview from データサイエンス設計マニュアル
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364 12 章 ビッグデータ：スケールを追求
して 1 個だけ
になるまで、半分にする操作は、log
2
(n) 回行われる。つまり、二分探索は O(log n) 時
間で実行される。
• マージソート：合計で n 個の要素を持つ 2 つのソート済みリストをマージして 1 つのソート済みリ
ストにするためにかかる時間は線形時間である。2 つのリストの先頭要素のうち、小さな方を新しい
要素に追加することを繰り返していけばよい。マージソートは、n 個の要素を半分に分割し、それ
ぞれをソートしてからマージする。また登場した要素を半分にして 1 個に達するまでの反復操作は、
log
2
(n) 回実行される（再度 2.4 節参照）。そして、あらゆる段階ですべての要素をマージするので、
マージソート全体でかかる時間は、O (n log n) である。
アルゴリズムの計算量を駆け足で説明した。速すぎて全部を説明することはできなかったが、6 種類の計
算量クラスの代表例を示すことはできた。これらの計算量クラスは、次のように最も高速なアルゴリズムか
ら遅いアルゴリズムまでの序列を定義する。
O (1) ≪ O(log n) ≪ O(n) ≪ O(n log n) ≪ O(n
2
) ≪ O(n
3
)
今後の課題
ビッ
グデータを処理するアルゴリズムは、線形時間かそれと大差のない計算時間（おそらく
O
(
n
log
n
)
）で動作するものでなければならない。
2
次式時間かかるアルゴリズムは、
n >
10
,
000
では問題外となる。
12.3.2 ハッシング（ハッシュ化） ...
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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.