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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144
7
章
GraphFrames
この
PageRank
のアルゴリズムの結果としては、米国の空港として最も重要なのは ATL（ハーツ
フィールドジャクソンアトランタ国際空港）ということになりました。ATLは米国で最も多忙な空港
（http://bit.ly/2eTGHs4）というだけでなく、世界的に見ても最も多忙な空港（2000 年から2015 年
http://bit.ly/2eTGDsy）なので、この結果は妥当でしょう。
7.10
最も人気のあるノンストップフライトの計算
tripGraph
DataFrameを拡張すれば、（このデータセットにおいて）米国で最も人気のあるノンス
トップフライトを次のクエリで見つけられます。
#
最も人気のあるノンストップフライトの計算
import pyspark.sql.functions as func
topTrips = tripGraph \
.edges \
.groupBy("src", "dst") \
.agg(func.count("delay").alias("trips"))
#
最も人気のあるフライトの上位
20
件を表示
display(topTrips.orderBy(topTrips.trips.desc()).limit(20))
注意が必要なのは、ここでは
delay
列を使っているものの、実際には利用回数の
count
を取ってい
るだけだということです。
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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.