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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136
7
章
GraphFrames
7.5. 2
データセット中での最大のディレイを求める
次のクエリを実行すれば、データセット中で最も大きな遅延が 1,642 分（27 時間以上です！）である
ことがわかります。
tripGraph.edges.groupBy().max("delay")
# Output
+----------+
|max(delay)|
+----------+
| 1642|
+----------+
7.5.3
遅延したフライトおよびオンタイム／繰り上げフライト数の計算
次のクエリを実行すれば、遅延したフライト数とオンタイム（あるいは繰り上げ）フライト数を知る
ことができます。
print "On-time / Early Flights: %d" % tripGraph.edges.filter("delay <= 0").count()
print "Delayed Flights: %d" % tripGraph.edges.filter("delay > 0"). count()
なんと、ほとんど 43%ものフライトが遅延しています！
7.5.4
シアトル発で最も大きくディレイしそうなフライトは？
このデータをさらに深く探って、シアトル発のフライトで大きく遅延する可能性が高い目的地の上位
5カ所を見つけましょう。これは、次のクエリで調べられます。
tripGraph.edges\
.filter("src = 'SEA' and delay > 0")\
.groupBy("src", ...
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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.