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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132
7
章
GraphFrames
7.3
flights
データセットの準備
フライト分析のサンプルシナリオでは、2つのデータセットを使用します。
●
Airline On -Time Performance and Causes of Flight Delays（http://bit.ly/2ccJPPM） このデー
タセットには、米国の航空会社によって報告された予定と実際の出発および到着時刻、そして遅
延の理由が含まれています。このデータは米国交通統計局の航空情報室によって収集されたもの
です。
●
Open Flights: Airports and airline data（https://openflights.org/data.html） このデータセット
には、米国の空港のリストが含まれており、IATAコード、空港 名、空 港の所在地がわかります。
作成するDataFrameは
airports
と
departureDelays
の2つで、それぞれがここで扱う
GraphFrameの頂点と辺になります。このフライトサンプルアプリケーションをPythonで作成しま
しょう。
この例では Databricksのノートブックを使うので、場所としては大量のサンプルデータセットが含ま
れている
/databricks-datasets/
を使いましょう。データは次からもダウンロードできます。
●
departureDelays.csv
（https://github.com/drabastomek/lear ...
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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.