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Apache Spark でSharePoint Data をSQL で操作

CData JDBC ドライバーを使用して、Apache Spark でSharePoint Data にデータ連携。

Apache Spark は大規模データ処理のための高速で一般的なエンジンです。CData JDBC Driver for SharePoint と組み合わせると、Spark はリアルタイムSharePoint data にデータ連携して処理ができます。ここでは、Spark シェルに接続してSharePoint data をクエリする方法について説明します。

CData JDBC Driver は、最適化されたデータ処理がドライバーに組み込まれているため、リアルタイムSharePoint data と対話するための高いパフォーマンスを提供します。SharePoint に複雑なSQL クエリを発行すると、ドライバーはフィルタや集計など、サポートされているSQL操作を直接SharePoint にプッシュし、組込みSQL エンジンを使用してサポートされていない操作(SQL 関数やJOIN 操作)をクライアント側で処理します。組み込みの動的メタデータクエリを使用すると、ネイティブデータ型を使用してSharePoint data を操作して分析できます。

CData JDBC Driver for SharePoint をインストール

CData JDBC Driver for SharePoint インストーラをダウンロードし、パッケージを解凍し、JAR ファイルを実行してドライバーをインストールします。

Spark Shell を起動してSharePoint Data に接続

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for SharePoint JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for SharePoint/lib/cdata.jdbc.sharepoint.jar
  2. With the shell running, you can connect to SharePoint with a JDBC URL and use the SQL Context load() function to read a table.

    Set the URL property to the base SharePoint site or to a sub-site. This allows you to query any lists and other SharePoint entities defined for the site or sub-site.

    The User and Password properties, under the Authentication section, must be set to valid SharePoint user credentials when using SharePoint On-Premise.

    If you are connecting to SharePoint Online, set the SharePointEdition to SHAREPOINTONLINE along with the User and Password connection string properties. For more details on connecting to SharePoint Online, see the "Getting Started" chapter of the help documentation

    組み込みの接続文字列デザイナー

    For assistance in constructing the JDBC URL, use the connection string designer built into the SharePoint JDBC Driver.Either double-click the JAR file or execute the jar file from the command-line.

    java -jar cdata.jdbc.sharepoint.jar

    Fill in the connection properties and copy the connection string to the clipboard.

    scala> val sharepoint_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:sharepoint:User=myuseraccount;Password=mypassword;Auth Scheme=NTLM;URL=http://sharepointserver/mysite;SharePointEdition=SharePointOnPremise;").option("dbtable","MyCustomList").option("driver","cdata.jdbc.sharepoint.SharePointDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the SharePoint data as a temporary table:

    scala> sharepoint_df.registerTable("mycustomlist")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> sharepoint_df.sqlContext.sql("SELECT Name, Revenue FROM MyCustomList WHERE Location = Chapel Hill").collect.foreach(println)

    You will see the results displayed in the console, similar to the following:

Using the CData JDBC Driver for SharePoint in Apache Spark, you are able to perform fast and complex analytics on SharePoint data, combining the power and utility of Spark with your data.Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.

 
 
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