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CData ODBC Driver for BigQuery を使って、SAS からリアルタイムBigQuery 連携レポートや分析を実施

CData ODBC Driver for BigQuery を使って、SAS からBigQuery データを連携利用。

SAS は、高度なアナリティクス、BI、データ管理、予測分析のためのソフトウェアです。SAS とCData ODBC Driver for BigQuery を合わせて使うことで、SAS からリアルタイムBigQuery data へのアクセスが可能になります。本記事では、SAS でBigQuery のライブラリを作成し、データベースのようにデータを扱い、レポートを作成します。

The CData ODBC Driver offers unmatched performance for interacting with live BigQuery data in SAS due to optimized data processing built into the driver. When you issue complex SQL queries from SAS to BigQuery, the driver pushes supported SQL operations, like filters and aggregations, directly to BigQuery and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can easily visualize and analyze BigQuery data in SAS.

Connect to BigQuery as an ODBC Data Source

Information for connecting to BigQuery follows, along with different instructions for configuring a DSN in Windows and Linux environments (the ODBC Driver for BigQuery must be installed on the machine hosting the SAS System).

Google はOAuth 認証標準を使用します。個々のユーザーとしてGoogle API にアクセスするには、組み込みクレデンシャルを使うか、OAuth アプリを作成します。

OAuth では、Google Apps ドメインのユーザーとしてサービスアカウントを使ってアクセスすることもできます。サービスカウントでの認証では、OAuth JWT を取得するためのアプリケーションを登録する必要があります。

OAuth 値に加え、DatasetId、ProjectId を設定する必要があります。詳細はヘルプドキュメントの「はじめに」を参照してください。

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

Windows

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

Linux

If you are installing the CData ODBC Driver for BigQuery in a Linux environment, the driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties.

/etc/odbc.ini

[CData GoogleBigQuery Sys] Driver = CData ODBC Driver for BigQuery Description = My Description DataSetId = MyDataSetId ProjectId = MyProjectId

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

Create a BigQuery Library in SAS

Connect to BigQuery in SAS by adding a library based on the CData ODBC Driver for BigQuery.

  1. Open SAS and expand Libraries in the Explorer pane.
  2. In the Active Libraries window, right-click and select New.
  3. Name your library (odbclib), select ODBC as the Engine, and click to Enable at startup (if you want the library to persist between sessions).
  4. Set Data Source to the DSN you previously configured and click OK.

Create a View from a BigQuery Query

SAS natively supports querying data either using a low-code, point-and-click Query tool or programmatically with PROC SQL and a custom SQL query. When you create a View in SAS, the defining query is executed each time the view is queried. This means that you always query live BigQuery data for reports, charts, and analytics.

Using the Query Tool

  1. In SAS, click Tools -> Query
  2. Select the table sources and the table(s) you wish to pull data from. Then, click OK.
  3. Select columns and right-click to add filtering, ordering, grouping, etc.
  4. Create a local view to contain the query results by right-clicking the SQL Query Tool window, selecting Show Query, and clicking Create View. Name the View and click OK.

Using PROC SQL

  1. In SAS, navigate to the Editor window.
  2. Use PROC SQL to query the data and create a local view.
    NOTE: This procedure creates a view in the Work library. You can optionally specify a library in the create view statement.
    proc sql;
      create view orders_view as
      select 
        ordername, 
        freight 
      from 
        odbclib.orders 
      where 
        ShipCity = 'New York';
    quit;
    
  3. Click Run -> Submit to execute the query and create a local view.

Report On or Visualize BigQuery Data in SAS

With a local view created, you can report, visualize, or otherwise analyze BigQuery data using the powerful SAS features. Print a simple report using PROC PRINT and create a basic graph based on the data using PROC GCHART.

Print an HTML Report

  1. In SAS, navigate to the Editor window.
  2. Use PROC PRINT to print an HTML report for the BigQuery Orders data.
    proc print data=orders;
      title "BigQuery Orders Data";
    run;
    

Print a Chart

  1. In SAS, navigate to the Editor window.
  2. Use PROC GCHART to create a chart for the Orders data.
    proc gchart data=orders;
      pie ordername / sumvar=freight
          value=arrow
          percent=arrow
          noheading
          percent=inside plabel=(height=12pt)
          slice=inside value=none
          name='OrdersChart';
    run;
    
 
 
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