Work with Google Data Catalog Data in Apache Spark Using SQL

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Google Data Catalog JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Google Data Catalog.



Access and process Google Data Catalog Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Google Data Catalog, Spark can work with live Google Data Catalog data. This article describes how to connect to and query Google Data Catalog data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Google Data Catalog data due to optimized data processing built into the driver. When you issue complex SQL queries to Google Data Catalog, the driver pushes supported SQL operations, like filters and aggregations, directly to Google Data Catalog 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 work with and analyze Google Data Catalog data using native data types.

Install the CData JDBC Driver for Google Data Catalog

Download the CData JDBC Driver for Google Data Catalog installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Google Data Catalog Data

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

    Google Data Catalog uses the OAuth authentication standard. Authorize access to Google APIs on behalf on individual users or on behalf of users in a domain.

    Before connecting, specify the following to identify the organization and project you would like to connect to:

    • OrganizationId: The ID associated with the Google Cloud Platform organization resource you would like to connect to. Find this by navigating to the cloud console.

      Click the project selection drop-down, and select your organization from the list. Then, click More -> Settings. The organization ID is displayed on this page.

    • ProjectId: The ID associated with the Google Cloud Platform project resource you would like to connect to.

      Find this by navigating to the cloud console dashboard and selecting your project from the Select from drop-down. The project ID will be present in the Project info card.

    When you connect, the OAuth endpoint opens in your default browser. Log in and grant permissions to the application to completes the OAuth process. For more information, refer to the OAuth section in the Help documentation.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.googledatacatalog.jar

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

    Configure the connection to Google Data Catalog, using the connection string generated above.

    scala> val googledatacatalog_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:googledatacatalog:ProjectId=YourProjectId;").option("dbtable","Schemas").option("driver","cdata.jdbc.googledatacatalog.GoogleDataCatalogDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Google Data Catalog data as a temporary table:

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

    scala> googledatacatalog_df.sqlContext.sql("SELECT Type, DatasetName FROM Schemas WHERE ProjectId = bigquery-public-data").collect.foreach(println)

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

Using the CData JDBC Driver for Google Data Catalog in Apache Spark, you are able to perform fast and complex analytics on Google Data Catalog 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.