Create a Spark Data Source for Denodo Platform

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Apache Spark JDBC Driver

Apache Spark 連携のパワフルなJava アプリケーションを素早く作成して配布。



Use the CData JDBC Driver for Spark to create a virtual data source for Spark data in the Denodo Virtual DataPort Administrator.

Denodo Platform is a data virtualization product providing a single point of contact for enterprise database data. When paired with the CData JDBC Driver for Spark, Denodo users can work with live Spark data alongside other enterprise data sources. This article walks through creating a virtual data source for Spark in the Denodo Virtual DataPort Administrator.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Spark data. When you issue complex SQL queries to Spark, the driver pushes supported SQL operations, like filters and aggregations, directly to Spark and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Spark data using native data types.

Create a Spark Virtual Port

To connect to live Spark data from Denodo, you need to copy the JDBC Driver JAR file to the external library directory for Denodo and create a new JDBC Data Source from the Virtual DataPort Administrator tool.

  1. Download the CData JDBC Driver for Spark installer, unzip the package, and run the JAR file to install the driver.
  2. Copy the JAR File (and license file if it exists) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Spark\lib\) to the Denodo external library directory (C:\Denodo\Denodo Platform\lib-external\jdbc-drivers\cdata-sparksql-19).
  3. Open the Denodo Virtual DataPort Administrator tool and navigate to the Server Explorer tab.
  4. Right-click "admin" and select New -> Data source -> JDBC.
  5. Configure the JDBC Connection:
    • Name: your choice, e.g.: sparksql
    • Database adapter: Generic
    • Driver class path: C:\Denodo\Denodo Platform\lib-external\jdbc-drivers\cdata-sparksql-19
    • Driver class: cdata.jdbc.sparksql.SparkSQLDriver
    • Database URI: Set this to a JDBC URL using the necessary connection properties. For example,

      jdbc:sparksql:Server=127.0.0.1;

      Information on creating the Database URI follows:

      Built-In Connection String Designer

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

      java -jar cdata.jdbc.sparksql.jar

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

      SparkSQL への接続

      SparkSQL への接続を確立するには以下を指定します。

      • Server:SparkSQL をホストするサーバーのホスト名またはIP アドレスに設定。
      • Port:SparkSQL インスタンスへの接続用のポートに設定。
      • TransportMode:SparkSQL サーバーとの通信に使用するトランスポートモード。有効な入力値は、BINARY およびHTTP です。デフォルトではBINARY が選択されます。
      • AuthScheme:使用される認証スキーム。有効な入力値はPLAIN、LDAP、NOSASL、およびKERBEROS です。デフォルトではPLAIN が選択されます。

      Databricks への接続

      Databricks クラスターに接続するには、以下の説明に従ってプロパティを設定します。Note:必要な値は、「クラスター」に移動して目的のクラスターを選択し、 「Advanced Options」の下にある「JDBC/ODBC」タブを選択することで、Databricks インスタンスで見つけることができます。

      • Server:Databricks クラスターのサーバーのホスト名に設定。
      • Port:443
      • TransportMode:HTTP
      • HTTPPath:Databricks クラスターのHTTP パスに設定。
      • UseSSL:True
      • AuthScheme:PLAIN
      • User:'token' に設定。
      • Password:個人用アクセストークンに設定(値は、Databricks インスタンスの「ユーザー設定」ページに移動して「アクセストークン」タブを選択することで取得できます)。

  6. Click the "Test connection" button to confirm the configuration and click Save.

View Spark Data in the VirtualPort Administrator Tool

After creating the data source, you can create a base view of Spark data for use in the Denodo Platform.

  1. Click the "Create base view" button in the newly created VirtualPort (admin.SparkSQL).
  2. Expand the object tree and select the objects (tables) you wish to import.
  3. Click the "Create selected" button to create views of the Spark data.
    Optional: Click "Create associations from foreign keys" to define relationships between the objects.
  4. With the view(s) created, navigate to a table (cdata_sparksql_customers) in the Server Explorer and double-click the selected table.
  5. In the new tab, click "Execution panel" to open a query panel.
  6. Customize the query in the "Execute" tab or use the default:
    SELECT * FROM cdata_sparksql_customers CONTEXT ('i18n'='us_est', 'cache_wait_for_load'='true')
    
  7. Click Execute to view the data.

With the base view created, you can now work with live Spark data like you would any other data source in Denodo Platform, for example, querying Spark in the Denodo Data Catalog.

Download a free, 30-day trial of the CData JDBC Driver for Spark and start working with your live Spark data in Denodo Platform. Reach out to our Support Team if you have any questions.