A PostgreSQL Interface for Spark Data

There are a vast number of PostgreSQL clients available on the Internet. From standard Drivers to BI and Analytics tools, PostgreSQL is a popular interface for data access. Using our JDBC Drivers, you can now create PostgreSQL entry-points that you can connect to from any standard client.

To access Spark data as a PostgreSQL database, use the CData JDBC Driver for Spark and a JDBC foreign data wrapper (FDW). In this article, we compile the FDW, install it, and query Spark data from PostgreSQL Server.

Connect to Spark Data as a JDBC Data Source

To connect to Spark as a JDBC data source, you will need the following:

• Driver JAR path: The JAR is located in the lib subfolder of the installation directory.

• Driver class: cdata.jdbc.sparksql.SparkSQLDriver

• JDBC URL: The URL must start with "jdbc:sparksql:" and can include any of the connection properties in name-value pairs separated with semicolons.

  Set the Server, Database, User, and Password connection properties to connect to SparkSQL.

  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.

  A typical JDBC URL is below:

  jdbc:sparksql:Server=127.0.0.1;

Build the JDBC Foreign Data Wrapper

The Foreign Data Wrapper can be installed as an extension to PostgreSQL, without recompiling PostgreSQL. The jdbc2_fdw extension is used as an example (downloadable here).

1. Add a symlink from the shared object for your version of the JRE to /usr/lib/libjvm.so. For example: ln -s /usr/lib/jvm/java-6-openjdk/jre/lib/amd64/server/libjvm.so /usr/lib/libjvm.so
2. Start the build: make install USE_PGXS=1

Query Spark Data as a PostgreSQL Database

After you have installed the extension, follow the steps below to start executing queries to Spark data:

1. Log into your database.
2. Load the extension for the database: CREATE EXTENSION jdbc2_fdw;
3. Create a server object for Spark: CREATE SERVER SparkSQL FOREIGN DATA WRAPPER jdbc2_fdw OPTIONS ( drivername 'cdata.jdbc.sparksql.SparkSQLDriver', url 'jdbc:sparksql:Server=127.0.0.1;', querytimeout '15', jarfile '/home/MyUser/CData/CData\ JDBC\ Driver\ for\ Salesforce MyDriverEdition/lib/cdata.jdbc.sparksql.jar');
4. Create a user mapping for the username and password of a user known to the MySQL daemon. CREATE USER MAPPING for postgres SERVER SparkSQL OPTIONS ( username 'admin', password 'test');
5. Create a foreign table in your local database: postgres=# CREATE FOREIGN TABLE customers ( customers_id text, customers_City text, customers_Balance numeric) SERVER SparkSQL OPTIONS ( table_name 'customers');