Build a PostgreSQL Interface for Spark Data using the CData JDBC Driver

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.

  👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
  

  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');
   

You can now execute read/write commands to Spark:

postgres=# SELECT * FROM customers;