How to work with SingleStore Data in Apache Spark using SQL

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

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

Install the CData JDBC Driver for SingleStore

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

Start a Spark Shell and Connect to SingleStore Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for SingleStore JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for SingleStore/lib/cdata.jdbc.singlestore.jar
   

2. With the shell running, you can connect to SingleStore with a JDBC URL and use the SQL Context load() function to read a table.

   The following connection properties are required in order to connect to data.

   • Server: The host name or IP of the server hosting the SingleStore database.
   • Port: The port of the server hosting the SingleStore database.
   • Database (Optional): The default database to connect to when connecting to the SingleStore Server. If this is not set, tables from all databases will be returned.

   Connect Using Standard Authentication

   To authenticate using standard authentication, set the following:

   • User: The user which will be used to authenticate with the SingleStore server.
   • Password: The password which will be used to authenticate with the SingleStore server.

   Connect Using Integrated Security

   As an alternative to providing the standard username and password, you can set IntegratedSecurity to True to authenticate trusted users to the server via Windows Authentication.

   Connect Using SSL Authentication

   You can leverage SSL authentication to connect to SingleStore data via a secure session. Configure the following connection properties to connect to data:

   • SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
   • SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSLClientCertType: The certificate type of the client store.
   • SSLServerCert: The certificate to be accepted from the server.

   Connect Using SSH Authentication

   Using SSH, you can securely login to a remote machine. To access SingleStore data via SSH, configure the following connection properties:

   • SSHClientCert: Set this to the name of the certificate store for the client certificate.
   • SSHClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
   • SSHClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
   • SSHClientCertType: The certificate type of the client store.
   • SSHPassword: The password that you use to authenticate with the SSH server.
   • SSHPort: The port used for SSH operations.
   • SSHServer: The SSH authentication server you are trying to authenticate against.
   • SSHServerFingerPrint: The SSH Server fingerprint used for verification of the host you are connecting to.
   • SSHUser: Set this to the username that you use to authenticate with the SSH server.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.singlestore.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.)
   

   Configure the connection to SingleStore, using the connection string generated above.

   scala> val singlestore_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:singlestore:User=myUser;Password=myPassword;Database=NorthWind;Server=myServer;Port=3306;").option("dbtable","Orders").option("driver","cdata.jdbc.singlestore.SingleStoreDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the SingleStore data as a temporary table:

   scala> singlestore_df.registerTable("orders")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> singlestore_df.sqlContext.sql("SELECT ShipName, ShipCity FROM Orders WHERE ShipCountry = USA").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for SingleStore in Apache Spark, you are able to perform fast and complex analytics on SingleStore data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.