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Get the Report →Replicate Spark Data to Multiple Databases
Replicate Spark data to disparate databases with a point-and-click configuration.
Always-on applications rely on automatic failover capabilities and real-time access to data. CData Sync integrates live Spark data into your mirrored databases, always-on cloud databases, and other databases such as your reporting server: Automatically synchronize with remote Spark data from Windows.
Configure Replication Destinations
Using CData Sync, you can replicate Spark data to any number of databases, both cloud-based and on-premises. To add a replication destination, navigate to the Connections tab.
For each destination database:
- Click Add Connection.
- Select a destination. In this article, we use SQLite.
- Enter the necessary connection properties. To replicate Spark to a SQLite database, enter a file path in the Data Source box.
- Click Test Connection to ensure that the connection is configured properly.
- Click Save Changes.
Configure the Spark Connection
You can configure a connection to Spark from the Connections tab. To add a connection to your Spark account, navigate to the Connections tab.
- Click Add Connection.
- Select a source (Spark).
- Configure the connection properties.
Set the Server, Database, User, and Password connection properties to connect to SparkSQL.
- Click Connect to ensure that the connection is configured properly.
- Click Save Changes.
Configure Replication Queries
CData Sync enables you to control replication with a point-and-click interface and with SQL queries. For each replication you wish to configure, navigate to the Jobs tab and click Add Job. Select the Source and Destination for your replication.
Replicate Entire Tables
To replicate an entire table, click Add Tables in the Tables section, choose the table(s) you wish to replicate, and click Add Selected Tables.
Customize Your Replication
You can use a SQL query to customize your replication. The REPLICATE statement is a high-level command that caches and maintains a table in your database. You can define any SELECT query supported by the Spark API. To customize your replication, click Add Custom Query in the Tables section and define the Query Statement.The statement below caches and incrementally updates a table of Spark data:
REPLICATE Customers;
You can specify a file containing the replication queries you want to use to update a particular database. Separate replication statements with semicolons. The following options are useful if you are replicating multiple Spark accounts into the same database:
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Use a different table prefix in the REPLICATE SELECT statement:
REPLICATE PROD_Customers SELECT * FROM Customers;
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Alternatively, use a different schema:
REPLICATE PROD.Customers SELECT * FROM Customers;
Schedule Your Replication
In the Schedule section, you can schedule a job to run automatically, configuring the job to run after specified intervals ranging from once every 10 minutes to once every month.
Once you have configured the replication job, click Save Changes. You can configure any number of jobs to manage the replication of your Spark data to disparate on-premises, cloud-based, and other databases.