JDBC Driver

Ignite is shipped with JDBC drivers that allow processing distributed data using standard SQL statements like SELECT, INSERT, UPDATE or DELETE directly from the JDBC side.

Presently, there are two drivers supported by Ignite - the lightweight and easy to use JDBC Thin Driver and the one that interacts with the cluster by means of a client node. This documentation explains how to set up and use both:

• JDBC Thin Driver
• JDBC Client Node Driver
• Example

JDBC Thin Driver

The JDBC Thin driver is lightweight and easy to use from an application side. To start using the driver, just add ignite-core-{version}.jar to the classpath of the application.

The driver connects to one of the cluster nodes and forwards all the queries to it for final execution. The node takes care of the query distribution and result's aggregations. Then, the result is sent back to the client application.

JDBC connection string has the following pattern:

jdbc:ignite:thin://host[:port][?<params>]

• host is required and defines host of the cluster node to connect to.
• port to connect to. 10800 is used by default if this parameter is omitted.
• <params> are optional and have the following below:

param1=value1?param2=value2?...:paramN=valueN

The name of the driver's class is org.apache.ignite.IgniteJdbcThinDriver. For instance, this is how you can open a JDBC connection to the Ignite cluster node listening on IP address 192.168.0.50:

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcThinDriver");
 
// Open the JDBC connection.
Connection conn = DriverManager.getConnection("jdbc:ignite:thin://192.168.0.50");

The table below lists all the parameters that are accepted and support by the JDBC connection string:

Additional Connection String Examples

• jdbc:ignite:thin://myHost - connect to myHost on the port 10800 with all defaults
• jdbc:ignite:thin://myHost:11900 - connect to myHost on custom port 11900 with all defaults
• jdbc:ignite:thin://myHost:11900?distributedJoins=true&autoCloseServerCursor=true - connect to myHost on custom port 11900 with enabled distributed joins and autoCloseServerCursor optimization.

Cluster Configuration

In order to accept and process requests from JDBC Thin Driver, a cluster node binds to a local network interface on port 10800 and listens to incoming requests.

Use ClientConnectorConfiguration, that is set via IgniteConfiguration, to change any parameters:

IgniteConfiguration cfg = new IgniteConfiguration()
    .setClientConnectorConfiguration(new ClientConnectorConfiguration());

<bean id="ignite.cfg" class="org.apache.ignite.configuration.IgniteConfiguration">
  <property name="sqlConnectorConfiguration">
    <bean class="org.apache.ignite.configuration.SqlConnectorConfiguration" />
  </property>
</bean>

The following parameters are supported:

JDBC Client Node Driver

JDBC Client Node Driver connects to the cluster using its own full-fledged client node connection. This requires users to provide a complete Spring XML configuration as part of the JDBC connection string and copy all the jar files below to the classpath of your application or SQL tool:

• All the jars under {apache_ignite_release}\libs directory.
• All the jars under {apache_ignite_release}\ignite-indexing and {apache_ignite_release}\ignite-spring directories.

The driver is more heavyweight and might not support the latest SQL features of Ignite but since it uses the client node connection underneath, it can execute, distribute queries, and aggregate their results directly from the application side.

The JDBC connection URL has the following pattern:

jdbc:ignite:cfg://[<params>@]<config_url>

• <config_url> is required and represents any valid URL that points to an Ignite configuration file for Ignite client node. This node will be started within the Ignite JDBC Client Node Driver when it (JDBC driver) tries to establish a connection with the cluster.
• <params> is optional and has the following format:

param1=value1:param2=value2:...:paramN=valueN

The name of the driver's class is org.apache.ignite.IgniteJdbcDriver. For instance, this is how you can open a JDBC connection to the Ignite cluster:

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcDriver");
 
// Open JDBC connection (cache name is not specified, which means that we use default cache).
Connection conn = DriverManager.getConnection("jdbc:ignite:cfg://file:///etc/config/ignite-jdbc.xml");

The following parameters are supported:

📘

Cross-Cache Queries

Cache that the driver is connected to is treated as the default schema. To query across multiple caches, Cross-Cache Query functionality can be used.

Streaming Mode

It's feasible to add data into an Ignite cluster in a streaming mode (bulk mode) using the JDBC driver. In this mode, the driver instantiates IgniteDataStreamer internally and feeds data to it. To activate this mode, add streaming parameter set to true to a JDBC connection string:

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcDriver");
 
// Opening connection in the streaming mode.
Connection conn = DriverManager.getConnection("jdbc:ignite:cfg://streaming=true@file:///etc/config/ignite-jdbc.xml");

Presently, the streaming mode is supported only for INSERT operations. This is useful for cases when you want to achieve fast data preloading into a cache. The JDBC driver defines multiple connection parameters that affect the behavior of the streaming mode. These parameters are listed in the parameters table above.

The parameters cover almost all settings of a general IgniteDataStreamer and allow you to fine tune the streamer according to your needs. Please refer to the Data Streamers section of Ignite docs for more information on how to configure the streamer.

📘

Time Based Flushing

By default, the data is flushed when either a connection is closed or streamingPerNodeBufferSize is met. If you need to flush the data in a timely manner, then adjust the streamingFlushFrequency parameter.

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcDriver");
 
// Opening a connection in the streaming mode and time based flushing set.
Connection conn = DriverManager.getConnection("jdbc:ignite:cfg://streaming=true:streamingFlushFrequency=1000@file:///etc/config/ignite-jdbc.xml");

PreparedStatement stmt = conn.prepareStatement(
  "INSERT INTO Person(_key, name, age) VALUES(CAST(? as BIGINT), ?, ?)");

// Adding the data.
for (int i = 1; i < 100000; i++) {
      // Inserting a Person object with a Long key.
      stmt.setInt(1, i);
      stmt.setString(2, "John Smith");
      stmt.setInt(3, 25);
  
      stmt.execute();
}

conn.close();

// Beyond this point, all data is guaranteed to be flushed into the cache.

Example

To start processing the data located in the cluster, you need to create a JDBC Connection object using one of the methods below:

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcThinDriver");
 
// Open the JDBC connection.
Connection conn = DriverManager.getConnection("`jdbc:ignite:thin://192.168.0.50");

// Register JDBC driver.
Class.forName("org.apache.ignite.IgniteJdbcDriver");
 
// Open JDBC connection (cache name is not specified, which means that we use default cache).
Connection conn = DriverManager.getConnection("jdbc:ignite:cfg://file:///etc/config/ignite-jdbc.xml");

Right after that you can execute SQL SELECT queries of your choice:

// Query names of all people.
ResultSet rs = conn.createStatement().executeQuery("select name from Person");
 
while (rs.next()) {
    String name = rs.getString(1);
    ...
}
 
// Query people with specific age using prepared statement.
PreparedStatement stmt = conn.prepareStatement("select name, age from Person where age = ?");
 
stmt.setInt(1, 30);
 
ResultSet rs = stmt.executeQuery();
 
while (rs.next()) {
    String name = rs.getString("name");
    int age = rs.getInt("age");
    ...
}

Moreover, you can modify the data with the usage of DML statements.

INSERT

// Insert a Person with a Long key.
PreparedStatement stmt = conn.prepareStatement("INSERT INTO Person(_key, name, age) VALUES(CAST(? as BIGINT), ?, ?)");
 
stmt.setInt(1, 1);
stmt.setString(2, "John Smith");
stmt.setInt(3, 25);

stmt.execute();

MERGE

// Merge a Person with a Long key.
PreparedStatement stmt = conn.prepareStatement("MERGE INTO Person(_key, name, age) VALUES(CAST(? as BIGINT), ?, ?)");
 
stmt.setInt(1, 1);
stmt.setString(2, "John Smith");
stmt.setInt(3, 25);
 
stmt.executeUpdate();

UPDATE

// Update a Person.
conn.createStatement().
  executeUpdate("UPDATE Person SET age = age + 1 WHERE age = 25");

DELETE

conn.createStatement().execute("DELETE FROM Person WHERE age = 25");