JDBC Batch Operations

Most JDBC drivers provide improved performance if you batch multiple calls to the same prepared statement. By grouping updates into batches, you limit the number of round trips to the database.

Basic Batch Operations with `JdbcTemplate`

You accomplish JdbcTemplate batch processing by implementing two methods of a special interface, BatchPreparedStatementSetter, and passing that implementation in as the second parameter in your batchUpdate method call. You can use the getBatchSize method to provide the size of the current batch. You can use the setValues method to set the values for the parameters of the prepared statement. This method is called the number of times that you specified in the getBatchSize call. The following example updates the t_actor table based on entries in a list, and the entire list is used as the batch:

Java
Kotlin

public class JdbcActorDao implements ActorDao {

	private JdbcTemplate jdbcTemplate;

	public void setDataSource(DataSource dataSource) {
		this.jdbcTemplate = new JdbcTemplate(dataSource);
	}

	public int[] batchUpdate(final List<Actor> actors) {
		return this.jdbcTemplate.batchUpdate(
				"update t_actor set first_name = ?, last_name = ? where id = ?",
				new BatchPreparedStatementSetter() {
					public void setValues(PreparedStatement ps, int i) throws SQLException {
						Actor actor = actors.get(i);
						ps.setString(1, actor.getFirstName());
						ps.setString(2, actor.getLastName());
						ps.setLong(3, actor.getId().longValue());
					}
					public int getBatchSize() {
						return actors.size();
					}
				});
	}

	// ... additional methods
}

class JdbcActorDao(dataSource: DataSource) : ActorDao {

	private val jdbcTemplate = JdbcTemplate(dataSource)

	fun batchUpdate(actors: List<Actor>): IntArray {
		return jdbcTemplate.batchUpdate(
				"update t_actor set first_name = ?, last_name = ? where id = ?",
				object: BatchPreparedStatementSetter {
					override fun setValues(ps: PreparedStatement, i: Int) {
						ps.setString(1, actors[i].firstName)
						ps.setString(2, actors[i].lastName)
						ps.setLong(3, actors[i].id)
					}

					override fun getBatchSize() = actors.size
				})
	}

	// ... additional methods
}

If you process a stream of updates or reading from a file, you might have a preferred batch size, but the last batch might not have that number of entries. In this case, you can use the InterruptibleBatchPreparedStatementSetter interface, which lets you interrupt a batch once the input source is exhausted. The isBatchExhausted method lets you signal the end of the batch.

Batch Operations with a List of Objects

Both the JdbcTemplate and the NamedParameterJdbcTemplate provides an alternate way of providing the batch update. Instead of implementing a special batch interface, you provide all parameter values in the call as a list. The framework loops over these values and uses an internal prepared statement setter. The API varies, depending on whether you use named parameters. For the named parameters, you provide an array of SqlParameterSource, one entry for each member of the batch. You can use the SqlParameterSourceUtils.createBatch convenience methods to create this array, passing in an array of bean-style objects (with getter methods corresponding to parameters), String-keyed Map instances (containing the corresponding parameters as values), or a mix of both.

The following example shows a batch update using named parameters:

Java
Kotlin

public class JdbcActorDao implements ActorDao {

	private NamedParameterTemplate namedParameterJdbcTemplate;

	public void setDataSource(DataSource dataSource) {
		this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource);
	}

	public int[] batchUpdate(List<Actor> actors) {
		return this.namedParameterJdbcTemplate.batchUpdate(
				"update t_actor set first_name = :firstName, last_name = :lastName where id = :id",
				SqlParameterSourceUtils.createBatch(actors));
	}

	// ... additional methods
}

class JdbcActorDao(dataSource: DataSource) : ActorDao {

	private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

	fun batchUpdate(actors: List<Actor>): IntArray {
		return this.namedParameterJdbcTemplate.batchUpdate(
				"update t_actor set first_name = :firstName, last_name = :lastName where id = :id",
				SqlParameterSourceUtils.createBatch(actors));
	}

		// ... additional methods
}

For an SQL statement that uses the classic ? placeholders, you pass in a list containing an object array with the update values. This object array must have one entry for each placeholder in the SQL statement, and they must be in the same order as they are defined in the SQL statement.

The following example is the same as the preceding example, except that it uses classic JDBC ? placeholders:

Java
Kotlin

public class JdbcActorDao implements ActorDao {

	private JdbcTemplate jdbcTemplate;

	public void setDataSource(DataSource dataSource) {
		this.jdbcTemplate = new JdbcTemplate(dataSource);
	}

	public int[] batchUpdate(final List<Actor> actors) {
		List<Object[]> batch = new ArrayList<>();
		for (Actor actor : actors) {
			Object[] values = new Object[] {
					actor.getFirstName(), actor.getLastName(), actor.getId()};
			batch.add(values);
		}
		return this.jdbcTemplate.batchUpdate(
				"update t_actor set first_name = ?, last_name = ? where id = ?",
				batch);
	}

	// ... additional methods
}

class JdbcActorDao(dataSource: DataSource) : ActorDao {

	private val jdbcTemplate = JdbcTemplate(dataSource)

	fun batchUpdate(actors: List<Actor>): IntArray {
		val batch = mutableListOf<Array<Any>>()
		for (actor in actors) {
			batch.add(arrayOf(actor.firstName, actor.lastName, actor.id))
		}
		return jdbcTemplate.batchUpdate(
				"update t_actor set first_name = ?, last_name = ? where id = ?", batch)
	}

	// ... additional methods
}

All of the batch update methods that we described earlier return an int array containing the number of affected rows for each batch entry. This count is reported by the JDBC driver. If the count is not available, the JDBC driver returns a value of -2.

In such a scenario, with automatic setting of values on an underlying PreparedStatement, the corresponding JDBC type for each value needs to be derived from the given Java type. While this usually works well, there is a potential for issues (for example, with Map-contained null values). Spring, by default, calls ParameterMetaData.getParameterType in such a case, which can be expensive with your JDBC driver. You should use a recent driver version and consider setting the spring.jdbc.getParameterType.ignore property to true (as a JVM system property or via the SpringProperties mechanism) if you encounter a specific performance issue for your application.

Alternatively, you could consider specifying the corresponding JDBC types explicitly, either through a BatchPreparedStatementSetter (as shown earlier), through an explicit type array given to a List<Object[]> based call, through registerSqlType calls on a custom MapSqlParameterSource instance, through a BeanPropertySqlParameterSource that derives the SQL type from the Java-declared property type even for a null value, or through providing individual SqlParameterValue instances instead of plain null values.

Batch Operations with Multiple Batches

The preceding example of a batch update deals with batches that are so large that you want to break them up into several smaller batches. You can do this with the methods mentioned earlier by making multiple calls to the batchUpdate method, but there is now a more convenient method. This method takes, in addition to the SQL statement, a Collection of objects that contain the parameters, the number of updates to make for each batch, and a ParameterizedPreparedStatementSetter to set the values for the parameters of the prepared statement. The framework loops over the provided values and breaks the update calls into batches of the size specified.

The following example shows a batch update that uses a batch size of 100:

Java
Kotlin

public class JdbcActorDao implements ActorDao {

	private JdbcTemplate jdbcTemplate;

	public void setDataSource(DataSource dataSource) {
		this.jdbcTemplate = new JdbcTemplate(dataSource);
	}

	public int[][] batchUpdate(final Collection<Actor> actors) {
		int[][] updateCounts = jdbcTemplate.batchUpdate(
				"update t_actor set first_name = ?, last_name = ? where id = ?",
				actors,
				100,
				(PreparedStatement ps, Actor actor) -> {
					ps.setString(1, actor.getFirstName());
					ps.setString(2, actor.getLastName());
					ps.setLong(3, actor.getId().longValue());
				});
		return updateCounts;
	}

	// ... additional methods
}

class JdbcActorDao(dataSource: DataSource) : ActorDao {

	private val jdbcTemplate = JdbcTemplate(dataSource)

	fun batchUpdate(actors: List<Actor>): Array<IntArray> {
		return jdbcTemplate.batchUpdate(
					"update t_actor set first_name = ?, last_name = ? where id = ?",
					actors, 100) { ps, argument ->
			ps.setString(1, argument.firstName)
			ps.setString(2, argument.lastName)
			ps.setLong(3, argument.id)
		}
	}

	// ... additional methods
}

The batch update method for this call returns an array of int arrays that contains an array entry for each batch with an array of the number of affected rows for each update. The top-level array’s length indicates the number of batches run, and the second level array’s length indicates the number of updates in that batch. The number of updates in each batch should be the batch size provided for all batches (except that the last one that might be less), depending on the total number of update objects provided. The update count for each update statement is the one reported by the JDBC driver. If the count is not available, the JDBC driver returns a value of -2.

JDBC Batch Operations

Basic Batch Operations with JdbcTemplate

Batch Operations with a List of Objects

Batch Operations with Multiple Batches

Basic Batch Operations with `JdbcTemplate`