A naive approach to inserting 100 000 rows in the database using Hibernate might look like this: This would fall over with an OutOfMemoryException somewhere around the 50 000th row. That's because Hibernate caches all the newly inserted Customer instances in the session-level cache. In this chapter we'll show you how to avoid this problem. First, however, if you are doing batch processing, it is absolutely critical that you enable the use of JDBC batching, if you intend to achieve reasonable performance. Set the JDBC batch size to a reasonable number (say, 10-50): You also might like to do this kind of work in a process where interaction with the second-level cache is completely disabled: When making new objects persistent, you must flush() and then clear() the session regularly, to control the size of the first-level cache. For retrieving and updating data the same ideas apply. In addition, you need to use scroll() to take advantage of server-side cursors for queries that return many rows of data. As already discussed, automatic and transparent object/relational mapping is concerned with the management of object state. This implies that the object state is available in memory, hence manipulating (using the SQL Data Manipulation Language (DML) statements: INSERT, UPDATE, DELETE) data directly in the database will not affect in-memory state. However, Hibernate provides methods for bulk SQL-style DML statement execution which are performed through the Hibernate Query Language (HQL). The psuedo-syntax for UPDATE and DELETE statements is: ( UPDATE | DELETE ) FROM? EntityName (WHERE where_conditions)?. Some points to note: In the from-clause, the FROM keyword is optional There can only be a single entity named in the from-clause; it can optionally be aliased. If the entity name is aliased, then any property references must be qualified using that alias; if the entity name is not aliased, then it is illegal for any property references to be qualified. No joins (either implicit or explicit) can be specified in a bulk HQL query. Sub-queries may be used in the where-clause; the subqueries, themselves, can contain joins. The where-clause is also optional. As an example, to execute an HQL UPDATE, use the Query.executeUpdate() method (the method is named for those familiar with JDBC's PreparedStatement.executeUpdate()): To execute an HQL DELETE, use the same Query.executeUpdate() method: The int value returned by the Query.executeUpdate() method indicate the number of entities effected by the operation. Consider this may or may not correlate to the number of rows effected in the database. An HQL bulk operation might result in multiple actual SQL statements being executed, for joined-subclass, for example. The returned number indicates the number of actual entities affected by the statement. Going back to the example of joined-subclass, a delete against one of the subclasses may actually result in deletes against not just the table to which that subclass is mapped, but also the "root" table and potentially joined-subclass tables further down the inheritence hierarchy. The psuedo-syntax for INSERT statements is: INSERT INTO EntityName (properties_list)? select_statement. Some points to note: Only the INSERT INTO ... SELECT ... form is supported; not the INSERT INTO ... VALUES ... form. The properties_list is optional. It is analogous to the column speficiation in the SQL INSERT statement. If omitted, all "eligible" (see next) properties are automatically included. For entities involved in mapped inheritence, only properties directly defined on that given class-level can be used in the properties_list. Superclass properties are not allowed; and subclass properties do not make sense. In other words, INSERT statements are inherently non-polymorphic. select_statement can be any valid HQL select query, with the caveat that the return types must match the types expected by the insert. Currently, this is checked during query compilation rather than allowing the check to relegate to the database. Note however that this might cause problems between Hibernate Types which are equivalent as opposed to equal. This might cause issues with mismatches between a property defined as a org.hibernate.type.DateType and a property defined as a org.hibernate.type.TimestampType, even though the database might not make a distinction or might be able to handle the conversion. An example HQL INSERT statement execution: