Question

I’m trying to do a cascading save on a large object graph using JPA. For example (my object graph is a little bigger but close enough):

@Entity
@Table(name="a")
public class A {
  private long id;
  @OneToMany(cascade = CascadeType.ALL, mappedBy = "a")
  private Collection<B> bs;
}

@Entity
@Table(name="b")
public class B {
  private long id;
  @ManyToOne
  private A a;
}

So I’m trying to persist A which has a collection of 100+ B’s. Code is just

em.persist(a);

Problem is, it’s SLOW. My save is taking approximately 1300ms. I looked at the SQL being generated and it’s horribly inefficient. Something like this:

select a_seq.nextval from dual;
select b_seq.nextval from dual;
select b_seq.nextval from dual;
select b_seq.nextval from dual;
...
insert into a (id) values (1);
insert into b (id, fk) values (1, 1);
insert into b (id, fk) values (2, 1);
insert into b (id, fk) values (3, 1);
...

Currently using toplink as the persistence provider but I’ve tried eclipselink and hibernate also. Backend is oracle 11g. Problem is really how the sql is put together. Each of these operations is getting done discretely rather than in bulk, so if there is a network latency of even 5ms between my appserver and db server, doing 200 discrete operations adds 1 second. I’ve tried increasing the allocationSize of my sequences but that only helps out a bit. I’ve also tried direct JDBC as a batch statement:

for...{
  statement = connection.prepareStatement(sql);
  statement.addBatch();
}
statement.executeBatch();

For my datamodel it takes about 33ms done as direct JDBC batch. Oracle itself is taking 5ms for the 100+ inserts.

Is there anyway of making JPA (i’m stuck with 1.0 right now…) go faster without delving into vendor specific things like hibernate bulk insert?

Thanks!

Answer 1

The solution would be to enable JDBC batching and to flush and clear the EntityManager at regular intervals (the same than the batch size) but I’m not aware of a vendor neutral way to do this:

• With Hibernate, you’d have to set the hibernate.jdbc.batch_size configuration option. See Chapter 13. Batch processing

• With EclipseLink, it looks like there is a batch writing mode. See Jeff Sutherland’s post in this thread (it should also be possible to specify the size).

• According to the comments of this blog post, batch writing is not available in TopLink Essentials 🙁