I am facing an issue while inserting 100 000 records at once using spring data JPA repository. When we execute repo.save(List<Objs>)
it is taking a lot of time if we use Sequence generator as it queries the database for the nextval. I am using Oracle, which ID generation is best here?
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What is your sequence generator configuration? – Lesiak Feb 13 '18 at 11:14
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Java Config @SequenceGenerator(name = "MY_SEQ_GEN", sequenceName = "MY_SEQ", allocationSize = 1) @GeneratedValue(strategy = GenerationType.SEQUENCE, generator = "MY_SEQ_GEN") DB Sequence: CREATE SEQUENCE MY_SEQ MINVALUE 1 MAXVALUE 9999999999999999999999999999 INCREMENT BY 1 START WITH 1; – VNR Feb 13 '18 at 12:32
2 Answers
Sequence generator is probably a good choice, but you have to tweak its parameters.
In your particular case, I'd start experimenting with allocation size, and then with strategy. See for example: JPA/Hibernate bulk inserts slow
Take a look at the optimizers configuration: https://vladmihalcea.com/hibernate-hidden-gem-the-pooled-lo-optimizer/
Note that your configuration resolves to:
SequenceHiLoGenerator
on Hibernate 4SequenceStyleGenerator
on Hibernate 5, (it hashibernate.id.new_generator_mappings
set to true)
You cannot use identity generator (see Hibernate disabled insert batching when using an identity identifier generator)
Table generator is not the best performant one (https://vladmihalcea.com/why-you-should-never-use-the-table-identifier-generator-with-jpa-and-hibernate/)
Additionally, make sure that the number of nextval()
is the actual problem.
Maybe changing batch size or statement ordering will help (see https://vladmihalcea.com/how-to-batch-insert-and-update-statements-with-hibernate/)

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What about using a GUID generator? I would think that's the best without needing to grab a sequence at all and not having to wait for insert? – Dean Hiller Aug 15 '20 at 15:31
allocationSize=1
is the real issue here. With this configuration hibernate will call nextVal()
for each insert so if you have 1000 inserts then hibernate will call nextVal()
a 1000 times.
For more information refer to this article by Vlad Mihalcea

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