How Can I Efficiently Process 90 Million Records with Hibernate Without Running Out of Memory?

Using Hibernate's ScrollableResults to Read 90 Million Records Incrementally

Hibernate's ScrollableResults interface provides a means to iterate through query results without loading the entire result set into memory. However, as this question highlights, using ScrollableResults with a large number of records can lead to memory issues if the MySQL Connector/J driver is used.

In such cases, the only practical option is to iterate through the results in batches using the setFirstResult and setMaxResults methods. While this approach may seem inefficient, especially when dealing with large offsets, it is the most reliable way to avoid memory problems.

Ideally, a stateless session should be used to prevent any session-level caching or dirty tracking issues.

Another potential optimization is to use the id field as the index's last column and modify the query to retrieve a batch of records at a time, using the highest id of the previous batch as the starting point. This can improve performance if other_conditions in the query use equality conditions.

By modifying the query as follows:

select * 
from person 
where id > <max_id_of_last_batch> and <other_conditions> 
order by id asc  
limit <batch_size>

you can avoid the performance hit caused by loading large offsets and achieve a more efficient iteration process.

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