How Can I Efficiently Stream 90 Million Records with Hibernate, Avoiding OutOfMemoryErrors?

Streaming 90 Million Records with Hibernate's Limited ScrollableResults

Despite its name, Hibernate's ScrollableResults is not suitable for efficiently processing large result sets. As discovered by a user, attempting to use it with 90 million records results in an OutOfMemoryError due to the driver loading the entire result set into memory.

The alternative, setFirstResult and setMaxResults, is also impractical for large datasets due to the time taken to reach higher offsets.

One solution is to manually retrieve records using SQL queries. By specifying a condition on the primary key and limiting the number of records returned, chunks of data can be streamed without overloading memory.

Another approach involves modifying the setFirstResult/setMaxResults strategy. Instead of gradually increasing the offset, one can use the maximum primary key value of the previous batch to retrieve the next batch. This method is particularly effective if the table is ordered by the primary key and additional conditions use equality comparisons limited to the last indexed column.

By following these strategies, one can work around the limitations of Hibernate's ScrollableResults and efficiently process large datasets in a streaming fashion.

The above is the detailed content of How Can I Efficiently Stream 90 Million Records with Hibernate, Avoiding OutOfMemoryErrors?. For more information, please follow other related articles on the PHP Chinese website!