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Asked: 2026-05-27T18:05:57+00:00

After investigating a bit at work I noticed that the application I’m working on

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After investigating a bit at work I noticed that the application I’m working on is using the default fetch size (which is 10 for Oracle from what I know). The problem is that in the majority of cases the users fetch large amount of data (ranging from few thousand to even hundreds of thousands) and that the default 10 is really a huge bottleneck.

So the obvious conclusion here would be to make the fetch size larger. At first I was thinking about setting the default to 100 and bumping it to a 1000 for several queries. But then I read on the net that the default is so small to prevent memory issues (i.e. when the JVM heap cannot handle so much data), should I be worried about it?

I haven’t seen anywhere further explanation to this. Does it mean that a bigger fetch sizes means more overhead while fetching the result set? Or do they just mean that with the default I can fetch 10 records and then GC them and fetch another 10 and so on (whereas lets say fetching a 10000 all at once would result in an OutOfMemory exception)? In such case I wouldn’t really care as I need all the records in the memory anyway. In the former case (where bigger result set means bigger memory overhead) I guess I should load test it first.

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  1. Editorial Team

    By setting the fetch size too, big you are risking OutOfMemoryError.

    The fact that you need all these records anyway is probably not justifiable. More chances you need the entities reflected by the returned ResultSets… Setting the fetch size to 10000 means you’re heaping 10000 records represented by JDBC classes. Of course, you don’t pass these around through your application. You first transform them into your favorite business-logic-entities and then hand them to your business-logic-executor. This way, The records form the first fetch bulk are available for GC as soon as JDBC fetches the next fetch bulk.

    Typically, this transformation is done a little bunch at a time exactly because of the memory threat aforementioned.

    One thing you’re absolutely right, though: you should test for performance with well-defined requirements before tweaking.

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