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Editorial Team
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Asked: 2026-05-22T01:01:09+00:00

I have a business app that I have written, that effectively recurses through a

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I have a business app that I have written, that effectively recurses through a directory structure looking for specific Excel files, and stores their addresses. It then loops through these files and parses them by creating a DocumentParser object for each file, this is done one at a time, and not async. The software seems to be very stable, so much so that the business would like to run it to recurse through a massive directory containing upwards of 10000 relevant Excel files.

My question is, as I am creating a new DocumentParser object each time, will the GC be effective enough to discard each of the objects when they go out of scope, ie when that Excel sheet has been parsed, or is there a way I can monitor this and where necessary manually do a GC? I’ve never had to deal with such large amounts of data before, generally only testing it on a maximum of 40-50 Excel files at a time.

Thanks.

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  1. Editorial Team

    I would leave the GC to its business. 10,000 objects is not really much work for the GC. And it’s likely the cost of the GC work will be much lower than the cost of the Excel work. So it’s not worth complicating your design to tweak things for the GC. If you end up with so many files to process that your application can’t finish in time, it’s most likely going to be the speed of the Excel processing holding you up.

    However one note which may be relevant: if the DocumentParser is using unmanaged memory in its work with the Excel file, you can use GC.Add/RemoveMemoryPressure to indicate to the GC the real added cost when opening the file. If you didn’t write the DocumentParser yourself, the author may already be doing this.

    The issue here is that you may have a managed object that costs something in the order of 100 bytes, which allocates a large amount of unmanaged memory when it does Excel work. The GC will have no way of knowing this, so these methods help notify the GC that there is more memory pressure than it was aware of. This may change its behaviour in how/when it decides to collect, which may lead to the application maintaining a lower memory footprint. If the application’s memory usage balloons out over time, then you may start seeing some slow downs from length garbage collection and possibly paging on the machine (depending on how much memory you have). You’ll want to keep an eye on its memory usage to make sure it’s not leaking memory as it processes – a memory profiler may be helpful there.

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