Comments (5)
Does the issue happen if you do COPY without PARTITIONED BY?
The partitioning code spawns a potentially large number of tokio tasks (one for each partition), so if those tasks are not being cleaned up properly, it could lead to a memory leak.
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@devinjdangelo do you have any suggestions on how to investigate this issue further? I am happy to take the lead on it. I was chatting with @alamb yesterday and he suggested using heaptrack, but I was wondering if you would suggest other options. Thanks!
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@devinjdangelo do you have any suggestions on how to investigate this issue further? I am happy to take the lead on it. I was chatting with @alamb yesterday and he suggested using heaptrack, but I was wondering if you would suggest other options. Thanks!
A self contained example script may be helpful. I have used peak_alloc crate in the past as a very simple way to measure how much memory is being consumed.
Heaptrack will provide more detail and will likely help narrow down the source of the issue faster, but a self contained script I think is useful for demonstration and sanity checking.
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BTW something we have seen in InfluxDB, especially for very compressible data, was that the arrow writer was consuming substantial memory.
Something that might be worth testing would be to set the parquet writer's options to set data_page_row_limit
to something like 20,000
By default it is unlimited. We just changed the default upstream in arrow-rs apache/arrow-rs#5957 but that is not yet released
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Yes, I can see the same behavior by running the following query multiple times:
COPY (SELECT col1, timestamp, col10, col12 FROM my_table ORDER BY col1 ASC, timestamp ASC)
TO './output/output.parquet' STORED AS PARQUET OPTIONS (compression 'uncompressed');
However, the memory increase is smaller and it takes many more queries to make it noticeable (10+).
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Related Issues (20)
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