Patrick Wendell created SPARK-4073:
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Summary: Parquet+Snappy can cause significant off-heap memory usage
Key: SPARK-4073
URL: https://issues.apache.org/jira/browse/SPARK-4073
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.1.0
Reporter: Patrick Wendell
Priority: Critical
The parquet snappy codec allocates off-heap buffers for decompression[1]. In
one cases the observed size of these buffers was high enough to add several GB
of data to the overall virtual memory usage of the Spark executor process. I
don't understand enough about our use of Snappy to fully grok how much data we
would _expect_ to be present in these buffers at any given time, but I can say
a few things.
1. The dataset had individual rows that were fairly large, e.g. megabytes.
2. Direct buffers are not cleaned up until GC events, and overall there was not
much heap contention. So maybe they just weren't being cleaned.
I opened PARQUET-118 to see if they can provide an option to use on-heap
buffers for decompression. In the mean time, we could consider changing the
default back to gzip, or we could do nothing (not sure how many other users
will hit this).
[1]
https://github.com/apache/incubator-parquet-mr/blob/master/parquet-hadoop/src/main/java/parquet/hadoop/codec/SnappyDecompressor.java#L28
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