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Posted to issues@drill.apache.org by "Kunal Khatua (JIRA)" <ji...@apache.org> on 2017/03/28 06:37:41 UTC

[jira] [Closed] (DRILL-5273) CompliantTextReader exhausts 4 GB memory when reading 5000 small files

     [ https://issues.apache.org/jira/browse/DRILL-5273?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Kunal Khatua closed DRILL-5273.
-------------------------------

Verified. Unable to reproduce the problem in 1.10.0, that is otherwise observed easily in 1.9.0 .

> CompliantTextReader exhausts 4 GB memory when reading 5000 small files
> ----------------------------------------------------------------------
>
>                 Key: DRILL-5273
>                 URL: https://issues.apache.org/jira/browse/DRILL-5273
>             Project: Apache Drill
>          Issue Type: Bug
>    Affects Versions: 1.10.0
>            Reporter: Paul Rogers
>            Assignee: Paul Rogers
>              Labels: ready-to-commit
>             Fix For: 1.10.0
>
>
> A test case was created that consists of 5000 text files, each with a single line with the file number: 1 to 5001. Each file has a single record, and at most 4 characters per record.
> Run the following query:
> {code}
> SELECT * FROM `dfs.data`.`5000files/text
> {code}
> The query will fail with an OOM in the scan batch on around record 3700 on a Mac with 4GB of direct memory.
> The code to read records in {ScanBatch} is complex. The following appears to occur:
> * Iterate over the record readers for each file.
> * For each, call setup
> The setup code is:
> {code}
>   public void setup(OperatorContext context, OutputMutator outputMutator) throws ExecutionSetupException {
>     oContext = context;
>     readBuffer = context.getManagedBuffer(READ_BUFFER);
>     whitespaceBuffer = context.getManagedBuffer(WHITE_SPACE_BUFFER);
> {code}
> The two buffers are in direct memory. There is no code that releases the buffers.
> The sizes are:
> {code}
>   private static final int READ_BUFFER = 1024*1024;
>   private static final int WHITE_SPACE_BUFFER = 64*1024;
> = 1,048,576 + 65536 = 1,114,112
> {code}
> This is exactly the amount of memory that accumulates per call to {{ScanBatch.next()}}
> {code}
> Ctor: 0  -- Initial memory in constructor
> Init setup: 1114112  -- After call to first record reader setup
> Entry Memory: 1114112  -- first next() call, returns one record
> Entry Memory: 1114112  -- second next(), eof and start second reader
> Entry Memory: 2228224 -- third next(), second reader returns EOF
> ...
> {code}
> If we leak 1 MB per file, with 5000 files we would leak 5 GB of memory, which would explain the OOM when given only 4 GB.



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