GitHub user brkyvz opened a pull request:

    https://github.com/apache/spark/pull/15437

    [SPARK-17876] Write StructuredStreaming WAL to a stream instead of 
materializing all at once

    ## What changes were proposed in this pull request?
    
    The CompactibleFileStreamLog materializes the whole metadata log in memory 
as a String. This can cause issues when there are lots of files that are being 
committed, especially during a compaction batch.
    You may come across stacktraces that look like:
    ```
    java.lang.OutOfMemoryError: Requested array size exceeds VM limit
    at java.lang.StringCoding.encode(StringCoding.java:350)
    at java.lang.String.getBytes(String.java:941)
    at 
org.apache.spark.sql.execution.streaming.FileStreamSinkLog.serialize(FileStreamSinkLog.scala:127)
     
    ```
    The safer way is to write to an output stream so that we don't have to 
materialize a huge string.
    
    ## How was this patch tested?
    
    Existing unit tests
    


You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/brkyvz/spark ser-to-stream

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/spark/pull/15437.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #15437
    
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