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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