[GitHub] spark pull request #15437: [SPARK-17876] Write StructuredStreaming WAL to a ...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/15437 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15437: [SPARK-17876] Write StructuredStreaming WAL to a ...
Github user zsxwing commented on a diff in the pull request: https://github.com/apache/spark/pull/15437#discussion_r83097076 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FileStreamSourceLog.scala --- @@ -17,6 +17,7 @@ package org.apache.spark.sql.execution.streaming +import java.io.OutputStream --- End diff -- nit: unused import --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15437: [SPARK-17876] Write StructuredStreaming WAL to a ...
Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/15437#discussion_r83096847
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CompactibleFileStreamLog.scala
---
@@ -93,20 +95,26 @@ abstract class CompactibleFileStreamLog[T: ClassTag](
}
}
- override def serialize(logData: Array[T]): Array[Byte] = {
-(metadataLogVersion +:
logData.map(serializeData)).mkString("\n").getBytes(UTF_8)
+ override def serialize(logData: Array[T], out: OutputStream): Unit = {
+// called inside a try-finally where the underlying stream is closed
in the caller
+out.write(metadataLogVersion.getBytes(UTF_8))
+logData.foreach { data =>
+ out.write('\n')
+ out.write(serializeData(data).getBytes(UTF_8))
+}
+out.flush()
}
- override def deserialize(bytes: Array[Byte]): Array[T] = {
-val lines = new String(bytes, UTF_8).split("\n")
-if (lines.length == 0) {
+ override def deserialize(in: InputStream): Array[T] = {
+val lines = IOUtils.lineIterator(in, UTF_8).asScala
--- End diff --
nit: why not use `Source.getLines` since this is Scala.
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[GitHub] spark pull request #15437: [SPARK-17876] Write StructuredStreaming WAL to a ...
Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/15437#discussion_r83096455
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala
---
@@ -17,19 +17,17 @@
package org.apache.spark.sql.execution.streaming
-import java.io.{FileNotFoundException, IOException}
-import java.nio.ByteBuffer
+import java.io.{FileNotFoundException, InputStream, IOException,
OutputStream}
import java.util.{ConcurrentModificationException, EnumSet, UUID}
import scala.reflect.ClassTag
-import org.apache.commons.io.IOUtils
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs._
import org.apache.hadoop.fs.permission.FsPermission
+import org.apache.hadoop.io.IOUtils
--- End diff --
nit: use org.apache.commons.io.IOUtils instead. Hadoop's IOUtils is
`@InterfaceStability.Evolving` which can break compatibility at minor release
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[GitHub] spark pull request #15437: [SPARK-17876] Write StructuredStreaming WAL to a ...
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 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
