[GitHub] [spark] jerrypeng commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog
jerrypeng commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1014297681
##
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
##
@@ -277,10 +295,34 @@ class HDFSMetadataLog[T <: AnyRef :
ClassTag](sparkSession: SparkSession, path:
for (batchId <- batchIds if batchId > thresholdBatchId) {
val path = batchIdToPath(batchId)
fileManager.delete(path)
+ if (metadataCacheEnabled) batchCache.remove(batchId)
logTrace(s"Removed metadata log file: $path")
}
}
+
+ /**
+ * List the available batches on file system. As a workaround for S3
inconsistent list, it also
Review Comment:
I think this comment is out of date. Amazon now delivers strong read after
write consistency. I will remove in a subsequent PR
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[GitHub] [spark] jerrypeng commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog
jerrypeng commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1011241156
##
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
##
@@ -19,7 +19,9 @@ package org.apache.spark.sql.execution.streaming
import java.io._
import java.nio.charset.StandardCharsets
+import java.util.{Collections, LinkedHashMap}
Review Comment:
sure
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[GitHub] [spark] jerrypeng commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog
jerrypeng commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1011239497
##
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
##
@@ -64,6 +67,17 @@ class HDFSMetadataLog[T <: AnyRef : ClassTag](sparkSession:
SparkSession, path:
fileManager.mkdirs(metadataPath)
}
+ protected val metadataCacheEnabled: Boolean
+ =
sparkSession.sessionState.conf.getConf(SQLConf.STREAMING_METADATA_CACHE_ENABLED)
+
+ /**
+ * Cache the latest two batches. [[StreamExecution]] usually just accesses
the latest two batches
+ * when committing offsets, this cache will save some file system operations.
+ */
+ protected[sql] val batchCache = Collections.synchronizedMap(new
LinkedHashMap[Long, T](2) {
Review Comment:
We could but the change is not really going to yield much difference. The
memory foot print of this is minimal.
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[GitHub] [spark] jerrypeng commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog
jerrypeng commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1011238096
##
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
##
@@ -277,10 +295,34 @@ class HDFSMetadataLog[T <: AnyRef :
ClassTag](sparkSession: SparkSession, path:
for (batchId <- batchIds if batchId > thresholdBatchId) {
val path = batchIdToPath(batchId)
fileManager.delete(path)
+ if (metadataCacheEnabled) batchCache.remove(batchId)
logTrace(s"Removed metadata log file: $path")
}
}
+
+ /**
+ * List the available batches on file system. As a workaround for S3
inconsistent list, it also
+ * tries to take `batchCache` into consideration to infer a better answer.
+ */
+ protected def listBatches: Array[Long] = {
+val batchIds = fileManager.list(metadataPath, batchFilesFilter)
+ .map(f => pathToBatchId(f.getPath)) ++
+ // Iterate over keySet is not thread safe. We call `toArray` to make a
copy in the lock to
+ // elimiate the race condition.
+ batchCache.synchronized {
+batchCache.keySet.asScala.toArray
+ }
+logInfo("BatchIds found from listing: " + batchIds.sorted.mkString(", "))
+
+if (batchIds.isEmpty) {
+ return Array.empty
Review Comment:
will fix
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[GitHub] [spark] jerrypeng commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog
jerrypeng commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1010692304
##
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
##
@@ -277,10 +295,34 @@ class HDFSMetadataLog[T <: AnyRef :
ClassTag](sparkSession: SparkSession, path:
for (batchId <- batchIds if batchId > thresholdBatchId) {
val path = batchIdToPath(batchId)
fileManager.delete(path)
+ if (metadataCacheEnabled) batchCache.remove(batchId)
logTrace(s"Removed metadata log file: $path")
}
}
+
+ /**
+ * List the available batches on file system. As a workaround for S3
inconsistent list, it also
+ * tries to take `batchCache` into consideration to infer a better answer.
+ */
+ protected def listBatches: Array[Long] = {
+val batchIds = fileManager.list(metadataPath, batchFilesFilter)
+ .map(f => pathToBatchId(f.getPath)) ++
+ // Iterate over keySet is not thread safe. We call `toArray` to make a
copy in the lock to
+ // elimiate the race condition.
+ batchCache.synchronized {
+batchCache.keySet.asScala.toArray
Review Comment:
We need to return a scala array not a Java array.
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