[GitHub] [spark] LuciferYang commented on a diff in pull request #38430: [SPARK-40957] Add in memory cache in HDFSMetadataLog

[GitBox <gi...@apache.org>]

LuciferYang commented on code in PR #38430:
URL: https://github.com/apache/spark/pull/38430#discussion_r1008810087


##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/HDFSMetadataLog.scala:
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@@ -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:
   Why not use Guava Cache like other places? In what scenarios will this change improve? How much performance improvement will it bring?I think It's better to have a benchmark to explain.



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