Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/13513#discussion_r78630727
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/CompactibleFileStreamLog.scala
---
@@ -0,0 +1,249 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.streaming
+
+import java.io.IOException
+import java.nio.charset.StandardCharsets.UTF_8
+import java.util.concurrent.TimeUnit
+
+import scala.reflect.ClassTag
+
+import org.apache.hadoop.fs.{Path, PathFilter}
+
+import org.apache.spark.sql.SparkSession
+
+/**
+ * An abstract class for compactible metadata logs. It will write one log
file for each batch.
+ * The first line of the log file is the version number, and there are
multiple JSON lines
+ * following.
+ *
+ * As reading from many small files is usually pretty slow, also too many
+ * small files in one folder will mess the FS,
[[CompactibleFileStreamLog]] will
+ * compact log files every 10 batches by default into a big file. When
+ * doing a compaction, it will read all old log files and merge them with
the new batch.
+ */
+abstract class CompactibleFileStreamLog[T: ClassTag](
+ sparkSession: SparkSession,
+ path: String)
+ extends HDFSMetadataLog[Array[T]](sparkSession, path) {
+
+ import CompactibleFileStreamLog._
+
+ /**
+ * If we delete the old files after compaction at once, there is a race
condition in S3: other
+ * processes may see the old files are deleted but still cannot see the
compaction file using
+ * "list". The `allFiles` handles this by looking for the next
compaction file directly, however,
+ * a live lock may happen if the compaction happens too frequently: one
processing keeps deleting
+ * old files while another one keeps retrying. Setting a reasonable
cleanup delay could avoid it.
+ */
+ protected val fileCleanupDelayMs = TimeUnit.MINUTES.toMillis(10)
+
+ protected val isDeletingExpiredLog = true
+
+ protected val compactInterval = 10
+
+ /**
+ * Serialize the data into encoded string.
+ */
+ protected def serializeData(t: T): String
+
+ /**
+ * Deserialize the string into data object.
+ */
+ protected def deserializeData(encodedString: String): T
+
+ /**
+ * Filter out the unwanted logs, by default it filters out nothing,
inherited class could
+ * override this method to do filtering.
+ */
+ protected def compactLogs(oldLogs: Seq[T], newLogs: Seq[T]): Seq[T] = {
+ oldLogs ++ newLogs
+ }
+
+ override def batchIdToPath(batchId: Long): Path = {
+ if (isCompactionBatch(batchId, compactInterval)) {
+ new Path(metadataPath, s"$batchId$COMPACT_FILE_SUFFIX")
+ } else {
+ new Path(metadataPath, batchId.toString)
+ }
+ }
+
+ override def pathToBatchId(path: Path): Long = {
+ getBatchIdFromFileName(path.getName)
+ }
+
+ override def isBatchFile(path: Path): Boolean = {
+ try {
+ getBatchIdFromFileName(path.getName)
+ true
+ } catch {
+ case _: NumberFormatException => false
+ }
+ }
+
+ override def serialize(logData: Array[T]): Array[Byte] = {
+ (VERSION +: logData.map(serializeData)).mkString("\n").getBytes(UTF_8)
--- End diff --
Could you make VERSION be a constructor parameter in order to support to
change source or sink format separately?
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