zifeif2 commented on code in PR #53703:
URL: https://github.com/apache/spark/pull/53703#discussion_r2666698849


##########
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/state/StateRewriter.scala:
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@@ -0,0 +1,373 @@
+/*
+ * 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.state
+
+import java.util.UUID
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+
+import org.apache.spark.{SparkIllegalStateException, TaskContext}
+import org.apache.spark.internal.Logging
+import org.apache.spark.internal.LogKeys._
+import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.execution.datasources.v2.state.StateSourceOptions
+import 
org.apache.spark.sql.execution.datasources.v2.state.metadata.StateMetadataPartitionReader
+import org.apache.spark.sql.execution.streaming.checkpointing.OffsetSeqMetadata
+import 
org.apache.spark.sql.execution.streaming.operators.stateful.StatefulOperatorsUtils
+import 
org.apache.spark.sql.execution.streaming.operators.stateful.transformwithstate.{StateVariableType,
 TransformWithStateOperatorProperties, TransformWithStateVariableInfo}
+import 
org.apache.spark.sql.execution.streaming.runtime.{StreamingCheckpointConstants, 
StreamingQueryCheckpointMetadata}
+import 
org.apache.spark.sql.execution.streaming.state.{StatePartitionAllColumnFamiliesWriter,
 StateSchemaCompatibilityChecker}
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.util.SerializableConfiguration
+
+/**
+ * State Rewriter is used to rewrite the state stores for a stateful streaming 
query.
+ * It reads state from a checkpoint location, optionally applies 
transformation to the state,
+ * and then writes the state back to a (possibly different) checkpoint 
location for a new batch ID.
+ *
+ * Example use case is for offline state repartitioning.
+ * Can also be used to support state rewind and other use cases.
+ *
+ * @param sparkSession The active Spark session.
+ * @param readBatchId The batch ID for reading state.
+ * @param writeBatchId The batch ID to which the (transformed) state will be 
written.
+ * @param resolvedCheckpointLocation The resolved checkpoint path where state 
will be written.
+ * @param hadoopConf Hadoop configuration for file system operations.
+ * @param readResolvedCheckpointLocation Optional separate checkpoint location 
to read state from.
+ *                                       If None, reads from 
resolvedCheckpointLocation.
+ * @param transformFunc Optional transformation function applied to each 
operator's state
+ *                      DataFrame. If None, state is written as-is.
+ * @param writeCheckpointMetadata Optional checkpoint metadata for the 
resolvedCheckpointLocation.
+ *                                If None, will create a new one for 
resolvedCheckpointLocation.
+ *                                Helps us to reuse already cached checkpoint 
log entries,
+ *                                instead of starting from scratch.
+ */
+class StateRewriter(
+    sparkSession: SparkSession,
+    readBatchId: Long,
+    writeBatchId: Long,
+    resolvedCheckpointLocation: String,
+    hadoopConf: Configuration,
+    readResolvedCheckpointLocation: Option[String] = None,
+    transformFunc: Option[DataFrame => DataFrame] = None,
+    writeCheckpointMetadata: Option[StreamingQueryCheckpointMetadata] = None
+) extends Logging {
+  require(readResolvedCheckpointLocation.isDefined || readBatchId < 
writeBatchId,
+    s"Read batch id $readBatchId must be less than write batch id 
$writeBatchId " +
+      "when reading and writing to the same checkpoint location")
+
+  // If a different location was specified for reading state, use it.
+  // Else, use same location for reading and writing state.
+  private val checkpointLocationForRead =
+    readResolvedCheckpointLocation.getOrElse(resolvedCheckpointLocation)
+  private val stateRootLocation = new Path(
+    resolvedCheckpointLocation, 
StreamingCheckpointConstants.DIR_NAME_STATE).toString
+
+  def run(): Unit = {

Review Comment:
   Though writer doesn't support checkpointV2 yet, do we still want to return 
`StateStoreCheckpointInfo` to unblock rewind/replay?



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