Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/21200#discussion_r185357003
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousDataSourceRDD.scala
---
@@ -0,0 +1,160 @@
+/*
+ * 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.continuous
+
+import java.util.concurrent.TimeUnit
+import javax.annotation.concurrent.GuardedBy
+
+import scala.collection.mutable
+
+import org.apache.spark._
+import org.apache.spark.internal.Logging
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.{Row, SQLContext}
+import org.apache.spark.sql.catalyst.expressions.UnsafeRow
+import
org.apache.spark.sql.execution.datasources.v2.{DataSourceRDDPartition,
RowToUnsafeDataReader}
+import org.apache.spark.sql.sources.v2.reader._
+import
org.apache.spark.sql.sources.v2.reader.streaming.{ContinuousDataReader,
PartitionOffset}
+import org.apache.spark.util.ThreadUtils
+
+/**
+ * The bottom-most RDD of a continuous processing read task. Wraps a
[[ContinuousQueuedDataReader]]
+ * to read from the remote source, and polls that queue for incoming rows.
+ *
+ * Note that continuous processing calls compute() multiple times, and the
same
+ * [[ContinuousQueuedDataReader]] instance will/must be shared between
each call for the same split.
+ */
+class ContinuousDataSourceRDD(
+ sc: SparkContext,
+ sqlContext: SQLContext,
+ @transient private val readerFactories:
Seq[DataReaderFactory[UnsafeRow]])
+ extends RDD[UnsafeRow](sc, Nil) {
+
+ private val dataQueueSize =
sqlContext.conf.continuousStreamingExecutorQueueSize
+ private val epochPollIntervalMs =
sqlContext.conf.continuousStreamingExecutorPollIntervalMs
+
+ // When computing the same partition multiple times, we need to use the
same data reader to
+ // do so for continuity in offsets.
+ @GuardedBy("dataReaders")
+ private val dataReaders: mutable.Map[Partition,
ContinuousQueuedDataReader] =
--- End diff --
Does this whole reader map need to be serialized for every task? because as
it is now, this whole this going to be serialized for every task. Per-partition
objects like this should be passed through the RDDPartition object.
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