Github user jose-torres commented on a diff in the pull request:
https://github.com/apache/spark/pull/20253#discussion_r161360701
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaContinuousReader.scala
---
@@ -0,0 +1,253 @@
+/*
+ * 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.kafka010
+
+import java.{util => ju}
+import java.util.concurrent.TimeoutException
+
+import org.apache.kafka.clients.consumer.{ConsumerRecord,
OffsetOutOfRangeException}
+import org.apache.kafka.common.TopicPartition
+
+import org.apache.spark.TaskContext
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.catalyst.expressions.UnsafeRow
+import org.apache.spark.sql.catalyst.expressions.codegen.{BufferHolder,
UnsafeRowWriter}
+import org.apache.spark.sql.catalyst.util.DateTimeUtils
+import
org.apache.spark.sql.kafka010.KafkaSource.{INSTRUCTION_FOR_FAIL_ON_DATA_LOSS_FALSE,
INSTRUCTION_FOR_FAIL_ON_DATA_LOSS_TRUE}
+import org.apache.spark.sql.sources.v2.reader._
+import
org.apache.spark.sql.sources.v2.streaming.reader.{ContinuousDataReader,
ContinuousReader, Offset, PartitionOffset}
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.unsafe.types.UTF8String
+
+/**
+ * A [[ContinuousReader]] for data from kafka.
+ *
+ * @param offsetReader a reader used to get kafka offsets. Note that the
actual data will be
+ * read by per-task consumers generated later.
+ * @param kafkaParams String params for per-task Kafka consumers.
+ * @param sourceOptions The
[[org.apache.spark.sql.sources.v2.DataSourceV2Options]] params which
+ * are not Kafka consumer params.
+ * @param metadataPath Path to a directory this reader can use for writing
metadata.
+ * @param initialOffsets The Kafka offsets to start reading data at.
+ * @param failOnDataLoss Flag indicating whether reading should fail in
data loss
+ * scenarios, where some offsets after the specified
initial ones can't be
+ * properly read.
+ */
+class KafkaContinuousReader(
+ offsetReader: KafkaOffsetReader,
+ kafkaParams: ju.Map[String, Object],
+ sourceOptions: Map[String, String],
+ metadataPath: String,
+ initialOffsets: KafkaOffsetRangeLimit,
+ failOnDataLoss: Boolean)
+ extends ContinuousReader with SupportsScanUnsafeRow with Logging {
+
+ private lazy val session = SparkSession.getActiveSession.get
+ private lazy val sc = session.sparkContext
+
+ // Initialized when creating read tasks. If this diverges from the
partitions at the latest
+ // offsets, we need to reconfigure.
+ // Exposed outside this object only for unit tests.
+ private[sql] var knownPartitions: Set[TopicPartition] = _
+
+ override def readSchema: StructType = KafkaOffsetReader.kafkaSchema
+
+ private var offset: Offset = _
+ override def setOffset(start: ju.Optional[Offset]): Unit = {
+ offset = start.orElse {
+ val offsets = initialOffsets match {
+ case EarliestOffsetRangeLimit =>
KafkaSourceOffset(offsetReader.fetchEarliestOffsets())
+ case LatestOffsetRangeLimit =>
KafkaSourceOffset(offsetReader.fetchLatestOffsets())
+ case SpecificOffsetRangeLimit(p) =>
offsetReader.fetchSpecificOffsets(p, reportDataLoss)
+ }
+ logInfo(s"Initial offsets: $offsets")
+ offsets
+ }
+ }
+
+ override def getStartOffset(): Offset = offset
+
+ override def deserializeOffset(json: String): Offset = {
+ KafkaSourceOffset(JsonUtils.partitionOffsets(json))
+ }
+
+ override def createUnsafeRowReadTasks(): ju.List[ReadTask[UnsafeRow]] = {
+ import scala.collection.JavaConverters._
+
+ val oldStartPartitionOffsets =
KafkaSourceOffset.getPartitionOffsets(offset)
+
+ val currentPartitionSet = offsetReader.fetchEarliestOffsets().keySet
+ val newPartitions =
currentPartitionSet.diff(oldStartPartitionOffsets.keySet)
+ val newPartitionOffsets =
offsetReader.fetchEarliestOffsets(newPartitions.toSeq)
+
+ val deletedPartitions =
oldStartPartitionOffsets.keySet.diff(currentPartitionSet)
+ if (deletedPartitions.nonEmpty) {
+ reportDataLoss(s"Some partitions were deleted: $deletedPartitions")
+ }
+
+ val startOffsets = newPartitionOffsets ++
+ oldStartPartitionOffsets.filterKeys(!deletedPartitions.contains(_))
+ knownPartitions = startOffsets.keySet
+
+ startOffsets.toSeq.map {
+ case (topicPartition, start) =>
+ KafkaContinuousReadTask(
+ topicPartition, start, kafkaParams, failOnDataLoss)
+ .asInstanceOf[ReadTask[UnsafeRow]]
+ }.asJava
+ }
+
+ /** Stop this source and free any resources it has allocated. */
+ def stop(): Unit = synchronized {
+ offsetReader.close()
+ }
+
+ override def commit(end: Offset): Unit = {}
+
+ override def mergeOffsets(offsets: Array[PartitionOffset]): Offset = {
+ val mergedMap = offsets.map {
+ case KafkaSourcePartitionOffset(p, o) => Map(p -> o)
+ }.reduce(_ ++ _)
+ KafkaSourceOffset(mergedMap)
+ }
+
+ override def needsReconfiguration(): Boolean = {
+ knownPartitions != null && offsetReader.fetchLatestOffsets().keySet !=
knownPartitions
+ }
+
+ override def toString(): String = s"KafkaSource[$offsetReader]"
+
+ /**
+ * If `failOnDataLoss` is true, this method will throw an
`IllegalStateException`.
+ * Otherwise, just log a warning.
+ */
+ private def reportDataLoss(message: String): Unit = {
+ if (failOnDataLoss) {
+ throw new IllegalStateException(message + s".
$INSTRUCTION_FOR_FAIL_ON_DATA_LOSS_TRUE")
+ } else {
+ logWarning(message + s". $INSTRUCTION_FOR_FAIL_ON_DATA_LOSS_FALSE")
+ }
+ }
+}
+
+/**
+ * A read task for continuous Kafka processing. This will be serialized
and transformed into a
+ * full reader on executors.
+ *
+ * @param topicPartition The (topic, partition) pair this task is
responsible for.
+ * @param startOffset The offset to start reading from within the
partition.
+ * @param kafkaParams Kafka consumer params to use.
+ * @param failOnDataLoss Flag indicating whether data reader should fail
if some offsets
+ * are skipped.
+ */
+case class KafkaContinuousReadTask(
+ topicPartition: TopicPartition,
+ startOffset: Long,
+ kafkaParams: ju.Map[String, Object],
+ failOnDataLoss: Boolean) extends ReadTask[UnsafeRow] {
+ override def createDataReader(): KafkaContinuousDataReader = {
+ new KafkaContinuousDataReader(topicPartition, startOffset,
kafkaParams, failOnDataLoss)
+ }
+}
+
+/**
+ * A per-task data reader for continuous Kafka processing.
+ *
+ * @param topicPartition The (topic, partition) pair this data reader is
responsible for.
+ * @param startOffset The offset to start reading from within the
partition.
+ * @param kafkaParams Kafka consumer params to use.
+ * @param failOnDataLoss Flag indicating whether data reader should fail
if some offsets
+ * are skipped.
+ */
+class KafkaContinuousDataReader(
+ topicPartition: TopicPartition,
+ startOffset: Long,
+ kafkaParams: ju.Map[String, Object],
+ failOnDataLoss: Boolean) extends ContinuousDataReader[UnsafeRow] {
+ private val topic = topicPartition.topic
+ private val kafkaPartition = topicPartition.partition
+ private val consumer = CachedKafkaConsumer.createUncached(topic,
kafkaPartition, kafkaParams)
+
+ private val sharedRow = new UnsafeRow(7)
+ private val bufferHolder = new BufferHolder(sharedRow)
+ private val rowWriter = new UnsafeRowWriter(bufferHolder, 7)
+
+ private var nextKafkaOffset = startOffset
+ private var currentRecord: ConsumerRecord[Array[Byte], Array[Byte]] = _
+
+ override def next(): Boolean = {
+ var r: ConsumerRecord[Array[Byte], Array[Byte]] = null
+ while (r == null) {
+ if (TaskContext.get().isInterrupted() ||
TaskContext.get().isCompleted()) return false
+ // Our consumer.get is not interruptible, so we have to set a low
poll timeout, leaving
+ // interrupt points to end the query rather than waiting for new
data that might never come.
+ try {
+ r = consumer.get(
+ nextKafkaOffset,
+ untilOffset = Long.MaxValue,
+ pollTimeoutMs = 1000,
+ failOnDataLoss)
+ } catch {
+ // We didn't read within the timeout. We're supposed to block
indefinitely for new data, so
+ // swallow and ignore this.
+ case _: TimeoutException =>
+ // This is a failOnDataLoss exception. Retry if nextKafkaOffset is
within the data range,
+ // or if it's the endpoint of the data range (i.e. the "true" next
offset).
+ case e: IllegalStateException =>
+ val range = consumer.getAvailableOffsetRange()
+ if (e.getCause.isInstanceOf[OffsetOutOfRangeException] &&
+ range.latest >= nextKafkaOffset && range.earliest <=
nextKafkaOffset) {
+ // retry
+ } else {
+ throw e
+ }
+ }
+ }
--- End diff --
Done. In a future PR (I want to minimize the delta on a roll-forward), I'm
going to figure out how to get this in ContinuousTest for the benefit of future
sources.
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