Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/15102#discussion_r79089110
--- Diff:
external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaSource.scala
---
@@ -0,0 +1,446 @@
+/*
+ * 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 scala.collection.JavaConverters._
+
+import org.apache.kafka.clients.consumer.{Consumer, ConsumerConfig,
KafkaConsumer}
+import
org.apache.kafka.clients.consumer.internals.NoOpConsumerRebalanceListener
+import org.apache.kafka.common.TopicPartition
+import org.apache.kafka.common.serialization.ByteArrayDeserializer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.scheduler.ExecutorCacheTaskLocation
+import org.apache.spark.sql._
+import org.apache.spark.sql.execution.streaming._
+import org.apache.spark.sql.kafka010.KafkaSource._
+import org.apache.spark.sql.sources.{DataSourceRegister,
StreamSourceProvider}
+import org.apache.spark.sql.types._
+import org.apache.spark.SparkContext
+
+/**
+ * A [[Source]] that uses Kafka's own [[KafkaConsumer]] API to reads data
from Kafka. The design
+ * for this source is as follows.
+ *
+ * - The [[KafkaSourceOffset]] is the custom [[Offset]] defined for this
source that contains
+ * a map of TopicPartition -> offset. Note that this offset is 1 +
(available offset). For
+ * example if the last record in a Kafka topic "t", partition 2 is
offset 5, then
+ * KafkaSourceOffset will contain TopicPartition("t", 2) -> 6. This is
done keep it consistent
+ * with the semantics of `KafkaConsumer.position()`.
+ *
+ * - The [[ConsumerStrategy]] class defines which Kafka topics and
partitions should be read
+ * by this source. These strategies directly correspond to the different
consumption options
+ * in . This class is designed to return a configured
+ * [[KafkaConsumer]] that is used by the [[KafkaSource]] to query for
the offsets.
+ * See the docs on
[[org.apache.spark.sql.kafka010.KafkaSource.ConsumerStrategy]] for
+ * more details.
+ *
+ * - The [[KafkaSource]] written to do the following.
+ *
+ * - As soon as the source is created, the pre-configured KafkaConsumer
returned by the
+ * [[ConsumerStrategy]] is used to query the initial offsets that this
source should
+ * start reading from. This used to create the first batch.
+ *
+ * - `getOffset()` uses the KafkaConsumer to query the latest available
offsets, which are
+ * returned as a [[KafkaSourceOffset]].
+ *
+ * - `getBatch()` returns a DF that reads from the 'start offset' until
the 'end offset' in
+ * for each partition. The end offset is excluded to be consistent
with the semantics of
+ * [[KafkaSourceOffset]] and `KafkaConsumer.position()`.
+ *
+ * - The DF returned is based on [[KafkaSourceRDD]] which is constructed
such that the
+ * data from Kafka topic + partition is consistently read by the same
executors across
+ * batches, and cached KafkaConsumers in the executors can be reused
efficiently. See the
+ * docs on [[KafkaSourceRDD]] for more details.
+ */
+private[kafka010] case class KafkaSource(
+ sqlContext: SQLContext,
+ consumerStrategy: ConsumerStrategy[Array[Byte], Array[Byte]],
+ executorKafkaParams: ju.Map[String, Object],
+ sourceOptions: Map[String, String])
+ extends Source with Logging {
+
+ @transient private val consumer = consumerStrategy.createConsumer()
+ @transient private val sc = sqlContext.sparkContext
+ @transient private val initialPartitionOffsets =
fetchPartitionOffsets(seekToLatest = false)
+ logInfo(s"Initial offsets: " + initialPartitionOffsets)
+
+ override def schema: StructType = KafkaSource.kafkaSchema
+
+ /** Returns the maximum available offset for this source. */
+ override def getOffset: Option[Offset] = {
+ val offset = KafkaSourceOffset(fetchPartitionOffsets(seekToLatest =
true))
+ logInfo(s"GetOffset: $offset")
+ Some(offset)
+ }
+
+ /**
+ * Returns the data that is between the offsets [`start`, `end`), i.e.
end is exclusive.
+ */
+ override def getBatch(start: Option[Offset], end: Offset): DataFrame = {
+ logDebug(s"GetBatch called with start = $start, end = $end")
+ val untilPartitionOffsets = KafkaSourceOffset.getPartitionOffsets(end)
+ val fromPartitionOffsets = start match {
+ case Some(prevBatchEndOffset) =>
+ KafkaSourceOffset.getPartitionOffsets(prevBatchEndOffset)
+ case None =>
+ initialPartitionOffsets
+ }
+
+ // Sort the partitions and current list of executors to consistently
assign each partition
+ // to the executor. This allows cached KafkaConsumers in the executors
to be re-used to
+ // read the same partition in every batch.
+ val topicPartitionOrdering = new Ordering[TopicPartition] {
+ override def compare(l: TopicPartition, r: TopicPartition): Int = {
+ implicitly[Ordering[(String, Long)]].compare(
+ (l.topic, l.partition),
+ (r.topic, r.partition))
+ }
+ }
+ val sortedTopicPartitions =
untilPartitionOffsets.keySet.toSeq.sorted(topicPartitionOrdering)
+ val sortedExecutors = getSortedExecutorList(sc)
+ val numExecutors = sortedExecutors.size
+ logDebug("Sorted executors: " + sortedExecutors.mkString(", "))
+ val offsetRanges = sortedTopicPartitions.flatMap { tp =>
+ fromPartitionOffsets.get(tp).map { fromOffset =>
+ val untilOffset = untilPartitionOffsets(tp)
+ val preferredLoc = if (numExecutors > 0) {
+ Some(sortedExecutors(positiveMod(tp.hashCode, numExecutors)))
+ } else None
+ KafkaSourceRDD.OffsetRange(tp, fromOffset, untilOffset,
preferredLoc)
+ }
+ }.toArray
+
+ // Create a RDD that reads from Kafka and get the (key, value) pair as
byte arrays.
+ val rdd = new KafkaSourceRDD[Array[Byte], Array[Byte]](
+ sc, executorKafkaParams, offsetRanges, sourceOptions).map { cr =>
+ Row(cr.checksum, cr.key, cr.offset, cr.partition,
cr.serializedKeySize,
+ cr.serializedValueSize, cr.timestamp, cr.timestampType.id,
cr.topic, cr.value)
+ }
+
+ logInfo("GetBatch: " +
offsetRanges.sortBy(_.topicPartition.toString).mkString(", "))
+ sqlContext.createDataFrame(rdd, schema)
+ }
+
+ /** Stop this source and free any resources it has allocated. */
+ override def stop(): Unit = synchronized {
+ consumer.close()
+ }
+
+ override def toString(): String = s"KafkaSource[$consumerStrategy]"
+
+ private def fetchPartitionOffsets(seekToLatest: Boolean):
Map[TopicPartition, Long] = {
+ synchronized {
+ logTrace("\tPolling")
+ consumer.poll(0)
+ val partitions = consumer.assignment()
+ consumer.pause(partitions)
+ logDebug(s"\tPartitioned assigned to consumer: $partitions")
+ if (seekToLatest) {
+ consumer.seekToEnd(partitions)
+ logDebug("\tSeeked to the end")
+ }
+ logTrace("Getting positions")
+ val partitionToOffsets = partitions.asScala.map(p => p ->
consumer.position(p))
+ logDebug(s"Got positions $partitionToOffsets")
+ partitionToOffsets.toMap
+ }
+ }
+
+ private def positiveMod(a: Long, b: Int): Int = ((a % b).toInt + b) % b
+}
+
+/** Companion object for the [[KafkaSource]]. */
+private[kafka010] object KafkaSource {
+
+ def kafkaSchema: StructType = StructType(Seq(
+ StructField("checksum", LongType),
+ StructField("key", BinaryType),
+ StructField("offset", LongType),
+ StructField("partition", IntegerType),
+ StructField("serializedKeySize", IntegerType),
+ StructField("serializedValueSize", IntegerType),
+ StructField("timestamp", LongType),
+ StructField("timestampType", IntegerType),
+ StructField("topic", StringType),
+ StructField("value", BinaryType)
+ ))
+
+ sealed trait ConsumerStrategy[K, V] {
+ def createConsumer(): Consumer[K, V]
+ }
+
+ case class SubscribeStrategy[K, V](topics: Seq[String], kafkaParams:
ju.Map[String, Object])
+ extends ConsumerStrategy[K, V] {
+ override def createConsumer(): Consumer[K, V] = {
+ val consumer = new KafkaConsumer[K, V](kafkaParams)
+ consumer.subscribe(topics.asJava)
+ consumer.poll(0)
+ consumer
+ }
+
+ override def toString: String = s"Subscribe[${topics.mkString(", ")}]"
+ }
+
+ case class SubscribePatternStrategy[K, V](
+ topicPattern: String, kafkaParams: ju.Map[String, Object])
+ extends ConsumerStrategy[K, V] {
+ override def createConsumer(): Consumer[K, V] = {
+ val consumer = new KafkaConsumer[K, V](kafkaParams)
+ consumer.subscribe(
+ ju.regex.Pattern.compile(topicPattern),
+ new NoOpConsumerRebalanceListener())
+ consumer.poll(0)
+ consumer
+ }
+
+ override def toString: String = s"SubscribePattern[$topicPattern]"
+ }
+
+ def getSortedExecutorList(sc: SparkContext): Array[String] = {
+ def compare(a: ExecutorCacheTaskLocation, b:
ExecutorCacheTaskLocation): Boolean = {
+ if (a.host == b.host) { a.executorId > b.executorId } else { a.host
> b.host }
+ }
+
+ val bm = sc.env.blockManager
+ bm.master.getPeers(bm.blockManagerId).toArray
+ .map(x => ExecutorCacheTaskLocation(x.host, x.executorId))
+ .sortWith(compare)
+ .map(_.toString)
+ }
+}
+
+
+/** An [[Offset]] for the [[KafkaSource]]. */
+private[kafka010]
+case class KafkaSourceOffset(partitionToOffsets: Map[TopicPartition,
Long]) extends Offset {
+ /**
+ * Returns a negative integer, zero, or a positive integer as this
object is less than, equal to,
+ * or greater than the specified object.
+ */
+ override def compareTo(other: Offset): Int = other match {
+ case KafkaSourceOffset(otherOffsets) =>
+ val allTopicAndPartitions = (this.partitionToOffsets.keySet ++
otherOffsets.keySet).toSeq
+
+ val comparisons = allTopicAndPartitions.map { tp =>
+ (this.partitionToOffsets.get(tp), otherOffsets.get(tp)) match {
+ case (Some(a), Some(b)) =>
+ if (a < b) {
+ -1
+ } else if (a > b) {
+ 1
+ } else {
+ 0
+ }
+ case (None, _) => -1
+ case (_, None) => 1
+ }
+ }
+ val nonZeroSigns = comparisons.filter { _ != 0 }.toSet
+ nonZeroSigns.size match {
+ case 0 => 0 // if both empty or only 0s
+ case 1 => nonZeroSigns.head // if there are only (0s and 1s) or
(0s and -1s)
+ case _ => // there are both 1s and -1s
+ throw new IllegalArgumentException(
+ s"Invalid comparison between non-linear histories: $this <=>
$other")
+ }
+
+ case _ =>
+ throw new IllegalArgumentException(s"Cannot compare $this <=>
$other")
+ }
+
+ override def toString(): String = {
+ partitionToOffsets.toSeq.sortBy(_._1.toString).mkString("[", ", ", "]")
+ }
+}
+
+/** Companion object of the [[KafkaSourceOffset]] */
+private[kafka010] object KafkaSourceOffset {
+
+ def getPartitionOffsets(offset: Offset): Map[TopicPartition, Long] = {
+ offset match {
+ case o: KafkaSourceOffset => o.partitionToOffsets
+ case _ =>
+ throw new IllegalArgumentException(
+ s"Invalid conversion from offset of ${offset.getClass} to
KafkaSourceOffset")
+ }
+ }
+
+ /**
+ * Returns [[KafkaSourceOffset]] from a variable sequence of (topic,
partitionId, offset)
+ * tuples.
+ */
+ def apply(offsetTuples: (String, Int, Long)*): KafkaSourceOffset = {
+ KafkaSourceOffset(offsetTuples.map { case(t, p, o) => (new
TopicPartition(t, p), o) }.toMap)
+ }
+}
+
+
+/**
+ * The provider class for the [[KafkaSource]]. This provider is designed
such that it throws
+ * IllegalArgumentException when the Kafka Dataset is created, so that it
can catch
+ * missing options even before the query is started.
+ */
+private[kafka010] class KafkaSourceProvider extends StreamSourceProvider
+ with DataSourceRegister with Logging {
+ private val strategyOptionNames = Set("subscribe", "subscribepattern")
+
+ /** Class to conveniently update Kafka config params, while logging the
changes */
+ private case class ConfigUpdater(module: String, kafkaParams:
Map[String, String]) {
+ private val map = new ju.HashMap[String, Object](kafkaParams.asJava)
+ def set(key: String, value: Object): this.type = {
+ map.put(key, value)
+ logInfo(s"$module: Set $key to $value, earlier value:
${kafkaParams.get(key).getOrElse("")}")
+ this
+ }
+
+ def setIfUnset(key: String, value: Object): ConfigUpdater = {
+ if (!map.containsKey(key)) {
+ map.put(key, value)
+ logInfo(s"$module: Set $key to $value")
+ }
+ this
+ }
+
+ def build(): ju.Map[String, Object] = map
+ }
+
+ /**
+ * Returns the name and schema of the source. In addition, it also
verifies whether the options
+ * are correct and sufficient to create the [[KafkaSource]] when the
query is started.
+ */
+ override def sourceSchema(
+ sqlContext: SQLContext,
+ schema: Option[StructType],
+ providerName: String,
+ parameters: Map[String, String]): (String, StructType) = {
+ validateOptions(parameters)
+ ("kafka", KafkaSource.kafkaSchema)
+ }
+
+ override def createSource(
+ sqlContext: SQLContext,
+ metadataPath: String,
+ schema: Option[StructType],
+ providerName: String,
+ parameters: Map[String, String]): Source = {
+ validateOptions(parameters)
+ val caseInsensitiveParams = parameters.map { case (k, v) =>
(k.toLowerCase, v) }
+ val specifiedKafkaParams =
+ parameters
+ .keySet
+ .filter(_.toLowerCase.startsWith("kafka."))
+ .map { k => k.drop(6).toString -> parameters(k) }
+ .toMap
+
+ val deserClassName = classOf[ByteArrayDeserializer].getName
+
+ val kafkaParamsForStrategy =
+ ConfigUpdater("source", specifiedKafkaParams)
+ .set(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, deserClassName)
+ .set(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
deserClassName)
+ .build()
+
+ val kafkaParamsForExecutors =
+ ConfigUpdater("source", specifiedKafkaParams)
+ .set(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, deserClassName)
+ .set(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
deserClassName)
+
+ // So that consumers in executors never throw
NoOffsetForPartitionException
+ .set(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "none")
+
+ // So that consumers in executors do not mess with user-specified
group id
+ .set(ConsumerConfig.GROUP_ID_CONFIG,
+ "spark-executor-" +
specifiedKafkaParams(ConsumerConfig.GROUP_ID_CONFIG))
+
+ // So that consumers in executors no keep committing offsets
unnecessaribly
+ .set(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false")
+
+ // If buffer config is not set, it to reasonable value to work
around
+ // buffer issues (see KAFKA-3135)
+ .setIfUnset(ConsumerConfig.RECEIVE_BUFFER_CONFIG, 65536:
java.lang.Integer)
+ .build()
+
+ val strategy = caseInsensitiveParams.find(x =>
strategyOptionNames.contains(x._1)).get match {
+ case ("subscribe", value) =>
+ SubscribeStrategy[Array[Byte], Array[Byte]](
+ value.split(",").map(_.trim()).filter(_.nonEmpty),
+ kafkaParamsForStrategy)
+ case ("subscribepattern", value) =>
+ SubscribePatternStrategy[Array[Byte], Array[Byte]](
+ value.trim(),
+ kafkaParamsForStrategy)
+ case _ =>
+ // Should never reach here as we are already matching on
+ // matched strategy names
+ throw new IllegalArgumentException("Unknown option")
+ }
+
+ new KafkaSource(sqlContext, strategy, kafkaParamsForExecutors,
parameters)
+ }
+
+ private def validateOptions(parameters: Map[String, String]): Unit = {
+ val caseInsensitiveParams = parameters.map { case (k, v) =>
(k.toLowerCase, v) }
+ val specifiedStrategies =
+ caseInsensitiveParams.filter { case(k, _) =>
strategyOptionNames.contains(k) }.toSeq
+ if (specifiedStrategies.isEmpty) {
+ throw new IllegalArgumentException(
+ "One of the following options must be specified for Kafka source: "
+ + strategyOptionNames.mkString(", ") + ". See docs for more
details.")
+ } else if (specifiedStrategies.size > 1) {
+ throw new IllegalArgumentException(
+ "Only one of the following options can be specified for Kafka
source: "
+ + strategyOptionNames.mkString(", ") + ". See docs for more
details.")
+ }
+
+ val strategy = caseInsensitiveParams.find(x =>
strategyOptionNames.contains(x._1)).get match {
+ case ("subscribe", value) =>
+ val topics = value.split(",").map(_.trim).filter(_.nonEmpty)
--- End diff --
I think the answer is "no", but can topics have `,`s in them?
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