Github user huitseeker commented on a diff in the pull request:
https://github.com/apache/spark/pull/7578#discussion_r35231803
--- Diff:
extras/kinesis-asl/src/main/scala/org/apache/spark/streaming/kinesis/KinesisBackedBlockRDD.scala
---
@@ -0,0 +1,223 @@
+/*
+ * 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.streaming.kinesis
+
+import scala.collection.JavaConversions._
+
+import com.amazonaws.auth.{AWSCredentials,
DefaultAWSCredentialsProviderChain}
+import com.amazonaws.services.kinesis.AmazonKinesisClient
+import com.amazonaws.services.kinesis.model._
+
+import org.apache.spark._
+import org.apache.spark.rdd.{BlockRDD, BlockRDDPartition}
+import org.apache.spark.storage.BlockId
+import org.apache.spark.util.NextIterator
+
+
+/** Class representing a range of Kinesis sequence numbers */
+private[kinesis]
+case class SequenceNumberRange(
+ streamName: String, shardId: String, fromSeqNumber: String,
toSeqNumber: String)
+
+/** Class representing an array of Kinesis sequence number ranges */
+private[kinesis]
+case class SequenceNumberRanges(ranges: Array[SequenceNumberRange]) {
+ def isEmpty(): Boolean = ranges.isEmpty
+ def nonEmpty(): Boolean = ranges.nonEmpty
+ override def toString(): String =
ranges.mkString("SequenceNumberRanges(", ", ", ")")
+}
+
+private[kinesis]
+object SequenceNumberRanges {
+ def apply(range: SequenceNumberRange): SequenceNumberRanges = {
+ new SequenceNumberRanges(Array(range))
+ }
+}
+
+
+/** Partition storing the information of the ranges of Kinesis sequence
numbers to read */
+private[kinesis]
+class KinesisBackedBlockRDDPartition(
+ idx: Int,
+ blockId: BlockId,
+ val isBlockIdValid: Boolean,
+ val seqNumberRanges: SequenceNumberRanges
+ ) extends BlockRDDPartition(blockId, idx)
+
+/**
+ * A BlockRDD where the block data is backed by Kinesis, which can
accessed using the
+ * sequence numbers of the corresponding blocks.
+ */
+private[kinesis]
+class KinesisBackedBlockRDD(
+ sc: SparkContext,
+ regionId: String,
+ endpointUrl: String,
+ @transient blockIds: Array[BlockId],
+ @transient arrayOfseqNumberRanges: Array[SequenceNumberRanges],
+ @transient isBlockIdValid: Array[Boolean] = Array.empty,
+ awsCredentialsOption: Option[SerializableAWSCredentials] = None
+) extends BlockRDD[Array[Byte]](sc, blockIds) {
+
+ require(blockIds.length == arrayOfseqNumberRanges.length,
+ "Number of blockIds is not equal to the number of sequence number
ranges")
+
+ override def isValid(): Boolean = true
+
+ override def getPartitions: Array[Partition] = {
+ Array.tabulate(blockIds.length) { i =>
+ val isValid = if (isBlockIdValid.length == 0) true else
isBlockIdValid(i)
+ new KinesisBackedBlockRDDPartition(i, blockIds(i), isValid,
arrayOfseqNumberRanges(i))
+ }
+ }
+
+ override def compute(split: Partition, context: TaskContext):
Iterator[Array[Byte]] = {
+ val blockManager = SparkEnv.get.blockManager
+ val partition = split.asInstanceOf[KinesisBackedBlockRDDPartition]
+ val blockId = partition.blockId
+
+ def getBlockFromBlockManager(): Option[Iterator[Array[Byte]]] = {
+ logDebug(s"Read partition data of $this from block manager, block
$blockId")
+
blockManager.get(blockId).map(_.data.asInstanceOf[Iterator[Array[Byte]]])
+ }
+
+ def getBlockFromKinesis(): Iterator[Array[Byte]] = {
+ val credenentials = awsCredentialsOption.getOrElse {
+ new DefaultAWSCredentialsProviderChain().getCredentials()
+ }
+ partition.seqNumberRanges.ranges.iterator.flatMap { range =>
+ new KinesisSequenceRangeIterator(credenentials, endpointUrl,
regionId, range)
+ }
+ }
+ if (partition.isBlockIdValid) {
+ getBlockFromBlockManager().getOrElse { getBlockFromKinesis() }
+ } else {
+ getBlockFromKinesis()
+ }
+ }
+}
+
+
+/** An iterator that return the Kinesis data based on the given range of
Sequence numbers */
+private[kinesis]
+class KinesisSequenceRangeIterator(
+ credentials: AWSCredentials,
+ endpointUrl: String,
+ regionId: String,
+ range: SequenceNumberRange
+ ) extends NextIterator[Array[Byte]] {
+
+ private val backoffTimeMillis = 1000
+ private val client = new AmazonKinesisClient(credentials)
+
+ private var toSeqNumberReceived = false
+ private var lastSeqNumber: String = null
+ private var internalIterator: Iterator[Record] = null
+
+ client.setEndpoint(endpointUrl, "kinesis", regionId)
+
+ override protected def getNext(): Array[Byte] = {
+ var nextBytes: Array[Byte] = null
+ if (toSeqNumberReceived) {
+ finished = true
+ } else {
+
+ if (internalIterator == null) {
+
+ // If the internal iterator has not been initialized,
+ // then fetch records from starting sequence number
+ getRecords(ShardIteratorType.AT_SEQUENCE_NUMBER,
range.fromSeqNumber)
--- End diff --
Forgive my unfamiliarity with Kinesis, but are sequence numbers contiguous
and increasing ? Because this seems to be the assumption here. In [the
doc](https://docs.aws.amazon.com/kinesis/latest/dev/key-concepts.html) I find
the scary quote:
> Sequence numbers cannot be used as indexes to sets of data within the
same stream. To logically separate sets of data, use partition keys or create a
separate stream for each data set.
[Here](https://docs.aws.amazon.com/AWSJavaSDK/latest/javadoc/com/amazonaws/services/kinesis/AmazonKinesisClient.html)
I also see:
> Sequence numbers generally increase over time. To guarantee strictly
increasing ordering, use the SequenceNumberForOrdering parameter
If they aren't, you might find yourself with :
- missing data, that may be with a sequence number `fromSeqNumber < x <
lastSeqNumber`, but not iterated on here because you request here with
`ShardIteratorType.AT_SEQUENCE_NUMBER` rather than
`ShardIteratorType.TRIM_HORIZON`
- superfluous data, because you're not checking that `fromSeqNumber <
nextRecord.getSequenceNumber() < lastSeqNumber` before returning `nextRecord`.
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