{"action":"created","comment":{"url":"https://api.github.com/repos/tdas/spark/pulls/comments/53863646","id":53863646,"diff_hunk":"@@ -0,0 +1,190 @@\n+/*\n+ * Licensed to the Apache Software Foundation (ASF) under one or more\n+ * contributor license agreements.  See the NOTICE file distributed with\n+ * this work for additional information regarding copyright ownership.\n+ * The ASF licenses this file to You under the Apache License, Version 2.0\n+ * (the \"License\"); you may not use this file except in compliance with\n+ * the License.  You may obtain a copy of the License at\n+ *\n+ *    http://www.apache.org/licenses/LICENSE-2.0\n+ *\n+ * Unless required by applicable law or agreed to in writing, software\n+ * distributed under the License is distributed on an \"AS IS\" BASIS,\n+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n+ * See the License for the specific language governing permissions and\n+ * limitations under the License.\n+ */\n+package org.apache.spark.streaming.kinesis\n+\n+import scala.collection.JavaConverters._\n+import scala.collection.mutable.ArrayBuffer\n+import scala.util.control.NonFatal\n+\n+import com.amazonaws.services.kinesis.AmazonKinesisClient\n+import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream\n+import com.amazonaws.services.kinesis.clientlibrary.types.UserRecord\n+import com.amazonaws.services.kinesis.model._\n+\n+import org.apache.spark.{Logging, SparkContext, SparkEnv, SparkException}\n+import org.apache.spark.network.util.JavaUtils\n+import org.apache.spark.storage.{BlockId, StorageLevel}\n+\n+/**\n+ * However, this class runs in the driver so could be a bottleneck.\n+ */\n+private[kinesis] class KinesisDataFetcher(\n+    credentials: SerializableAWSCredentials,\n+    endpointUrl: String,\n+    fromSeqNums: Seq[(Shard, Option[String])],\n+    initialPositionInStream: InitialPositionInStream,\n+    readTimeoutMs: Long = 2000L\n+) extends Serializable with Logging {\n+\n+  /**\n+   * Use lazy because the client needs to be created in executors\n+   */\n+  @transient private lazy val client = new AmazonKinesisClient(credentials)\n+\n+  def fetch(sc: SparkContext): Array[(BlockId, SequenceNumberRange)] = {\n+    sc.makeRDD(fromSeqNums, fromSeqNums.size).map {\n+      case (shard, fromSeqNum) => fetchPartition(shard, fromSeqNum)\n+    }.collect().flatten\n+  }\n+\n+  private def 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