Merge remote-tracking branch 'apache/master' into fix-runid

Author: jose-torres

R/pkg/R/mllib_utils.R

@@ -130,4 +130,3 @@ read.ml <- function(path) {
     stop("Unsupported model: ", jobj)
   }
 }
-

dev/merge_spark_pr.py

@@ -30,6 +30,7 @@
 import re
 import subprocess
 import sys
+import traceback
 import urllib2
 
 try:
@@ -298,24 +299,37 @@ def choose_jira_assignee(issue, asf_jira):
     Prompt the user to choose who to assign the issue to in jira, given a list of candidates,
     including the original reporter and all commentors
     """
-    reporter = issue.fields.reporter
-    commentors = map(lambda x: x.author, issue.fields.comment.comments)
-    candidates = set(commentors)
-    candidates.add(reporter)
-    candidates = list(candidates)
-    print("JIRA is unassigned, choose assignee")
-    for idx, author in enumerate(candidates):
-        annotations = ["Reporter"] if author == reporter else []
-        if author in commentors:
-            annotations.append("Commentor")
-        print("[%d] %s (%s)" % (idx, author.displayName, ",".join(annotations)))
-    assignee = raw_input("Enter number of user to assign to (blank to leave unassigned):")
-    if assignee == "":
-        return None
-    else:
-        assignee = candidates[int(assignee)]
-        asf_jira.assign_issue(issue.key, assignee.key)
-        return assignee
+    while True:
+        try:
+            reporter = issue.fields.reporter
+            commentors = map(lambda x: x.author, issue.fields.comment.comments)
+            candidates = set(commentors)
+            candidates.add(reporter)
+            candidates = list(candidates)
+            print("JIRA is unassigned, choose assignee")
+            for idx, author in enumerate(candidates):
+                if author.key == "apachespark":
+                    continue
+                annotations = ["Reporter"] if author == reporter else []
+                if author in commentors:
+                    annotations.append("Commentor")
+                print("[%d] %s (%s)" % (idx, author.displayName, ",".join(annotations)))
+            raw_assignee = raw_input(
+                "Enter number of user, or userid,  to assign to (blank to leave unassigned):")
+            if raw_assignee == "":
+                return None
+            else:
+                try:
+                    id = int(raw_assignee)
+                    assignee = candidates[id]
+                except:
+                    # assume it's a user id, and try to assign (might fail, we just prompt again)
+                    assignee = asf_jira.user(raw_assignee)
+                asf_jira.assign_issue(issue.key, assignee.key)
+                return assignee
+        except:
+            traceback.print_exc()
+            print("Error assigning JIRA, try again (or leave blank and fix manually)")
 
 
 def resolve_jira_issues(title, merge_branches, comment):

external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaContinuousReader.scala

@@ -0,0 +1,260 @@
+/*
+ * 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
+
+  private val pollTimeoutMs = sourceOptions.getOrElse("kafkaConsumer.pollTimeoutMs", "512").toLong
+
+  // 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: $deletedPartitions")
+    }
+
+    val startOffsets = newPartitionOffsets ++
+      oldStartPartitionOffsets.filterKeys(!deletedPartitions.contains(_))
+    knownPartitions = startOffsets.keySet
+
+    startOffsets.toSeq.map {
+      case (topicPartition, start) =>
+        KafkaContinuousReadTask(
+          topicPartition, start, kafkaParams, pollTimeoutMs, failOnDataLoss)
+          .asInstanceOf[ReadTask[UnsafeRow]]
+    }.asJava
+  }
+
+  /** Stop this source and free any resources it has allocated. */
+  def stop(): Unit = synchronized {
+    offsetReader.close()
+  }
+
+  override def commit(end: Offset): Unit = {}
+
+  override def mergeOffsets(offsets: Array[PartitionOffset]): Offset = {
+    val mergedMap = offsets.map {
+      case KafkaSourcePartitionOffset(p, o) => Map(p -> o)
+    }.reduce(_ ++ _)
+    KafkaSourceOffset(mergedMap)
+  }
+
+  override def needsReconfiguration(): Boolean = {
+    knownPartitions != null && offsetReader.fetchLatestOffsets().keySet != knownPartitions
+  }
+
+  override def toString(): String = s"KafkaSource[$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 pollTimeoutMs The timeout for Kafka consumer polling.
+ * @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],
+    pollTimeoutMs: Long,
+    failOnDataLoss: Boolean) extends ReadTask[UnsafeRow] {
+  override def createDataReader(): KafkaContinuousDataReader = {
+    new KafkaContinuousDataReader(
+      topicPartition, startOffset, kafkaParams, pollTimeoutMs, 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 pollTimeoutMs The timeout for Kafka consumer polling.
+ * @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],
+    pollTimeoutMs: Long,
+    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,
+          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  if e.getCause.isInstanceOf[OffsetOutOfRangeException] =>
+          val range = consumer.getAvailableOffsetRange()
+          if (range.latest >= nextKafkaOffset && range.earliest <= nextKafkaOffset) {
+            // retry
+          } else {
+            throw e
+          }
+      }
+    }
+    nextKafkaOffset = r.offset + 1
+    currentRecord = r
+    true
+  }
+
+  override def get(): UnsafeRow = {
+    bufferHolder.reset()
+
+    if (currentRecord.key == null) {
+      rowWriter.setNullAt(0)
+    } else {
+      rowWriter.write(0, currentRecord.key)
+    }
+    rowWriter.write(1, currentRecord.value)
+    rowWriter.write(2, UTF8String.fromString(currentRecord.topic))
+    rowWriter.write(3, currentRecord.partition)
+    rowWriter.write(4, currentRecord.offset)
+    rowWriter.write(5,
+      DateTimeUtils.fromJavaTimestamp(new java.sql.Timestamp(currentRecord.timestamp)))
+    rowWriter.write(6, currentRecord.timestampType.id)
+    sharedRow.setTotalSize(bufferHolder.totalSize)
+    sharedRow
+  }
+
+  override def getOffset(): KafkaSourcePartitionOffset = {
+    KafkaSourcePartitionOffset(topicPartition, nextKafkaOffset)
+  }
+
+  override def close(): Unit = {
+    consumer.close()
+  }
+}