[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
Github user hhbyyh commented on the issue: https://github.com/apache/spark/pull/21981 Ah, this triggers the doc check. Updating. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21965: [SPARK-23909][SQL] Add filter function.
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[GitHub] spark issue #21965: [SPARK-23909][SQL] Add filter function.
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[GitHub] spark issue #21965: [SPARK-23909][SQL] Add filter function.
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[GitHub] spark issue #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/21952 we can keep investigating the perf regression, this patch itself LGTM --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21963: [SPARK-24997[SQL] Enable support of MINUS ALL
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[GitHub] spark issue #21952: [SPARK-24993] [SQL] Make Avro Fast Again
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/21981 Looks we should fix the doc in PrefixSpan too. LGTM if the check pass. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21965: [SPARK-23909][SQL] Add filter function.
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[GitHub] spark issue #21952: [SPARK-24993] [SQL] Make Avro Fast Again
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[GitHub] spark issue #21898: [SPARK-24817][Core] Implement BarrierTaskContext.barrier...
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[GitHub] spark issue #21952: [SPARK-24993] [SQL] Make Avro Fast Again
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[GitHub] spark issue #21898: [SPARK-24817][Core] Implement BarrierTaskContext.barrier...
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[GitHub] spark issue #21898: [SPARK-24817][Core] Implement BarrierTaskContext.barrier...
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[GitHub] spark pull request #21964: [SPARK-24788][SQL] RelationalGroupedDataset.toStr...
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[GitHub] spark pull request #21752: [SPARK-24788][SQL] fixed UnresolvedException when...
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[GitHub] spark issue #21941: [SPARK-24966][SQL] Implement precedence rules for set op...
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[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207444701
--- Diff: core/src/main/scala/org/apache/spark/BarrierTaskContext.scala ---
@@ -39,6 +44,17 @@ class BarrierTaskContext(
extends TaskContextImpl(stageId, stageAttemptNumber, partitionId,
taskAttemptId, attemptNumber,
taskMemoryManager, localProperties, metricsSystem, taskMetrics) {
+ private val barrierCoordinator: RpcEndpointRef = {
+val env = SparkEnv.get
+RpcUtils.makeDriverRef("barrierSync", env.conf, env.rpcEnv)
--- End diff --
It would be nice to define `"barrierSync"` as a constant.
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[GitHub] spark issue #21586: [SPARK-24586][SQL] Upcast should not allow casting from ...
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[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207442439
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,199 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), AtomicInteger]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int = 0): ArrayBuffer[RpcCallContext] = {
+val requests = syncRequestsByStageIdAndAttempt.putIfAbsent((stageId,
stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+if (requests == null) {
+ syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+} else {
+ requests
+}
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
--- End diff --
Agree with @cloud-fan that this is not necessary. It only explicitly clears
the ArrayBuffer object instead of the contexts.
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[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207444103
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,229 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+ cancelTimerTask(stageInfo.stageId, stageInfo.attemptNumber)
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), Int]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ // Remember all the TimerTasks for each barrier (stage, attempt).
+ private val timerTaskByStageIdAndAttempt = new ConcurrentHashMap[(Int,
Int), TimerTask]
+
+ // Number of tasks for each stage.
+ private val numTasksByStage = new ConcurrentHashMap[Int, Int]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int): ArrayBuffer[RpcCallContext] = {
+syncRequestsByStageIdAndAttempt.putIfAbsent((stageId, stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
+}
+logInfo(s"Removed all the pending barrier sync requests from Stage
$stageId (Attempt " +
+ s"$stageAttemptId).")
+ }
+
+ /**
+ * Get the barrier epoch that correspond to a barrier sync request from
a stage attempt.
+ */
+ private def getOrInitBarrierEpoch(stageId: Int, stageAttemptId: Int):
[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207443099
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,229 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+ cancelTimerTask(stageInfo.stageId, stageInfo.attemptNumber)
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), Int]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ // Remember all the TimerTasks for each barrier (stage, attempt).
+ private val timerTaskByStageIdAndAttempt = new ConcurrentHashMap[(Int,
Int), TimerTask]
+
+ // Number of tasks for each stage.
+ private val numTasksByStage = new ConcurrentHashMap[Int, Int]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int): ArrayBuffer[RpcCallContext] = {
+syncRequestsByStageIdAndAttempt.putIfAbsent((stageId, stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
+}
+logInfo(s"Removed all the pending barrier sync requests from Stage
$stageId (Attempt " +
+ s"$stageAttemptId).")
+ }
+
+ /**
+ * Get the barrier epoch that correspond to a barrier sync request from
a stage attempt.
+ */
+ private def getOrInitBarrierEpoch(stageId: Int, stageAttemptId: Int):
[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207444041
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,229 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+ cancelTimerTask(stageInfo.stageId, stageInfo.attemptNumber)
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), Int]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ // Remember all the TimerTasks for each barrier (stage, attempt).
+ private val timerTaskByStageIdAndAttempt = new ConcurrentHashMap[(Int,
Int), TimerTask]
+
+ // Number of tasks for each stage.
+ private val numTasksByStage = new ConcurrentHashMap[Int, Int]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int): ArrayBuffer[RpcCallContext] = {
+syncRequestsByStageIdAndAttempt.putIfAbsent((stageId, stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
+}
+logInfo(s"Removed all the pending barrier sync requests from Stage
$stageId (Attempt " +
+ s"$stageAttemptId).")
+ }
+
+ /**
+ * Get the barrier epoch that correspond to a barrier sync request from
a stage attempt.
+ */
+ private def getOrInitBarrierEpoch(stageId: Int, stageAttemptId: Int):
[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r207442661
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,229 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+ cancelTimerTask(stageInfo.stageId, stageInfo.attemptNumber)
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), Int]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ // Remember all the TimerTasks for each barrier (stage, attempt).
+ private val timerTaskByStageIdAndAttempt = new ConcurrentHashMap[(Int,
Int), TimerTask]
+
+ // Number of tasks for each stage.
+ private val numTasksByStage = new ConcurrentHashMap[Int, Int]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int): ArrayBuffer[RpcCallContext] = {
+syncRequestsByStageIdAndAttempt.putIfAbsent((stageId, stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
+}
+logInfo(s"Removed all the pending barrier sync requests from Stage
$stageId (Attempt " +
+ s"$stageAttemptId).")
+ }
+
+ /**
+ * Get the barrier epoch that correspond to a barrier sync request from
a stage attempt.
+ */
+ private def getOrInitBarrierEpoch(stageId: Int, stageAttemptId: Int):
[GitHub] spark pull request #21898: [SPARK-24817][Core] Implement BarrierTaskContext....
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/21898#discussion_r20759
--- Diff: core/src/main/scala/org/apache/spark/BarrierCoordinator.scala ---
@@ -0,0 +1,229 @@
+/*
+ * 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
+
+import java.util.{Timer, TimerTask}
+import java.util.concurrent.ConcurrentHashMap
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
+import org.apache.spark.scheduler.{LiveListenerBus, SparkListener,
SparkListenerStageCompleted}
+
+/**
+ * A coordinator that handles all global sync requests from
BarrierTaskContext. Each global sync
+ * request is generated by `BarrierTaskContext.barrier()`, and identified
by
+ * stageId + stageAttemptId + barrierEpoch. Reply all the blocking global
sync requests upon
+ * received all the requests for a group of `barrier()` calls. If the
coordinator doesn't collect
+ * enough global sync requests within a configured time, fail all the
requests due to timeout.
+ */
+private[spark] class BarrierCoordinator(
+timeout: Int,
+listenerBus: LiveListenerBus,
+override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with
Logging {
+
+ private val timer = new Timer("BarrierCoordinator barrier epoch
increment timer")
+
+ private val listener = new SparkListener {
+override def onStageCompleted(stageCompleted:
SparkListenerStageCompleted): Unit = {
+ val stageInfo = stageCompleted.stageInfo
+ // Remove internal data from a finished stage attempt.
+ cleanupSyncRequests(stageInfo.stageId, stageInfo.attemptNumber)
+ barrierEpochByStageIdAndAttempt.remove((stageInfo.stageId,
stageInfo.attemptNumber))
+ cancelTimerTask(stageInfo.stageId, stageInfo.attemptNumber)
+}
+ }
+
+ // Epoch counter for each barrier (stage, attempt).
+ private val barrierEpochByStageIdAndAttempt = new
ConcurrentHashMap[(Int, Int), Int]
+
+ // Remember all the blocking global sync requests for each barrier
(stage, attempt).
+ private val syncRequestsByStageIdAndAttempt =
+new ConcurrentHashMap[(Int, Int), ArrayBuffer[RpcCallContext]]
+
+ // Remember all the TimerTasks for each barrier (stage, attempt).
+ private val timerTaskByStageIdAndAttempt = new ConcurrentHashMap[(Int,
Int), TimerTask]
+
+ // Number of tasks for each stage.
+ private val numTasksByStage = new ConcurrentHashMap[Int, Int]
+
+ override def onStart(): Unit = {
+super.onStart()
+listenerBus.addToStatusQueue(listener)
+ }
+
+ /**
+ * Get the array of [[RpcCallContext]]s that correspond to a barrier
sync request from a stage
+ * attempt.
+ */
+ private def getOrInitSyncRequests(
+ stageId: Int,
+ stageAttemptId: Int,
+ numTasks: Int): ArrayBuffer[RpcCallContext] = {
+syncRequestsByStageIdAndAttempt.putIfAbsent((stageId, stageAttemptId),
+ new ArrayBuffer[RpcCallContext](numTasks))
+syncRequestsByStageIdAndAttempt.get((stageId, stageAttemptId))
+ }
+
+ /**
+ * Clean up the array of [[RpcCallContext]]s that correspond to a
barrier sync request from a
+ * stage attempt.
+ */
+ private def cleanupSyncRequests(stageId: Int, stageAttemptId: Int): Unit
= {
+val requests = syncRequestsByStageIdAndAttempt.remove((stageId,
stageAttemptId))
+if (requests != null) {
+ requests.clear()
+}
+logInfo(s"Removed all the pending barrier sync requests from Stage
$stageId (Attempt " +
+ s"$stageAttemptId).")
+ }
+
+ /**
+ * Get the barrier epoch that correspond to a barrier sync request from
a stage attempt.
+ */
+ private def getOrInitBarrierEpoch(stageId: Int, stageAttemptId: Int):
[GitHub] spark pull request #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/21952#discussion_r207444698 --- Diff: external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala --- @@ -151,11 +155,12 @@ class AvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: case (f1, f2) => newConverter(f1.dataType, resolveNullableType(f2.schema(), f1.nullable)) } val numFields = catalystStruct.length +val containsNull = catalystStruct.exists(_.nullable) --- End diff -- Let's remove it. We can fix the issue that Spark always turn schema to nullable later. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21974: [SPARK-25002][SQL] Avro: revise the output record...
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[GitHub] spark issue #21860: [SPARK-24901][SQL]Merge the codegen of RegularHashMap an...
Github user heary-cao commented on the issue: https://github.com/apache/spark/pull/21860 cc @kiszk,Can you review it again if you have some time? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21895: [SPARK-24948][SHS] Delegate check access permissions to ...
Github user jerryshao commented on the issue: https://github.com/apache/spark/pull/21895 Ping @mridulm , would you please also take a review, thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user dbtsai commented on a diff in the pull request: https://github.com/apache/spark/pull/21952#discussion_r207444381 --- Diff: external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala --- @@ -151,11 +155,12 @@ class AvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: case (f1, f2) => newConverter(f1.dataType, resolveNullableType(f2.schema(), f1.nullable)) } val numFields = catalystStruct.length +val containsNull = catalystStruct.exists(_.nullable) --- End diff -- Was addressing the feedback from @gengliangwang We can remove it since the cases when all the fields are not nullable will be probably fairly rare. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21974: [SPARK-25002][SQL] Avro: revise the output record namesp...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/21974 thanks, merging to master! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/21952#discussion_r207444037
--- Diff:
external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala ---
@@ -100,17 +100,20 @@ class AvroSerializer(rootCatalystType: DataType,
rootAvroType: Schema, nullable:
et, resolveNullableType(avroType.getElementType, containsNull))
(getter, ordinal) => {
val arrayData = getter.getArray(ordinal)
- val result = new java.util.ArrayList[Any]
--- End diff --
My previous experience in ml project told me that `ArrayList` has slower
setter performance due to one extra function call, so my preference is using
array as much as possible, and wrap it into the right container in the end.
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/21981 **[Test build #94102 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/94102/testReport)** for PR 21981 at commit [`6af3644`](https://github.com/apache/spark/commit/6af364429263f1d9d427c23e7a84b4d57d30261d). * This patch **fails Python style tests**. * This patch merges cleanly. * This patch adds no public classes. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user cloud-fan commented on a diff in the pull request: https://github.com/apache/spark/pull/21952#discussion_r207443421 --- Diff: external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala --- @@ -151,11 +155,12 @@ class AvroSerializer(rootCatalystType: DataType, rootAvroType: Schema, nullable: case (f1, f2) => newConverter(f1.dataType, resolveNullableType(f2.schema(), f1.nullable)) } val numFields = catalystStruct.length +val containsNull = catalystStruct.exists(_.nullable) --- End diff -- this only works when all the fields are not nullable, I don't think it's very useful. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21953: [SPARK-24992][Core] spark should randomize yarn local di...
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[GitHub] spark issue #21953: [SPARK-24992][Core] spark should randomize yarn local di...
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[GitHub] spark pull request #21952: [SPARK-24993] [SQL] Make Avro Fast Again
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/21952#discussion_r207443196
--- Diff:
external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala ---
@@ -100,17 +100,20 @@ class AvroSerializer(rootCatalystType: DataType,
rootAvroType: Schema, nullable:
et, resolveNullableType(avroType.getElementType, containsNull))
(getter, ordinal) => {
val arrayData = getter.getArray(ordinal)
- val result = new java.util.ArrayList[Any]
--- End diff --
can we just `new java.util.ArrayList[Any](len)` here instead of creating an
array and wrap it with array list?
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[GitHub] spark issue #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
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[GitHub] spark pull request #21981: [SAPRK-25011][ML]add prefix to __all__ in fpm.py
GitHub user hhbyyh opened a pull request: https://github.com/apache/spark/pull/21981 [SAPRK-25011][ML]add prefix to __all__ in fpm.py ## What changes were proposed in this pull request? jira: https://issues.apache.org/jira/browse/SPARK-25011 add prefix to __all__ in fpm.py ## How was this patch tested? existing unit test. You can merge this pull request into a Git repository by running: $ git pull https://github.com/hhbyyh/spark prefixall Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/21981.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #21981 commit 6af364429263f1d9d427c23e7a84b4d57d30261d Author: Yuhao Yang Date: 2018-08-03T05:04:03Z add prefix to all --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21980: [SPARK-25010][SQL] Rand/Randn should produce diff...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/21980#discussion_r207442765
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala
---
@@ -75,14 +75,15 @@ class IncrementalExecution(
* with the desired literal
*/
override lazy val optimizedPlan: LogicalPlan = {
-val random = new Random()
-
sparkSession.sessionState.optimizer.execute(withCachedData)
transformAllExpressions {
case ts @ CurrentBatchTimestamp(timestamp, _, _) =>
logInfo(s"Current batch timestamp = $timestamp")
ts.toLiteral
// SPARK-24896: Set the seed for random number generation in Uuid
expressions.
- case _: Uuid => Uuid(Some(random.nextLong()))
+ case _: Uuid => Uuid(Some(Utils.random.nextLong()))
--- End diff --
Sounds good. Let me update it accordingly.
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[GitHub] spark pull request #21941: [SPARK-24966][SQL] Implement precedence rules for...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/21941 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21980: [SPARK-25010][SQL] Rand/Randn should produce diff...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/21980#discussion_r207441687
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/IncrementalExecution.scala
---
@@ -75,14 +75,15 @@ class IncrementalExecution(
* with the desired literal
*/
override lazy val optimizedPlan: LogicalPlan = {
-val random = new Random()
-
sparkSession.sessionState.optimizer.execute(withCachedData)
transformAllExpressions {
case ts @ CurrentBatchTimestamp(timestamp, _, _) =>
logInfo(s"Current batch timestamp = $timestamp")
ts.toLiteral
// SPARK-24896: Set the seed for random number generation in Uuid
expressions.
- case _: Uuid => Uuid(Some(random.nextLong()))
+ case _: Uuid => Uuid(Some(Utils.random.nextLong()))
--- End diff --
shall we create a trait `ExpressionWithRandomSeed` which has a
`withNewSeed` method for these expressions?
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[GitHub] spark issue #21941: [SPARK-24966][SQL] Implement precedence rules for set op...
Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/21941 LGTM Thanks! Merged to master. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21966: [SPARK-23915][SQL][followup] Add array_except function
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[GitHub] spark issue #21933: [SPARK-24917][CORE] make chunk size configurable
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[GitHub] spark issue #21889: [SPARK-4502][SQL] Parquet nested column pruning - founda...
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[GitHub] spark issue #21966: [SPARK-23915][SQL][followup] Add array_except function
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[GitHub] spark issue #21966: [SPARK-23915][SQL][followup] Add array_except function
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[GitHub] spark pull request #21917: [SPARK-24720][STREAMING-KAFKA] add option to alig...
Github user koeninger commented on a diff in the pull request:
https://github.com/apache/spark/pull/21917#discussion_r207437645
--- Diff:
external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/DirectKafkaInputDStream.scala
---
@@ -223,17 +240,46 @@ private[spark] class DirectKafkaInputDStream[K, V](
}.getOrElse(offsets)
}
- override def compute(validTime: Time): Option[KafkaRDD[K, V]] = {
-val untilOffsets = clamp(latestOffsets())
-val offsetRanges = untilOffsets.map { case (tp, uo) =>
- val fo = currentOffsets(tp)
- OffsetRange(tp.topic, tp.partition, fo, uo)
+ /**
+ * Return the offset range. For non consecutive offset the last offset
must have record.
+ * If offsets have missing data (transaction marker or abort), increases
the
+ * range until we get the requested number of record or no more records.
+ * Because we have to iterate over all the records in this case,
+ * we also return the total number of records.
+ * @param offsets the target range we would like if offset were continue
+ * @return (totalNumberOfRecords, updated offset)
+ */
+ private def alignRanges(offsets: Map[TopicPartition, Long]):
Iterable[OffsetRange] = {
+if (nonConsecutive) {
+ val localRw = rewinder()
+ val localOffsets = currentOffsets
+ context.sparkContext.parallelize(offsets.toList).mapPartitions(tpos
=> {
+tpos.map { case (tp, o) =>
+ val offsetAndCount =
localRw.getLastOffsetAndCount(localOffsets(tp), tp, o)
+ (tp, offsetAndCount)
+}
+ }).collect()
--- End diff --
What exactly is the benefit gained by doing a duplicate read of all the
messages?
---
-
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