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/**
* 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.hadoop.hive.ql.optimizer.physical;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Stack;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.ContentSummary;
import org.apache.hadoop.hive.common.ObjectPair;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.ql.Context;
import org.apache.hadoop.hive.ql.exec.ConditionalTask;
import org.apache.hadoop.hive.ql.exec.FileSinkOperator;
import org.apache.hadoop.hive.ql.exec.JoinOperator;
import org.apache.hadoop.hive.ql.exec.MapRedTask;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.Task;
import org.apache.hadoop.hive.ql.exec.TaskFactory;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.lib.Dispatcher;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.lib.TaskGraphWalker;
import org.apache.hadoop.hive.ql.lib.TaskGraphWalker.TaskGraphWalkerContext;
import org.apache.hadoop.hive.ql.optimizer.GenMapRedUtils;
import org.apache.hadoop.hive.ql.optimizer.MapJoinProcessor;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.QBJoinTree;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin;
import org.apache.hadoop.hive.ql.plan.ConditionalResolverCommonJoin.ConditionalResolverCommonJoinCtx;
import org.apache.hadoop.hive.ql.plan.ConditionalWork;
import org.apache.hadoop.hive.ql.plan.JoinDesc;
import org.apache.hadoop.hive.ql.plan.MapredLocalWork;
import org.apache.hadoop.hive.ql.plan.MapredWork;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
import org.apache.hadoop.hive.ql.plan.PartitionDesc;
/*
* Convert tasks involving JOIN into MAPJOIN.
* If hive.auto.convert.join is true, the tasks involving join are converted.
* Consider the query:
* select .... from T1 join T2 on T1.key = T2.key join T3 on T1.key = T3.key
*
* There is a map-reduce task which performs a 3-way join (T1, T2, T3).
* The task would be converted to a conditional task which would have 4 children
* a. Mapjoin considering T1 as the big table
* b. Mapjoin considering T2 as the big table
* c. Mapjoin considering T3 as the big table
* d. Map-reduce join (the original task).
*
* Note that the sizes of all the inputs may not be available at compile time. At runtime, it is
* determined which branch we want to pick up from the above.
*
* However, if hive.auto.convert.join.noconditionaltask is set to true, and
* the sum of any n-1 tables is smaller than hive.auto.convert.join.noconditionaltask.size,
* then a mapjoin is created instead of the conditional task. For the above, if the size of
* T1 + T2 is less than the threshold, then the task is converted to a mapjoin task with T3 as
* the big table.
*
* In this case, further optimization is performed by merging 2 consecutive map-only jobs.
* Consider the query:
* select ... from T1 join T2 on T1.key1 = T2.key1 join T3 on T1.key2 = T3.key2
*
* Initially, the plan would consist of 2 Map-reduce jobs (1 to perform join for T1 and T2)
* followed by another map-reduce job (to perform join of the result with T3). After the
* optimization, both these tasks would be converted to map-only tasks. These 2 map-only jobs
* are then merged into a single map-only job. As a followup (HIVE-3952), it would be possible to
* merge a map-only task with a map-reduce task.
* Consider the query:
* select T1.key2, count(*) from T1 join T2 on T1.key1 = T2.key1 group by T1.key2;
* Initially, the plan would consist of 2 Map-reduce jobs (1 to perform join for T1 and T2)
* followed by another map-reduce job (to perform groupby of the result). After the
* optimization, the join task would be converted to map-only tasks. After HIVE-3952, the map-only
* task would be merged with the map-reduce task to create a single map-reduce task.
*/
public class CommonJoinResolver implements PhysicalPlanResolver {
@Override
public PhysicalContext resolve(PhysicalContext pctx) throws SemanticException {
// create dispatcher and graph walker
Dispatcher disp = new CommonJoinTaskDispatcher(pctx);
TaskGraphWalker ogw = new TaskGraphWalker(disp);
// get all the tasks nodes from root task
ArrayList topNodes = new ArrayList();
topNodes.addAll(pctx.rootTasks);
// begin to walk through the task tree.
ogw.startWalking(topNodes, null);
return pctx;
}
/**
* Iterator each tasks. If this task has a local work,create a new task for this local work, named
* MapredLocalTask. then make this new generated task depends on current task's parent task, and
* make current task depends on this new generated task
*/
class CommonJoinTaskDispatcher implements Dispatcher {
HashMap aliasToSize = null;
private final PhysicalContext physicalContext;
public CommonJoinTaskDispatcher(PhysicalContext context) {
super();
physicalContext = context;
}
// Get the position of the big table for this join operator and the given alias
private int getPosition(MapredWork work, Operator joinOp,
String alias) {
Operator parentOp = work.getAliasToWork().get(alias);
// reduceSinkOperator's child is null, but joinOperator's parents is reduceSink
while ((parentOp.getChildOperators() != null) &&
(!parentOp.getChildOperators().isEmpty())) {
parentOp = parentOp.getChildOperators().get(0);
}
return joinOp.getParentOperators().indexOf(parentOp);
}
/*
* A task and its child task has been converted from join to mapjoin.
* See if the two tasks can be merged.
*/
private void mergeMapJoinTaskWithChildMapJoinTask(MapRedTask task, Configuration conf) {
MapRedTask childTask = (MapRedTask)task.getChildTasks().get(0);
MapredWork work = task.getWork();
MapredLocalWork localWork = work.getMapLocalWork();
MapredWork childWork = childTask.getWork();
MapredLocalWork childLocalWork = childWork.getMapLocalWork();
// Can this be merged
Map> aliasToWork = work.getAliasToWork();
if (aliasToWork.size() > 1) {
return;
}
Operator op = aliasToWork.values().iterator().next();
while (op.getChildOperators() != null) {
// Dont perform this optimization for multi-table inserts
if (op.getChildOperators().size() > 1) {
return;
}
op = op.getChildOperators().get(0);
}
if (!(op instanceof FileSinkOperator)) {
return;
}
FileSinkOperator fop = (FileSinkOperator)op;
String workDir = fop.getConf().getDirName();
Map> childPathToAliases = childWork.getPathToAliases();
if (childPathToAliases.size() > 1) {
return;
}
// The filesink writes to a different directory
if (!childPathToAliases.keySet().iterator().next().equals(workDir)) {
return;
}
// Either of them should not be bucketed
if ((localWork.getBucketMapjoinContext() != null) ||
(childLocalWork.getBucketMapjoinContext() != null)) {
return;
}
// Merge the trees
if (childWork.getAliasToWork().size() > 1) {
return;
}
long mapJoinSize = HiveConf.getLongVar(conf,
HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASKTHRESHOLD);
long localTableTotalSize = 0;
for (String alias : localWork.getAliasToWork().keySet()) {
Long tabSize = aliasToSize.get(alias);
if (tabSize == null) {
/* if the size is unavailable, we need to assume a size 1 greater than mapJoinSize
* this implies that merge cannot happen so we can return.
*/
return;
}
localTableTotalSize += tabSize;
}
for (String alias : childLocalWork.getAliasToWork().keySet()) {
Long tabSize = aliasToSize.get(alias);
if (tabSize == null) {
/* if the size is unavailable, we need to assume a size 1 greater than mapJoinSize
* this implies that merge cannot happen so we can return.
*/
return;
}
localTableTotalSize += tabSize;
if (localTableTotalSize > mapJoinSize) {
return;
}
}
Operator childAliasOp =
childWork.getAliasToWork().values().iterator().next();
if (fop.getParentOperators().size() > 1) {
return;
}
// Merge the 2 trees - remove the FileSinkOperator from the first tree pass it to the
// top of the second
Operator parentFOp = fop.getParentOperators().get(0);
parentFOp.getChildOperators().remove(fop);
parentFOp.getChildOperators().add(childAliasOp);
List> parentOps =
new ArrayList>();
parentOps.add(parentFOp);
childAliasOp.setParentOperators(parentOps);
work.getAliasToPartnInfo().putAll(childWork.getAliasToPartnInfo());
for (Map.Entry childWorkEntry :
childWork.getPathToPartitionInfo().entrySet()) {
if (childWork.getAliasToPartnInfo().containsValue(childWorkEntry.getKey())) {
work.getPathToPartitionInfo().put(childWorkEntry.getKey(), childWorkEntry.getValue());
}
}
localWork.getAliasToFetchWork().putAll(childLocalWork.getAliasToFetchWork());
localWork.getAliasToWork().putAll(childLocalWork.getAliasToWork());
// remove the child task
List> oldChildTasks = childTask.getChildTasks();
task.setChildTasks(oldChildTasks);
if (oldChildTasks != null) {
for (Task oldChildTask : oldChildTasks) {
oldChildTask.getParentTasks().remove(childTask);
oldChildTask.getParentTasks().add(task);
}
}
boolean convertToSingleJob = HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVEOPTIMIZEMAPJOINFOLLOWEDBYMR);
if (convertToSingleJob) {
copyReducerConf(task, childTask);
}
}
/**
* Copy reducer configuration if the childTask also has a reducer.
*
* @param task
* @param childTask
*/
private void copyReducerConf(MapRedTask task, MapRedTask childTask) {
MapredWork childWork = childTask.getWork();
Operator childReducer = childWork.getReducer();
MapredWork work = task.getWork();
if (childReducer == null) {
return;
}
work.setReducer(childReducer);
work.setNumReduceTasks(childWork.getNumReduceTasks());
work.setJoinTree(childWork.getJoinTree());
work.setNeedsTagging(childWork.getNeedsTagging());
// Make sure the key configuration is correct, clear and regenerate.
work.getTagToValueDesc().clear();
GenMapRedUtils.setKeyAndValueDescForTaskTree(task);
}
// create map join task and set big table as bigTablePosition
private ObjectPair convertTaskToMapJoinTask(MapredWork newWork,
int bigTablePosition) throws SemanticException {
// create a mapred task for this work
MapRedTask newTask = (MapRedTask) TaskFactory.get(newWork, physicalContext
.getParseContext().getConf());
JoinOperator newJoinOp = getJoinOp(newTask);
// optimize this newWork and assume big table position is i
String bigTableAlias =
MapJoinProcessor.genMapJoinOpAndLocalWork(newWork, newJoinOp, bigTablePosition);
return new ObjectPair(newTask, bigTableAlias);
}
/*
* A task and its child task has been converted from join to mapjoin.
* See if the two tasks can be merged.
*/
private void mergeMapJoinTaskWithMapReduceTask(MapRedTask mapJoinTask, Configuration conf) {
if (mapJoinTask.getChildTasks() == null
|| mapJoinTask.getChildTasks().size() > 1) {
// No child-task to merge, nothing to do or there are more than one
// child-tasks in which case we don't want to do anything.
return;
}
Task firstChildTask = mapJoinTask.getChildTasks().get(0);
if (!(firstChildTask instanceof MapRedTask)) {
// Nothing to do if it is not a mapreduce task.
return;
}
MapRedTask childTask = (MapRedTask) firstChildTask;
MapredWork mapJoinWork = mapJoinTask.getWork();
MapredWork childWork = childTask.getWork();
Operator childReducer = childWork.getReducer();
if (childReducer == null) {
// Not a MR job, nothing to merge.
return;
}
// Can this be merged
Map> aliasToWork = mapJoinWork.getAliasToWork();
if (aliasToWork.size() > 1) {
return;
}
Map> childPathToAliases = childWork.getPathToAliases();
if (childPathToAliases.size() > 1) {
return;
}
// Locate leaf operator of the map-join task. Start by initializing leaf
// operator to be root operator.
Operator mapJoinLeafOperator = aliasToWork.values().iterator().next();
while (mapJoinLeafOperator.getChildOperators() != null) {
// Dont perform this optimization for multi-table inserts
if (mapJoinLeafOperator.getChildOperators().size() > 1) {
return;
}
mapJoinLeafOperator = mapJoinLeafOperator.getChildOperators().get(0);
}
assert (mapJoinLeafOperator instanceof FileSinkOperator);
if (!(mapJoinLeafOperator instanceof FileSinkOperator)) {
// Sanity check, shouldn't happen.
return;
}
FileSinkOperator mapJoinTaskFileSinkOperator = (FileSinkOperator) mapJoinLeafOperator;
// The filesink writes to a different directory
String workDir = mapJoinTaskFileSinkOperator.getConf().getDirName();
if (!childPathToAliases.keySet().iterator().next().equals(workDir)) {
return;
}
MapredLocalWork mapJoinLocalWork = mapJoinWork.getMapLocalWork();
MapredLocalWork childLocalWork = childWork.getMapLocalWork();
// Either of them should not be bucketed
if ((mapJoinLocalWork != null && mapJoinLocalWork.getBucketMapjoinContext() != null) ||
(childLocalWork != null && childLocalWork.getBucketMapjoinContext() != null)) {
return;
}
if (childWork.getAliasToWork().size() > 1) {
return;
}
Operator childAliasOp =
childWork.getAliasToWork().values().iterator().next();
if (mapJoinTaskFileSinkOperator.getParentOperators().size() > 1) {
return;
}
// Merge the 2 trees - remove the FileSinkOperator from the first tree pass it to the
// top of the second
Operator parentFOp = mapJoinTaskFileSinkOperator
.getParentOperators().get(0);
parentFOp.getChildOperators().remove(mapJoinTaskFileSinkOperator);
parentFOp.getChildOperators().add(childAliasOp);
List> parentOps =
new ArrayList>();
parentOps.add(parentFOp);
childAliasOp.setParentOperators(parentOps);
mapJoinWork.getAliasToPartnInfo().putAll(childWork.getAliasToPartnInfo());
for (Map.Entry childWorkEntry : childWork.getPathToPartitionInfo()
.entrySet()) {
if (childWork.getAliasToPartnInfo().containsValue(childWorkEntry.getKey())) {
mapJoinWork.getPathToPartitionInfo()
.put(childWorkEntry.getKey(), childWorkEntry.getValue());
}
}
// Fill up stuff in local work
if (mapJoinLocalWork != null && childLocalWork != null) {
mapJoinLocalWork.getAliasToFetchWork().putAll(childLocalWork.getAliasToFetchWork());
mapJoinLocalWork.getAliasToWork().putAll(childLocalWork.getAliasToWork());
}
// remove the child task
List> oldChildTasks = childTask.getChildTasks();
mapJoinTask.setChildTasks(oldChildTasks);
if (oldChildTasks != null) {
for (Task oldChildTask : oldChildTasks) {
oldChildTask.getParentTasks().remove(childTask);
oldChildTask.getParentTasks().add(mapJoinTask);
}
}
// Copy the reducer conf.
copyReducerConf(mapJoinTask, childTask);
}
private Task processCurrentTask(MapRedTask currTask,
ConditionalTask conditionalTask, Context context)
throws SemanticException {
// whether it contains common join op; if contains, return this common join op
JoinOperator joinOp = getJoinOp(currTask);
if (joinOp == null || joinOp.getConf().isFixedAsSorted()) {
return null;
}
currTask.setTaskTag(Task.COMMON_JOIN);
MapredWork currWork = currTask.getWork();
// create conditional work list and task list
List listWorks = new ArrayList();
List> listTasks = new ArrayList>();
// create alias to task mapping and alias to input file mapping for resolver
HashMap> aliasToTask = new HashMap>();
HashMap> pathToAliases = currWork.getPathToAliases();
Map> aliasToWork = currWork.getAliasToWork();
// get parseCtx for this Join Operator
ParseContext parseCtx = physicalContext.getParseContext();
QBJoinTree joinTree = parseCtx.getJoinContext().get(joinOp);
// start to generate multiple map join tasks
JoinDesc joinDesc = joinOp.getConf();
Byte[] order = joinDesc.getTagOrder();
int numAliases = order.length;
long aliasTotalKnownInputSize = 0;
if (aliasToSize == null) {
aliasToSize = new HashMap();
}
try {
// go over all the input paths, and calculate a known total size, known
// size for each input alias.
Utilities.getInputSummary(context, currWork, null).getLength();
// set alias to size mapping, this can be used to determine if one table
// is choosen as big table, what's the total size of left tables, which
// are going to be small tables.
for (Map.Entry> entry : pathToAliases.entrySet()) {
String path = entry.getKey();
List aliasList = entry.getValue();
ContentSummary cs = context.getCS(path);
if (cs != null) {
long size = cs.getLength();
for (String alias : aliasList) {
aliasTotalKnownInputSize += size;
Long es = aliasToSize.get(alias);
if (es == null) {
es = new Long(0);
}
es += size;
aliasToSize.put(alias, es);
}
}
}
HashSet bigTableCandidates = MapJoinProcessor.getBigTableCandidates(joinDesc.getConds());
// no table could be the big table; there is no need to convert
if (bigTableCandidates == null) {
return null;
}
Configuration conf = context.getConf();
// If sizes of atleast n-1 tables in a n-way join is known, and their sum is smaller than
// the threshold size, convert the join into map-join and don't create a conditional task
boolean convertJoinMapJoin = HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASK);
int bigTablePosition = -1;
if (convertJoinMapJoin) {
// This is the threshold that the user has specified to fit in mapjoin
long mapJoinSize = HiveConf.getLongVar(conf,
HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASKTHRESHOLD);
boolean bigTableFound = false;
long largestBigTableCandidateSize = -1;
long sumTableSizes = 0;
for (String alias : aliasToWork.keySet()) {
int tablePosition = getPosition(currWork, joinOp, alias);
boolean bigTableCandidate = bigTableCandidates.contains(tablePosition);
Long size = aliasToSize.get(alias);
// The size is not available at compile time if the input is a sub-query.
// If the size of atleast n-1 inputs for a n-way join are available at compile time,
// and the sum of them is less than the specified threshold, then convert the join
// into a map-join without the conditional task.
if ((size == null) || (size > mapJoinSize)) {
sumTableSizes += largestBigTableCandidateSize;
if (bigTableFound || (sumTableSizes > mapJoinSize) || !bigTableCandidate) {
convertJoinMapJoin = false;
break;
}
bigTableFound = true;
bigTablePosition = tablePosition;
largestBigTableCandidateSize = mapJoinSize + 1;
} else {
if (bigTableCandidate && size > largestBigTableCandidateSize) {
bigTablePosition = tablePosition;
sumTableSizes += largestBigTableCandidateSize;
largestBigTableCandidateSize = size;
}
else {
sumTableSizes += size;
}
if (sumTableSizes > mapJoinSize) {
convertJoinMapJoin = false;
break;
}
}
}
}
String bigTableAlias = null;
currWork.setOpParseCtxMap(parseCtx.getOpParseCtx());
currWork.setJoinTree(joinTree);
if (convertJoinMapJoin) {
// create map join task and set big table as bigTablePosition
MapRedTask newTask = convertTaskToMapJoinTask(currWork, bigTablePosition).getFirst();
newTask.setTaskTag(Task.MAPJOIN_ONLY_NOBACKUP);
replaceTask(currTask, newTask, physicalContext);
// Can this task be merged with the child task. This can happen if a big table is being
// joined with multiple small tables on different keys
if ((newTask.getChildTasks() != null) && (newTask.getChildTasks().size() == 1)) {
if (newTask.getChildTasks().get(0).getTaskTag() == Task.MAPJOIN_ONLY_NOBACKUP) {
// Merging two map-join tasks
mergeMapJoinTaskWithChildMapJoinTask(newTask, conf);
}
// Converted the join operator into a map-join. Now see if it can
// be merged into the following map-reduce job.
boolean convertToSingleJob = HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVEOPTIMIZEMAPJOINFOLLOWEDBYMR);
if (convertToSingleJob) {
// Try merging a map-join task with a mapreduce job to have a
// single job.
mergeMapJoinTaskWithMapReduceTask(newTask, conf);
}
}
return newTask;
}
long ThresholdOfSmallTblSizeSum = HiveConf.getLongVar(conf,
HiveConf.ConfVars.HIVESMALLTABLESFILESIZE);
String xml = currWork.toXML();
for (int i = 0; i < numAliases; i++) {
// this table cannot be big table
if (!bigTableCandidates.contains(i)) {
continue;
}
// deep copy a new mapred work from xml
InputStream in = new ByteArrayInputStream(xml.getBytes("UTF-8"));
MapredWork newWork = Utilities.deserializeMapRedWork(in, physicalContext.getConf());
// create map join task and set big table as i
ObjectPair newTaskAlias = convertTaskToMapJoinTask(newWork, i);
MapRedTask newTask = newTaskAlias.getFirst();
bigTableAlias = newTaskAlias.getSecond();
Long aliasKnownSize = aliasToSize.get(bigTableAlias);
if (aliasKnownSize != null && aliasKnownSize.longValue() > 0) {
long smallTblTotalKnownSize = aliasTotalKnownInputSize
- aliasKnownSize.longValue();
if(smallTblTotalKnownSize > ThresholdOfSmallTblSizeSum) {
//this table is not good to be a big table.
continue;
}
}
// add into conditional task
listWorks.add(newTask.getWork());
listTasks.add(newTask);
newTask.setTaskTag(Task.CONVERTED_MAPJOIN);
//set up backup task
newTask.setBackupTask(currTask);
newTask.setBackupChildrenTasks(currTask.getChildTasks());
// put the mapping alias to task
aliasToTask.put(bigTableAlias, newTask);
}
} catch (Exception e) {
e.printStackTrace();
throw new SemanticException("Generate Map Join Task Error: " + e.getMessage());
}
// insert current common join task to conditional task
listWorks.add(currTask.getWork());
listTasks.add(currTask);
// clear JoinTree and OP Parse Context
currWork.setOpParseCtxMap(null);
currWork.setJoinTree(null);
// create conditional task and insert conditional task into task tree
ConditionalWork cndWork = new ConditionalWork(listWorks);
ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork, parseCtx.getConf());
cndTsk.setListTasks(listTasks);
// set resolver and resolver context
cndTsk.setResolver(new ConditionalResolverCommonJoin());
ConditionalResolverCommonJoinCtx resolverCtx = new ConditionalResolverCommonJoinCtx();
resolverCtx.setPathToAliases(pathToAliases);
resolverCtx.setAliasToKnownSize(aliasToSize);
resolverCtx.setAliasToTask(aliasToTask);
resolverCtx.setCommonJoinTask(currTask);
resolverCtx.setLocalTmpDir(context.getLocalScratchDir(false));
resolverCtx.setHdfsTmpDir(context.getMRScratchDir());
cndTsk.setResolverCtx(resolverCtx);
//replace the current task with the new generated conditional task
this.replaceTaskWithConditionalTask(currTask, cndTsk, physicalContext);
return cndTsk;
}
private void replaceTaskWithConditionalTask(
Task currTask, ConditionalTask cndTsk,
PhysicalContext physicalContext) {
// add this task into task tree
// set all parent tasks
List> parentTasks = currTask.getParentTasks();
currTask.setParentTasks(null);
if (parentTasks != null) {
for (Task tsk : parentTasks) {
// make new generated task depends on all the parent tasks of current task.
tsk.addDependentTask(cndTsk);
// remove the current task from its original parent task's dependent task
tsk.removeDependentTask(currTask);
}
} else {
// remove from current root task and add conditional task to root tasks
physicalContext.removeFromRootTask(currTask);
physicalContext.addToRootTask(cndTsk);
}
// set all child tasks
List> oldChildTasks = currTask.getChildTasks();
if (oldChildTasks != null) {
for (Task tsk : cndTsk.getListTasks()) {
if (tsk.equals(currTask)) {
continue;
}
for (Task oldChild : oldChildTasks) {
tsk.addDependentTask(oldChild);
}
}
}
}
// Replace the task with the new task. Copy the children and parents of the old
// task to the new task.
private void replaceTask(
Task currTask, Task newTask,
PhysicalContext physicalContext) {
// add this task into task tree
// set all parent tasks
List> parentTasks = currTask.getParentTasks();
currTask.setParentTasks(null);
if (parentTasks != null) {
for (Task tsk : parentTasks) {
// remove the current task from its original parent task's dependent task
tsk.removeDependentTask(currTask);
// make new generated task depends on all the parent tasks of current task.
tsk.addDependentTask(newTask);
}
} else {
// remove from current root task and add conditional task to root tasks
physicalContext.removeFromRootTask(currTask);
physicalContext.addToRootTask(newTask);
}
// set all child tasks
List> oldChildTasks = currTask.getChildTasks();
currTask.setChildTasks(null);
if (oldChildTasks != null) {
for (Task tsk : oldChildTasks) {
// remove the current task from its original parent task's dependent task
tsk.getParentTasks().remove(currTask);
// make new generated task depends on all the parent tasks of current task.
newTask.addDependentTask(tsk);
}
}
}
@Override
public Object dispatch(Node nd, Stack stack, Object... nodeOutputs)
throws SemanticException {
if (nodeOutputs == null || nodeOutputs.length == 0) {
throw new SemanticException("No Dispatch Context");
}
TaskGraphWalkerContext walkerCtx = (TaskGraphWalkerContext) nodeOutputs[0];
Task currTask = (Task) nd;
// not map reduce task or not conditional task, just skip
if (currTask.isMapRedTask()) {
if (currTask instanceof ConditionalTask) {
// get the list of task
List> taskList = ((ConditionalTask) currTask).getListTasks();
for (Task tsk : taskList) {
if (tsk.isMapRedTask()) {
Task newTask = this.processCurrentTask((MapRedTask) tsk,
((ConditionalTask) currTask), physicalContext.getContext());
walkerCtx.addToDispatchList(newTask);
}
}
} else {
Task newTask =
this.processCurrentTask((MapRedTask) currTask, null, physicalContext.getContext());
walkerCtx.addToDispatchList(newTask);
}
}
return null;
}
/*
* If any operator which does not allow map-side conversion is present in the mapper, dont
* convert it into a conditional task.
*/
private boolean checkOperatorOKMapJoinConversion(Operator op) {
if (!op.opAllowedConvertMapJoin()) {
return false;
}
if (op.getChildOperators() == null) {
return true;
}
for (Operator childOp : op.getChildOperators()) {
if (!checkOperatorOKMapJoinConversion(childOp)) {
return false;
}
}
return true;
}
private JoinOperator getJoinOp(MapRedTask task) throws SemanticException {
MapredWork work = task.getWork();
if (work == null) {
return null;
}
Operator reducerOp = work.getReducer();
if (reducerOp instanceof JoinOperator) {
/* Is any operator present, which prevents the conversion */
Map> aliasToWork = work.getAliasToWork();
for (Operator op : aliasToWork.values()) {
if (!checkOperatorOKMapJoinConversion(op)) {
return null;
}
}
return (JoinOperator) reducerOp;
} else {
return null;
}
}
}
}
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