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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;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.fs.Path;
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.ExecDriver;
import org.apache.hadoop.hive.ql.exec.JoinOperator;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorFactory;
import org.apache.hadoop.hive.ql.exec.ReduceSinkOperator;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.exec.Task;
import org.apache.hadoop.hive.ql.exec.TaskFactory;
import org.apache.hadoop.hive.ql.exec.UnionOperator;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.hooks.ReadEntity;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.metadata.Partition;
import org.apache.hadoop.hive.ql.optimizer.GenMRProcContext.GenMRUnionCtx;
import org.apache.hadoop.hive.ql.optimizer.GenMRProcContext.GenMapRedCtx;
import org.apache.hadoop.hive.ql.optimizer.listbucketingpruner.ListBucketingPruner;
import org.apache.hadoop.hive.ql.optimizer.ppr.PartitionPruner;
import org.apache.hadoop.hive.ql.parse.OpParseContext;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.PrunedPartitionList;
import org.apache.hadoop.hive.ql.parse.RowResolver;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.FetchWork;
import org.apache.hadoop.hive.ql.plan.FileSinkDesc;
import org.apache.hadoop.hive.ql.plan.FilterDesc.sampleDesc;
import org.apache.hadoop.hive.ql.plan.MapJoinDesc;
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;
import org.apache.hadoop.hive.ql.plan.PlanUtils;
import org.apache.hadoop.hive.ql.plan.ReduceSinkDesc;
import org.apache.hadoop.hive.ql.plan.TableDesc;
import org.apache.hadoop.hive.ql.plan.TableScanDesc;
/**
* General utility common functions for the Processor to convert operator into
* map-reduce tasks.
*/
public final class GenMapRedUtils {
private static Log LOG;
static {
LOG = LogFactory.getLog("org.apache.hadoop.hive.ql.optimizer.GenMapRedUtils");
}
/**
* Initialize the current plan by adding it to root tasks.
*
* @param op
* the reduce sink operator encountered
* @param opProcCtx
* processing context
*/
public static void initPlan(ReduceSinkOperator op, GenMRProcContext opProcCtx)
throws SemanticException {
Operator reducer = op.getChildOperators().get(0);
Map, GenMapRedCtx> mapCurrCtx =
opProcCtx.getMapCurrCtx();
GenMapRedCtx mapredCtx = mapCurrCtx.get(op.getParentOperators().get(0));
Task currTask = mapredCtx.getCurrTask();
MapredWork plan = (MapredWork) currTask.getWork();
HashMap, Task> opTaskMap =
opProcCtx.getOpTaskMap();
Operator currTopOp = opProcCtx.getCurrTopOp();
opTaskMap.put(reducer, currTask);
plan.setReducer(reducer);
ReduceSinkDesc desc = op.getConf();
plan.setNumReduceTasks(desc.getNumReducers());
List> rootTasks = opProcCtx.getRootTasks();
if (!rootTasks.contains(currTask)
&& (currTask.getParentTasks() == null
|| currTask.getParentTasks().isEmpty())) {
rootTasks.add(currTask);
}
if (reducer.getClass() == JoinOperator.class) {
plan.setNeedsTagging(true);
}
assert currTopOp != null;
List> seenOps = opProcCtx.getSeenOps();
String currAliasId = opProcCtx.getCurrAliasId();
if (!seenOps.contains(currTopOp)) {
seenOps.add(currTopOp);
setTaskPlan(currAliasId, currTopOp, plan, false, opProcCtx);
}
currTopOp = null;
currAliasId = null;
opProcCtx.setCurrTask(currTask);
opProcCtx.setCurrTopOp(currTopOp);
opProcCtx.setCurrAliasId(currAliasId);
}
/**
* Initialize the current union plan.
*
* @param op
* the reduce sink operator encountered
* @param opProcCtx
* processing context
*/
public static void initUnionPlan(ReduceSinkOperator op, UnionOperator currUnionOp,
GenMRProcContext opProcCtx,
Task unionTask) throws SemanticException {
Operator reducer = op.getChildOperators().get(0);
MapredWork plan = (MapredWork) unionTask.getWork();
HashMap, Task> opTaskMap =
opProcCtx.getOpTaskMap();
opTaskMap.put(reducer, unionTask);
plan.setReducer(reducer);
ReduceSinkDesc desc = op.getConf();
plan.setNumReduceTasks(desc.getNumReducers());
if (reducer.getClass() == JoinOperator.class) {
plan.setNeedsTagging(true);
}
initUnionPlan(opProcCtx, currUnionOp, unionTask, false);
}
private static void setUnionPlan(GenMRProcContext opProcCtx,
boolean local, MapredWork plan, GenMRUnionCtx uCtx,
boolean mergeTask) throws SemanticException {
Operator currTopOp = opProcCtx.getCurrTopOp();
if (currTopOp != null) {
List> seenOps = opProcCtx.getSeenOps();
String currAliasId = opProcCtx.getCurrAliasId();
if (!seenOps.contains(currTopOp) || mergeTask) {
seenOps.add(currTopOp);
setTaskPlan(currAliasId, currTopOp, plan, local, opProcCtx);
}
currTopOp = null;
opProcCtx.setCurrTopOp(currTopOp);
} else {
List taskTmpDirLst = uCtx.getTaskTmpDir();
if ((taskTmpDirLst != null) && !(taskTmpDirLst.isEmpty())) {
List tt_descLst = uCtx.getTTDesc();
assert !taskTmpDirLst.isEmpty() && !tt_descLst.isEmpty();
assert taskTmpDirLst.size() == tt_descLst.size();
int size = taskTmpDirLst.size();
assert local == false;
List> topOperators =
uCtx.getListTopOperators();
for (int pos = 0; pos < size; pos++) {
String taskTmpDir = taskTmpDirLst.get(pos);
TableDesc tt_desc = tt_descLst.get(pos);
if (plan.getPathToAliases().get(taskTmpDir) == null) {
plan.getPathToAliases().put(taskTmpDir,
new ArrayList());
plan.getPathToAliases().get(taskTmpDir).add(taskTmpDir);
plan.getPathToPartitionInfo().put(taskTmpDir,
new PartitionDesc(tt_desc, null));
plan.getAliasToWork().put(taskTmpDir, topOperators.get(pos));
}
}
}
}
}
/*
* It is a idempotent function to add various intermediate files as the source
* for the union. The plan has already been created.
*/
public static void initUnionPlan(GenMRProcContext opProcCtx, UnionOperator currUnionOp,
Task currTask, boolean local)
throws SemanticException {
MapredWork plan = (MapredWork) currTask.getWork();
// In case of lateral views followed by a join, the same tree
// can be traversed more than one
if (currUnionOp != null) {
GenMRUnionCtx uCtx = opProcCtx.getUnionTask(currUnionOp);
assert uCtx != null;
setUnionPlan(opProcCtx, local, plan, uCtx, false);
}
}
/*
* join current union task to old task
*/
public static void joinUnionPlan(GenMRProcContext opProcCtx,
UnionOperator currUnionOp,
Task currentUnionTask,
Task existingTask, boolean local)
throws SemanticException {
MapredWork plan = (MapredWork) existingTask.getWork();
assert currUnionOp != null;
GenMRUnionCtx uCtx = opProcCtx.getUnionTask(currUnionOp);
assert uCtx != null;
setUnionPlan(opProcCtx, local, plan, uCtx, true);
List> parTasks = null;
if (opProcCtx.getRootTasks().contains(currentUnionTask)) {
opProcCtx.getRootTasks().remove(currentUnionTask);
if (!opProcCtx.getRootTasks().contains(existingTask) &&
(existingTask.getParentTasks() == null || existingTask.getParentTasks().isEmpty())) {
opProcCtx.getRootTasks().add(existingTask);
}
}
if ((currentUnionTask != null) && (currentUnionTask.getParentTasks() != null)
&& !currentUnionTask.getParentTasks().isEmpty()) {
parTasks = new ArrayList>();
parTasks.addAll(currentUnionTask.getParentTasks());
Object[] parTaskArr = parTasks.toArray();
for (Object parTask : parTaskArr) {
((Task) parTask)
.removeDependentTask(currentUnionTask);
}
}
if ((currentUnionTask != null) && (parTasks != null)) {
for (Task parTask : parTasks) {
parTask.addDependentTask(existingTask);
if (opProcCtx.getRootTasks().contains(existingTask)) {
opProcCtx.getRootTasks().remove(existingTask);
}
}
}
opProcCtx.setCurrTask(existingTask);
}
/**
* Merge the current task with the task for the current reducer.
*
* @param op
* operator being processed
* @param oldTask
* the old task for the current reducer
* @param task
* the current task for the current reducer
* @param opProcCtx
* processing context
* @param pos
* position of the parent in the stack
*/
public static void joinPlan(Operator op,
Task oldTask, Task task,
GenMRProcContext opProcCtx, int pos, boolean split)
throws SemanticException {
Task currTask = task;
MapredWork plan = (MapredWork) currTask.getWork();
Operator currTopOp = opProcCtx.getCurrTopOp();
List> parTasks = null;
// terminate the old task and make current task dependent on it
if (split) {
assert oldTask != null;
splitTasks(op, oldTask, currTask, opProcCtx, true, false, 0);
} else {
if ((oldTask != null) && (oldTask.getParentTasks() != null)
&& !oldTask.getParentTasks().isEmpty()) {
parTasks = new ArrayList>();
parTasks.addAll(oldTask.getParentTasks());
Object[] parTaskArr = parTasks.toArray();
for (Object element : parTaskArr) {
((Task) element).removeDependentTask(oldTask);
}
}
}
if (currTopOp != null) {
List> seenOps = opProcCtx.getSeenOps();
String currAliasId = opProcCtx.getCurrAliasId();
if (!seenOps.contains(currTopOp)) {
seenOps.add(currTopOp);
boolean local = false;
if (pos != -1) {
local = (pos == ((MapJoinDesc) op.getConf()).getPosBigTable()) ? false
: true;
}
setTaskPlan(currAliasId, currTopOp, plan, local, opProcCtx);
}
currTopOp = null;
opProcCtx.setCurrTopOp(currTopOp);
}
if ((oldTask != null) && (parTasks != null)) {
for (Task parTask : parTasks) {
parTask.addDependentTask(currTask);
if (opProcCtx.getRootTasks().contains(currTask)) {
opProcCtx.getRootTasks().remove(currTask);
}
}
}
opProcCtx.setCurrTask(currTask);
}
/**
* Split the current plan by creating a temporary destination.
*
* @param op
* the reduce sink operator encountered
* @param opProcCtx
* processing context
*/
public static void splitPlan(ReduceSinkOperator op, GenMRProcContext opProcCtx)
throws SemanticException {
// Generate a new task
ParseContext parseCtx = opProcCtx.getParseCtx();
MapredWork cplan = getMapRedWork(parseCtx);
Task redTask = TaskFactory.get(cplan, parseCtx
.getConf());
Operator reducer = op.getChildOperators().get(0);
// Add the reducer
cplan.setReducer(reducer);
ReduceSinkDesc desc = op.getConf();
cplan.setNumReduceTasks(new Integer(desc.getNumReducers()));
HashMap, Task> opTaskMap =
opProcCtx.getOpTaskMap();
opTaskMap.put(reducer, redTask);
Task currTask = opProcCtx.getCurrTask();
splitTasks(op, currTask, redTask, opProcCtx, true, false, 0);
opProcCtx.getRootOps().add(op);
}
/**
* set the current task in the mapredWork.
*
* @param alias_id
* current alias
* @param topOp
* the top operator of the stack
* @param plan
* current plan
* @param local
* whether you need to add to map-reduce or local work
* @param opProcCtx
* processing context
*/
public static void setTaskPlan(String alias_id,
Operator topOp, MapredWork plan, boolean local,
GenMRProcContext opProcCtx) throws SemanticException {
setTaskPlan(alias_id, topOp, plan, local, opProcCtx, null);
}
private static ReadEntity getParentViewInfo(String alias_id,
Map viewAliasToInput) {
String[] aliases = alias_id.split(":");
String currentAlias = null;
ReadEntity currentInput = null;
// Find the immediate parent possible.
// For eg: for a query like 'select * from V3', where V3 -> V2, V2 -> V1, V1 -> T
// -> implies depends on.
// T's parent would be V1
for (int pos = 0; pos < aliases.length; pos++) {
currentAlias = currentAlias == null ? aliases[pos] : currentAlias + ":" + aliases[pos];
ReadEntity input = viewAliasToInput.get(currentAlias);
if (input == null) {
return currentInput;
}
currentInput = input;
}
return currentInput;
}
/**
* set the current task in the mapredWork.
*
* @param alias_id
* current alias
* @param topOp
* the top operator of the stack
* @param plan
* current plan
* @param local
* whether you need to add to map-reduce or local work
* @param opProcCtx
* processing context
* @param pList
* pruned partition list. If it is null it will be computed on-the-fly.
*/
public static void setTaskPlan(String alias_id,
Operator topOp, MapredWork plan, boolean local,
GenMRProcContext opProcCtx, PrunedPartitionList pList) throws SemanticException {
ParseContext parseCtx = opProcCtx.getParseCtx();
Set inputs = opProcCtx.getInputs();
ArrayList partDir = new ArrayList();
ArrayList partDesc = new ArrayList();
Path tblDir = null;
TableDesc tblDesc = null;
PrunedPartitionList partsList = pList;
plan.setNameToSplitSample(parseCtx.getNameToSplitSample());
if (partsList == null) {
try {
partsList = parseCtx.getOpToPartList().get((TableScanOperator) topOp);
if (partsList == null) {
partsList = PartitionPruner.prune(parseCtx.getTopToTable().get(topOp),
parseCtx.getOpToPartPruner().get(topOp), opProcCtx.getConf(),
alias_id, parseCtx.getPrunedPartitions());
parseCtx.getOpToPartList().put((TableScanOperator) topOp, partsList);
}
} catch (SemanticException e) {
throw e;
} catch (HiveException e) {
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
}
// Generate the map work for this alias_id
Set parts = null;
// pass both confirmed and unknown partitions through the map-reduce
// framework
parts = partsList.getConfirmedPartns();
parts.addAll(partsList.getUnknownPartns());
PartitionDesc aliasPartnDesc = null;
try {
if (!parts.isEmpty()) {
aliasPartnDesc = Utilities.getPartitionDesc(parts.iterator().next());
}
} catch (HiveException e) {
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
// The table does not have any partitions
if (aliasPartnDesc == null) {
aliasPartnDesc = new PartitionDesc(Utilities.getTableDesc(parseCtx
.getTopToTable().get(topOp)), null);
}
plan.getAliasToPartnInfo().put(alias_id, aliasPartnDesc);
long sizeNeeded = Integer.MAX_VALUE;
int fileLimit = -1;
if (parseCtx.getGlobalLimitCtx().isEnable()) {
long sizePerRow = HiveConf.getLongVar(parseCtx.getConf(),
HiveConf.ConfVars.HIVELIMITMAXROWSIZE);
sizeNeeded = parseCtx.getGlobalLimitCtx().getGlobalLimit() * sizePerRow;
// for the optimization that reduce number of input file, we limit number
// of files allowed. If more than specific number of files have to be
// selected, we skip this optimization. Since having too many files as
// inputs can cause unpredictable latency. It's not necessarily to be
// cheaper.
fileLimit =
HiveConf.getIntVar(parseCtx.getConf(), HiveConf.ConfVars.HIVELIMITOPTLIMITFILE);
if (sizePerRow <= 0 || fileLimit <= 0) {
LOG.info("Skip optimization to reduce input size of 'limit'");
parseCtx.getGlobalLimitCtx().disableOpt();
} else if (parts.isEmpty()) {
LOG.info("Empty input: skip limit optimiztion");
} else {
LOG.info("Try to reduce input size for 'limit' " +
"sizeNeeded: " + sizeNeeded +
" file limit : " + fileLimit);
}
}
boolean isFirstPart = true;
boolean emptyInput = true;
boolean singlePartition = (parts.size() == 1);
// Track the dependencies for the view. Consider a query like: select * from V;
// where V is a view of the form: select * from T
// The dependencies should include V at depth 0, and T at depth 1 (inferred).
ReadEntity parentViewInfo = getParentViewInfo(alias_id, parseCtx.getViewAliasToInput());
// The table should also be considered a part of inputs, even if the table is a
// partitioned table and whether any partition is selected or not
PlanUtils.addInput(inputs,
new ReadEntity(parseCtx.getTopToTable().get(topOp), parentViewInfo));
for (Partition part : parts) {
if (part.getTable().isPartitioned()) {
PlanUtils.addInput(inputs, new ReadEntity(part, parentViewInfo));
} else {
PlanUtils.addInput(inputs, new ReadEntity(part.getTable(), parentViewInfo));
}
// Later the properties have to come from the partition as opposed
// to from the table in order to support versioning.
Path[] paths = null;
sampleDesc sampleDescr = parseCtx.getOpToSamplePruner().get(topOp);
// Lookup list bucketing pruner
Map partToPruner = parseCtx.getOpToPartToSkewedPruner().get(topOp);
ExprNodeDesc listBucketingPruner = (partToPruner != null) ? partToPruner.get(part.getName())
: null;
if (sampleDescr != null) {
assert (listBucketingPruner == null) : "Sampling and list bucketing can't coexit.";
paths = SamplePruner.prune(part, sampleDescr);
parseCtx.getGlobalLimitCtx().disableOpt();
} else if (listBucketingPruner != null) {
assert (sampleDescr == null) : "Sampling and list bucketing can't coexist.";
/* Use list bucketing prunner's path. */
paths = ListBucketingPruner.prune(parseCtx, part, listBucketingPruner);
} else {
// Now we only try the first partition, if the first partition doesn't
// contain enough size, we change to normal mode.
if (parseCtx.getGlobalLimitCtx().isEnable()) {
if (isFirstPart) {
long sizeLeft = sizeNeeded;
ArrayList retPathList = new ArrayList();
SamplePruner.LimitPruneRetStatus status = SamplePruner.limitPrune(part, sizeLeft,
fileLimit, retPathList);
if (status.equals(SamplePruner.LimitPruneRetStatus.NoFile)) {
continue;
} else if (status.equals(SamplePruner.LimitPruneRetStatus.NotQualify)) {
LOG.info("Use full input -- first " + fileLimit + " files are more than "
+ sizeNeeded
+ " bytes");
parseCtx.getGlobalLimitCtx().disableOpt();
} else {
emptyInput = false;
paths = new Path[retPathList.size()];
int index = 0;
for (Path path : retPathList) {
paths[index++] = path;
}
if (status.equals(SamplePruner.LimitPruneRetStatus.NeedAllFiles) && singlePartition) {
// if all files are needed to meet the size limit, we disable
// optimization. It usually happens for empty table/partition or
// table/partition with only one file. By disabling this
// optimization, we can avoid retrying the query if there is
// not sufficient rows.
parseCtx.getGlobalLimitCtx().disableOpt();
}
}
isFirstPart = false;
} else {
paths = new Path[0];
}
}
if (!parseCtx.getGlobalLimitCtx().isEnable()) {
paths = part.getPath();
}
}
// is it a partitioned table ?
if (!part.getTable().isPartitioned()) {
assert ((tblDir == null) && (tblDesc == null));
tblDir = paths[0];
tblDesc = Utilities.getTableDesc(part.getTable());
} else if (tblDesc == null) {
tblDesc = Utilities.getTableDesc(part.getTable());
}
for (Path p : paths) {
if (p == null) {
continue;
}
String path = p.toString();
if (LOG.isDebugEnabled()) {
LOG.debug("Adding " + path + " of table" + alias_id);
}
partDir.add(p);
try {
if (part.getTable().isPartitioned()) {
partDesc.add(Utilities.getPartitionDesc(part));
}
else {
partDesc.add(Utilities.getPartitionDescFromTableDesc(tblDesc, part));
}
} catch (HiveException e) {
LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
throw new SemanticException(e.getMessage(), e);
}
}
}
if (emptyInput) {
parseCtx.getGlobalLimitCtx().disableOpt();
}
Iterator iterPath = partDir.iterator();
Iterator iterPartnDesc = partDesc.iterator();
if (!local) {
while (iterPath.hasNext()) {
assert iterPartnDesc.hasNext();
String path = iterPath.next().toString();
PartitionDesc prtDesc = iterPartnDesc.next();
// Add the path to alias mapping
if (plan.getPathToAliases().get(path) == null) {
plan.getPathToAliases().put(path, new ArrayList());
}
plan.getPathToAliases().get(path).add(alias_id);
plan.getPathToPartitionInfo().put(path, prtDesc);
if (LOG.isDebugEnabled()) {
LOG.debug("Information added for path " + path);
}
}
assert plan.getAliasToWork().get(alias_id) == null;
plan.getAliasToWork().put(alias_id, topOp);
} else {
// populate local work if needed
MapredLocalWork localPlan = plan.getMapLocalWork();
if (localPlan == null) {
localPlan = new MapredLocalWork(
new LinkedHashMap>(),
new LinkedHashMap());
}
assert localPlan.getAliasToWork().get(alias_id) == null;
assert localPlan.getAliasToFetchWork().get(alias_id) == null;
localPlan.getAliasToWork().put(alias_id, topOp);
if (tblDir == null) {
tblDesc = Utilities.getTableDesc(partsList.getSourceTable());
localPlan.getAliasToFetchWork().put(
alias_id,
new FetchWork(FetchWork.convertPathToStringArray(partDir), partDesc, tblDesc));
} else {
localPlan.getAliasToFetchWork().put(alias_id,
new FetchWork(tblDir.toString(), tblDesc));
}
plan.setMapLocalWork(localPlan);
}
}
/**
* set the current task in the mapredWork.
*
* @param alias
* current alias
* @param topOp
* the top operator of the stack
* @param plan
* current plan
* @param local
* whether you need to add to map-reduce or local work
* @param tt_desc
* table descriptor
*/
public static void setTaskPlan(String path, String alias,
Operator topOp, MapredWork plan, boolean local,
TableDesc tt_desc) throws SemanticException {
if (path == null || alias == null) {
return;
}
if (!local) {
if (plan.getPathToAliases().get(path) == null) {
plan.getPathToAliases().put(path, new ArrayList());
}
plan.getPathToAliases().get(path).add(alias);
plan.getPathToPartitionInfo().put(path, new PartitionDesc(tt_desc, null));
plan.getAliasToWork().put(alias, topOp);
} else {
// populate local work if needed
MapredLocalWork localPlan = plan.getMapLocalWork();
if (localPlan == null) {
localPlan = new MapredLocalWork(
new LinkedHashMap>(),
new LinkedHashMap());
}
assert localPlan.getAliasToWork().get(alias) == null;
assert localPlan.getAliasToFetchWork().get(alias) == null;
localPlan.getAliasToWork().put(alias, topOp);
localPlan.getAliasToFetchWork().put(alias, new FetchWork(alias, tt_desc));
plan.setMapLocalWork(localPlan);
}
}
/**
* set key and value descriptor.
*
* @param plan
* current plan
* @param topOp
* current top operator in the path
*/
public static void setKeyAndValueDesc(MapredWork plan,
Operator topOp) {
if (topOp == null) {
return;
}
if (topOp instanceof ReduceSinkOperator) {
ReduceSinkOperator rs = (ReduceSinkOperator) topOp;
plan.setKeyDesc(rs.getConf().getKeySerializeInfo());
int tag = Math.max(0, rs.getConf().getTag());
List tagToSchema = plan.getTagToValueDesc();
while (tag + 1 > tagToSchema.size()) {
tagToSchema.add(null);
}
tagToSchema.set(tag, rs.getConf().getValueSerializeInfo());
} else {
List> children = topOp.getChildOperators();
if (children != null) {
for (Operator op : children) {
setKeyAndValueDesc(plan, op);
}
}
}
}
/**
* Set the key and value description for all the tasks rooted at the given
* task. Loops over all the tasks recursively.
*
* @param task
*/
public static void setKeyAndValueDescForTaskTree(Task task) {
if (task instanceof ConditionalTask) {
List> listTasks = ((ConditionalTask) task)
.getListTasks();
for (Task tsk : listTasks) {
setKeyAndValueDescForTaskTree(tsk);
}
} else if (task instanceof ExecDriver) {
MapredWork work = (MapredWork) task.getWork();
work.deriveExplainAttributes();
HashMap> opMap = work
.getAliasToWork();
if (opMap != null && !opMap.isEmpty()) {
for (Operator op : opMap.values()) {
setKeyAndValueDesc(work, op);
}
}
}
if (task.getChildTasks() == null) {
return;
}
for (Task childTask : task.getChildTasks()) {
setKeyAndValueDescForTaskTree(childTask);
}
}
/**
* create a new plan and return.
*
* @return the new plan
*/
public static MapredWork getMapRedWork(ParseContext parseCtx) {
MapredWork work = getMapRedWorkFromConf(parseCtx.getConf());
work.setNameToSplitSample(parseCtx.getNameToSplitSample());
return work;
}
/**
* create a new plan and return. The pan won't contain the name to split
* sample information in parse context.
*
* @return the new plan
*/
public static MapredWork getMapRedWorkFromConf(HiveConf conf) {
MapredWork work = new MapredWork();
boolean mapperCannotSpanPartns =
conf.getBoolVar(
HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
work.setMapperCannotSpanPartns(mapperCannotSpanPartns);
work.setPathToAliases(new LinkedHashMap>());
work.setPathToPartitionInfo(new LinkedHashMap());
work.setAliasToWork(new LinkedHashMap>());
work.setTagToValueDesc(new ArrayList());
work.setReducer(null);
work.setHadoopSupportsSplittable(
conf.getBoolVar(HiveConf.ConfVars.HIVE_COMBINE_INPUT_FORMAT_SUPPORTS_SPLITTABLE));
return work;
}
/**
* insert in the map for the operator to row resolver.
*
* @param op
* operator created
* @param rr
* row resolver
* @param parseCtx
* parse context
*/
@SuppressWarnings("nls")
public static Operator putOpInsertMap(
Operator op, RowResolver rr, ParseContext parseCtx) {
OpParseContext ctx = new OpParseContext(rr);
parseCtx.getOpParseCtx().put(op, ctx);
return op;
}
@SuppressWarnings("nls")
/**
* Merge the tasks - by creating a temporary file between them.
* @param op reduce sink operator being processed
* @param oldTask the parent task
* @param task the child task
* @param opProcCtx context
* @param setReducer does the reducer needs to be set
* @param pos position of the parent
**/
public static void splitTasks(Operator op,
Task parentTask,
Task childTask, GenMRProcContext opProcCtx,
boolean setReducer, boolean local, int posn) throws SemanticException {
childTask.getWork();
Operator currTopOp = opProcCtx.getCurrTopOp();
ParseContext parseCtx = opProcCtx.getParseCtx();
parentTask.addDependentTask(childTask);
// Root Task cannot depend on any other task, therefore childTask cannot be
// a root Task
List> rootTasks = opProcCtx.getRootTasks();
if (rootTasks.contains(childTask)) {
rootTasks.remove(childTask);
}
// generate the temporary file
Context baseCtx = parseCtx.getContext();
String taskTmpDir = baseCtx.getMRTmpFileURI();
Operator parent = op.getParentOperators().get(posn);
TableDesc tt_desc = PlanUtils.getIntermediateFileTableDesc(PlanUtils
.getFieldSchemasFromRowSchema(parent.getSchema(), "temporarycol"));
// Create a file sink operator for this file name
boolean compressIntermediate = parseCtx.getConf().getBoolVar(
HiveConf.ConfVars.COMPRESSINTERMEDIATE);
FileSinkDesc desc = new FileSinkDesc(taskTmpDir, tt_desc,
compressIntermediate);
if (compressIntermediate) {
desc.setCompressCodec(parseCtx.getConf().getVar(
HiveConf.ConfVars.COMPRESSINTERMEDIATECODEC));
desc.setCompressType(parseCtx.getConf().getVar(
HiveConf.ConfVars.COMPRESSINTERMEDIATETYPE));
}
Operator fs_op = putOpInsertMap(OperatorFactory
.get(desc, parent.getSchema()), null, parseCtx);
// replace the reduce child with this operator
List> childOpList = parent
.getChildOperators();
for (int pos = 0; pos < childOpList.size(); pos++) {
if (childOpList.get(pos) == op) {
childOpList.set(pos, fs_op);
break;
}
}
List> parentOpList =
new ArrayList>();
parentOpList.add(parent);
fs_op.setParentOperators(parentOpList);
// create a dummy tableScan operator on top of op
// TableScanOperator is implicitly created here for each MapOperator
RowResolver rowResolver = opProcCtx.getParseCtx().getOpParseCtx().get(parent).getRowResolver();
Operator ts_op = putOpInsertMap(OperatorFactory
.get(TableScanDesc.class, parent.getSchema()), rowResolver, parseCtx);
childOpList = new ArrayList>();
childOpList.add(op);
ts_op.setChildOperators(childOpList);
op.getParentOperators().set(posn, ts_op);
Map, GenMapRedCtx> mapCurrCtx =
opProcCtx.getMapCurrCtx();
mapCurrCtx.put(ts_op, new GenMapRedCtx(childTask, null, null));
String streamDesc = taskTmpDir;
MapredWork cplan = (MapredWork) childTask.getWork();
if (setReducer) {
Operator reducer = op.getChildOperators().get(0);
if (reducer.getClass() == JoinOperator.class) {
String origStreamDesc;
streamDesc = "$INTNAME";
origStreamDesc = streamDesc;
int pos = 0;
while (cplan.getAliasToWork().get(streamDesc) != null) {
streamDesc = origStreamDesc.concat(String.valueOf(++pos));
}
}
// TODO: Allocate work to remove the temporary files and make that
// dependent on the redTask
if (reducer.getClass() == JoinOperator.class) {
cplan.setNeedsTagging(true);
}
}
// Add the path to alias mapping
setTaskPlan(taskTmpDir, streamDesc, ts_op, cplan, local, tt_desc);
opProcCtx.setCurrTopOp(null);
opProcCtx.setCurrAliasId(null);
opProcCtx.setCurrTask(childTask);
}
private GenMapRedUtils() {
// prevent instantiation
}
}
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