/**
* 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.File;
import java.io.Serializable;
import java.io.UnsupportedEncodingException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.ql.exec.ConditionalTask;
import org.apache.hadoop.hive.ql.exec.JoinOperator;
import org.apache.hadoop.hive.ql.exec.MapJoinOperator;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorFactory;
import org.apache.hadoop.hive.ql.exec.RowSchema;
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.Utilities;
import org.apache.hadoop.hive.ql.io.HiveInputFormat;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.ConditionalResolverSkewJoin;
import org.apache.hadoop.hive.ql.plan.ConditionalWork;
import org.apache.hadoop.hive.ql.plan.ExprNodeColumnDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.FetchWork;
import org.apache.hadoop.hive.ql.plan.JoinDesc;
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.PartitionDesc;
import org.apache.hadoop.hive.ql.plan.PlanUtils;
import org.apache.hadoop.hive.ql.plan.TableDesc;
import org.apache.hadoop.hive.ql.plan.TableScanDesc;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory;
/**
* GenMRSkewJoinProcessor.
*
*/
public final class GenMRSkewJoinProcessor {
private GenMRSkewJoinProcessor() {
// prevent instantiation
}
/**
* Create tasks for processing skew joins. The idea is (HIVE-964) to use
* separated jobs and map-joins to handle skew joins.
* <p>
* <ul>
* <li>
* Number of mr jobs to handle skew keys is the number of table minus 1 (we
* can stream the last table, so big keys in the last table will not be a
* problem).
* <li>
* At runtime in Join, we output big keys in one table into one corresponding
* directories, and all same keys in other tables into different dirs(one for
* each table). The directories will look like:
* <ul>
* <li>
* dir-T1-bigkeys(containing big keys in T1), dir-T2-keys(containing keys
* which is big in T1),dir-T3-keys(containing keys which is big in T1), ...
* <li>
* dir-T1-keys(containing keys which is big in T2), dir-T2-bigkeys(containing
* big keys in T2),dir-T3-keys(containing keys which is big in T2), ...
* <li>
* dir-T1-keys(containing keys which is big in T3), dir-T2-keys(containing big
* keys in T3),dir-T3-bigkeys(containing keys which is big in T3), ... .....
* </ul>
* </ul>
* For each table, we launch one mapjoin job, taking the directory containing
* big keys in this table and corresponding dirs in other tables as input.
* (Actally one job for one row in the above.)
*
* <p>
* For more discussions, please check
* https://issues.apache.org/jira/browse/HIVE-964.
*
*/
public static void processSkewJoin(JoinOperator joinOp,
Task<? extends Serializable> currTask, ParseContext parseCtx)
throws SemanticException {
// We are trying to adding map joins to handle skew keys, and map join right
// now does not work with outer joins
if (!GenMRSkewJoinProcessor.skewJoinEnabled(parseCtx.getConf(), joinOp)) {
return;
}
String baseTmpDir = parseCtx.getContext().getMRTmpFileURI();
JoinDesc joinDescriptor = joinOp.getConf();
Map<Byte, List<ExprNodeDesc>> joinValues = joinDescriptor.getExprs();
int numAliases = joinValues.size();
Map<Byte, String> bigKeysDirMap = new HashMap<Byte, String>();
Map<Byte, Map<Byte, String>> smallKeysDirMap = new HashMap<Byte, Map<Byte, String>>();
Map<Byte, String> skewJoinJobResultsDir = new HashMap<Byte, String>();
Byte[] tags = joinDescriptor.getTagOrder();
for (int i = 0; i < numAliases; i++) {
Byte alias = tags[i];
String bigKeysDir = getBigKeysDir(baseTmpDir, alias);
bigKeysDirMap.put(alias, bigKeysDir);
Map<Byte, String> smallKeysMap = new HashMap<Byte, String>();
smallKeysDirMap.put(alias, smallKeysMap);
for (Byte src2 : tags) {
if (!src2.equals(alias)) {
smallKeysMap.put(src2, getSmallKeysDir(baseTmpDir, alias, src2));
}
}
skewJoinJobResultsDir.put(alias, getBigKeysSkewJoinResultDir(baseTmpDir,
alias));
}
joinDescriptor.setHandleSkewJoin(true);
joinDescriptor.setBigKeysDirMap(bigKeysDirMap);
joinDescriptor.setSmallKeysDirMap(smallKeysDirMap);
joinDescriptor.setSkewKeyDefinition(HiveConf.getIntVar(parseCtx.getConf(),
HiveConf.ConfVars.HIVESKEWJOINKEY));
HashMap<String, Task<? extends Serializable>> bigKeysDirToTaskMap =
new HashMap<String, Task<? extends Serializable>>();
List<Serializable> listWorks = new ArrayList<Serializable>();
List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
MapredWork currPlan = (MapredWork) currTask.getWork();
TableDesc keyTblDesc = (TableDesc) currPlan.getKeyDesc().clone();
List<String> joinKeys = Utilities
.getColumnNames(keyTblDesc.getProperties());
List<String> joinKeyTypes = Utilities.getColumnTypes(keyTblDesc
.getProperties());
Map<Byte, TableDesc> tableDescList = new HashMap<Byte, TableDesc>();
Map<Byte, List<ExprNodeDesc>> newJoinValues = new HashMap<Byte, List<ExprNodeDesc>>();
Map<Byte, List<ExprNodeDesc>> newJoinKeys = new HashMap<Byte, List<ExprNodeDesc>>();
// used for create mapJoinDesc, should be in order
List<TableDesc> newJoinValueTblDesc = new ArrayList<TableDesc>();
for (Byte tag : tags) {
newJoinValueTblDesc.add(null);
}
for (int i = 0; i < numAliases; i++) {
Byte alias = tags[i];
List<ExprNodeDesc> valueCols = joinValues.get(alias);
String colNames = "";
String colTypes = "";
int columnSize = valueCols.size();
List<ExprNodeDesc> newValueExpr = new ArrayList<ExprNodeDesc>();
List<ExprNodeDesc> newKeyExpr = new ArrayList<ExprNodeDesc>();
boolean first = true;
for (int k = 0; k < columnSize; k++) {
TypeInfo type = valueCols.get(k).getTypeInfo();
String newColName = i + "_VALUE_" + k; // any name, it does not matter.
newValueExpr
.add(new ExprNodeColumnDesc(type, newColName, "" + i, false));
if (!first) {
colNames = colNames + ",";
colTypes = colTypes + ",";
}
first = false;
colNames = colNames + newColName;
colTypes = colTypes + valueCols.get(k).getTypeString();
}
// we are putting join keys at last part of the spilled table
for (int k = 0; k < joinKeys.size(); k++) {
if (!first) {
colNames = colNames + ",";
colTypes = colTypes + ",";
}
first = false;
colNames = colNames + joinKeys.get(k);
colTypes = colTypes + joinKeyTypes.get(k);
newKeyExpr.add(new ExprNodeColumnDesc(TypeInfoFactory
.getPrimitiveTypeInfo(joinKeyTypes.get(k)), joinKeys.get(k),
"" + i, false));
}
newJoinValues.put(alias, newValueExpr);
newJoinKeys.put(alias, newKeyExpr);
tableDescList.put(alias, Utilities.getTableDesc(colNames, colTypes));
// construct value table Desc
String valueColNames = "";
String valueColTypes = "";
first = true;
for (int k = 0; k < columnSize; k++) {
String newColName = i + "_VALUE_" + k; // any name, it does not matter.
if (!first) {
valueColNames = valueColNames + ",";
valueColTypes = valueColTypes + ",";
}
valueColNames = valueColNames + newColName;
valueColTypes = valueColTypes + valueCols.get(k).getTypeString();
first = false;
}
newJoinValueTblDesc.set(Byte.valueOf((byte) i), Utilities.getTableDesc(
valueColNames, valueColTypes));
}
joinDescriptor.setSkewKeysValuesTables(tableDescList);
joinDescriptor.setKeyTableDesc(keyTblDesc);
for (int i = 0; i < numAliases - 1; i++) {
Byte src = tags[i];
MapredWork newPlan = PlanUtils.getMapRedWork();
// This code has been only added for testing
boolean mapperCannotSpanPartns =
parseCtx.getConf().getBoolVar(
HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
newPlan.setMapperCannotSpanPartns(mapperCannotSpanPartns);
MapredWork clonePlan = null;
try {
String xmlPlan = currPlan.toXML();
StringBuilder sb = new StringBuilder(xmlPlan);
ByteArrayInputStream bis;
bis = new ByteArrayInputStream(sb.toString().getBytes("UTF-8"));
clonePlan = Utilities.deserializeMapRedWork(bis, parseCtx.getConf());
} catch (UnsupportedEncodingException e) {
throw new SemanticException(e);
}
Operator<? extends Serializable>[] parentOps = new TableScanOperator[tags.length];
for (int k = 0; k < tags.length; k++) {
Operator<? extends Serializable> ts = OperatorFactory.get(
TableScanDesc.class, (RowSchema) null);
((TableScanOperator)ts).setTableDesc(tableDescList.get((byte)k));
parentOps[k] = ts;
}
Operator<? extends Serializable> tblScan_op = parentOps[i];
ArrayList<String> aliases = new ArrayList<String>();
String alias = src.toString();
aliases.add(alias);
String bigKeyDirPath = bigKeysDirMap.get(src);
newPlan.getPathToAliases().put(bigKeyDirPath, aliases);
newPlan.getAliasToWork().put(alias, tblScan_op);
PartitionDesc part = new PartitionDesc(tableDescList.get(src), null);
newPlan.getPathToPartitionInfo().put(bigKeyDirPath, part);
newPlan.getAliasToPartnInfo().put(alias, part);
Operator<? extends Serializable> reducer = clonePlan.getReducer();
assert reducer instanceof JoinOperator;
JoinOperator cloneJoinOp = (JoinOperator) reducer;
String dumpFilePrefix = "mapfile"+PlanUtils.getCountForMapJoinDumpFilePrefix();
MapJoinDesc mapJoinDescriptor = new MapJoinDesc(newJoinKeys, keyTblDesc,
newJoinValues, newJoinValueTblDesc, newJoinValueTblDesc,joinDescriptor
.getOutputColumnNames(), i, joinDescriptor.getConds(),
joinDescriptor.getFilters(), joinDescriptor.getNoOuterJoin(), dumpFilePrefix);
mapJoinDescriptor.setTagOrder(tags);
mapJoinDescriptor.setHandleSkewJoin(false);
mapJoinDescriptor.setNullSafes(joinDescriptor.getNullSafes());
MapredLocalWork localPlan = new MapredLocalWork(
new LinkedHashMap<String, Operator<? extends Serializable>>(),
new LinkedHashMap<String, FetchWork>());
Map<Byte, String> smallTblDirs = smallKeysDirMap.get(src);
for (int j = 0; j < numAliases; j++) {
if (j == i) {
continue;
}
Byte small_alias = tags[j];
Operator<? extends Serializable> tblScan_op2 = parentOps[j];
localPlan.getAliasToWork().put(small_alias.toString(), tblScan_op2);
Path tblDir = new Path(smallTblDirs.get(small_alias));
localPlan.getAliasToFetchWork().put(small_alias.toString(),
new FetchWork(tblDir.toString(), tableDescList.get(small_alias)));
}
newPlan.setMapLocalWork(localPlan);
// construct a map join and set it as the child operator of tblScan_op
MapJoinOperator mapJoinOp = (MapJoinOperator) OperatorFactory
.getAndMakeChild(mapJoinDescriptor, (RowSchema) null, parentOps);
// change the children of the original join operator to point to the map
// join operator
List<Operator<? extends Serializable>> childOps = cloneJoinOp
.getChildOperators();
for (Operator<? extends Serializable> childOp : childOps) {
childOp.replaceParent(cloneJoinOp, mapJoinOp);
}
mapJoinOp.setChildOperators(childOps);
HiveConf jc = new HiveConf(parseCtx.getConf(),
GenMRSkewJoinProcessor.class);
newPlan.setNumMapTasks(HiveConf
.getIntVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINNUMMAPTASK));
newPlan
.setMinSplitSize(HiveConf.getLongVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINMINSPLIT));
newPlan.setInputformat(HiveInputFormat.class.getName());
Task<? extends Serializable> skewJoinMapJoinTask = TaskFactory.get(
newPlan, jc);
bigKeysDirToTaskMap.put(bigKeyDirPath, skewJoinMapJoinTask);
listWorks.add(skewJoinMapJoinTask.getWork());
listTasks.add(skewJoinMapJoinTask);
}
ConditionalWork cndWork = new ConditionalWork(listWorks);
ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork,
parseCtx.getConf());
cndTsk.setListTasks(listTasks);
cndTsk.setResolver(new ConditionalResolverSkewJoin());
cndTsk
.setResolverCtx(new ConditionalResolverSkewJoin.ConditionalResolverSkewJoinCtx(
bigKeysDirToTaskMap));
List<Task<? extends Serializable>> oldChildTasks = currTask.getChildTasks();
currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
currTask.addDependentTask(cndTsk);
if (oldChildTasks != null) {
for (Task<? extends Serializable> tsk : cndTsk.getListTasks()) {
for (Task<? extends Serializable> oldChild : oldChildTasks) {
tsk.addDependentTask(oldChild);
}
}
}
return;
}
public static boolean skewJoinEnabled(HiveConf conf, JoinOperator joinOp) {
if (conf != null && !conf.getBoolVar(HiveConf.ConfVars.HIVESKEWJOIN)) {
return false;
}
if (!joinOp.getConf().isNoOuterJoin()) {
return false;
}
byte pos = 0;
for (Byte tag : joinOp.getConf().getTagOrder()) {
if (tag != pos) {
return false;
}
pos++;
}
return true;
}
private static String skewJoinPrefix = "hive_skew_join";
private static String UNDERLINE = "_";
private static String BIGKEYS = "bigkeys";
private static String SMALLKEYS = "smallkeys";
private static String RESULTS = "results";
static String getBigKeysDir(String baseDir, Byte srcTbl) {
return baseDir + File.separator + skewJoinPrefix + UNDERLINE + BIGKEYS
+ UNDERLINE + srcTbl;
}
static String getBigKeysSkewJoinResultDir(String baseDir, Byte srcTbl) {
return baseDir + File.separator + skewJoinPrefix + UNDERLINE + BIGKEYS
+ UNDERLINE + RESULTS + UNDERLINE + srcTbl;
}
static String getSmallKeysDir(String baseDir, Byte srcTblBigTbl,
Byte srcTblSmallTbl) {
return baseDir + File.separator + skewJoinPrefix + UNDERLINE + SMALLKEYS
+ UNDERLINE + srcTblBigTbl + UNDERLINE + srcTblSmallTbl;
}
}