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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.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import java.util.Stack;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
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.RowSchema;
import org.apache.hadoop.hive.ql.exec.SelectOperator;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.exec.UDFArgumentException;
import org.apache.hadoop.hive.ql.lib.DefaultGraphWalker;
import org.apache.hadoop.hive.ql.lib.DefaultRuleDispatcher;
import org.apache.hadoop.hive.ql.lib.Dispatcher;
import org.apache.hadoop.hive.ql.lib.GraphWalker;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.lib.NodeProcessor;
import org.apache.hadoop.hive.ql.lib.NodeProcessorCtx;
import org.apache.hadoop.hive.ql.lib.Rule;
import org.apache.hadoop.hive.ql.lib.RuleRegExp;
import org.apache.hadoop.hive.ql.metadata.Table;
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.ExprNodeColumnDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeConstantDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc.ExprNodeDescEqualityWrapper;
import org.apache.hadoop.hive.ql.plan.ExprNodeGenericFuncDesc;
import org.apache.hadoop.hive.ql.plan.FilterDesc;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
import org.apache.hadoop.hive.ql.plan.ReduceSinkDesc;
import org.apache.hadoop.hive.ql.plan.SelectDesc;
import org.apache.hadoop.hive.ql.plan.UnionDesc;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPAnd;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPEqual;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPNot;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFOPOr;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorConverters.Converter;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils;
/**
* SkewJoinOptimizer.
*
*/
public class SkewJoinOptimizer implements Transform {
private static final Log LOG = LogFactory.getLog(SkewJoinOptimizer.class.getName());
public static class SkewJoinProc implements NodeProcessor {
private ParseContext parseContext;
public SkewJoinProc(ParseContext parseContext) {
super();
this.parseContext = parseContext;
}
@Override
public Object process(Node nd, Stack stack, NodeProcessorCtx procCtx,
Object... nodeOutputs) throws SemanticException {
// We should be having a tree which looks like this
// TS -> * -> RS -
// \
// -> JOIN -> ..
// /
// TS -> * -> RS -
//
// We are in the join operator now.
SkewJoinOptProcCtx ctx = (SkewJoinOptProcCtx) procCtx;
parseContext = ctx.getpGraphContext();
JoinOperator joinOp = (JoinOperator)nd;
// This join has already been processed
if (ctx.getDoneJoins().contains(joinOp)) {
return null;
}
ctx.getDoneJoins().add(joinOp);
Operator currOp = joinOp;
boolean processSelect = false;
// Is there a select following
// Clone the select also. It is useful for a follow-on optimization where the union
// followed by a select star is completely removed.
if ((joinOp.getChildOperators().size() == 1) &&
(joinOp.getChildOperators().get(0) instanceof SelectOperator)) {
currOp = joinOp.getChildOperators().get(0);
processSelect = true;
}
List tableScanOpsForJoin = new ArrayList();
if (!getTableScanOpsForJoin(joinOp, tableScanOpsForJoin)) {
return null;
}
if ((tableScanOpsForJoin == null) || (tableScanOpsForJoin.isEmpty())) {
return null;
}
// Get the skewed values in all the tables
Map, List>> skewedValues =
getSkewedValues(joinOp, tableScanOpsForJoin);
// If there are no skewed values, nothing needs to be done
if (skewedValues == null || skewedValues.size() == 0) {
return null;
}
// After this optimization, the tree should be like:
// TS -> (FIL "skewed rows") * -> RS -
// \
// -> JOIN
// / \
// TS -> (FIL "skewed rows") * -> RS - \
// \
// -> UNION -> ..
// /
// TS -> (FIL "no skewed rows") * -> RS - /
// \ /
// -> JOIN
// /
// TS -> (FIL "no skewed rows") * -> RS -
//
// Create a clone of the operator
Operator currOpClone;
try {
currOpClone = currOp.clone();
insertRowResolvers(currOp, currOpClone, ctx);
} catch (CloneNotSupportedException e) {
LOG.debug("Operator tree could not be cloned");
return null;
}
JoinOperator joinOpClone;
if (processSelect) {
joinOpClone = (JoinOperator)(currOpClone.getParentOperators().get(0));
} else {
joinOpClone = (JoinOperator)currOpClone;
}
joinOpClone.getConf().cloneQBJoinTreeProps(joinOp.getConf());
parseContext.getJoinOps().add(joinOpClone);
List tableScanCloneOpsForJoin =
new ArrayList();
if (!getTableScanOpsForJoin(joinOpClone, tableScanCloneOpsForJoin)) {
LOG.debug("Operator tree not properly cloned!");
return null;
}
// Put the filter "skewed column = skewed keys" in op
// and "skewed columns != skewed keys" in selectOpClone
insertSkewFilter(tableScanOpsForJoin, skewedValues, true);
insertSkewFilter(tableScanCloneOpsForJoin, skewedValues, false);
// Update the topOps appropriately
Map> topOps = getTopOps(joinOpClone);
Map> origTopOps = parseContext.getTopOps();
for (Entry> topOp : topOps.entrySet()) {
TableScanOperator tso = (TableScanOperator) topOp.getValue();
String tabAlias = tso.getConf().getAlias();
int initCnt = 1;
String newAlias = "subquery" + initCnt + ":" + tabAlias;
while (origTopOps.containsKey(newAlias)) {
initCnt++;
newAlias = "subquery" + initCnt + ":" + tabAlias;
}
parseContext.getTopOps().put(newAlias, tso);
setUpAlias(joinOp, joinOpClone, tabAlias, newAlias, tso);
}
// Now do a union of the select operators: selectOp and selectOpClone
// Store the operator that follows the select after the join, we will be
// adding this as a child to the Union later
List> finalOps = currOp.getChildOperators();
currOp.setChildOperators(null);
currOpClone.setChildOperators(null);
// Make the union operator
List> oplist =
new ArrayList>();
oplist.add(currOp);
oplist.add(currOpClone);
Operator unionOp =
OperatorFactory.getAndMakeChild(
new UnionDesc(), new RowSchema(currOp.getSchema().getSignature()), oplist);
// Introduce a select after the union
List> unionList =
new ArrayList>();
unionList.add(unionOp);
Operator selectUnionOp =
OperatorFactory.getAndMakeChild(
new SelectDesc(true),
new RowSchema(unionOp.getSchema().getSignature()), unionList);
// add the finalOp after the union
selectUnionOp.setChildOperators(finalOps);
// replace the original selectOp in the parents with selectUnionOp
for (Operator finalOp : finalOps) {
finalOp.replaceParent(currOp, selectUnionOp);
}
return null;
}
/*
* Get the list of table scan operators for this join. A interface supportSkewJoinOptimization
* has been provided. Currently, it is only enabled for simple filters and selects.
*/
private boolean getTableScanOpsForJoin(
JoinOperator op,
List tsOps) {
for (Operator parent : op.getParentOperators()) {
if (!getTableScanOps(parent, tsOps)) {
return false;
}
}
return true;
}
private boolean getTableScanOps(
Operator op,
List tsOps) {
for (Operator parent : op.getParentOperators()) {
if (!parent.supportSkewJoinOptimization()) {
return false;
}
if (parent instanceof TableScanOperator) {
tsOps.add((TableScanOperator)parent);
} else if (!getTableScanOps(parent, tsOps)) {
return false;
}
}
return true;
}
/**
* Returns the skewed values in all the tables which are going to be scanned.
* If the join is on columns c1, c2 and c3 on tables T1 and T2,
* T1 is skewed on c1 and c4 with the skew values ((1,2),(3,4)),
* whereas T2 is skewed on c1, c2 with skew values ((5,6),(7,8)), the resulting
* map would be: <(c1) -> ((1), (3)), (c1,c2) -> ((5,6),(7,8))>
* @param op The join operator being optimized
* @param tableScanOpsForJoin table scan operators which are parents of the join operator
* @return map.
*/
private Map, List>>
getSkewedValues(
Operator op, List tableScanOpsForJoin) {
Map , List>> skewDataReturn =
new HashMap, List>>();
Map , List>> skewData =
new HashMap, List>>();
// The join keys are available in the reduceSinkOperators before join
for (Operator reduceSinkOp : op.getParentOperators()) {
ReduceSinkDesc rsDesc = ((ReduceSinkOperator) reduceSinkOp).getConf();
if (rsDesc.getKeyCols() != null) {
Table table = null;
// Find the skew information corresponding to the table
List skewedColumns = null;
List> skewedValueList = null;
// The join columns which are also skewed
List joinKeysSkewedCols =
new ArrayList();
// skewed Keys which intersect with join keys
List positionSkewedKeys = new ArrayList();
// Update the joinKeys appropriately.
for (ExprNodeDesc keyColDesc : rsDesc.getKeyCols()) {
ExprNodeColumnDesc keyCol = null;
// If the key column is not a column, then dont apply this optimization.
// This will be fixed as part of https://issues.apache.org/jira/browse/HIVE-3445
// for type conversion UDFs.
if (keyColDesc instanceof ExprNodeColumnDesc) {
keyCol = (ExprNodeColumnDesc) keyColDesc;
if (table == null) {
table = getTable(parseContext, reduceSinkOp, tableScanOpsForJoin);
skewedColumns =
table == null ? null : table.getSkewedColNames();
// No skew on the table to take care of
if ((skewedColumns == null) || (skewedColumns.isEmpty())) {
continue;
}
skewedValueList =
table == null ? null : table.getSkewedColValues();
}
int pos = skewedColumns.indexOf(keyCol.getColumn());
if ((pos >= 0) && (!positionSkewedKeys.contains(pos))) {
positionSkewedKeys.add(pos);
ExprNodeColumnDesc keyColClone = (ExprNodeColumnDesc) keyCol.clone();
keyColClone.setTabAlias(null);
joinKeysSkewedCols.add(new ExprNodeDescEqualityWrapper(keyColClone));
}
}
}
// If the skew keys match the join keys, then add it to the list
if ((skewedColumns != null) && (!skewedColumns.isEmpty())) {
if (!joinKeysSkewedCols.isEmpty()) {
// If the join keys matches the skewed keys, use the table skewed keys
List> skewedJoinValues;
if (skewedColumns.size() == positionSkewedKeys.size()) {
skewedJoinValues = skewedValueList;
}
else {
skewedJoinValues =
getSkewedJoinValues(skewedValueList, positionSkewedKeys);
}
List> oldSkewedJoinValues =
skewData.get(joinKeysSkewedCols);
if (oldSkewedJoinValues == null) {
oldSkewedJoinValues = new ArrayList>();
}
for (List skewValue : skewedJoinValues) {
if (!oldSkewedJoinValues.contains(skewValue)) {
oldSkewedJoinValues.add(skewValue);
}
}
skewData.put(joinKeysSkewedCols, oldSkewedJoinValues);
}
}
}
}
// convert skewData to contain ExprNodeDesc in the keys
for (Map.Entry, List>> mapEntry :
skewData.entrySet()) {
List skewedKeyJoinCols = new ArrayList();
for (ExprNodeDescEqualityWrapper key : mapEntry.getKey()) {
skewedKeyJoinCols.add(key.getExprNodeDesc());
}
skewDataReturn.put(skewedKeyJoinCols, mapEntry.getValue());
}
return skewDataReturn;
}
/**
* Get the table alias from the candidate table scans.
*/
private Table getTable(
ParseContext parseContext,
Operator op,
List tableScanOpsForJoin) {
while (true) {
if (op instanceof TableScanOperator) {
TableScanOperator tsOp = (TableScanOperator)op;
if (tableScanOpsForJoin.contains(tsOp)) {
return tsOp.getConf().getTableMetadata();
}
}
if ((op.getParentOperators() == null) || (op.getParentOperators().isEmpty()) ||
(op.getParentOperators().size() > 1)) {
return null;
}
op = op.getParentOperators().get(0);
}
}
/*
* If the skewedValues contains ((1,2,3),(4,5,6)), and the user is looking for
* positions (0,2), the result would be ((1,3),(4,6))
* Get the skewed key values that are part of the join key.
* @param skewedValuesList List of all the skewed values
* @param positionSkewedKeys the requested positions
* @return sub-list of skewed values with the positions present
*/
private List> getSkewedJoinValues(
List> skewedValueList, List positionSkewedKeys) {
List> skewedJoinValues = new ArrayList>();
for (List skewedValuesAllColumns : skewedValueList) {
List skewedValuesSpecifiedColumns = new ArrayList();
for (int pos : positionSkewedKeys) {
skewedValuesSpecifiedColumns.add(skewedValuesAllColumns.get(pos));
}
skewedJoinValues.add(skewedValuesSpecifiedColumns);
}
return skewedJoinValues;
}
/**
* Inserts a filter comparing the join keys with the skewed keys. If the table
* is skewed with values (k1, v1) and (k2, v2) on columns (key, value), then
* filter ((key=k1 AND value=v1) OR (key=k2 AND value=v2)) is inserted. If @skewed
* is false, a NOT is inserted before it.
* @param tableScanOpsForJoin table scans for which the filter will be inserted
* @param skewedValuesList the map of
* @param skewed True if we want skewedCol = skewedValue, false if we want
* not (skewedCol = skewedValue)
*/
private void insertSkewFilter(
List tableScanOpsForJoin,
Map, List>> skewedValuesList,
boolean skewed) {
ExprNodeDesc filterExpr = constructFilterExpr(skewedValuesList, skewed);
for (TableScanOperator tableScanOp : tableScanOpsForJoin) {
insertFilterOnTop(tableScanOp, filterExpr);
}
}
/**
* Inserts a filter below the table scan operator. Construct the filter
* from the filter expression provided.
* @param tableScanOp the table scan operators
* @param filterExpr the filter expression
*/
private void insertFilterOnTop(
TableScanOperator tableScanOp,
ExprNodeDesc filterExpr) {
// Get the top operator and it's child, all operators have a single parent
Operator currChild = tableScanOp.getChildOperators().get(0);
// Create the filter Operator and update the parents and children appropriately
tableScanOp.setChildOperators(null);
currChild.setParentOperators(null);
Operator filter = OperatorFactory.getAndMakeChild(
new FilterDesc(filterExpr, false),
new RowSchema(tableScanOp.getSchema().getSignature()),
tableScanOp);
OperatorFactory.makeChild(filter, currChild);
}
/**
* Construct the filter expression from the skewed keys and skewed values.
* If the skewed join keys are (k1), and (k1,k3) with the skewed values
* (1,2) and ((2,3),(4,5)) respectively, the filter expression would be:
* (k1=1) or (k1=2) or ((k1=2) and (k3=3)) or ((k1=4) and (k3=5)).
*/
private ExprNodeDesc constructFilterExpr(
Map, List>> skewedValuesMap,
boolean skewed) {
ExprNodeDesc finalExprNodeDesc = null;
try {
for (Map.Entry, List>> mapEntry :
skewedValuesMap.entrySet()) {
List keyCols = mapEntry.getKey();
List> skewedValuesList = mapEntry.getValue();
for (List skewedValues : skewedValuesList) {
int keyPos = 0;
ExprNodeDesc currExprNodeDesc = null;
// Make the following condition: all the values match for all the columns
for (String skewedValue : skewedValues) {
List children = new ArrayList();
// We have ensured that the keys are columns
ExprNodeColumnDesc keyCol = (ExprNodeColumnDesc) keyCols.get(keyPos).clone();
keyPos++;
children.add(keyCol);
// Convert the constants available as strings to the corresponding objects
children.add(createConstDesc(skewedValue, keyCol));
ExprNodeGenericFuncDesc expr = null;
// Create the equality condition
expr = ExprNodeGenericFuncDesc.newInstance(new GenericUDFOPEqual(), children);
if (currExprNodeDesc == null) {
currExprNodeDesc = expr;
} else {
// If there are previous nodes, then AND the current node with the previous one
List childrenAND = new ArrayList();
childrenAND.add(currExprNodeDesc);
childrenAND.add(expr);
currExprNodeDesc =
ExprNodeGenericFuncDesc.newInstance(new GenericUDFOPAnd(), childrenAND);
}
}
// If there are more than one skewed values,
// then OR the current node with the previous one
if (finalExprNodeDesc == null) {
finalExprNodeDesc = currExprNodeDesc;
} else {
List childrenOR = new ArrayList();
childrenOR.add(finalExprNodeDesc);
childrenOR.add(currExprNodeDesc);
finalExprNodeDesc =
ExprNodeGenericFuncDesc.newInstance(new GenericUDFOPOr(), childrenOR);
}
}
}
// Add a NOT operator in the beginning (this is for the cloned operator because we
// want the values which are not skewed
if (skewed == false) {
List childrenNOT = new ArrayList();
childrenNOT.add(finalExprNodeDesc);
finalExprNodeDesc =
ExprNodeGenericFuncDesc.newInstance(new GenericUDFOPNot(), childrenNOT);
}
} catch (UDFArgumentException e) {
// Ignore the exception because we are not comparing Long vs. String here.
// There should never be an exception
assert false;
}
return finalExprNodeDesc;
}
/**
* Converts the skewedValue available as a string in the metadata to the appropriate object
* by using the type of the column from the join key.
* @param skewedValue
* @param keyCol
* @return an expression node descriptor of the appropriate constant
*/
private ExprNodeConstantDesc createConstDesc(
String skewedValue, ExprNodeColumnDesc keyCol) {
ObjectInspector inputOI = TypeInfoUtils.getStandardJavaObjectInspectorFromTypeInfo(
TypeInfoFactory.stringTypeInfo);
ObjectInspector outputOI = TypeInfoUtils.getStandardJavaObjectInspectorFromTypeInfo(
keyCol.getTypeInfo());
Converter converter = ObjectInspectorConverters.getConverter(inputOI, outputOI);
Object skewedValueObject = converter.convert(skewedValue);
return new ExprNodeConstantDesc(keyCol.getTypeInfo(), skewedValueObject);
}
private Map> getTopOps(
Operator op) {
// Must be deterministic order map for consistent q-test output across
// Java versions
Map> topOps =
new LinkedHashMap>();
if (op.getParentOperators() == null || op.getParentOperators().size() == 0) {
topOps.put(((TableScanOperator)op).getConf().getAlias(), op);
} else {
for (Operator parent : op.getParentOperators()) {
if (parent != null) {
topOps.putAll(getTopOps(parent));
}
}
}
return topOps;
}
private void insertRowResolvers(
Operator op,
Operator opClone,
SkewJoinOptProcCtx ctx) {
if (op instanceof TableScanOperator) {
ctx.getCloneTSOpMap().put((TableScanOperator)opClone, (TableScanOperator)op);
}
List> parents = op.getParentOperators();
List> parentClones = opClone.getParentOperators();
if ((parents != null) && (!parents.isEmpty()) &&
(parentClones != null) && (!parentClones.isEmpty())) {
for (int pos = 0; pos < parents.size(); pos++) {
insertRowResolvers(parents.get(pos), parentClones.get(pos), ctx);
}
}
}
/**
* Set alias in the cloned join tree
*/
private static void setUpAlias(JoinOperator origin, JoinOperator cloned, String origAlias,
String newAlias, Operator topOp) {
cloned.getConf().getAliasToOpInfo().remove(origAlias);
cloned.getConf().getAliasToOpInfo().put(newAlias, topOp);
if (origin.getConf().getLeftAlias().equals(origAlias)) {
cloned.getConf().setLeftAlias(null);
cloned.getConf().setLeftAlias(newAlias);
}
replaceAlias(origin.getConf().getLeftAliases(), cloned.getConf().getLeftAliases(), origAlias, newAlias);
replaceAlias(origin.getConf().getRightAliases(), cloned.getConf().getRightAliases(), origAlias, newAlias);
replaceAlias(origin.getConf().getBaseSrc(), cloned.getConf().getBaseSrc(), origAlias, newAlias);
replaceAlias(origin.getConf().getMapAliases(), cloned.getConf().getMapAliases(), origAlias, newAlias);
replaceAlias(origin.getConf().getStreamAliases(), cloned.getConf().getStreamAliases(), origAlias, newAlias);
}
private static void replaceAlias(String[] origin, String[] cloned,
String alias, String newAlias) {
if (origin == null || cloned == null || origin.length != cloned.length) {
return;
}
for (int i = 0; i < origin.length; i++) {
if (origin[i].equals(alias)) {
cloned[i] = newAlias;
}
}
}
private static void replaceAlias(List origin, List cloned,
String alias, String newAlias) {
if (origin == null || cloned == null || origin.size() != cloned.size()) {
return;
}
for (int i = 0; i < origin.size(); i++) {
if (origin.get(i).equals(alias)) {
cloned.set(i, newAlias);
}
}
}
}
/* (non-Javadoc)
* @see org.apache.hadoop.hive.ql.optimizer.Transform#transform
* (org.apache.hadoop.hive.ql.parse.ParseContext)
*/
@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
Map opRules = new LinkedHashMap();
opRules.put(new RuleRegExp("R1", "TS%.*RS%JOIN%"), getSkewJoinProc(pctx));
SkewJoinOptProcCtx skewJoinOptProcCtx = new SkewJoinOptProcCtx(pctx);
// The dispatcher fires the processor corresponding to the closest matching
// rule and passes the context along
Dispatcher disp = new DefaultRuleDispatcher(
null, opRules, skewJoinOptProcCtx);
GraphWalker ogw = new DefaultGraphWalker(disp);
// Create a list of topop nodes
List topNodes = new ArrayList();
topNodes.addAll(pctx.getTopOps().values());
ogw.startWalking(topNodes, null);
return pctx;
}
private NodeProcessor getSkewJoinProc(ParseContext parseContext) {
return new SkewJoinProc(parseContext);
}
/**
* SkewJoinOptProcCtx.
*
*/
public static class SkewJoinOptProcCtx implements NodeProcessorCtx {
private ParseContext pGraphContext;
// set of joins already processed
private Set doneJoins;
private Map cloneTSOpMap;
public SkewJoinOptProcCtx(ParseContext pctx) {
this.pGraphContext = pctx;
doneJoins = new HashSet();
cloneTSOpMap = new HashMap();
}
public ParseContext getpGraphContext() {
return pGraphContext;
}
public void setPGraphContext(ParseContext graphContext) {
pGraphContext = graphContext;
}
public Set getDoneJoins() {
return doneJoins;
}
public void setDoneJoins(Set doneJoins) {
this.doneJoins = doneJoins;
}
public Map getCloneTSOpMap() {
return cloneTSOpMap;
}
public void setCloneTSOpMap(Map cloneTSOpMap) {
this.cloneTSOpMap = cloneTSOpMap;
}
}
}
