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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.exec.vector.mapjoin;
import java.io.IOException;
import java.util.Arrays;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.hive.ql.exec.JoinUtil;
import org.apache.hadoop.hive.ql.exec.vector.ColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorizationContext;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
// Multi-Key hash table import.
import org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinBytesHashMap;
// Multi-Key specific imports.
import org.apache.hadoop.hive.ql.exec.vector.VectorSerializeRow;
import org.apache.hadoop.hive.serde2.ByteStream.Output;
import org.apache.hadoop.hive.serde2.binarysortable.fast.BinarySortableSerializeWrite;
/*
* Specialized class for doing a vectorized map join that is an outer join on Multi-Key
* using a hash map.
*/
public class VectorMapJoinOuterMultiKeyOperator extends VectorMapJoinOuterGenerateResultOperator {
private static final long serialVersionUID = 1L;
private static final Log LOG = LogFactory.getLog(VectorMapJoinOuterMultiKeyOperator.class.getName());
private static final String CLASS_NAME = VectorMapJoinOuterMultiKeyOperator.class.getName();
// (none)
// The above members are initialized by the constructor and must not be
// transient.
//---------------------------------------------------------------------------
// The hash map for this specialized class.
private transient VectorMapJoinBytesHashMap hashMap;
//---------------------------------------------------------------------------
// Multi-Key specific members.
//
// Object that can take a set of columns in row in a vectorized row batch and serialized it.
private transient VectorSerializeRow keyVectorSerializeWrite;
// The BinarySortable serialization of the current key.
private transient Output currentKeyOutput;
// The BinarySortable serialization of the saved key for a possible series of equal keys.
private transient Output saveKeyOutput;
//---------------------------------------------------------------------------
// Pass-thru constructors.
//
public VectorMapJoinOuterMultiKeyOperator() {
super();
}
public VectorMapJoinOuterMultiKeyOperator(VectorizationContext vContext, OperatorDesc conf) throws HiveException {
super(vContext, conf);
}
//---------------------------------------------------------------------------
// Process Multi-Key Outer Join on a vectorized row batch.
//
@Override
public void process(Object row, int tag) throws HiveException {
try {
VectorizedRowBatch batch = (VectorizedRowBatch) row;
alias = (byte) tag;
if (needCommonSetup) {
// Our one time process method initialization.
commonSetup(batch);
/*
* Initialize Multi-Key members for this specialized class.
*/
keyVectorSerializeWrite = new VectorSerializeRow(
new BinarySortableSerializeWrite(bigTableKeyColumnMap.length));
keyVectorSerializeWrite.init(bigTableKeyTypeNames, bigTableKeyColumnMap);
currentKeyOutput = new Output();
saveKeyOutput = new Output();
needCommonSetup = false;
}
if (needHashTableSetup) {
// Setup our hash table specialization. It will be the first time the process
// method is called, or after a Hybrid Grace reload.
/*
* Get our Multi-Key hash map information for this specialized class.
*/
hashMap = (VectorMapJoinBytesHashMap) vectorMapJoinHashTable;
needHashTableSetup = false;
}
batchCounter++;
final int inputLogicalSize = batch.size;
if (inputLogicalSize == 0) {
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
}
return;
}
// Do the per-batch setup for an outer join.
outerPerBatchSetup(batch);
// For outer join, remember our input rows before ON expression filtering or before
// hash table matching so we can generate results for all rows (matching and non matching)
// later.
boolean inputSelectedInUse = batch.selectedInUse;
if (inputSelectedInUse) {
// if (!verifyMonotonicallyIncreasing(batch.selected, batch.size)) {
// throw new HiveException("batch.selected is not in sort order and unique");
// }
System.arraycopy(batch.selected, 0, inputSelected, 0, inputLogicalSize);
}
// Filtering for outer join just removes rows available for hash table matching.
boolean someRowsFilteredOut = false;
if (bigTableFilterExpressions.length > 0) {
// Since the input
for (VectorExpression ve : bigTableFilterExpressions) {
ve.evaluate(batch);
}
someRowsFilteredOut = (batch.size != inputLogicalSize);
if (LOG.isDebugEnabled()) {
if (batch.selectedInUse) {
if (inputSelectedInUse) {
LOG.debug(CLASS_NAME +
" inputSelected " + intArrayToRangesString(inputSelected, inputLogicalSize) +
" filtered batch.selected " + intArrayToRangesString(batch.selected, batch.size));
} else {
LOG.debug(CLASS_NAME +
" inputLogicalSize " + inputLogicalSize +
" filtered batch.selected " + intArrayToRangesString(batch.selected, batch.size));
}
}
}
}
// Perform any key expressions. Results will go into scratch columns.
if (bigTableKeyExpressions != null) {
for (VectorExpression ve : bigTableKeyExpressions) {
ve.evaluate(batch);
}
}
/*
* Multi-Key specific declarations.
*/
// None.
/*
* Multi-Key Long check for repeating.
*/
// If all BigTable input columns to key expressions are isRepeating, then
// calculate key once; lookup once.
// Also determine if any nulls are present since for a join that means no match.
boolean allKeyInputColumnsRepeating;
boolean someKeyInputColumnIsNull = false; // Only valid if allKeyInputColumnsRepeating is true.
if (bigTableKeyColumnMap.length == 0) {
allKeyInputColumnsRepeating = false;
} else {
allKeyInputColumnsRepeating = true;
for (int i = 0; i < bigTableKeyColumnMap.length; i++) {
ColumnVector colVector = batch.cols[bigTableKeyColumnMap[i]];
if (!colVector.isRepeating) {
allKeyInputColumnsRepeating = false;
break;
}
if (!colVector.noNulls && colVector.isNull[0]) {
someKeyInputColumnIsNull = true;
}
}
}
if (allKeyInputColumnsRepeating) {
/*
* Repeating.
*/
// All key input columns are repeating. Generate key once. Lookup once.
// Since the key is repeated, we must use entry 0 regardless of selectedInUse.
/*
* Multi-Key specific repeated lookup.
*/
JoinUtil.JoinResult joinResult;
if (batch.size == 0) {
// Whole repeated key batch was filtered out.
joinResult = JoinUtil.JoinResult.NOMATCH;
} else if (someKeyInputColumnIsNull) {
// Any (repeated) null key column is no match for whole batch.
joinResult = JoinUtil.JoinResult.NOMATCH;
} else {
// All key input columns are repeating. Generate key once. Lookup once.
keyVectorSerializeWrite.setOutput(currentKeyOutput);
keyVectorSerializeWrite.serializeWrite(batch, 0);
byte[] keyBytes = currentKeyOutput.getData();
int keyLength = currentKeyOutput.getLength();
joinResult = hashMap.lookup(keyBytes, 0, keyLength, hashMapResults[0]);
}
/*
* Common repeated join result processing.
*/
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
}
finishOuterRepeated(batch, joinResult, hashMapResults[0], someRowsFilteredOut,
inputSelectedInUse, inputLogicalSize);
} else {
/*
* NOT Repeating.
*/
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
}
int selected[] = batch.selected;
boolean selectedInUse = batch.selectedInUse;
int hashMapResultCount = 0;
int allMatchCount = 0;
int equalKeySeriesCount = 0;
int spillCount = 0;
boolean atLeastOneNonMatch = someRowsFilteredOut;
/*
* Multi-Key specific variables.
*/
Output temp;
// We optimize performance by only looking up the first key in a series of equal keys.
boolean haveSaveKey = false;
JoinUtil.JoinResult saveJoinResult = JoinUtil.JoinResult.NOMATCH;
// Logical loop over the rows in the batch since the batch may have selected in use.
for (int logical = 0; logical < batch.size; logical++) {
int batchIndex = (selectedInUse ? selected[logical] : logical);
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, taskName + ", " + getOperatorId() + " candidate " + CLASS_NAME + " batch");
/*
* Multi-Key outer null detection.
*/
// Generate binary sortable key for current row in vectorized row batch.
keyVectorSerializeWrite.setOutput(currentKeyOutput);
boolean isNull = keyVectorSerializeWrite.serializeWrite(batch, batchIndex);
if (isNull) {
// Have that the NULL does not interfere with the current equal key series, if there
// is one. We do not set saveJoinResult.
//
// Let a current MATCH equal key series keep going, or
// Let a current SPILL equal key series keep going, or
// Let a current NOMATCH keep not matching.
atLeastOneNonMatch = true;
// LOG.debug(CLASS_NAME + " logical " + logical + " batchIndex " + batchIndex + " NULL");
} else {
/*
* Multi-Key outer get key.
*/
// Generated earlier to get possible null(s).
/*
* Equal key series checking.
*/
if (!haveSaveKey || !saveKeyOutput.arraysEquals(currentKeyOutput)) {
// New key.
if (haveSaveKey) {
// Move on with our counts.
switch (saveJoinResult) {
case MATCH:
hashMapResultCount++;
equalKeySeriesCount++;
break;
case SPILL:
hashMapResultCount++;
break;
case NOMATCH:
break;
}
}
// Regardless of our matching result, we keep that information to make multiple use
// of it for a possible series of equal keys.
haveSaveKey = true;
/*
* Multi-Key specific save key.
*/
temp = saveKeyOutput;
saveKeyOutput = currentKeyOutput;
currentKeyOutput = temp;
/*
* Multi-Key specific lookup key.
*/
byte[] keyBytes = saveKeyOutput.getData();
int keyLength = saveKeyOutput.getLength();
saveJoinResult = hashMap.lookup(keyBytes, 0, keyLength, hashMapResults[hashMapResultCount]);
/*
* Common outer join result processing.
*/
switch (saveJoinResult) {
case MATCH:
equalKeySeriesHashMapResultIndices[equalKeySeriesCount] = hashMapResultCount;
equalKeySeriesAllMatchIndices[equalKeySeriesCount] = allMatchCount;
equalKeySeriesIsSingleValue[equalKeySeriesCount] = hashMapResults[hashMapResultCount].isSingleRow();
equalKeySeriesDuplicateCounts[equalKeySeriesCount] = 1;
allMatchs[allMatchCount++] = batchIndex;
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " MATCH isSingleValue " + equalKeySeriesIsSingleValue[equalKeySeriesCount] + " currentKey " + currentKey);
break;
case SPILL:
spills[spillCount] = batchIndex;
spillHashMapResultIndices[spillCount] = hashMapResultCount;
spillCount++;
break;
case NOMATCH:
atLeastOneNonMatch = true;
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH" + " currentKey " + currentKey);
break;
}
} else {
// LOG.debug(CLASS_NAME + " logical " + logical + " batchIndex " + batchIndex + " Key Continues " + saveKey + " " + saveJoinResult.name());
// Series of equal keys.
switch (saveJoinResult) {
case MATCH:
equalKeySeriesDuplicateCounts[equalKeySeriesCount]++;
allMatchs[allMatchCount++] = batchIndex;
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " MATCH duplicate");
break;
case SPILL:
spills[spillCount] = batchIndex;
spillHashMapResultIndices[spillCount] = hashMapResultCount;
spillCount++;
break;
case NOMATCH:
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH duplicate");
break;
}
}
// if (!verifyMonotonicallyIncreasing(allMatchs, allMatchCount)) {
// throw new HiveException("allMatchs is not in sort order and unique");
// }
}
}
if (haveSaveKey) {
// Update our counts for the last key.
switch (saveJoinResult) {
case MATCH:
hashMapResultCount++;
equalKeySeriesCount++;
break;
case SPILL:
hashMapResultCount++;
break;
case NOMATCH:
break;
}
}
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter +
" allMatchs " + intArrayToRangesString(allMatchs,allMatchCount) +
" equalKeySeriesHashMapResultIndices " + intArrayToRangesString(equalKeySeriesHashMapResultIndices, equalKeySeriesCount) +
" equalKeySeriesAllMatchIndices " + intArrayToRangesString(equalKeySeriesAllMatchIndices, equalKeySeriesCount) +
" equalKeySeriesIsSingleValue " + Arrays.toString(Arrays.copyOfRange(equalKeySeriesIsSingleValue, 0, equalKeySeriesCount)) +
" equalKeySeriesDuplicateCounts " + Arrays.toString(Arrays.copyOfRange(equalKeySeriesDuplicateCounts, 0, equalKeySeriesCount)) +
" atLeastOneNonMatch " + atLeastOneNonMatch +
" inputSelectedInUse " + inputSelectedInUse +
" inputLogicalSize " + inputLogicalSize +
" spills " + intArrayToRangesString(spills, spillCount) +
" spillHashMapResultIndices " + intArrayToRangesString(spillHashMapResultIndices, spillCount) +
" hashMapResults " + Arrays.toString(Arrays.copyOfRange(hashMapResults, 0, hashMapResultCount)));
}
// We will generate results for all matching and non-matching rows.
finishOuter(batch,
allMatchCount, equalKeySeriesCount, atLeastOneNonMatch,
inputSelectedInUse, inputLogicalSize,
spillCount, hashMapResultCount);
}
if (batch.size > 0) {
// Forward any remaining selected rows.
forwardBigTableBatch(batch);
}
} catch (IOException e) {
throw new HiveException(e);
} catch (Exception e) {
throw new HiveException(e);
}
}
}
