[
https://issues.apache.org/jira/browse/HIVE-23716?focusedWorklogId=463349&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-463349
]
ASF GitHub Bot logged work on HIVE-23716:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Jul/20 12:36
Start Date: 26/Jul/20 12:36
Worklog Time Spent: 10m
Work Description: maheshk114 commented on a change in pull request #1147:
URL: https://github.com/apache/hive/pull/1147#discussion_r460522312
##########
File path:
ql/src/java/org/apache/hadoop/hive/ql/exec/vector/mapjoin/VectorMapJoinAntiJoinLongOperator.java
##########
@@ -0,0 +1,315 @@
+/*
+ * 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 org.apache.hadoop.hive.ql.CompilationOpContext;
+import org.apache.hadoop.hive.ql.exec.JoinUtil;
+import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
+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.exec.vector.mapjoin.hashtable.VectorMapJoinLongHashSet;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.ql.plan.OperatorDesc;
+import org.apache.hadoop.hive.ql.plan.VectorDesc;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.Arrays;
+
+// TODO : Duplicate codes need to merge with semi join.
+// Single-Column Long hash table import.
+// Single-Column Long specific imports.
+
+/*
+ * Specialized class for doing a vectorized map join that is an anti join on a
Single-Column Long
+ * using a hash set.
+ */
+public class VectorMapJoinAntiJoinLongOperator extends
VectorMapJoinAntiJoinGenerateResultOperator {
+
+ private static final long serialVersionUID = 1L;
+ private static final String CLASS_NAME =
VectorMapJoinAntiJoinLongOperator.class.getName();
+ private static final Logger LOG = LoggerFactory.getLogger(CLASS_NAME);
+ protected String getLoggingPrefix() {
+ return super.getLoggingPrefix(CLASS_NAME);
+ }
+
+ // The above members are initialized by the constructor and must not be
+ // transient.
+
+ // The hash map for this specialized class.
+ private transient VectorMapJoinLongHashSet hashSet;
+
+ // Single-Column Long specific members.
+ // For integers, we have optional min/max filtering.
+ private transient boolean useMinMax;
+ private transient long min;
+ private transient long max;
+
+ // The column number for this one column join specialization.
+ private transient int singleJoinColumn;
+
+ // Pass-thru constructors.
+ /** Kryo ctor. */
+ protected VectorMapJoinAntiJoinLongOperator() {
+ super();
+ }
+
+ public VectorMapJoinAntiJoinLongOperator(CompilationOpContext ctx) {
+ super(ctx);
+ }
+
+ public VectorMapJoinAntiJoinLongOperator(CompilationOpContext ctx,
OperatorDesc conf,
+ VectorizationContext vContext,
VectorDesc vectorDesc) throws HiveException {
+ super(ctx, conf, vContext, vectorDesc);
+ }
+
+ // Process Single-Column Long Anti Join on a vectorized row batch.
+ @Override
+ protected void commonSetup() throws HiveException {
+ super.commonSetup();
+
+ // Initialize Single-Column Long members for this specialized class.
+ singleJoinColumn = bigTableKeyColumnMap[0];
+ }
+
+ @Override
+ public void hashTableSetup() throws HiveException {
+ super.hashTableSetup();
+
+ // Get our Single-Column Long hash set information for this specialized
class.
+ hashSet = (VectorMapJoinLongHashSet) vectorMapJoinHashTable;
+ useMinMax = hashSet.useMinMax();
+ if (useMinMax) {
+ min = hashSet.min();
+ max = hashSet.max();
+ }
+ }
+
+ @Override
+ public void processBatch(VectorizedRowBatch batch) throws HiveException {
+
+ try {
+ // (Currently none)
+ // antiPerBatchSetup(batch);
+
+ // For anti joins, we may apply the filter(s) now.
+ for(VectorExpression ve : bigTableFilterExpressions) {
+ ve.evaluate(batch);
+ }
+
+ final int inputLogicalSize = batch.size;
+ if (inputLogicalSize == 0) {
+ return;
+ }
+
+ // Perform any key expressions. Results will go into scratch columns.
+ if (bigTableKeyExpressions != null) {
+ for (VectorExpression ve : bigTableKeyExpressions) {
+ ve.evaluate(batch);
+ }
+ }
+
+ // The one join column for this specialized class.
+ LongColumnVector joinColVector = (LongColumnVector)
batch.cols[singleJoinColumn];
+ long[] vector = joinColVector.vector;
+
+ // Check single column for repeating.
+ boolean allKeyInputColumnsRepeating = joinColVector.isRepeating;
+
+ if (allKeyInputColumnsRepeating) {
+ // All key input columns are repeating. Generate key once. Lookup
once.
+ // Since the key is repeated, we must use entry 0 regardless of
selectedInUse.
+ JoinUtil.JoinResult joinResult;
+ if (!joinColVector.noNulls && joinColVector.isNull[0]) {
+ // For anti join, if the right side is null then its a match.
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else {
+ long key = vector[0];
+ if (useMinMax && (key < min || key > max)) {
+ // Out of range for whole batch. Its a match for anti join. We can
emit the row.
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else {
+ joinResult = hashSet.contains(key, hashSetResults[0]);
+ // reverse the join result for anti join.
+ if (joinResult == JoinUtil.JoinResult.NOMATCH) {
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else if (joinResult == JoinUtil.JoinResult.MATCH) {
+ joinResult = JoinUtil.JoinResult.NOMATCH;
+ }
+ }
+ }
+
+ // Common repeated join result processing.
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated
joinResult " + joinResult.name());
+ }
+ finishAntiRepeated(batch, joinResult, hashSetResults[0]);
+ } else {
+ // NOT Repeating.
+
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
+ }
+
+ // We remember any matching rows in matches / matchSize. At the end
of the loop,
+ // selected / batch.size will represent both matching and non-matching
rows for outer join.
+ // Only deferred rows will have been removed from selected.
+ int selected[] = batch.selected;
+ boolean selectedInUse = batch.selectedInUse;
+
+ int hashSetResultCount = 0;
+ int allMatchCount = 0;
+ int spillCount = 0;
+ long saveKey = 0;
+
+ // 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 < inputLogicalSize; logical++) {
+ int batchIndex = (selectedInUse ? selected[logical] : logical);
+
+ // Single-Column Long get key.
+ long currentKey;
+ boolean isNull;
+ if (!joinColVector.noNulls && joinColVector.isNull[batchIndex]) {
+ currentKey = 0;
+ isNull = true;
+ } else {
+ currentKey = vector[batchIndex];
+ isNull = false;
+ }
+
+ // Equal key series checking.
+ if (isNull || !haveSaveKey || currentKey != saveKey) {
+ // New key.
+ if (haveSaveKey) {
+ // Move on with our counts.
+ switch (saveJoinResult) {
+ case MATCH:
+ // We have extracted the existence from the hash set result,
so we don't keep it.
+ break;
+ case SPILL:
+ // We keep the hash set result for its spill information.
+ hashSetResultCount++;
+ break;
+ case NOMATCH:
+ break;
+ }
+ }
+
+ if (isNull) {
+ saveJoinResult = JoinUtil.JoinResult.MATCH;
+ haveSaveKey = false;
+ } else {
+ // Regardless of our matching result, we keep that information
to make multiple use
+ // of it for a possible series of equal keys.
+ haveSaveKey = true;
+ saveKey = currentKey;
+ if (useMinMax && (currentKey < min || currentKey > max)) {
+ // Key out of range for whole hash table, is a valid match for
anti join.
+ saveJoinResult = JoinUtil.JoinResult.NOMATCH;
+ } else {
+ saveJoinResult = hashSet.contains(currentKey,
hashSetResults[hashSetResultCount]);
+ }
+
+ // Reverse the match result for anti join.
+ if (saveJoinResult == JoinUtil.JoinResult.NOMATCH) {
+ saveJoinResult = JoinUtil.JoinResult.MATCH;
+ } else if (saveJoinResult == JoinUtil.JoinResult.MATCH) {
+ saveJoinResult = JoinUtil.JoinResult.NOMATCH;
+ }
+ }
+
+ // Common anti join result processing.
+ switch (saveJoinResult) {
+ case MATCH:
+ allMatchs[allMatchCount++] = batchIndex;
+ // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex,
CLASS_NAME + " MATCH isSingleValue " +
equalKeySeriesIsSingleValue[equalKeySeriesCount] + " currentKey " + currentKey);
+ break;
+
+ case SPILL:
+ spills[spillCount] = batchIndex;
+ spillHashMapResultIndices[spillCount] = hashSetResultCount;
+ spillCount++;
+ break;
+
+ case NOMATCH:
+ // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex,
CLASS_NAME + " NOMATCH" + " currentKey " + currentKey);
+ break;
+ }
+ } else {
+ // Series of equal keys.
Review comment:
done
##########
File path:
ql/src/java/org/apache/hadoop/hive/ql/exec/vector/mapjoin/VectorMapJoinAntiJoinLongOperator.java
##########
@@ -0,0 +1,315 @@
+/*
+ * 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 org.apache.hadoop.hive.ql.CompilationOpContext;
+import org.apache.hadoop.hive.ql.exec.JoinUtil;
+import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
+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.exec.vector.mapjoin.hashtable.VectorMapJoinLongHashSet;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.apache.hadoop.hive.ql.plan.OperatorDesc;
+import org.apache.hadoop.hive.ql.plan.VectorDesc;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.Arrays;
+
+// TODO : Duplicate codes need to merge with semi join.
+// Single-Column Long hash table import.
+// Single-Column Long specific imports.
+
+/*
+ * Specialized class for doing a vectorized map join that is an anti join on a
Single-Column Long
+ * using a hash set.
+ */
+public class VectorMapJoinAntiJoinLongOperator extends
VectorMapJoinAntiJoinGenerateResultOperator {
+
+ private static final long serialVersionUID = 1L;
+ private static final String CLASS_NAME =
VectorMapJoinAntiJoinLongOperator.class.getName();
+ private static final Logger LOG = LoggerFactory.getLogger(CLASS_NAME);
+ protected String getLoggingPrefix() {
+ return super.getLoggingPrefix(CLASS_NAME);
+ }
+
+ // The above members are initialized by the constructor and must not be
+ // transient.
+
+ // The hash map for this specialized class.
+ private transient VectorMapJoinLongHashSet hashSet;
+
+ // Single-Column Long specific members.
+ // For integers, we have optional min/max filtering.
+ private transient boolean useMinMax;
+ private transient long min;
+ private transient long max;
+
+ // The column number for this one column join specialization.
+ private transient int singleJoinColumn;
+
+ // Pass-thru constructors.
+ /** Kryo ctor. */
+ protected VectorMapJoinAntiJoinLongOperator() {
+ super();
+ }
+
+ public VectorMapJoinAntiJoinLongOperator(CompilationOpContext ctx) {
+ super(ctx);
+ }
+
+ public VectorMapJoinAntiJoinLongOperator(CompilationOpContext ctx,
OperatorDesc conf,
+ VectorizationContext vContext,
VectorDesc vectorDesc) throws HiveException {
+ super(ctx, conf, vContext, vectorDesc);
+ }
+
+ // Process Single-Column Long Anti Join on a vectorized row batch.
+ @Override
+ protected void commonSetup() throws HiveException {
+ super.commonSetup();
+
+ // Initialize Single-Column Long members for this specialized class.
+ singleJoinColumn = bigTableKeyColumnMap[0];
+ }
+
+ @Override
+ public void hashTableSetup() throws HiveException {
+ super.hashTableSetup();
+
+ // Get our Single-Column Long hash set information for this specialized
class.
+ hashSet = (VectorMapJoinLongHashSet) vectorMapJoinHashTable;
+ useMinMax = hashSet.useMinMax();
+ if (useMinMax) {
+ min = hashSet.min();
+ max = hashSet.max();
+ }
+ }
+
+ @Override
+ public void processBatch(VectorizedRowBatch batch) throws HiveException {
+
+ try {
+ // (Currently none)
+ // antiPerBatchSetup(batch);
+
+ // For anti joins, we may apply the filter(s) now.
+ for(VectorExpression ve : bigTableFilterExpressions) {
+ ve.evaluate(batch);
+ }
+
+ final int inputLogicalSize = batch.size;
+ if (inputLogicalSize == 0) {
+ return;
+ }
+
+ // Perform any key expressions. Results will go into scratch columns.
+ if (bigTableKeyExpressions != null) {
+ for (VectorExpression ve : bigTableKeyExpressions) {
+ ve.evaluate(batch);
+ }
+ }
+
+ // The one join column for this specialized class.
+ LongColumnVector joinColVector = (LongColumnVector)
batch.cols[singleJoinColumn];
+ long[] vector = joinColVector.vector;
+
+ // Check single column for repeating.
+ boolean allKeyInputColumnsRepeating = joinColVector.isRepeating;
+
+ if (allKeyInputColumnsRepeating) {
+ // All key input columns are repeating. Generate key once. Lookup
once.
+ // Since the key is repeated, we must use entry 0 regardless of
selectedInUse.
+ JoinUtil.JoinResult joinResult;
+ if (!joinColVector.noNulls && joinColVector.isNull[0]) {
+ // For anti join, if the right side is null then its a match.
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else {
+ long key = vector[0];
+ if (useMinMax && (key < min || key > max)) {
+ // Out of range for whole batch. Its a match for anti join. We can
emit the row.
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else {
+ joinResult = hashSet.contains(key, hashSetResults[0]);
+ // reverse the join result for anti join.
+ if (joinResult == JoinUtil.JoinResult.NOMATCH) {
+ joinResult = JoinUtil.JoinResult.MATCH;
+ } else if (joinResult == JoinUtil.JoinResult.MATCH) {
+ joinResult = JoinUtil.JoinResult.NOMATCH;
+ }
+ }
+ }
+
+ // Common repeated join result processing.
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated
joinResult " + joinResult.name());
+ }
+ finishAntiRepeated(batch, joinResult, hashSetResults[0]);
+ } else {
+ // NOT Repeating.
+
+ if (LOG.isDebugEnabled()) {
+ LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
+ }
+
+ // We remember any matching rows in matches / matchSize. At the end
of the loop,
+ // selected / batch.size will represent both matching and non-matching
rows for outer join.
+ // Only deferred rows will have been removed from selected.
+ int selected[] = batch.selected;
+ boolean selectedInUse = batch.selectedInUse;
+
+ int hashSetResultCount = 0;
+ int allMatchCount = 0;
+ int spillCount = 0;
+ long saveKey = 0;
+
+ // 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 < inputLogicalSize; logical++) {
+ int batchIndex = (selectedInUse ? selected[logical] : logical);
+
+ // Single-Column Long get key.
+ long currentKey;
+ boolean isNull;
+ if (!joinColVector.noNulls && joinColVector.isNull[batchIndex]) {
+ currentKey = 0;
+ isNull = true;
+ } else {
+ currentKey = vector[batchIndex];
+ isNull = false;
+ }
+
+ // Equal key series checking.
+ if (isNull || !haveSaveKey || currentKey != saveKey) {
+ // New key.
+ if (haveSaveKey) {
+ // Move on with our counts.
+ switch (saveJoinResult) {
+ case MATCH:
+ // We have extracted the existence from the hash set result,
so we don't keep it.
+ break;
+ case SPILL:
+ // We keep the hash set result for its spill information.
+ hashSetResultCount++;
+ break;
+ case NOMATCH:
+ break;
+ }
+ }
+
+ if (isNull) {
+ saveJoinResult = JoinUtil.JoinResult.MATCH;
+ haveSaveKey = false;
+ } else {
+ // Regardless of our matching result, we keep that information
to make multiple use
+ // of it for a possible series of equal keys.
+ haveSaveKey = true;
+ saveKey = currentKey;
+ if (useMinMax && (currentKey < min || currentKey > max)) {
+ // Key out of range for whole hash table, is a valid match for
anti join.
+ saveJoinResult = JoinUtil.JoinResult.NOMATCH;
+ } else {
+ saveJoinResult = hashSet.contains(currentKey,
hashSetResults[hashSetResultCount]);
+ }
+
+ // Reverse the match result for anti join.
Review comment:
done
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Issue Time Tracking
-------------------
Worklog Id: (was: 463349)
Time Spent: 12h 40m (was: 12.5h)
> Support Anti Join in Hive
> --------------------------
>
> Key: HIVE-23716
> URL: https://issues.apache.org/jira/browse/HIVE-23716
> Project: Hive
> Issue Type: Bug
> Reporter: mahesh kumar behera
> Assignee: mahesh kumar behera
> Priority: Major
> Labels: pull-request-available
> Attachments: HIVE-23716.01.patch
>
> Time Spent: 12h 40m
> Remaining Estimate: 0h
>
> Currently hive does not support Anti join. The query for anti join is
> converted to left outer join and null filter on right side join key is added
> to get the desired result. This is causing
> # Extra computation — The left outer join projects the redundant columns
> from right side. Along with that, filtering is done to remove the redundant
> rows. This is can be avoided in case of anti join as anti join will project
> only the required columns and rows from the left side table.
> # Extra shuffle — In case of anti join the duplicate records moved to join
> node can be avoided from the child node. This can reduce significant amount
> of data movement if the number of distinct rows( join keys) is significant.
> # Extra Memory Usage - In case of map based anti join , hash set is
> sufficient as just the key is required to check if the records matches the
> join condition. In case of left join, we need the key and the non key columns
> also and thus a hash table will be required.
> For a query like
> {code:java}
> select wr_order_number FROM web_returns LEFT JOIN web_sales ON
> wr_order_number = ws_order_number WHERE ws_order_number IS NULL;{code}
> The number of distinct ws_order_number in web_sales table in a typical 10TB
> TPCDS set up is just 10% of total records. So when we convert this query to
> anti join, instead of 7 billion rows, only 600 million rows are moved to join
> node.
> In the current patch, just one conversion is done. The pattern of
> project->filter->left-join is converted to project->anti-join. This will take
> care of sub queries with “not exists” clause. The queries with “not exists”
> are converted first to filter + left-join and then its converted to anti
> join. The queries with “not in” are not handled in the current patch.
> From execution side, both merge join and map join with vectorized execution
> is supported for anti join.
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