Examples with VectorMapJoinHashTableResult org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult used on opensource projects

Example 1 with VectorMapJoinHashTableResult

use of org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult in project hive by apache.

the class VectorMapJoinLeftSemiMultiKeyOperator method process.

//---------------------------------------------------------------------------
// Process Multi-Key Left-Semi 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(bigTableKeyTypeInfos, 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 set information for this specialized class.
         */
            hashSet = (VectorMapJoinBytesHashSet) vectorMapJoinHashTable;
            needHashTableSetup = false;
        }
        batchCounter++;
        // For left semi joins, we may apply the filter(s) now.
        for (VectorExpression ve : bigTableFilterExpressions) {
            ve.evaluate(batch);
        }
        final int inputLogicalSize = batch.size;
        if (inputLogicalSize == 0) {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
            }
            return;
        }
        // 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.
        boolean allKeyInputColumnsRepeating;
        if (bigTableKeyColumnMap.length == 0) {
            allKeyInputColumnsRepeating = false;
        } else {
            allKeyInputColumnsRepeating = true;
            for (int i = 0; i < bigTableKeyColumnMap.length; i++) {
                if (!batch.cols[bigTableKeyColumnMap[i]].isRepeating) {
                    allKeyInputColumnsRepeating = false;
                    break;
                }
            }
        }
        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.
         */
            keyVectorSerializeWrite.setOutput(currentKeyOutput);
            keyVectorSerializeWrite.serializeWrite(batch, 0);
            JoinUtil.JoinResult joinResult;
            if (keyVectorSerializeWrite.getHasAnyNulls()) {
                joinResult = JoinUtil.JoinResult.NOMATCH;
            } else {
                byte[] keyBytes = currentKeyOutput.getData();
                int keyLength = currentKeyOutput.getLength();
                // LOG.debug(CLASS_NAME + " processOp all " + displayBytes(keyBytes, 0, keyLength));
                joinResult = hashSet.contains(keyBytes, 0, keyLength, hashSetResults[0]);
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
            }
            finishLeftSemiRepeated(batch, joinResult, hashSetResults[0]);
        } else {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
            }
            // We remember any matching rows in matchs / 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;
            /*
         * 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 < inputLogicalSize; logical++) {
                int batchIndex = (selectedInUse ? selected[logical] : logical);
                /*
           * Multi-Key get key.
           */
                // Generate binary sortable key for current row in vectorized row batch.
                keyVectorSerializeWrite.setOutput(currentKeyOutput);
                keyVectorSerializeWrite.serializeWrite(batch, batchIndex);
                boolean isAnyNull = keyVectorSerializeWrite.getHasAnyNulls();
                if (isAnyNull || !haveSaveKey || !saveKeyOutput.arraysEquals(currentKeyOutput)) {
                    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 (isAnyNull) {
                        saveJoinResult = JoinUtil.JoinResult.NOMATCH;
                        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;
                        /*
               * Multi-Key specific save key and lookup.
               */
                        temp = saveKeyOutput;
                        saveKeyOutput = currentKeyOutput;
                        currentKeyOutput = temp;
                        /*
               * Multi-key specific lookup key.
               */
                        byte[] keyBytes = saveKeyOutput.getData();
                        int keyLength = saveKeyOutput.getLength();
                        saveJoinResult = hashSet.contains(keyBytes, 0, keyLength, hashSetResults[hashSetResultCount]);
                    }
                    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 {
                    switch(saveJoinResult) {
                        case MATCH:
                            allMatchs[allMatchCount++] = batchIndex;
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " MATCH duplicate");
                            break;
                        case SPILL:
                            spills[spillCount] = batchIndex;
                            spillHashMapResultIndices[spillCount] = hashSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH duplicate");
                            break;
                    }
                }
            }
            if (haveSaveKey) {
                // Update our counts for the last key.
                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 (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " allMatchs " + intArrayToRangesString(allMatchs, allMatchCount) + " spills " + intArrayToRangesString(spills, spillCount) + " spillHashMapResultIndices " + intArrayToRangesString(spillHashMapResultIndices, spillCount) + " hashMapResults " + Arrays.toString(Arrays.copyOfRange(hashSetResults, 0, hashSetResultCount)));
            }
            finishLeftSemi(batch, allMatchCount, spillCount, (VectorMapJoinHashTableResult[]) hashSetResults);
        }
        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);
    }
}

Example 2 with VectorMapJoinHashTableResult

use of org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult in project hive by apache.

the class VectorMapJoinLeftSemiStringOperator method process.

//---------------------------------------------------------------------------
// Process Single-Column String Left-Semi 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 Single-Column String members for this specialized class.
         */
            singleJoinColumn = bigTableKeyColumnMap[0];
            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 Single-Column String hash set information for this specialized class.
         */
            hashSet = (VectorMapJoinBytesHashSet) vectorMapJoinHashTable;
            needHashTableSetup = false;
        }
        batchCounter++;
        // For left semi joins, we may apply the filter(s) now.
        for (VectorExpression ve : bigTableFilterExpressions) {
            ve.evaluate(batch);
        }
        final int inputLogicalSize = batch.size;
        if (inputLogicalSize == 0) {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
            }
            return;
        }
        // Perform any key expressions.  Results will go into scratch columns.
        if (bigTableKeyExpressions != null) {
            for (VectorExpression ve : bigTableKeyExpressions) {
                ve.evaluate(batch);
            }
        }
        /*
       * Single-Column String specific declarations.
       */
        // The one join column for this specialized class.
        BytesColumnVector joinColVector = (BytesColumnVector) batch.cols[singleJoinColumn];
        byte[][] vector = joinColVector.vector;
        int[] start = joinColVector.start;
        int[] length = joinColVector.length;
        /*
       * Single-Column Long check for repeating.
       */
        // Check single column for repeating.
        boolean allKeyInputColumnsRepeating = joinColVector.isRepeating;
        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.
            /*
         * Single-Column String specific repeated lookup.
         */
            JoinUtil.JoinResult joinResult;
            if (!joinColVector.noNulls && joinColVector.isNull[0]) {
                joinResult = JoinUtil.JoinResult.NOMATCH;
            } else {
                byte[] keyBytes = vector[0];
                int keyStart = start[0];
                int keyLength = length[0];
                joinResult = hashSet.contains(keyBytes, keyStart, keyLength, hashSetResults[0]);
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
            }
            finishLeftSemiRepeated(batch, joinResult, hashSetResults[0]);
        } else {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
            }
            // We remember any matching rows in matchs / 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;
            /*
         * Single-Column String specific variables.
         */
            int saveKeyBatchIndex = -1;
            // 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 String get key.
           */
                // Implicit -- use batchIndex.
                boolean isNull = !joinColVector.noNulls && joinColVector.isNull[batchIndex];
                if (isNull || !haveSaveKey || StringExpr.equal(vector[saveKeyBatchIndex], start[saveKeyBatchIndex], length[saveKeyBatchIndex], vector[batchIndex], start[batchIndex], length[batchIndex]) == false) {
                    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.NOMATCH;
                        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;
                        /*
               * Single-Column String specific save key and lookup.
               */
                        saveKeyBatchIndex = batchIndex;
                        /*
               * Single-Column String specific lookup key.
               */
                        byte[] keyBytes = vector[batchIndex];
                        int keyStart = start[batchIndex];
                        int keyLength = length[batchIndex];
                        saveJoinResult = hashSet.contains(keyBytes, keyStart, keyLength, hashSetResults[hashSetResultCount]);
                    }
                    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 {
                    switch(saveJoinResult) {
                        case MATCH:
                            allMatchs[allMatchCount++] = batchIndex;
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " MATCH duplicate");
                            break;
                        case SPILL:
                            spills[spillCount] = batchIndex;
                            spillHashMapResultIndices[spillCount] = hashSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH duplicate");
                            break;
                    }
                }
            }
            if (haveSaveKey) {
                // Update our counts for the last key.
                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 (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " allMatchs " + intArrayToRangesString(allMatchs, allMatchCount) + " spills " + intArrayToRangesString(spills, spillCount) + " spillHashMapResultIndices " + intArrayToRangesString(spillHashMapResultIndices, spillCount) + " hashMapResults " + Arrays.toString(Arrays.copyOfRange(hashSetResults, 0, hashSetResultCount)));
            }
            finishLeftSemi(batch, allMatchCount, spillCount, (VectorMapJoinHashTableResult[]) hashSetResults);
        }
        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);
    }
}

Example 3 with VectorMapJoinHashTableResult

use of org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult in project hive by apache.

the class VectorMapJoinOuterGenerateResultOperator method finishOuter.

/**
   * Generate the outer join output results for one vectorized row batch.
   *
   * @param batch
   *          The big table batch with any matching and any non matching rows both as
   *          selected in use.
   * @param allMatchCount
   *          Number of matches in allMatchs.
   * @param equalKeySeriesCount
   *          Number of single value matches.
   * @param atLeastOneNonMatch
   *          Whether at least one row was a non-match.
   * @param inputSelectedInUse
   *          A copy of the batch's selectedInUse flag on input to the process method.
   * @param inputLogicalSize
   *          The batch's size on input to the process method.
   * @param spillCount
   *          Number of spills in spills.
   * @param hashMapResultCount
   *          Number of entries in hashMapResults.
   */
public void finishOuter(VectorizedRowBatch batch, int allMatchCount, int equalKeySeriesCount, boolean atLeastOneNonMatch, boolean inputSelectedInUse, int inputLogicalSize, int spillCount, int hashMapResultCount) throws IOException, HiveException {
    // Get rid of spills before we start modifying the batch.
    if (spillCount > 0) {
        spillHashMapBatch(batch, (VectorMapJoinHashTableResult[]) hashMapResults, spills, spillHashMapResultIndices, spillCount);
    }
    int noMatchCount = 0;
    if (spillCount > 0) {
        // Subtract the spills to get all match and non-match rows.
        int nonSpillCount = subtractFromInputSelected(inputSelectedInUse, inputLogicalSize, spills, spillCount, nonSpills);
        if (isLogDebugEnabled) {
            LOG.debug("finishOuter spillCount > 0" + " nonSpills " + intArrayToRangesString(nonSpills, nonSpillCount));
        }
        // Big table value expressions apply to ALL matching and non-matching rows.
        if (bigTableValueExpressions != null) {
            doValueExpr(batch, nonSpills, nonSpillCount);
        }
        if (atLeastOneNonMatch) {
            noMatchCount = subtract(nonSpills, nonSpillCount, allMatchs, allMatchCount, noMatchs);
            if (isLogDebugEnabled) {
                LOG.debug("finishOuter spillCount > 0" + " noMatchs " + intArrayToRangesString(noMatchs, noMatchCount));
            }
        }
    } else {
        // Run value expressions over original (whole) input batch.
        doValueExprOnInputSelected(batch, inputSelectedInUse, inputLogicalSize);
        if (atLeastOneNonMatch) {
            noMatchCount = subtractFromInputSelected(inputSelectedInUse, inputLogicalSize, allMatchs, allMatchCount, noMatchs);
            if (isLogDebugEnabled) {
                LOG.debug("finishOuter spillCount == 0" + " noMatchs " + intArrayToRangesString(noMatchs, noMatchCount));
            }
        }
    }
    // overflow batch.
    if (allMatchCount > 0) {
        int numSel = 0;
        for (int i = 0; i < equalKeySeriesCount; i++) {
            int hashMapResultIndex = equalKeySeriesHashMapResultIndices[i];
            VectorMapJoinHashMapResult hashMapResult = hashMapResults[hashMapResultIndex];
            int allMatchesIndex = equalKeySeriesAllMatchIndices[i];
            boolean isSingleValue = equalKeySeriesIsSingleValue[i];
            int duplicateCount = equalKeySeriesDuplicateCounts[i];
            if (isSingleValue) {
                numSel = generateHashMapResultSingleValue(batch, hashMapResult, allMatchs, allMatchesIndex, duplicateCount, numSel);
            } else {
                generateHashMapResultMultiValue(batch, hashMapResult, allMatchs, allMatchesIndex, duplicateCount);
            }
        }
        // The number of single value rows that were generated in the big table batch.
        batch.size = numSel;
        batch.selectedInUse = true;
        if (isLogDebugEnabled) {
            LOG.debug("finishOuter allMatchCount > 0" + " batch.selected " + intArrayToRangesString(batch.selected, batch.size));
        }
    } else {
        batch.size = 0;
    }
    if (noMatchCount > 0) {
        if (batch.size > 0) {
            generateOuterNulls(batch, noMatchs, noMatchCount);
            // Merge noMatchs and (match) selected.
            int mergeCount = sortMerge(noMatchs, noMatchCount, batch.selected, batch.size, merged);
            if (isLogDebugEnabled) {
                LOG.debug("finishOuter noMatchCount > 0 && batch.size > 0" + " merged " + intArrayToRangesString(merged, mergeCount));
            }
            System.arraycopy(merged, 0, batch.selected, 0, mergeCount);
            batch.size = mergeCount;
            batch.selectedInUse = true;
        } else {
            // We can use the whole batch for output of no matches.
            generateOuterNullsRepeatedAll(batch);
            System.arraycopy(noMatchs, 0, batch.selected, 0, noMatchCount);
            batch.size = noMatchCount;
            batch.selectedInUse = true;
            if (isLogDebugEnabled) {
                LOG.debug("finishOuter noMatchCount > 0 && batch.size == 0" + " batch.selected " + intArrayToRangesString(batch.selected, batch.size));
            }
        }
    }
}

Example 4 with VectorMapJoinHashTableResult

use of org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult in project hive by apache.

the class VectorMapJoinInnerBigOnlyMultiKeyOperator method process.

//---------------------------------------------------------------------------
// Process Multi-Key Inner Big-Only 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(bigTableKeyTypeInfos, 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 multi-set information for this specialized class.
         */
            hashMultiSet = (VectorMapJoinBytesHashMultiSet) vectorMapJoinHashTable;
            needHashTableSetup = false;
        }
        batchCounter++;
        // For inner joins, we may apply the filter(s) now.
        for (VectorExpression ve : bigTableFilterExpressions) {
            ve.evaluate(batch);
        }
        final int inputLogicalSize = batch.size;
        if (inputLogicalSize == 0) {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
            }
            return;
        }
        // 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 check for repeating.
       */
        // If all BigTable input columns to key expressions are isRepeating, then
        // calculate key once; lookup once.
        boolean allKeyInputColumnsRepeating;
        if (bigTableKeyColumnMap.length == 0) {
            allKeyInputColumnsRepeating = false;
        } else {
            allKeyInputColumnsRepeating = true;
            for (int i = 0; i < bigTableKeyColumnMap.length; i++) {
                if (!batch.cols[bigTableKeyColumnMap[i]].isRepeating) {
                    allKeyInputColumnsRepeating = false;
                    break;
                }
            }
        }
        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.
         */
            keyVectorSerializeWrite.setOutput(currentKeyOutput);
            keyVectorSerializeWrite.serializeWrite(batch, 0);
            JoinUtil.JoinResult joinResult;
            if (keyVectorSerializeWrite.getHasAnyNulls()) {
                joinResult = JoinUtil.JoinResult.NOMATCH;
            } else {
                byte[] keyBytes = currentKeyOutput.getData();
                int keyLength = currentKeyOutput.getLength();
                joinResult = hashMultiSet.contains(keyBytes, 0, keyLength, hashMultiSetResults[0]);
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
            }
            finishInnerBigOnlyRepeated(batch, joinResult, hashMultiSetResults[0]);
        } else {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
            }
            // We remember any matching rows in matchs / 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 hashMultiSetResultCount = 0;
            int allMatchCount = 0;
            int equalKeySeriesCount = 0;
            int spillCount = 0;
            /*
         * 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 < inputLogicalSize; logical++) {
                int batchIndex = (selectedInUse ? selected[logical] : logical);
                /*
           * Multi-Key get key.
           */
                // Generate binary sortable key for current row in vectorized row batch.
                keyVectorSerializeWrite.setOutput(currentKeyOutput);
                keyVectorSerializeWrite.serializeWrite(batch, batchIndex);
                boolean isAnyNulls = keyVectorSerializeWrite.getHasAnyNulls();
                if (isAnyNulls || !haveSaveKey || !saveKeyOutput.arraysEquals(currentKeyOutput)) {
                    if (haveSaveKey) {
                        // Move on with our counts.
                        switch(saveJoinResult) {
                            case MATCH:
                                // We have extracted the count from the hash multi-set result, so we don't keep it.
                                equalKeySeriesCount++;
                                break;
                            case SPILL:
                                // We keep the hash multi-set result for its spill information.
                                hashMultiSetResultCount++;
                                break;
                            case NOMATCH:
                                break;
                        }
                    }
                    if (isAnyNulls) {
                        saveJoinResult = JoinUtil.JoinResult.NOMATCH;
                        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;
                        /*
               * Multi-Key specific save key.
               */
                        temp = saveKeyOutput;
                        saveKeyOutput = currentKeyOutput;
                        currentKeyOutput = temp;
                        /*
               * Single-Column Long specific lookup key.
               */
                        byte[] keyBytes = saveKeyOutput.getData();
                        int keyLength = saveKeyOutput.getLength();
                        saveJoinResult = hashMultiSet.contains(keyBytes, 0, keyLength, hashMultiSetResults[hashMultiSetResultCount]);
                    }
                    switch(saveJoinResult) {
                        case MATCH:
                            equalKeySeriesValueCounts[equalKeySeriesCount] = hashMultiSetResults[hashMultiSetResultCount].count();
                            equalKeySeriesAllMatchIndices[equalKeySeriesCount] = allMatchCount;
                            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] = hashMultiSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH" + " currentKey " + currentKey);
                            break;
                    }
                } else {
                    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] = hashMultiSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH duplicate");
                            break;
                    }
                }
            }
            if (haveSaveKey) {
                // Update our counts for the last key.
                switch(saveJoinResult) {
                    case MATCH:
                        // We have extracted the count from the hash multi-set result, so we don't keep it.
                        equalKeySeriesCount++;
                        break;
                    case SPILL:
                        // We keep the hash multi-set result for its spill information.
                        hashMultiSetResultCount++;
                        break;
                    case NOMATCH:
                        break;
                }
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " allMatchs " + intArrayToRangesString(allMatchs, allMatchCount) + " equalKeySeriesValueCounts " + longArrayToRangesString(equalKeySeriesValueCounts, equalKeySeriesCount) + " equalKeySeriesAllMatchIndices " + intArrayToRangesString(equalKeySeriesAllMatchIndices, equalKeySeriesCount) + " equalKeySeriesDuplicateCounts " + intArrayToRangesString(equalKeySeriesDuplicateCounts, equalKeySeriesCount) + " spills " + intArrayToRangesString(spills, spillCount) + " spillHashMapResultIndices " + intArrayToRangesString(spillHashMapResultIndices, spillCount) + " hashMapResults " + Arrays.toString(Arrays.copyOfRange(hashMultiSetResults, 0, hashMultiSetResultCount)));
            }
            finishInnerBigOnly(batch, allMatchCount, equalKeySeriesCount, spillCount, (VectorMapJoinHashTableResult[]) hashMultiSetResults, hashMultiSetResultCount);
        }
        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);
    }
}

Example 5 with VectorMapJoinHashTableResult

use of org.apache.hadoop.hive.ql.exec.vector.mapjoin.hashtable.VectorMapJoinHashTableResult in project hive by apache.

the class VectorMapJoinInnerBigOnlyLongOperator method process.

//---------------------------------------------------------------------------
// Process Single-Column Long Inner Big-Only 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 Single-Column Long members for this specialized class.
         */
            singleJoinColumn = bigTableKeyColumnMap[0];
            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 Single-Column Long hash multi-set information for this specialized class.
         */
            hashMultiSet = (VectorMapJoinLongHashMultiSet) vectorMapJoinHashTable;
            useMinMax = hashMultiSet.useMinMax();
            if (useMinMax) {
                min = hashMultiSet.min();
                max = hashMultiSet.max();
            }
            needHashTableSetup = false;
        }
        batchCounter++;
        // For inner joins, we may apply the filter(s) now.
        for (VectorExpression ve : bigTableFilterExpressions) {
            ve.evaluate(batch);
        }
        final int inputLogicalSize = batch.size;
        if (inputLogicalSize == 0) {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
            }
            return;
        }
        // Perform any key expressions.  Results will go into scratch columns.
        if (bigTableKeyExpressions != null) {
            for (VectorExpression ve : bigTableKeyExpressions) {
                ve.evaluate(batch);
            }
        }
        /*
       * Single-Column Long specific declarations.
       */
        // The one join column for this specialized class.
        LongColumnVector joinColVector = (LongColumnVector) batch.cols[singleJoinColumn];
        long[] vector = joinColVector.vector;
        /*
       * Single-Column Long check for repeating.
       */
        // Check single column for repeating.
        boolean allKeyInputColumnsRepeating = joinColVector.isRepeating;
        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.
            /*
         * Single-Column Long specific repeated lookup.
         */
            JoinUtil.JoinResult joinResult;
            if (!joinColVector.noNulls && joinColVector.isNull[0]) {
                joinResult = JoinUtil.JoinResult.NOMATCH;
            } else {
                long key = vector[0];
                if (useMinMax && (key < min || key > max)) {
                    // Out of range for whole batch.
                    joinResult = JoinUtil.JoinResult.NOMATCH;
                } else {
                    joinResult = hashMultiSet.contains(key, hashMultiSetResults[0]);
                }
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
            }
            finishInnerBigOnlyRepeated(batch, joinResult, hashMultiSetResults[0]);
        } else {
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
            }
            // We remember any matching rows in matchs / 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 hashMultiSetResultCount = 0;
            int allMatchCount = 0;
            int equalKeySeriesCount = 0;
            int spillCount = 0;
            /*
         * Single-Column Long specific variables.
         */
            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;
                }
                if (isNull || !haveSaveKey || currentKey != saveKey) {
                    if (haveSaveKey) {
                        // Move on with our counts.
                        switch(saveJoinResult) {
                            case MATCH:
                                // We have extracted the count from the hash multi-set result, so we don't keep it.
                                equalKeySeriesCount++;
                                break;
                            case SPILL:
                                // We keep the hash multi-set result for its spill information.
                                hashMultiSetResultCount++;
                                break;
                            case NOMATCH:
                                break;
                        }
                    }
                    if (isNull) {
                        saveJoinResult = JoinUtil.JoinResult.NOMATCH;
                        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;
                        /*
               * Single-Column Long specific save key.
               */
                        saveKey = currentKey;
                        if (useMinMax && (currentKey < min || currentKey > max)) {
                            // Key out of range for whole hash table.
                            saveJoinResult = JoinUtil.JoinResult.NOMATCH;
                        } else {
                            saveJoinResult = hashMultiSet.contains(currentKey, hashMultiSetResults[hashMultiSetResultCount]);
                        }
                    }
                    switch(saveJoinResult) {
                        case MATCH:
                            equalKeySeriesValueCounts[equalKeySeriesCount] = hashMultiSetResults[hashMultiSetResultCount].count();
                            equalKeySeriesAllMatchIndices[equalKeySeriesCount] = allMatchCount;
                            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] = hashMultiSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH" + " currentKey " + currentKey);
                            break;
                    }
                } else {
                    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] = hashMultiSetResultCount;
                            spillCount++;
                            break;
                        case NOMATCH:
                            // VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH duplicate");
                            break;
                    }
                }
            }
            if (haveSaveKey) {
                // Update our counts for the last key.
                switch(saveJoinResult) {
                    case MATCH:
                        // We have extracted the count from the hash multi-set result, so we don't keep it.
                        equalKeySeriesCount++;
                        break;
                    case SPILL:
                        // We keep the hash multi-set result for its spill information.
                        hashMultiSetResultCount++;
                        break;
                    case NOMATCH:
                        break;
                }
            }
            if (isLogDebugEnabled) {
                LOG.debug(CLASS_NAME + " allMatchs " + intArrayToRangesString(allMatchs, allMatchCount) + " equalKeySeriesValueCounts " + longArrayToRangesString(equalKeySeriesValueCounts, equalKeySeriesCount) + " equalKeySeriesAllMatchIndices " + intArrayToRangesString(equalKeySeriesAllMatchIndices, equalKeySeriesCount) + " equalKeySeriesDuplicateCounts " + intArrayToRangesString(equalKeySeriesDuplicateCounts, equalKeySeriesCount) + " spills " + intArrayToRangesString(spills, spillCount) + " spillHashMapResultIndices " + intArrayToRangesString(spillHashMapResultIndices, spillCount) + " hashMapResults " + Arrays.toString(Arrays.copyOfRange(hashMultiSetResults, 0, hashMultiSetResultCount)));
            }
            finishInnerBigOnly(batch, allMatchCount, equalKeySeriesCount, spillCount, (VectorMapJoinHashTableResult[]) hashMultiSetResults, hashMultiSetResultCount);
        }
        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);
    }
}