Examples with ScalarFunctionCallExpression org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression used on opensource projects

Example 31 with ScalarFunctionCallExpression

use of org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression in project asterixdb by apache.

the class StaticTypeCastUtil method injectCastFunction.

/**
     * Inject a dynamic cast function wrapping an existing expression
     *
     * @param funcInfo
     *            the cast function
     * @param reqType
     *            the required type
     * @param inputType
     *            the original type
     * @param exprRef
     *            the expression reference
     * @param argExpr
     *            the original expression
     * @throws AlgebricksException
     */
private static void injectCastFunction(IFunctionInfo funcInfo, IAType reqType, IAType inputType, Mutable<ILogicalExpression> exprRef, ILogicalExpression argExpr) throws AlgebricksException {
    ScalarFunctionCallExpression cast = new ScalarFunctionCallExpression(funcInfo);
    cast.getArguments().add(new MutableObject<ILogicalExpression>(argExpr));
    exprRef.setValue(cast);
    TypeCastUtils.setRequiredAndInputTypes(cast, reqType, inputType);
}

Example 32 with ScalarFunctionCallExpression

use of org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression in project asterixdb by apache.

the class ConsolidateSelectsRule method rewritePre.

@Override
public boolean rewritePre(Mutable<ILogicalOperator> opRef, IOptimizationContext context) throws AlgebricksException {
    AbstractLogicalOperator op = (AbstractLogicalOperator) opRef.getValue();
    if (op.getOperatorTag() != LogicalOperatorTag.SELECT) {
        return false;
    }
    SelectOperator firstSelect = (SelectOperator) op;
    IFunctionInfo andFn = context.getMetadataProvider().lookupFunction(AlgebricksBuiltinFunctions.AND);
    // New conjuncts for consolidated select.
    AbstractFunctionCallExpression conj = null;
    AbstractLogicalOperator topMostOp = null;
    AbstractLogicalOperator selectParent = null;
    AbstractLogicalOperator nextSelect = firstSelect;
    do {
        // Skip through assigns.
        do {
            selectParent = nextSelect;
            nextSelect = (AbstractLogicalOperator) selectParent.getInputs().get(0).getValue();
        } while (nextSelect.getOperatorTag() == LogicalOperatorTag.ASSIGN && OperatorPropertiesUtil.isMovable(nextSelect));
        // Stop if the child op is not a select.
        if (nextSelect.getOperatorTag() != LogicalOperatorTag.SELECT) {
            break;
        }
        // Remember the top-most op that we are not removing.
        topMostOp = selectParent;
        // Initialize the new conjuncts, if necessary.
        if (conj == null) {
            conj = new ScalarFunctionCallExpression(andFn);
            // Add the first select's condition.
            conj.getArguments().add(new MutableObject<ILogicalExpression>(firstSelect.getCondition().getValue()));
        }
        // Consolidate all following selects.
        do {
            // Add the condition nextSelect to the new list of conjuncts.
            conj.getArguments().add(((SelectOperator) nextSelect).getCondition());
            selectParent = nextSelect;
            nextSelect = (AbstractLogicalOperator) nextSelect.getInputs().get(0).getValue();
        } while (nextSelect.getOperatorTag() == LogicalOperatorTag.SELECT);
        // Hook up the input of the top-most remaining op if necessary.
        if (topMostOp.getOperatorTag() == LogicalOperatorTag.ASSIGN || topMostOp == firstSelect) {
            topMostOp.getInputs().set(0, selectParent.getInputs().get(0));
        }
        // Prepare for next iteration.
        nextSelect = selectParent;
    } while (true);
    // Did we consolidate any selects?
    if (conj == null) {
        return false;
    }
    // Set the new conjuncts.
    firstSelect.getCondition().setValue(conj);
    context.computeAndSetTypeEnvironmentForOperator(firstSelect);
    return true;
}

Example 33 with ScalarFunctionCallExpression

use of org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression in project asterixdb by apache.

the class CopyLimitDownRule method rewritePre.

@Override
public boolean rewritePre(Mutable<ILogicalOperator> opRef, IOptimizationContext context) throws AlgebricksException {
    AbstractLogicalOperator op = (AbstractLogicalOperator) opRef.getValue();
    if (op.getOperatorTag() != LogicalOperatorTag.LIMIT) {
        return false;
    }
    LimitOperator limitOp = (LimitOperator) op;
    if (!limitOp.isTopmostLimitOp()) {
        return false;
    }
    List<LogicalVariable> limitUsedVars = new ArrayList<>();
    VariableUtilities.getUsedVariables(limitOp, limitUsedVars);
    Mutable<ILogicalOperator> safeOpRef = null;
    Mutable<ILogicalOperator> candidateOpRef = limitOp.getInputs().get(0);
    List<LogicalVariable> candidateProducedVars = new ArrayList<>();
    while (true) {
        candidateProducedVars.clear();
        ILogicalOperator candidateOp = candidateOpRef.getValue();
        LogicalOperatorTag candidateOpTag = candidateOp.getOperatorTag();
        if (candidateOp.getInputs().size() > 1 || !candidateOp.isMap() || candidateOpTag == LogicalOperatorTag.SELECT || candidateOpTag == LogicalOperatorTag.LIMIT || candidateOpTag == LogicalOperatorTag.UNNEST_MAP || !OperatorPropertiesUtil.disjoint(limitUsedVars, candidateProducedVars)) {
            break;
        }
        safeOpRef = candidateOpRef;
        candidateOpRef = safeOpRef.getValue().getInputs().get(0);
    }
    if (safeOpRef != null) {
        ILogicalOperator safeOp = safeOpRef.getValue();
        Mutable<ILogicalOperator> unsafeOpRef = safeOp.getInputs().get(0);
        ILogicalOperator unsafeOp = unsafeOpRef.getValue();
        LimitOperator limitCloneOp = null;
        if (limitOp.getOffset().getValue() == null) {
            limitCloneOp = new LimitOperator(limitOp.getMaxObjects().getValue(), false);
        } else {
            // Need to add an offset to the given limit value
            // since the original topmost limit will use the offset value.
            // We can't apply the offset multiple times.
            IFunctionInfo finfoAdd = context.getMetadataProvider().lookupFunction(AlgebricksBuiltinFunctions.NUMERIC_ADD);
            List<Mutable<ILogicalExpression>> addArgs = new ArrayList<>();
            addArgs.add(new MutableObject<ILogicalExpression>(limitOp.getMaxObjects().getValue().cloneExpression()));
            addArgs.add(new MutableObject<ILogicalExpression>(limitOp.getOffset().getValue().cloneExpression()));
            ScalarFunctionCallExpression maxPlusOffset = new ScalarFunctionCallExpression(finfoAdd, addArgs);
            limitCloneOp = new LimitOperator(maxPlusOffset, false);
        }
        limitCloneOp.setPhysicalOperator(new StreamLimitPOperator());
        limitCloneOp.getInputs().add(new MutableObject<ILogicalOperator>(unsafeOp));
        limitCloneOp.setExecutionMode(unsafeOp.getExecutionMode());
        OperatorPropertiesUtil.computeSchemaRecIfNull((AbstractLogicalOperator) unsafeOp);
        limitCloneOp.recomputeSchema();
        unsafeOpRef.setValue(limitCloneOp);
        context.computeAndSetTypeEnvironmentForOperator(limitCloneOp);
        context.addToDontApplySet(this, limitOp);
    }
    return safeOpRef != null;
}

Example 34 with ScalarFunctionCallExpression

use of org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression in project asterixdb by apache.

the class RTreeAccessMethod method createSecondaryToPrimaryPlan.

private ILogicalOperator createSecondaryToPrimaryPlan(OptimizableOperatorSubTree indexSubTree, OptimizableOperatorSubTree probeSubTree, Index chosenIndex, AccessMethodAnalysisContext analysisCtx, boolean retainInput, boolean retainNull, boolean requiresBroadcast, IOptimizationContext context) throws AlgebricksException {
    IOptimizableFuncExpr optFuncExpr = AccessMethodUtils.chooseFirstOptFuncExpr(chosenIndex, analysisCtx);
    Dataset dataset = indexSubTree.getDataset();
    ARecordType recordType = indexSubTree.getRecordType();
    ARecordType metaRecordType = indexSubTree.getMetaRecordType();
    int optFieldIdx = AccessMethodUtils.chooseFirstOptFuncVar(chosenIndex, analysisCtx);
    Pair<IAType, Boolean> keyPairType = Index.getNonNullableOpenFieldType(optFuncExpr.getFieldType(optFieldIdx), optFuncExpr.getFieldName(optFieldIdx), recordType);
    if (keyPairType == null) {
        return null;
    }
    // Get the number of dimensions corresponding to the field indexed by chosenIndex.
    IAType spatialType = keyPairType.first;
    int numDimensions = NonTaggedFormatUtil.getNumDimensions(spatialType.getTypeTag());
    int numSecondaryKeys = numDimensions * 2;
    // we made sure indexSubTree has datasource scan
    AbstractDataSourceOperator dataSourceOp = (AbstractDataSourceOperator) indexSubTree.getDataSourceRef().getValue();
    RTreeJobGenParams jobGenParams = new RTreeJobGenParams(chosenIndex.getIndexName(), IndexType.RTREE, dataset.getDataverseName(), dataset.getDatasetName(), retainInput, requiresBroadcast);
    // A spatial object is serialized in the constant of the func expr we are optimizing.
    // The R-Tree expects as input an MBR represented with 1 field per dimension.
    // Here we generate vars and funcs for extracting MBR fields from the constant into fields of a tuple (as the
    // R-Tree expects them).
    // List of variables for the assign.
    ArrayList<LogicalVariable> keyVarList = new ArrayList<>();
    // List of expressions for the assign.
    ArrayList<Mutable<ILogicalExpression>> keyExprList = new ArrayList<>();
    Pair<ILogicalExpression, Boolean> returnedSearchKeyExpr = AccessMethodUtils.createSearchKeyExpr(optFuncExpr, indexSubTree, probeSubTree);
    ILogicalExpression searchKeyExpr = returnedSearchKeyExpr.first;
    for (int i = 0; i < numSecondaryKeys; i++) {
        // The create MBR function "extracts" one field of an MBR around the given spatial object.
        AbstractFunctionCallExpression createMBR = new ScalarFunctionCallExpression(FunctionUtil.getFunctionInfo(BuiltinFunctions.CREATE_MBR));
        // Spatial object is the constant from the func expr we are optimizing.
        createMBR.getArguments().add(new MutableObject<>(searchKeyExpr));
        // The number of dimensions.
        createMBR.getArguments().add(new MutableObject<ILogicalExpression>(new ConstantExpression(new AsterixConstantValue(new AInt32(numDimensions)))));
        // Which part of the MBR to extract.
        createMBR.getArguments().add(new MutableObject<ILogicalExpression>(new ConstantExpression(new AsterixConstantValue(new AInt32(i)))));
        // Add a variable and its expr to the lists which will be passed into an assign op.
        LogicalVariable keyVar = context.newVar();
        keyVarList.add(keyVar);
        keyExprList.add(new MutableObject<ILogicalExpression>(createMBR));
    }
    jobGenParams.setKeyVarList(keyVarList);
    // Assign operator that "extracts" the MBR fields from the func-expr constant into a tuple.
    AssignOperator assignSearchKeys = new AssignOperator(keyVarList, keyExprList);
    if (probeSubTree == null) {
        // We are optimizing a selection query.
        // Input to this assign is the EmptyTupleSource (which the dataSourceScan also must have had as input).
        assignSearchKeys.getInputs().add(new MutableObject<>(OperatorManipulationUtil.deepCopy(dataSourceOp.getInputs().get(0).getValue())));
        assignSearchKeys.setExecutionMode(dataSourceOp.getExecutionMode());
    } else {
        // We are optimizing a join, place the assign op top of the probe subtree.
        assignSearchKeys.getInputs().add(probeSubTree.getRootRef());
    }
    ILogicalOperator secondaryIndexUnnestOp = AccessMethodUtils.createSecondaryIndexUnnestMap(dataset, recordType, metaRecordType, chosenIndex, assignSearchKeys, jobGenParams, context, false, retainInput, retainNull);
    // Generate the rest of the upstream plan which feeds the search results into the primary index.
    return dataset.getDatasetType() == DatasetType.EXTERNAL ? AccessMethodUtils.createExternalDataLookupUnnestMap(dataSourceOp, dataset, recordType, secondaryIndexUnnestOp, context, retainInput, retainNull) : AccessMethodUtils.createPrimaryIndexUnnestMap(dataSourceOp, dataset, recordType, metaRecordType, secondaryIndexUnnestOp, context, true, retainInput, false, false);
}

Example 35 with ScalarFunctionCallExpression

use of org.apache.hyracks.algebricks.core.algebra.expressions.ScalarFunctionCallExpression in project asterixdb by apache.

the class IntroduceJoinAccessMethodRule method checkAndApplyJoinTransformation.

/**
     * Recursively traverse the given plan and check whether a INNERJOIN or LEFTOUTERJOIN operator exists.
     * If one is found, maintain the path from the root to the given join operator and
     * optimize the path from the given join operator to the EMPTY_TUPLE_SOURCE operator
     * if it is not already optimized.
     */
protected boolean checkAndApplyJoinTransformation(Mutable<ILogicalOperator> opRef, IOptimizationContext context) throws AlgebricksException {
    AbstractLogicalOperator op = (AbstractLogicalOperator) opRef.getValue();
    boolean joinFoundAndOptimizationApplied;
    // Check the current operator pattern to see whether it is a JOIN or not.
    boolean isThisOpInnerJoin = isInnerJoin(op);
    boolean isThisOpLeftOuterJoin = isLeftOuterJoin(op);
    boolean isParentOpGroupBy = hasGroupBy;
    Mutable<ILogicalOperator> joinRefFromThisOp = null;
    AbstractBinaryJoinOperator joinOpFromThisOp = null;
    if (isThisOpInnerJoin) {
        // Set join operator.
        joinRef = opRef;
        joinOp = (InnerJoinOperator) op;
        joinRefFromThisOp = opRef;
        joinOpFromThisOp = (InnerJoinOperator) op;
    } else if (isThisOpLeftOuterJoin) {
        // Set left-outer-join op.
        // The current operator is GROUP and the child of this op is LEFTOUERJOIN.
        joinRef = op.getInputs().get(0);
        joinOp = (LeftOuterJoinOperator) joinRef.getValue();
        joinRefFromThisOp = op.getInputs().get(0);
        joinOpFromThisOp = (LeftOuterJoinOperator) joinRefFromThisOp.getValue();
    }
    // to make sure an earlier join in the path is optimized first.
    for (Mutable<ILogicalOperator> inputOpRef : op.getInputs()) {
        joinFoundAndOptimizationApplied = checkAndApplyJoinTransformation(inputOpRef, context);
        if (joinFoundAndOptimizationApplied) {
            return true;
        }
    }
    // For a JOIN case, try to transform the given plan.
    if (isThisOpInnerJoin || isThisOpLeftOuterJoin) {
        // Restore the information from this operator since it might have been be set to null
        // if there are other join operators in the earlier path.
        joinRef = joinRefFromThisOp;
        joinOp = joinOpFromThisOp;
        boolean continueCheck = true;
        // Already checked? If not, this operator may be optimized.
        if (context.checkIfInDontApplySet(this, joinOp)) {
            continueCheck = false;
        }
        // For each access method, this contains the information about
        // whether an available index can be applicable or not.
        Map<IAccessMethod, AccessMethodAnalysisContext> analyzedAMs = null;
        if (continueCheck) {
            analyzedAMs = new HashMap<>();
        }
        // whether the given plan is truly optimizable or not.
        if (continueCheck && !checkJoinOpConditionAndInitSubTree(context)) {
            continueCheck = false;
        }
        // Analyze the condition of SELECT operator and initialize analyzedAMs.
        // Check whether the function in the SELECT operator can be truly transformed.
        boolean matchInLeftSubTree = false;
        boolean matchInRightSubTree = false;
        if (continueCheck) {
            if (leftSubTree.hasDataSource()) {
                matchInLeftSubTree = analyzeSelectOrJoinOpConditionAndUpdateAnalyzedAM(joinCond, leftSubTree.getAssignsAndUnnests(), analyzedAMs, context, typeEnvironment);
            }
            if (rightSubTree.hasDataSource()) {
                matchInRightSubTree = analyzeSelectOrJoinOpConditionAndUpdateAnalyzedAM(joinCond, rightSubTree.getAssignsAndUnnests(), analyzedAMs, context, typeEnvironment);
            }
        }
        // Find the dataset from the data-source and the record type of the dataset from the metadata.
        // This will be used to find an applicable index on the dataset.
        boolean checkLeftSubTreeMetadata = false;
        boolean checkRightSubTreeMetadata = false;
        if (continueCheck && (matchInLeftSubTree || matchInRightSubTree)) {
            // Set dataset and type metadata.
            if (matchInLeftSubTree) {
                checkLeftSubTreeMetadata = leftSubTree.setDatasetAndTypeMetadata(metadataProvider);
            }
            if (matchInRightSubTree) {
                checkRightSubTreeMetadata = rightSubTree.setDatasetAndTypeMetadata(metadataProvider);
            }
        }
        if (continueCheck && (checkLeftSubTreeMetadata || checkRightSubTreeMetadata)) {
            // Then find the applicable indexes for the variables used in the JOIN condition.
            if (checkLeftSubTreeMetadata) {
                fillSubTreeIndexExprs(leftSubTree, analyzedAMs, context);
            }
            if (checkRightSubTreeMetadata) {
                fillSubTreeIndexExprs(rightSubTree, analyzedAMs, context);
            }
            // Prune the access methods based on the function expression and access methods.
            pruneIndexCandidates(analyzedAMs, context, typeEnvironment);
            // If the right subtree (inner branch) has indexes, one of those indexes will be used.
            // Remove the indexes from the outer branch in the optimizer's consideration list for this rule.
            pruneIndexCandidatesFromOuterBranch(analyzedAMs);
            // We are going to use indexes from the inner branch.
            // If no index is available, then we stop here.
            Pair<IAccessMethod, Index> chosenIndex = chooseBestIndex(analyzedAMs);
            if (chosenIndex == null) {
                context.addToDontApplySet(this, joinOp);
                continueCheck = false;
            }
            if (continueCheck) {
                // Apply plan transformation using chosen index.
                AccessMethodAnalysisContext analysisCtx = analyzedAMs.get(chosenIndex.first);
                // in GroupByOp.
                if (isThisOpLeftOuterJoin && isParentOpGroupBy) {
                    analysisCtx.setLOJGroupbyOpRef(opRef);
                    ScalarFunctionCallExpression isNullFuncExpr = AccessMethodUtils.findLOJIsMissingFuncInGroupBy((GroupByOperator) opRef.getValue());
                    analysisCtx.setLOJIsNullFuncInGroupBy(isNullFuncExpr);
                }
                Dataset indexDataset = analysisCtx.getDatasetFromIndexDatasetMap(chosenIndex.second);
                // from the right subtree. The following is just a sanity check.
                if (!rightSubTree.hasDataSourceScan() && !indexDataset.getDatasetName().equals(rightSubTree.getDataset().getDatasetName())) {
                    return false;
                }
                // Finally, try to apply plan transformation using chosen index.
                boolean res = chosenIndex.first.applyJoinPlanTransformation(joinRef, leftSubTree, rightSubTree, chosenIndex.second, analysisCtx, context, isThisOpLeftOuterJoin, isParentOpGroupBy);
                // will find them.
                if (res) {
                    return res;
                }
            }
        }
        joinRef = null;
        joinOp = null;
    }
    return false;
}