Examples with RelDataType org.apache.calcite.rel.type.RelDataType used on opensource projects

Example 51 with RelDataType

use of org.apache.calcite.rel.type.RelDataType in project hive by apache.

the class HiveMaterializedViewsRegistry method createTableScan.

private static RelNode createTableScan(Table viewTable) {
    // 0. Recreate cluster
    final RelOptPlanner planner = HiveVolcanoPlanner.createPlanner(null);
    final RexBuilder rexBuilder = new RexBuilder(new JavaTypeFactoryImpl());
    final RelOptCluster cluster = RelOptCluster.create(planner, rexBuilder);
    // 1. Create column schema
    final RowResolver rr = new RowResolver();
    // 1.1 Add Column info for non partion cols (Object Inspector fields)
    StructObjectInspector rowObjectInspector;
    try {
        rowObjectInspector = (StructObjectInspector) viewTable.getDeserializer().getObjectInspector();
    } catch (SerDeException e) {
        // Bail out
        return null;
    }
    List<? extends StructField> fields = rowObjectInspector.getAllStructFieldRefs();
    ColumnInfo colInfo;
    String colName;
    ArrayList<ColumnInfo> cInfoLst = new ArrayList<ColumnInfo>();
    for (int i = 0; i < fields.size(); i++) {
        colName = fields.get(i).getFieldName();
        colInfo = new ColumnInfo(fields.get(i).getFieldName(), TypeInfoUtils.getTypeInfoFromObjectInspector(fields.get(i).getFieldObjectInspector()), null, false);
        rr.put(null, colName, colInfo);
        cInfoLst.add(colInfo);
    }
    ArrayList<ColumnInfo> nonPartitionColumns = new ArrayList<ColumnInfo>(cInfoLst);
    // 1.2 Add column info corresponding to partition columns
    ArrayList<ColumnInfo> partitionColumns = new ArrayList<ColumnInfo>();
    for (FieldSchema part_col : viewTable.getPartCols()) {
        colName = part_col.getName();
        colInfo = new ColumnInfo(colName, TypeInfoFactory.getPrimitiveTypeInfo(part_col.getType()), null, true);
        rr.put(null, colName, colInfo);
        cInfoLst.add(colInfo);
        partitionColumns.add(colInfo);
    }
    // 1.3 Build row type from field <type, name>
    RelDataType rowType;
    try {
        rowType = TypeConverter.getType(cluster, rr, null);
    } catch (CalciteSemanticException e) {
        // Bail out
        return null;
    }
    // 2. Build RelOptAbstractTable
    String fullyQualifiedTabName = viewTable.getDbName();
    if (fullyQualifiedTabName != null && !fullyQualifiedTabName.isEmpty()) {
        fullyQualifiedTabName = fullyQualifiedTabName + "." + viewTable.getTableName();
    } else {
        fullyQualifiedTabName = viewTable.getTableName();
    }
    RelOptHiveTable optTable = new RelOptHiveTable(null, fullyQualifiedTabName, rowType, viewTable, nonPartitionColumns, partitionColumns, new ArrayList<VirtualColumn>(), SessionState.get().getConf(), new HashMap<String, PrunedPartitionList>(), new AtomicInteger());
    RelNode tableRel;
    // 3. Build operator
    if (obtainTableType(viewTable) == TableType.DRUID) {
        // Build Druid query
        String address = HiveConf.getVar(SessionState.get().getConf(), HiveConf.ConfVars.HIVE_DRUID_BROKER_DEFAULT_ADDRESS);
        String dataSource = viewTable.getParameters().get(Constants.DRUID_DATA_SOURCE);
        Set<String> metrics = new HashSet<>();
        List<RelDataType> druidColTypes = new ArrayList<>();
        List<String> druidColNames = new ArrayList<>();
        for (RelDataTypeField field : rowType.getFieldList()) {
            druidColTypes.add(field.getType());
            druidColNames.add(field.getName());
            if (field.getName().equals(DruidTable.DEFAULT_TIMESTAMP_COLUMN)) {
                // timestamp
                continue;
            }
            if (field.getType().getSqlTypeName() == SqlTypeName.VARCHAR) {
                // dimension
                continue;
            }
            metrics.add(field.getName());
        }
        List<Interval> intervals = Arrays.asList(DruidTable.DEFAULT_INTERVAL);
        DruidTable druidTable = new DruidTable(new DruidSchema(address, address, false), dataSource, RelDataTypeImpl.proto(rowType), metrics, DruidTable.DEFAULT_TIMESTAMP_COLUMN, intervals);
        final TableScan scan = new HiveTableScan(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION), optTable, viewTable.getTableName(), null, false, false);
        tableRel = DruidQuery.create(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION), optTable, druidTable, ImmutableList.<RelNode>of(scan));
    } else {
        // Build Hive Table Scan Rel
        tableRel = new HiveTableScan(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION), optTable, viewTable.getTableName(), null, false, false);
    }
    return tableRel;
}

Example 52 with RelDataType

use of org.apache.calcite.rel.type.RelDataType in project hive by apache.

the class RexNodeConverter method convert.

private RexNode convert(ExprNodeGenericFuncDesc func) throws SemanticException {
    ExprNodeDesc tmpExprNode;
    RexNode tmpRN;
    List<RexNode> childRexNodeLst = new ArrayList<RexNode>();
    Builder<RelDataType> argTypeBldr = ImmutableList.<RelDataType>builder();
    // TODO: 1) Expand to other functions as needed 2) What about types other than primitive.
    TypeInfo tgtDT = null;
    GenericUDF tgtUdf = func.getGenericUDF();
    boolean isNumeric = (tgtUdf instanceof GenericUDFBaseBinary && func.getTypeInfo().getCategory() == Category.PRIMITIVE && (PrimitiveGrouping.NUMERIC_GROUP == PrimitiveObjectInspectorUtils.getPrimitiveGrouping(((PrimitiveTypeInfo) func.getTypeInfo()).getPrimitiveCategory())));
    boolean isCompare = !isNumeric && tgtUdf instanceof GenericUDFBaseCompare;
    boolean isWhenCase = tgtUdf instanceof GenericUDFWhen || tgtUdf instanceof GenericUDFCase;
    boolean isTransformableTimeStamp = func.getGenericUDF() instanceof GenericUDFUnixTimeStamp && func.getChildren().size() != 0;
    if (isNumeric) {
        tgtDT = func.getTypeInfo();
        assert func.getChildren().size() == 2;
    // TODO: checking 2 children is useless, compare already does that.
    } else if (isCompare && (func.getChildren().size() == 2)) {
        tgtDT = FunctionRegistry.getCommonClassForComparison(func.getChildren().get(0).getTypeInfo(), func.getChildren().get(1).getTypeInfo());
    } else if (isWhenCase) {
        // as they are not allowed
        if (checkForStatefulFunctions(func.getChildren())) {
            throw new SemanticException("Stateful expressions cannot be used inside of CASE");
        }
    } else if (isTransformableTimeStamp) {
        // unix_timestamp(args) -> to_unix_timestamp(args)
        func = ExprNodeGenericFuncDesc.newInstance(new GenericUDFToUnixTimeStamp(), func.getChildren());
    }
    for (ExprNodeDesc childExpr : func.getChildren()) {
        tmpExprNode = childExpr;
        if (tgtDT != null && TypeInfoUtils.isConversionRequiredForComparison(tgtDT, childExpr.getTypeInfo())) {
            if (isCompare) {
                // For compare, we will convert requisite children
                tmpExprNode = ParseUtils.createConversionCast(childExpr, (PrimitiveTypeInfo) tgtDT);
            } else if (isNumeric) {
                // For numeric, we'll do minimum necessary cast - if we cast to the type
                // of expression, bad things will happen.
                PrimitiveTypeInfo minArgType = ExprNodeDescUtils.deriveMinArgumentCast(childExpr, tgtDT);
                tmpExprNode = ParseUtils.createConversionCast(childExpr, minArgType);
            } else {
                throw new AssertionError("Unexpected " + tgtDT + " - not a numeric op or compare");
            }
        }
        argTypeBldr.add(TypeConverter.convert(tmpExprNode.getTypeInfo(), cluster.getTypeFactory()));
        tmpRN = convert(tmpExprNode);
        childRexNodeLst.add(tmpRN);
    }
    // See if this is an explicit cast.
    RexNode expr = null;
    RelDataType retType = null;
    expr = handleExplicitCast(func, childRexNodeLst);
    if (expr == null) {
        // This is not a cast; process the function.
        retType = TypeConverter.convert(func.getTypeInfo(), cluster.getTypeFactory());
        SqlOperator calciteOp = SqlFunctionConverter.getCalciteOperator(func.getFuncText(), func.getGenericUDF(), argTypeBldr.build(), retType);
        if (calciteOp.getKind() == SqlKind.CASE) {
            // If it is a case operator, we need to rewrite it
            childRexNodeLst = rewriteCaseChildren(func, childRexNodeLst);
        } else if (HiveExtractDate.ALL_FUNCTIONS.contains(calciteOp)) {
            // If it is a extract operator, we need to rewrite it
            childRexNodeLst = rewriteExtractDateChildren(calciteOp, childRexNodeLst);
        } else if (HiveFloorDate.ALL_FUNCTIONS.contains(calciteOp)) {
            // If it is a floor <date> operator, we need to rewrite it
            childRexNodeLst = rewriteFloorDateChildren(calciteOp, childRexNodeLst);
        }
        expr = cluster.getRexBuilder().makeCall(calciteOp, childRexNodeLst);
    } else {
        retType = expr.getType();
    }
    // an exception
    if (flattenExpr && (expr instanceof RexCall) && !(((RexCall) expr).getOperator() instanceof SqlCastFunction)) {
        RexCall call = (RexCall) expr;
        expr = cluster.getRexBuilder().makeCall(retType, call.getOperator(), RexUtil.flatten(call.getOperands(), call.getOperator()));
    }
    return expr;
}

Example 53 with RelDataType

use of org.apache.calcite.rel.type.RelDataType in project hive by apache.

the class RexNodeConverter method convert.

protected RexNode convert(ExprNodeColumnDesc col) throws SemanticException {
    //if this is co-rrelated we need to make RexCorrelVariable(with id and type)
    // id and type should be retrieved from outerRR
    InputCtx ic = getInputCtx(col);
    if (ic == null) {
        // we have correlated column, build data type from outer rr
        RelDataType rowType = TypeConverter.getType(cluster, this.outerRR, null);
        if (this.outerNameToPosMap.get(col.getColumn()) == null) {
            throw new SemanticException(ErrorMsg.INVALID_COLUMN_NAME.getMsg(col.getColumn()));
        }
        int pos = this.outerNameToPosMap.get(col.getColumn());
        CorrelationId colCorr = new CorrelationId(this.correlatedId);
        RexNode corExpr = cluster.getRexBuilder().makeCorrel(rowType, colCorr);
        return cluster.getRexBuilder().makeFieldAccess(corExpr, pos);
    }
    int pos = ic.hiveNameToPosMap.get(col.getColumn());
    return cluster.getRexBuilder().makeInputRef(ic.calciteInpDataType.getFieldList().get(pos).getType(), pos + ic.offsetInCalciteSchema);
}

Example 54 with RelDataType

use of org.apache.calcite.rel.type.RelDataType in project hive by apache.

the class SqlFunctionConverter method getUDFInfo.

private static CalciteUDFInfo getUDFInfo(String hiveUdfName, ImmutableList<RelDataType> calciteArgTypes, RelDataType calciteRetType) {
    CalciteUDFInfo udfInfo = new CalciteUDFInfo();
    udfInfo.udfName = hiveUdfName;
    udfInfo.returnTypeInference = ReturnTypes.explicit(calciteRetType);
    udfInfo.operandTypeInference = InferTypes.explicit(calciteArgTypes);
    ImmutableList.Builder<SqlTypeFamily> typeFamilyBuilder = new ImmutableList.Builder<SqlTypeFamily>();
    for (RelDataType at : calciteArgTypes) {
        typeFamilyBuilder.add(Util.first(at.getSqlTypeName().getFamily(), SqlTypeFamily.ANY));
    }
    udfInfo.operandTypeChecker = OperandTypes.family(typeFamilyBuilder.build());
    return udfInfo;
}

Example 55 with RelDataType

use of org.apache.calcite.rel.type.RelDataType in project hive by apache.

the class TypeConverter method convert.

public static RelDataType convert(MapTypeInfo mapType, RelDataTypeFactory dtFactory) throws CalciteSemanticException {
    RelDataType keyType = convert(mapType.getMapKeyTypeInfo(), dtFactory);
    RelDataType valueType = convert(mapType.getMapValueTypeInfo(), dtFactory);
    return dtFactory.createMapType(keyType, valueType);
}