Java Code Examples for org.apache.kylin.metadata.model.FunctionDesc#getRewriteFieldName()

private List<ColumnDesc> listSourceColumns() {
    ProjectManager mgr = ProjectManager.getInstance(olapSchema.getConfig());
    List<ColumnDesc> exposedColumns = Lists.newArrayList(mgr.listExposedColumns(olapSchema.getProjectName(), sourceTable.getIdentity()));

    List<MeasureDesc> countMeasures = mgr.listEffectiveRewriteMeasures(olapSchema.getProjectName(), sourceTable.getIdentity());
    HashSet<String> metFields = new HashSet<String>();
    for (MeasureDesc m : countMeasures) {
        FunctionDesc func = m.getFunction();
        String fieldName = func.getRewriteFieldName();
        if (!metFields.contains(fieldName)) {
            metFields.add(fieldName);
            ColumnDesc fakeCountCol = new ColumnDesc();
            fakeCountCol.setName(fieldName);
            fakeCountCol.setDatatype(func.getSQLType());
            fakeCountCol.setNullable(false);
            fakeCountCol.init(sourceTable);
            exposedColumns.add(fakeCountCol);
        }
    }

    return exposedColumns;
}
 

TblColRef buildRewriteColumn(FunctionDesc aggFunc) {
    TblColRef colRef;
    if (aggFunc.needRewriteField()) {
        String colName = aggFunc.getRewriteFieldName();
        colRef = this.context.firstTableScan.makeRewriteColumn(colName);
    } else {
        throw new IllegalStateException("buildRewriteColumn on a aggrFunc that does not need rewrite " + aggFunc);
    }
    return colRef;
}
 

private List<ColumnDesc> listSourceColumns() {
    ProjectManager mgr = ProjectManager.getInstance(olapSchema.getConfig());

    List<ColumnDesc> tableColumns = mgr.listExposedColumns(olapSchema.getProjectName(), sourceTable, exposeMore);

    List<ColumnDesc> metricColumns = Lists.newArrayList();
    List<MeasureDesc> countMeasures = mgr.listEffectiveRewriteMeasures(olapSchema.getProjectName(),
            sourceTable.getIdentity());
    HashSet<String> metFields = new HashSet<String>();
    for (MeasureDesc m : countMeasures) {

        FunctionDesc func = m.getFunction();
        String fieldName = func.getRewriteFieldName();
        if (!metFields.contains(fieldName)) {
            metFields.add(fieldName);
            ColumnDesc fakeCountCol = func.newFakeRewriteColumn(sourceTable);
            metricColumns.add(fakeCountCol);
        }
    }

    Collections.sort(tableColumns, new Comparator<ColumnDesc>() {
        @Override
        public int compare(ColumnDesc o1, ColumnDesc o2) {
            return o1.getZeroBasedIndex() - o2.getZeroBasedIndex();
        }
    });
    return Lists.newArrayList(Iterables.concat(tableColumns, metricColumns));
}
 

TblColRef buildRewriteColumn(FunctionDesc aggFunc) {
    TblColRef colRef;
    if (aggFunc.needRewriteField()) {
        String colName = aggFunc.getRewriteFieldName();
        colRef = this.context.firstTableScan.makeRewriteColumn(colName);
    } else {
        throw new IllegalStateException("buildRewriteColumn on a aggrFunc that does not need rewrite " + aggFunc);
    }
    return colRef;
}
 

private List<ColumnDesc> listSourceColumns() {
    ProjectManager mgr = ProjectManager.getInstance(olapSchema.getConfig());

    List<ColumnDesc> tableColumns = mgr.listExposedColumns(olapSchema.getProjectName(), sourceTable, exposeMore);

    List<ColumnDesc> metricColumns = Lists.newArrayList();
    List<MeasureDesc> countMeasures = mgr.listEffectiveRewriteMeasures(olapSchema.getProjectName(),
            sourceTable.getIdentity());
    HashSet<String> metFields = new HashSet<String>();
    for (MeasureDesc m : countMeasures) {

        FunctionDesc func = m.getFunction();
        String fieldName = func.getRewriteFieldName();
        if (!metFields.contains(fieldName)) {
            metFields.add(fieldName);
            ColumnDesc fakeCountCol = func.newFakeRewriteColumn(sourceTable);
            metricColumns.add(fakeCountCol);
        }
    }

    Collections.sort(tableColumns, new Comparator<ColumnDesc>() {
        @Override
        public int compare(ColumnDesc o1, ColumnDesc o2) {
            return o1.getZeroBasedIndex() - o2.getZeroBasedIndex();
        }
    });
    return Lists.newArrayList(Iterables.concat(tableColumns, metricColumns));
}
 

private AggregateCall rewriteAggregateCall(AggregateCall aggCall, FunctionDesc func) {

        // rebuild parameters
        List<Integer> newArgList = new ArrayList<Integer>(1);
        String fieldName = func.getRewriteFieldName();
        RelDataTypeField field = getChild().getRowType().getField(fieldName, true);
        newArgList.add(field.getIndex());

        // rebuild function
        RelDataType fieldType = aggCall.getType();
        Aggregation newAgg = aggCall.getAggregation();
        if (func.isCountDistinct()) {
            newAgg = createHyperLogLogAggFunction(fieldType);
        } else if (func.isCount()) {
            newAgg = new SqlSumEmptyIsZeroAggFunction(fieldType);
        }

        // rebuild aggregate call
        AggregateCall newAggCall = new AggregateCall(newAgg, false, newArgList, fieldType, newAgg.getName());

        // To make sure specified type matches the inferReturnType, or otherwise
        // there will be assertion failure in optiq
        // The problem is BIGINT != BIGINT NOT NULL
        // Details see https://github.scm.corp.ebay.com/Kylin/Kylin/issues/323
        SqlAggFunction aggFunction = (SqlAggFunction) newAggCall.getAggregation();
        AggCallBinding callBinding = newAggCall.createBinding(this);
        RelDataType inferReturnType = aggFunction.inferReturnType(callBinding);

        return new AggregateCall(newAgg, false, newArgList, inferReturnType, newAgg.getName());
    }
 

ColumnRowType buildColumnRowType() {
    buildGroups();
    buildAggregations();

    ColumnRowType inputColumnRowType = ((OLAPRel) getInput()).getColumnRowType();
    List<TblColRef> columns = new ArrayList<TblColRef>(this.rowType.getFieldCount());
    columns.addAll(this.groups);

    // Add group column indicators
    if (indicator) {
        final Set<String> containedNames = Sets.newHashSet();
        for (TblColRef groupCol : groups) {
            String base = "i$" + groupCol.getName();
            String name = base;
            int i = 0;
            while (containedNames.contains(name)) {
                name = base + "_" + i++;
            }
            containedNames.add(name);
            TblColRef indicatorCol = TblColRef.newInnerColumn(name, TblColRef.InnerDataTypeEnum.LITERAL);
            columns.add(indicatorCol);
        }
    }

    for (int i = 0; i < this.aggregations.size(); i++) {
        FunctionDesc aggFunc = this.aggregations.get(i);
        String aggOutName;
        if (aggFunc != null) {
            aggOutName = aggFunc.getRewriteFieldName();
        } else {
            AggregateCall aggCall = this.rewriteAggCalls.get(i);
            int index = aggCall.getArgList().get(0);
            aggOutName = getSqlFuncName(aggCall) + "_"
                    + inputColumnRowType.getColumnByIndex(index).getIdentity().replace('.', '_') + "_";
        }
        TblColRef aggOutCol = TblColRef.newInnerColumn(aggOutName, TblColRef.InnerDataTypeEnum.LITERAL);
        aggOutCol.getColumnDesc().setId("" + (i + 1)); // mark the index of aggregation
        columns.add(aggOutCol);
    }
    return new ColumnRowType(columns);
}
 

@Override
public IAdvMeasureFiller getAdvancedTupleFiller(FunctionDesc function, TupleInfo tupleInfo,
        Map<TblColRef, Dictionary<String>> dictionaryMap) {
    final List<TblColRef> literalCols = getTopNLiteralColumn(function);
    final TblColRef numericCol = getTopNNumericColumn(function);
    final int[] literalTupleIdx = new int[literalCols.size()];
    final DimensionEncoding[] dimensionEncodings = getDimensionEncodings(function, literalCols, dictionaryMap);
    for (int i = 0; i < literalCols.size(); i++) {
        TblColRef colRef = literalCols.get(i);
        literalTupleIdx[i] = tupleInfo.hasColumn(colRef) ? tupleInfo.getColumnIndex(colRef) : -1;
    }

    // for TopN, the aggr must be SUM
    final int numericTupleIdx;
    if (numericCol != null) {
        FunctionDesc sumFunc = FunctionDesc.newInstance(FunctionDesc.FUNC_SUM,
                ParameterDesc.newInstance(numericCol), numericCol.getType().toString());
        String sumFieldName = sumFunc.getRewriteFieldName();
        numericTupleIdx = tupleInfo.hasField(sumFieldName) ? tupleInfo.getFieldIndex(sumFieldName) : -1;
    } else {
        FunctionDesc countFunction = FunctionDesc.newInstance(FunctionDesc.FUNC_COUNT,
                ParameterDesc.newInstance("1"), "bigint");
        numericTupleIdx = tupleInfo.getFieldIndex(countFunction.getRewriteFieldName());
    }
    return new IAdvMeasureFiller() {
        private TopNCounter<ByteArray> topNCounter;
        private Iterator<Counter<ByteArray>> topNCounterIterator;
        private int expectRow = 0;

        @SuppressWarnings("unchecked")
        @Override
        public void reload(Object measureValue) {
            this.topNCounter = (TopNCounter<ByteArray>) measureValue;
            this.topNCounterIterator = topNCounter.iterator();
            this.expectRow = 0;
        }

        @Override
        public int getNumOfRows() {
            return topNCounter.size();
        }

        @Override
        public void fillTuple(Tuple tuple, int row) {
            if (expectRow++ != row)
                throw new IllegalStateException();

            Counter<ByteArray> counter = topNCounterIterator.next();
            int offset = counter.getItem().offset();
            for (int i = 0; i < dimensionEncodings.length; i++) {
                String colValue = dimensionEncodings[i].decode(counter.getItem().array(), offset,
                        dimensionEncodings[i].getLengthOfEncoding());
                tuple.setDimensionValue(literalTupleIdx[i], colValue);
                offset += dimensionEncodings[i].getLengthOfEncoding();
            }
            tuple.setMeasureValue(numericTupleIdx, counter.getCount());
        }
    };
}
 

public CubeTupleConverter(CubeSegment cubeSeg, Cuboid cuboid, //
        Set<TblColRef> selectedDimensions, Set<FunctionDesc> selectedMetrics, int[] gtColIdx, TupleInfo returnTupleInfo) {
    this.cubeSeg = cubeSeg;
    this.cuboid = cuboid;
    this.gtColIdx = gtColIdx;
    this.tupleInfo = returnTupleInfo;
    this.derivedColFillers = Lists.newArrayList();

    nSelectedDims = selectedDimensions.size();
    tupleIdx = new int[selectedDimensions.size() + selectedMetrics.size()];

    // measure types don't have this many, but aligned length make programming easier
    measureTypes = new MeasureType[selectedDimensions.size() + selectedMetrics.size()];

    advMeasureFillers = Lists.newArrayListWithCapacity(1);
    advMeasureIndexInGTValues = Lists.newArrayListWithCapacity(1);
    usedLookupTables = Lists.newArrayList();
    eventTimezone = cubeSeg.getConfig().getStreamingDerivedTimeTimezone();
    autoJustByTimezone = eventTimezone.length() > 0
            && cubeSeg.getCubeDesc().getModel().getRootFactTable().getTableDesc().isStreamingTable();
    if (autoJustByTimezone) {
        logger.debug("Will ajust dimsension for Time Derived Column.");
        timeZoneOffset = TimeZone.getTimeZone(eventTimezone).getRawOffset();
    } else {
        timeZoneOffset = 0;
    }
    ////////////

    int i = 0;

    // pre-calculate dimension index mapping to tuple
    for (TblColRef dim : selectedDimensions) {
        tupleIdx[i] = tupleInfo.hasColumn(dim) ? tupleInfo.getColumnIndex(dim) : -1;
        if (TimeDerivedColumnType.isTimeDerivedColumn(dim.getName())
                && !TimeDerivedColumnType.isTimeDerivedColumnAboveDayLevel(dim.getName())) {
            timestampColumn.add(tupleIdx[i]);
        }
        i++;
    }

    for (FunctionDesc metric : selectedMetrics) {
        if (metric.needRewrite()) {
            String rewriteFieldName = metric.getRewriteFieldName();
            tupleIdx[i] = tupleInfo.hasField(rewriteFieldName) ? tupleInfo.getFieldIndex(rewriteFieldName) : -1;
        } else {
            // a non-rewrite metrics (like sum, or dimension playing as metrics) is like a dimension column
            TblColRef col = metric.getParameter().getColRefs().get(0);
            tupleIdx[i] = tupleInfo.hasColumn(col) ? tupleInfo.getColumnIndex(col) : -1;
        }

        MeasureType<?> measureType = metric.getMeasureType();
        if (measureType.needAdvancedTupleFilling()) {
            Map<TblColRef, Dictionary<String>> dictionaryMap = buildDictionaryMap(measureType.getColumnsNeedDictionary(metric));
            advMeasureFillers.add(measureType.getAdvancedTupleFiller(metric, returnTupleInfo, dictionaryMap));
            advMeasureIndexInGTValues.add(i);
        } else {
            measureTypes[i] = measureType;
        }

        i++;
    }

    // prepare derived columns and filler
    Map<Array<TblColRef>, List<DeriveInfo>> hostToDerivedInfo = cuboid.getCubeDesc().getHostToDerivedInfo(cuboid.getColumns(), null);
    for (Entry<Array<TblColRef>, List<DeriveInfo>> entry : hostToDerivedInfo.entrySet()) {
        TblColRef[] hostCols = entry.getKey().data;
        for (DeriveInfo deriveInfo : entry.getValue()) {
            IDerivedColumnFiller filler = newDerivedColumnFiller(hostCols, deriveInfo);
            if (filler != null) {
                derivedColFillers.add(filler);
            }
        }
    }
}
 

public StreamingTupleConverter(ResponseResultSchema schema, TupleInfo returnTupleInfo) {
    this.tupleInfo = returnTupleInfo;
    dimCnt = schema.getDimensionCount();
    metricsCnt = schema.getMetricsCount();
    dimTupleIdx = new int[dimCnt];
    metricsTupleIdx = new int[metricsCnt];

    // measure types don't have this many, but aligned length make programming easier
    measureTypes = new MeasureType[metricsCnt];

    advMeasureFillers = Lists.newArrayListWithCapacity(1);
    advMeasureIndexInGTValues = Lists.newArrayListWithCapacity(1);

    int idx = 0;
    // pre-calculate dimension index mapping to tuple
    for (TblColRef dim : schema.getDimensions()) {
        dimTupleIdx[idx] = tupleInfo.hasColumn(dim) ? tupleInfo.getColumnIndex(dim) : -1;
        if (dim.getType().isDateTimeFamily() && TimeDerivedColumnType.isTimeDerivedColumn(dim.getName()))
            timestampColumn.add(dimTupleIdx[idx]);
        idx++;
    }

    idx = 0;
    for (FunctionDesc metric : schema.getMetrics()) {
        if (metric.needRewrite()) {
            String rewriteFieldName = metric.getRewriteFieldName();
            metricsTupleIdx[idx] = tupleInfo.hasField(rewriteFieldName) ? tupleInfo.getFieldIndex(rewriteFieldName) : -1;
        } else { // a non-rewrite metrics (like sum, or dimension playing as metrics) is like a dimension column
            TblColRef col = metric.getParameter().getColRefs().get(0);
            metricsTupleIdx[idx] = tupleInfo.hasColumn(col) ? tupleInfo.getColumnIndex(col) : -1;
        }

        MeasureType<?> measureType = metric.getMeasureType();
        if (measureType.needAdvancedTupleFilling()) {
            advMeasureFillers.add(measureType.getAdvancedTupleFiller(metric, returnTupleInfo, null));
            advMeasureIndexInGTValues.add(idx);
        } else {
            measureTypes[idx] = measureType;
        }
        idx++;
    }
}
 

ColumnRowType buildColumnRowType() {
    buildGroups();
    buildAggregations();

    ColumnRowType inputColumnRowType = ((OLAPRel) getInput()).getColumnRowType();
    List<TblColRef> columns = new ArrayList<TblColRef>(this.rowType.getFieldCount());
    columns.addAll(this.groups);

    // Add group column indicators
    if (indicator) {
        final Set<String> containedNames = Sets.newHashSet();
        for (TblColRef groupCol : groups) {
            String base = "i$" + groupCol.getName();
            String name = base;
            int i = 0;
            while (containedNames.contains(name)) {
                name = base + "_" + i++;
            }
            containedNames.add(name);
            TblColRef indicatorCol = TblColRef.newInnerColumn(name, TblColRef.InnerDataTypeEnum.LITERAL);
            columns.add(indicatorCol);
        }
    }

    for (int i = 0; i < this.aggregations.size(); i++) {
        FunctionDesc aggFunc = this.aggregations.get(i);
        String aggOutName;
        if (aggFunc != null) {
            aggOutName = aggFunc.getRewriteFieldName();
        } else {
            AggregateCall aggCall = this.rewriteAggCalls.get(i);
            int index = aggCall.getArgList().get(0);
            aggOutName = getSqlFuncName(aggCall) + "_"
                    + inputColumnRowType.getColumnByIndex(index).getIdentity().replace('.', '_') + "_";
        }
        TblColRef aggOutCol = TblColRef.newInnerColumn(aggOutName, TblColRef.InnerDataTypeEnum.LITERAL);
        aggOutCol.getColumnDesc().setId("" + (i + 1)); // mark the index of aggregation
        columns.add(aggOutCol);
    }
    return new ColumnRowType(columns);
}
 

@Override
public IAdvMeasureFiller getAdvancedTupleFiller(FunctionDesc function, TupleInfo tupleInfo,
        Map<TblColRef, Dictionary<String>> dictionaryMap) {
    final List<TblColRef> literalCols = getTopNLiteralColumn(function);
    final TblColRef numericCol = getTopNNumericColumn(function);
    final int[] literalTupleIdx = new int[literalCols.size()];
    final DimensionEncoding[] dimensionEncodings = getDimensionEncodings(function, literalCols, dictionaryMap);
    for (int i = 0; i < literalCols.size(); i++) {
        TblColRef colRef = literalCols.get(i);
        literalTupleIdx[i] = tupleInfo.hasColumn(colRef) ? tupleInfo.getColumnIndex(colRef) : -1;
    }

    // for TopN, the aggr must be SUM
    final int numericTupleIdx;
    if (numericCol != null) {
        FunctionDesc sumFunc = FunctionDesc.newInstance(FunctionDesc.FUNC_SUM,
                ParameterDesc.newInstance(numericCol), numericCol.getType().toString());
        String sumFieldName = sumFunc.getRewriteFieldName();
        numericTupleIdx = tupleInfo.hasField(sumFieldName) ? tupleInfo.getFieldIndex(sumFieldName) : -1;
    } else {
        FunctionDesc countFunction = FunctionDesc.newInstance(FunctionDesc.FUNC_COUNT,
                ParameterDesc.newInstance("1"), "bigint");
        numericTupleIdx = tupleInfo.getFieldIndex(countFunction.getRewriteFieldName());
    }
    return new IAdvMeasureFiller() {
        private TopNCounter<ByteArray> topNCounter;
        private Iterator<Counter<ByteArray>> topNCounterIterator;
        private int expectRow = 0;

        @SuppressWarnings("unchecked")
        @Override
        public void reload(Object measureValue) {
            this.topNCounter = (TopNCounter<ByteArray>) measureValue;
            this.topNCounterIterator = topNCounter.iterator();
            this.expectRow = 0;
        }

        @Override
        public int getNumOfRows() {
            return topNCounter.size();
        }

        @Override
        public void fillTuple(Tuple tuple, int row) {
            if (expectRow++ != row)
                throw new IllegalStateException();

            Counter<ByteArray> counter = topNCounterIterator.next();
            int offset = counter.getItem().offset();
            for (int i = 0; i < dimensionEncodings.length; i++) {
                String colValue = dimensionEncodings[i].decode(counter.getItem().array(), offset,
                        dimensionEncodings[i].getLengthOfEncoding());
                tuple.setDimensionValue(literalTupleIdx[i], colValue);
                offset += dimensionEncodings[i].getLengthOfEncoding();
            }
            tuple.setMeasureValue(numericTupleIdx, counter.getCount());
        }
    };
}
 

public CubeTupleConverter(CubeSegment cubeSeg, Cuboid cuboid, //
        Set<TblColRef> selectedDimensions, Set<FunctionDesc> selectedMetrics, int[] gtColIdx, TupleInfo returnTupleInfo) {
    this.cubeSeg = cubeSeg;
    this.cuboid = cuboid;
    this.gtColIdx = gtColIdx;
    this.tupleInfo = returnTupleInfo;
    this.derivedColFillers = Lists.newArrayList();

    nSelectedDims = selectedDimensions.size();
    tupleIdx = new int[selectedDimensions.size() + selectedMetrics.size()];

    // measure types don't have this many, but aligned length make programming easier
    measureTypes = new MeasureType[selectedDimensions.size() + selectedMetrics.size()];

    advMeasureFillers = Lists.newArrayListWithCapacity(1);
    advMeasureIndexInGTValues = Lists.newArrayListWithCapacity(1);
    usedLookupTables = Lists.newArrayList();
    eventTimezone = cubeSeg.getConfig().getStreamingDerivedTimeTimezone();
    autoJustByTimezone = eventTimezone.length() > 0
            && cubeSeg.getCubeDesc().getModel().getRootFactTable().getTableDesc().isStreamingTable();
    if (autoJustByTimezone) {
        logger.debug("Will ajust dimsension for Time Derived Column.");
        timeZoneOffset = TimeZone.getTimeZone(eventTimezone).getRawOffset();
    } else {
        timeZoneOffset = 0;
    }
    ////////////

    int i = 0;

    // pre-calculate dimension index mapping to tuple
    for (TblColRef dim : selectedDimensions) {
        tupleIdx[i] = tupleInfo.hasColumn(dim) ? tupleInfo.getColumnIndex(dim) : -1;
        if (TimeDerivedColumnType.isTimeDerivedColumn(dim.getName())
                && !TimeDerivedColumnType.isTimeDerivedColumnAboveDayLevel(dim.getName())) {
            timestampColumn.add(tupleIdx[i]);
        }
        i++;
    }

    for (FunctionDesc metric : selectedMetrics) {
        if (metric.needRewriteField()) {
            String rewriteFieldName = metric.getRewriteFieldName();
            tupleIdx[i] = tupleInfo.hasField(rewriteFieldName) ? tupleInfo.getFieldIndex(rewriteFieldName) : -1;
        } else {
            // a non-rewrite metrics (like sum, or dimension playing as metrics) is like a dimension column
            TblColRef col = metric.getParameter().getColRefs().get(0);
            tupleIdx[i] = tupleInfo.hasColumn(col) ? tupleInfo.getColumnIndex(col) : -1;
        }

        MeasureType<?> measureType = metric.getMeasureType();
        if (measureType.needAdvancedTupleFilling()) {
            Map<TblColRef, Dictionary<String>> dictionaryMap = buildDictionaryMap(measureType.getColumnsNeedDictionary(metric));
            advMeasureFillers.add(measureType.getAdvancedTupleFiller(metric, returnTupleInfo, dictionaryMap));
            advMeasureIndexInGTValues.add(i);
        } else {
            measureTypes[i] = measureType;
        }

        i++;
    }

    // prepare derived columns and filler
    Map<Array<TblColRef>, List<DeriveInfo>> hostToDerivedInfo = cuboid.getCubeDesc().getHostToDerivedInfo(cuboid.getColumns(), null);
    for (Entry<Array<TblColRef>, List<DeriveInfo>> entry : hostToDerivedInfo.entrySet()) {
        TblColRef[] hostCols = entry.getKey().data;
        for (DeriveInfo deriveInfo : entry.getValue()) {
            IDerivedColumnFiller filler = newDerivedColumnFiller(hostCols, deriveInfo);
            if (filler != null) {
                derivedColFillers.add(filler);
            }
        }
    }

    rowKeyDesc = cubeSeg.getCubeDesc().getRowkey();
}
 

public StreamingTupleConverter(ResponseResultSchema schema, TupleInfo returnTupleInfo) {
    this.tupleInfo = returnTupleInfo;
    dimCnt = schema.getDimensionCount();
    metricsCnt = schema.getMetricsCount();
    dimTupleIdx = new int[dimCnt];
    metricsTupleIdx = new int[metricsCnt];

    // measure types don't have this many, but aligned length make programming easier
    measureTypes = new MeasureType[metricsCnt];

    advMeasureFillers = Lists.newArrayListWithCapacity(1);
    advMeasureIndexInGTValues = Lists.newArrayListWithCapacity(1);

    int idx = 0;
    // pre-calculate dimension index mapping to tuple
    for (TblColRef dim : schema.getDimensions()) {
        dimTupleIdx[idx] = tupleInfo.hasColumn(dim) ? tupleInfo.getColumnIndex(dim) : -1;
        if (dim.getType().isDateTimeFamily() && TimeDerivedColumnType.isTimeDerivedColumn(dim.getName()))
            timestampColumn.add(dimTupleIdx[idx]);
        idx++;
    }

    idx = 0;
    for (FunctionDesc metric : schema.getMetrics()) {
        if (metric.needRewrite()) {
            String rewriteFieldName = metric.getRewriteFieldName();
            metricsTupleIdx[idx] = tupleInfo.hasField(rewriteFieldName) ? tupleInfo.getFieldIndex(rewriteFieldName) : -1;
        } else { // a non-rewrite metrics (like sum, or dimension playing as metrics) is like a dimension column
            TblColRef col = metric.getParameter().getColRefs().get(0);
            metricsTupleIdx[idx] = tupleInfo.hasColumn(col) ? tupleInfo.getColumnIndex(col) : -1;
        }

        MeasureType<?> measureType = metric.getMeasureType();
        if (measureType.needAdvancedTupleFilling()) {
            advMeasureFillers.add(measureType.getAdvancedTupleFiller(metric, returnTupleInfo, null));
            advMeasureIndexInGTValues.add(idx);
        } else {
            measureTypes[idx] = measureType;
        }
        idx++;
    }
}