org.apache.kylin.metadata.model.ParameterDesc Java Examples

public static MeasureDesc getMeasureSum(String column, String dataType) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_SUM);
    function.setParameter(parameterDesc);
    function.setReturnType(dataType.equals(HiveTableCreator.HiveTypeEnum.HDOUBLE.toString())
            ? HiveTableCreator.HiveTypeEnum.HDECIMAL.toString()
            : dataType);

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_SUM");
    result.setFunction(function);
    return result;
}
 

private List<FunctionDesc> buildAggregations() {
    List<FunctionDesc> functions = new ArrayList<FunctionDesc>();

    FunctionDesc f1 = new FunctionDesc();
    f1.setExpression("SUM");
    ParameterDesc p1 = new ParameterDesc();
    p1.setType("column");
    p1.setValue("PRICE");
    f1.setParameter(p1);
    functions.add(f1);

    FunctionDesc f2 = new FunctionDesc();
    f2.setExpression("COUNT_DISTINCT");
    ParameterDesc p2 = new ParameterDesc();
    p2.setType("column");
    p2.setValue("SELLER_ID");
    f2.setParameter(p2);
    functions.add(f2);

    return functions;
}
 

private byte[] getValueBytes(SplittedBytes[] splitBuffers, int measureIdx) {
    MeasureDesc desc = cubeDesc.getMeasures().get(measureIdx);
    ParameterDesc paramDesc = desc.getFunction().getParameter();
    int[] flatTableIdx = this.measureColumnIndice[measureIdx];

    byte[] result = null;

    // constant
    if (flatTableIdx == null) {
        result = Bytes.toBytes(paramDesc.getValue());
    }
    // column values
    else {
        for (int i = 0; i < flatTableIdx.length; i++) {
            SplittedBytes split = splitBuffers[flatTableIdx[i]];
            result = Arrays.copyOf(split.value, split.length);
        }
    }

    if (desc.getFunction().isCount()) {
        result = Bytes.toBytes("1");
    }

    return result;
}
 

public Set<FunctionDesc> simulateMetrics() {
        List<FunctionDesc> functions = Lists.newArrayList();
        TblColRef gmvCol = getColumnRef("STREAMING_V2_TABLE.GMV");

//        FunctionDesc f1 = new FunctionDesc();
//        f1.setExpression("SUM");
//        ParameterDesc p1 = ParameterDesc.newInstance(gmvCol);
//        f1.setParameter(p1);
//        f1.setReturnType("decimal(19,6)");
//        functions.add(f1);

        FunctionDesc f2 = new FunctionDesc();
        f2.setExpression(PercentileMeasureType.FUNC_PERCENTILE_APPROX);
        ParameterDesc p2 = ParameterDesc.newInstance(gmvCol);
        f2.setParameter(p2);
        f2.setReturnType("percentile(100)");
        functions.add(f2);

        return Sets.newHashSet(functions);
    }
 

private Object buildValueOf(int idxOfMeasure, List<String> row) {
    MeasureDesc measure = parsedStreamingCubeInfo.measureDescs[idxOfMeasure];
    FunctionDesc function = measure.getFunction();
    int[] colIdxOnFlatTable = parsedStreamingCubeInfo.intermediateTableDesc.getMeasureColumnIndexes()[idxOfMeasure];

    int paramCount = function.getParameterCount();
    String[] inputToMeasure = new String[paramCount];

    // pick up parameter values
    ParameterDesc param = function.getParameter();
    int paramColIdx = 0; // index among parameters of column type
    for (int i = 0; i < paramCount; i++, param = param.getNextParameter()) {
        String value;
        if (function.isCount()) {
            value = "1";
        } else if (param.isColumnType()) {
            value = row.get(colIdxOnFlatTable[paramColIdx++]);
        } else {
            value = param.getValue();
        }
        inputToMeasure[i] = value;
    }
    return parsedStreamingCubeInfo.measureIngesters[idxOfMeasure].valueOf(inputToMeasure, measure, dictionaryMap);
}
 

public List<FunctionDesc> buildAggregations() {
    List<FunctionDesc> functions = new ArrayList<FunctionDesc>();

    TblColRef priceCol = model.findColumn("DEFAULT.TEST_KYLIN_FACT.PRICE");
    TblColRef sellerCol = model.findColumn("DEFAULT.TEST_KYLIN_FACT.SELLER_ID");

    FunctionDesc f1 = FunctionDesc.newInstance("SUM", //
            ParameterDesc.newInstance(priceCol), "decimal(19,4)");
    functions.add(f1);

    FunctionDesc f2 = FunctionDesc.newInstance("COUNT_DISTINCT", //
            ParameterDesc.newInstance(sellerCol), "hllc(10)");
    functions.add(f2);

    return functions;
}
 

@Override
public void adjustSqlDigest(List<MeasureDesc> measureDescs, SQLDigest sqlDigest) {

    if (sqlDigest.isRawQuery) {
        for (MeasureDesc measureDesc : measureDescs) {
            if (!sqlDigest.involvedMeasure.contains(measureDesc)) {
                continue;
            }
            TblColRef col = this.getRawColumn(measureDesc.getFunction());
            ParameterDesc colParameter = ParameterDesc.newInstance(col);
            FunctionDesc rawFunc = FunctionDesc.newInstance("RAW", colParameter, null);

            if (sqlDigest.allColumns.contains(col)) {
                if (measureDesc.getFunction().equals(rawFunc)) {
                    FunctionDesc sumFunc = FunctionDesc.newInstance("SUM", colParameter, null);
                    sqlDigest.aggregations.remove(sumFunc);
                    sqlDigest.aggregations.add(rawFunc);
                    logger.info("Add RAW measure on column " + col);
                }
                if (!sqlDigest.metricColumns.contains(col)) {
                    sqlDigest.metricColumns.add(col);
                }
            }
        }
    }
}
 

public static MeasureDesc getMeasureSum(String column, String dataType) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_SUM);
    function.setParameter(parameterDesc);
    function.setReturnType(dataType.equals(HiveTableCreator.HiveTypeEnum.HDOUBLE.toString())
            ? HiveTableCreator.HiveTypeEnum.HDECIMAL.toString()
            : dataType);

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_SUM");
    result.setFunction(function);
    return result;
}
 

public Set<FunctionDesc> simulateMetrics() {
        List<FunctionDesc> functions = Lists.newArrayList();
        TblColRef gmvCol = getColumnRef("STREAMING_V2_TABLE.GMV");

//        FunctionDesc f1 = new FunctionDesc();
//        f1.setExpression("SUM");
//        ParameterDesc p1 = ParameterDesc.newInstance(gmvCol);
//        f1.setParameter(p1);
//        f1.setReturnType("decimal(19,6)");
//        functions.add(f1);

        FunctionDesc f2 = new FunctionDesc();
        f2.setExpression(PercentileMeasureType.FUNC_PERCENTILE_APPROX);
        ParameterDesc p2 = ParameterDesc.newInstance(gmvCol);
        f2.setParameter(p2);
        f2.setReturnType("percentile(100)");
        functions.add(f2);

        return Sets.newHashSet(functions);
    }
 

private Object buildValueOf(int idxOfMeasure, List<String> row) {
    MeasureDesc measure = parsedStreamingCubeInfo.measureDescs[idxOfMeasure];
    FunctionDesc function = measure.getFunction();
    int[] colIdxOnFlatTable = parsedStreamingCubeInfo.intermediateTableDesc.getMeasureColumnIndexes()[idxOfMeasure];

    int paramCount = function.getParameterCount();
    String[] inputToMeasure = new String[paramCount];

    // pick up parameter values
    ParameterDesc param = function.getParameter();
    int paramColIdx = 0; // index among parameters of column type
    for (int i = 0; i < paramCount; i++, param = param.getNextParameter()) {
        String value;
        if (function.isCount()) {
            value = "1";
        } else if (param.isColumnType()) {
            value = row.get(colIdxOnFlatTable[paramColIdx++]);
        } else {
            value = param.getValue();
        }
        inputToMeasure[i] = value;
    }
    return parsedStreamingCubeInfo.measureIngesters[idxOfMeasure].valueOf(inputToMeasure, measure, dictionaryMap);
}
 

public List<FunctionDesc> buildAggregations() {
    List<FunctionDesc> functions = new ArrayList<FunctionDesc>();

    TblColRef priceCol = model.findColumn("DEFAULT.TEST_KYLIN_FACT.PRICE");
    TblColRef sellerCol = model.findColumn("DEFAULT.TEST_KYLIN_FACT.SELLER_ID");

    FunctionDesc f1 = FunctionDesc.newInstance("SUM", //
            ParameterDesc.newInstance(priceCol), "decimal(19,4)");
    functions.add(f1);

    FunctionDesc f2 = FunctionDesc.newInstance("COUNT_DISTINCT", //
            ParameterDesc.newInstance(sellerCol), "hllc(10)");
    functions.add(f2);

    return functions;
}
 

@Override
public void adjustSqlDigest(List<MeasureDesc> measureDescs, SQLDigest sqlDigest) {

    if (sqlDigest.isRawQuery) {
        for (MeasureDesc measureDesc : measureDescs) {
            if (!sqlDigest.involvedMeasure.contains(measureDesc)) {
                continue;
            }
            TblColRef col = this.getRawColumn(measureDesc.getFunction());
            ParameterDesc colParameter = ParameterDesc.newInstance(col);
            FunctionDesc rawFunc = FunctionDesc.newInstance("RAW", colParameter, null);

            if (sqlDigest.allColumns.contains(col)) {
                if (measureDesc.getFunction().equals(rawFunc)) {
                    FunctionDesc sumFunc = FunctionDesc.newInstance("SUM", colParameter, null);
                    sqlDigest.aggregations.remove(sumFunc);
                    sqlDigest.aggregations.add(rawFunc);
                    logger.info("Add RAW measure on column " + col);
                }
                if (!sqlDigest.metricColumns.contains(col)) {
                    sqlDigest.metricColumns.add(col);
                }
            }
        }
    }
}
 

public FunctionDesc simulateMetric(String columnName, String funcName, String returnType) {
    TblColRef gmvCol = getColumnRef(columnName);

    FunctionDesc f1 = new FunctionDesc();
    f1.setExpression(funcName);
    ParameterDesc p1 = ParameterDesc.newInstance(gmvCol);
    f1.setParameter(p1);
    f1.setReturnType(returnType);
    return f1;
}
 

private static void tryDimensionAsMeasures(Collection<FunctionDesc> unmatchedAggregations, CapabilityResult result,
        Set<TblColRef> dimCols) {

    Iterator<FunctionDesc> it = unmatchedAggregations.iterator();
    while (it.hasNext()) {
        FunctionDesc functionDesc = it.next();

        // let calcite handle count
        if (functionDesc.isCount()) {
            logger.warn("No count measure found for column {}, will use count(1) to replace it, please note that it will count all value(include null value)", functionDesc.getParameter() == null ? "" : functionDesc.getParameter().getColRef().getName());
            it.remove();
            continue;
        }

        // calcite can do aggregation from columns on-the-fly
        ParameterDesc parameterDesc = functionDesc.getParameter();
        if (parameterDesc == null) {
            continue;
        }
        List<TblColRef> neededCols = parameterDesc.getColRefs();
        if (neededCols.size() > 0 && dimCols.containsAll(neededCols)
                && FunctionDesc.BUILT_IN_AGGREGATIONS.contains(functionDesc.getExpression())) {
            result.influences.add(new CapabilityResult.DimensionAsMeasure(functionDesc));
            it.remove();
            continue;
        }
    }
}
 

public static MeasureDesc getMeasurePercentile(String column) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(PercentileMeasureType.FUNC_PERCENTILE);
    function.setParameter(parameterDesc);
    function.setReturnType("percentile(100)");

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_PERCENTILE");
    result.setFunction(function);
    return result;
}
 

private static void tryDimensionAsMeasures(Collection<FunctionDesc> unmatchedAggregations, CapabilityResult result,
        Set<TblColRef> dimCols) {

    Iterator<FunctionDesc> it = unmatchedAggregations.iterator();
    while (it.hasNext()) {
        FunctionDesc functionDesc = it.next();

        // let calcite handle count
        if (functionDesc.isCount()) {
            logger.warn("No count measure found for column {}, will use count(1) to replace it, please note that it will count all value(include null value)", functionDesc.getParameter() == null ? "" : functionDesc.getParameter().getColRef().getName());
            it.remove();
            continue;
        }

        // calcite can do aggregation from columns on-the-fly
        ParameterDesc parameterDesc = functionDesc.getParameter();
        if (parameterDesc == null) {
            continue;
        }

        List<TblColRef> neededCols = functionDesc instanceof ExpressionDynamicFunctionDesc
                ? Lists.newArrayList(ExpressionColCollector
                        .collectColumns(((ExpressionDynamicFunctionDesc) functionDesc).getTupleExpression()))
                : parameterDesc.getColRefs();
        if (neededCols.size() > 0 && dimCols.containsAll(neededCols)
                && FunctionDesc.BUILT_IN_AGGREGATIONS.contains(functionDesc.getExpression())) {
            result.influences.add(new CapabilityResult.DimensionAsMeasure(functionDesc));
            it.remove();
            continue;
        }
    }
}
 

public String[] buildValueOf(int idxOfMeasure, String[] row) {
    MeasureDesc measure = cubeDesc.getMeasures().get(idxOfMeasure);
    FunctionDesc function = measure.getFunction();
    int[] colIdxOnFlatTable = flatDesc.getMeasureColumnIndexes()[idxOfMeasure];

    int paramCount = function.getParameterCount();
    List<String> inputToMeasure = Lists.newArrayListWithExpectedSize(paramCount);

    // pick up parameter values
    ParameterDesc param = function.getParameter();
    int colParamIdx = 0; // index among parameters of column type
    for (int i = 0; i < paramCount; i++, param = param.getNextParameter()) {
        String value;
        if (param.isColumnType()) {
            value = getCell(colIdxOnFlatTable[colParamIdx++], row);
            if (function.isCount() && value == null) {
                value = ZERO;
            } else if (function.isCount()) {
                value = ONE;
            }
        } else {
            value = param.getValue();
            if (function.isCount()) {
                value = ONE;
            }
        }
        inputToMeasure.add(value);
    }
    if (BitmapMapMeasureType.DATATYPE_BITMAP_MAP.equalsIgnoreCase(function.getReturnType())) {
        inputToMeasure.add(segmentStartTime);
    }

    return inputToMeasure.toArray(new String[inputToMeasure.size()]);
}
 

public static MeasureDesc getMeasureHLL(String column) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_COUNT_DISTINCT);
    function.setParameter(parameterDesc);
    function.setReturnType("hllc12");

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_HLL");
    result.setFunction(function);
    return result;
}
 

private Set<FunctionDesc> simulateMetrics() {
    List<FunctionDesc> functions = Lists.newArrayList();

    TblColRef gmvCol = cubeDesc.getModel().findColumn("STREAMING_V2_TABLE.GMV");
    FunctionDesc f1 = new FunctionDesc();
    f1.setExpression("SUM");
    ParameterDesc p1 = ParameterDesc.newInstance(gmvCol);
    f1.setParameter(p1);
    f1.setReturnType("decimal(19,6)");
    functions.add(f1);

    return Sets.newHashSet(functions);
}
 

public static MeasureDesc getMeasureMin(String column, String dataType) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_MIN);
    function.setParameter(parameterDesc);
    function.setReturnType(dataType);

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_MIN");
    result.setFunction(function);
    return result;
}
 

public List<FunctionDesc> buildAggregations1() {
    List<FunctionDesc> functions = new ArrayList<FunctionDesc>();

    TblColRef priceCol = model.findColumn("DEFAULT.TEST_KYLIN_FACTPRICE");

    FunctionDesc f1 = FunctionDesc.newInstance("SUM", //
            ParameterDesc.newInstance(priceCol), "decimal(19,4)");
    functions.add(f1);

    return functions;
}
 

public FunctionDesc simulateCountMetric() {
    FunctionDesc f1 = new FunctionDesc();
    f1.setExpression("COUNT");
    ParameterDesc p1 = ParameterDesc.newInstance("1");
    f1.setParameter(p1);
    f1.setReturnType("bigint");
    return f1;
}
 

public static MeasureDesc getMeasureMax(String column, String dataType) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_MAX);
    function.setParameter(parameterDesc);
    function.setReturnType(dataType);

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_MAX");
    result.setFunction(function);
    return result;
}
 

private byte[] getValueBytes(SplittedBytes[] splitBuffers, int measureIdx) {
    MeasureDesc desc = cubeDesc.getMeasures().get(measureIdx);
    FunctionDesc func = desc.getFunction();
    ParameterDesc paramDesc = func.getParameter();
    int[] flatTableIdx = intermediateTableDesc.getMeasureColumnIndexes()[measureIdx];

    byte[] result = null;

    // constant
    if (flatTableIdx == null) {
        result = Bytes.toBytes(paramDesc.getValue());
    }
    // column values
    else {
        // for multiple columns, their values are joined
        for (int i = 0; i < flatTableIdx.length; i++) {
            SplittedBytes split = splitBuffers[flatTableIdx[i]];
            if (result == null) {
                result = Arrays.copyOf(split.value, split.length);
            } else {
                byte[] newResult = new byte[result.length + split.length];
                System.arraycopy(result, 0, newResult, 0, result.length);
                System.arraycopy(split.value, 0, newResult, result.length, split.length);
                result = newResult;
            }
        }
    }

    if (func.isCount() || func.isHolisticCountDistinct()) {
        // note for holistic count distinct, this value will be ignored
        result = ONE;
    }

    if (isNull(result)) {
        result = null;
    }

    return result;
}
 

private void initMeasureColumns(Map<String, TableDesc> tables) {
    if (measures == null || measures.isEmpty()) {
        return;
    }

    TableDesc factTable = tables.get(getFactTable());
    for (MeasureDesc m : measures) {
        m.setName(m.getName().toUpperCase());

        if (m.getDependentMeasureRef() != null) {
            m.setDependentMeasureRef(m.getDependentMeasureRef().toUpperCase());
        }

        FunctionDesc f = m.getFunction();
        f.setExpression(f.getExpression().toUpperCase());
        f.setReturnDataType(DataType.getInstance(f.getReturnType()));

        ParameterDesc p = f.getParameter();
        p.normalizeColumnValue();

        if (p.isColumnType()) {
            ArrayList<TblColRef> colRefs = Lists.newArrayList();
            for (String cName : p.getValue().split("\\s*,\\s*")) {
                ColumnDesc sourceColumn = factTable.findColumnByName(cName);
                TblColRef colRef = new TblColRef(sourceColumn);
                colRefs.add(colRef);
                allColumns.add(colRef);
            }
            if (colRefs.isEmpty() == false)
                p.setColRefs(colRefs);
        }
    }
}
 

private void initMeasureColumns(Map<String, TableDesc> tables) {
    if (measures == null || measures.isEmpty()) {
        return;
    }

    TableDesc factTable = tables.get(getFactTable());
    for (MeasureDesc m : measures) {
        m.setName(m.getName().toUpperCase());

        if (m.getDependentMeasureRef() != null) {
            m.setDependentMeasureRef(m.getDependentMeasureRef().toUpperCase());
        }
        
        FunctionDesc f = m.getFunction();
        f.setExpression(f.getExpression().toUpperCase());
        f.setReturnDataType(DataType.getInstance(f.getReturnType()));

        ParameterDesc p = f.getParameter();
        p.normalizeColumnValue();

        if (p.isColumnType()) {
            ArrayList<TblColRef> colRefs = Lists.newArrayList();
            for (String cName : p.getValue().split("\\s*,\\s*")) {
                ColumnDesc sourceColumn = factTable.findColumnByName(cName);
                TblColRef colRef = new TblColRef(sourceColumn);
                colRefs.add(colRef);
                allColumns.add(colRef);
            }
            if (colRefs.isEmpty() == false)
                p.setColRefs(colRefs);
        }
        
        // verify holistic count distinct as a dependent measure
        if (m.isHolisticCountDistinct() && StringUtils.isBlank(m.getDependentMeasureRef())) {
            throw new IllegalStateException(m + " is a holistic count distinct but it has no DependentMeasureRef defined!");
        }
    }
}
 

public static MeasureDesc getMeasureCount() {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue("1");
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_CONSTANT);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_COUNT);
    function.setParameter(parameterDesc);
    function.setReturnType(HiveTableCreator.HiveTypeEnum.HBIGINT.toString());

    MeasureDesc result = new MeasureDesc();
    result.setName("_COUNT_");
    result.setFunction(function);
    return result;
}
 

public static MeasureDesc getMeasurePercentile(String column) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(PercentileMeasureType.FUNC_PERCENTILE);
    function.setParameter(parameterDesc);
    function.setReturnType("percentile(100)");

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_PERCENTILE");
    result.setFunction(function);
    return result;
}
 

public String[] buildValueOf(int idxOfMeasure, String[] row) {
    MeasureDesc measure = cubeDesc.getMeasures().get(idxOfMeasure);
    FunctionDesc function = measure.getFunction();
    int[] colIdxOnFlatTable = flatDesc.getMeasureColumnIndexes()[idxOfMeasure];

    int paramCount = function.getParameterCount();
    List<String> inputToMeasure = Lists.newArrayListWithExpectedSize(paramCount);

    // pick up parameter values
    ParameterDesc param = function.getParameter();
    int colParamIdx = 0; // index among parameters of column type
    for (int i = 0; i < paramCount; i++, param = param.getNextParameter()) {
        String value;
        if (param.isColumnType()) {
            value = getCell(colIdxOnFlatTable[colParamIdx++], row);
            if (function.isCount() && value == null) {
                value = ZERO;
            } else if (function.isCount()) {
                value = ONE;
            }
        } else {
            value = param.getValue();
            if (function.isCount()) {
                value = ONE;
            }
        }
        inputToMeasure.add(value);
    }

    return inputToMeasure.toArray(new String[inputToMeasure.size()]);
}
 

public static MeasureDesc getMeasureHLL(String column) {
    ParameterDesc parameterDesc = new ParameterDesc();
    parameterDesc.setValue(column);
    parameterDesc.setType(FunctionDesc.PARAMETER_TYPE_COLUMN);

    FunctionDesc function = new FunctionDesc();
    function.setExpression(FunctionDesc.FUNC_COUNT_DISTINCT);
    function.setParameter(parameterDesc);
    function.setReturnType("hllc12");

    MeasureDesc result = new MeasureDesc();
    result.setName(column + "_HLL");
    result.setFunction(function);
    return result;
}