How to use

isDimension

method

in

org.apache.carbondata.core.metadata.schema.table.column.CarbonColumn

/**
 * @return true if column is measure, otherwise false
 */
public Boolean isMeasure() {
 return !isDimension();
}

public static boolean[] getNoDictionaryMapping(CarbonColumn[] carbonColumns) {
 List<Boolean> noDictionaryMapping = new ArrayList<Boolean>();
 for (CarbonColumn column : carbonColumns) {
  // for  complex type need to break the loop
  if (column.isComplex()) {
   break;
  }
  if (!column.hasEncoding(Encoding.DICTIONARY) && column.isDimension()) {
   noDictionaryMapping.add(true);
  } else if (column.isDimension()) {
   noDictionaryMapping.add(false);
  }
 }
 return ArrayUtils
   .toPrimitive(noDictionaryMapping.toArray(new Boolean[noDictionaryMapping.size()]));
}

/**
 * Preparing the boolean [] to map whether the dimension use inverted index or not.
 */
public static boolean[] getIsUseInvertedIndex(DataField[] fields) {
 List<Boolean> isUseInvertedIndexList = new ArrayList<Boolean>();
 for (DataField field : fields) {
  if (field.getColumn().isUseInvertedIndex() && field.getColumn().isDimension()) {
   isUseInvertedIndexList.add(true);
  } else if (field.getColumn().isDimension()) {
   isUseInvertedIndexList.add(false);
  }
 }
 return ArrayUtils
   .toPrimitive(isUseInvertedIndexList.toArray(new Boolean[isUseInvertedIndexList.size()]));
}

public DataType[] getMeasureDataType() {
 List<Integer> measureIndexes = new ArrayList<>(dataFields.length);
 int measureCount = 0;
 for (int i = 0; i < dataFields.length; i++) {
  if (!dataFields[i].getColumn().isDimension()) {
   measureIndexes.add(i);
   measureCount++;
  }
 }
 DataType[] type = new DataType[measureCount];
 for (int i = 0; i < type.length; i++) {
  type[i] = dataFields[measureIndexes.get(i)].getColumn().getDataType();
 }
 return type;
}

/**
 * Preparing the boolean [] to map whether the dimension is no Dictionary or not.
 */
public static boolean[] getNoDictionaryMapping(DataField[] fields) {
 List<Boolean> noDictionaryMapping = new ArrayList<Boolean>();
 for (DataField field : fields) {
  // for  complex type need to break the loop
  if (field.getColumn().isComplex()) {
   break;
  }
  if (!field.hasDictionaryEncoding() && field.getColumn().isDimension()) {
   noDictionaryMapping.add(true);
  } else if (field.getColumn().isDimension()) {
   noDictionaryMapping.add(false);
  }
 }
 return ArrayUtils
   .toPrimitive(noDictionaryMapping.toArray(new Boolean[noDictionaryMapping.size()]));
}

/**
 * Preparing the boolean [] to map whether the dimension is varchar data type or not.
 */
public static boolean[] getIsVarcharColumnMapping(DataField[] fields) {
 List<Boolean> isVarcharColumnMapping = new ArrayList<Boolean>();
 for (DataField field : fields) {
  // for complex type need to break the loop
  if (field.getColumn().isComplex()) {
   break;
  }
  if (field.getColumn().isDimension()) {
   isVarcharColumnMapping.add(
     field.getColumn().getColumnSchema().getDataType() == DataTypes.VARCHAR);
  }
 }
 return ArrayUtils.toPrimitive(
   isVarcharColumnMapping.toArray(new Boolean[isVarcharColumnMapping.size()]));
}

/**
 * Get the data types of the no dictionary and the complex dimensions of the table
 *
 * @return
 */
public CarbonColumn[] getNoDictAndComplexDimensions() {
 List<Integer> noDicOrCompIndexes = new ArrayList<>(dataFields.length);
 int noDicCount = 0;
 for (int i = 0; i < dataFields.length; i++) {
  if (dataFields[i].getColumn().isDimension() && (
    !(dataFields[i].getColumn().hasEncoding(Encoding.DICTIONARY)) || dataFields[i].getColumn()
      .isComplex())) {
   noDicOrCompIndexes.add(i);
   noDicCount++;
  }
 }
 CarbonColumn[] dims = new CarbonColumn[noDicCount];
 for (int i = 0; i < dims.length; i++) {
  dims[i] = dataFields[noDicOrCompIndexes.get(i)].getColumn();
 }
 return dims;
}

public static void updateIndexOfColumnExpression(Expression exp, int dimOridnalMax) {
 // if expression is null, not require to update index.
 if (exp == null) {
  return;
 }
 if (exp.getChildren() == null || exp.getChildren().size() == 0) {
  if (exp instanceof ColumnExpression) {
   ColumnExpression ce = (ColumnExpression) exp;
   CarbonColumn column = ce.getCarbonColumn();
   if (column.isDimension()) {
    ce.setColIndex(column.getOrdinal());
   } else {
    ce.setColIndex(dimOridnalMax + column.getOrdinal());
   }
  }
 } else {
  if (exp.getChildren().size() > 0) {
   List<Expression> children = exp.getChildren();
   for (int i = 0; i < children.size(); i++) {
    updateIndexOfColumnExpression(children.get(i), dimOridnalMax);
   }
  }
 }
}

public void setDataFields(DataField[] dataFields) {
 this.dataFields = dataFields;
 // set counts for each column category
 for (DataField dataField : dataFields) {
  CarbonColumn column = dataField.getColumn();
  if (column.isDimension()) {
   dimensionCount++;
   if (column.isComplex()) {
    if (!dataField.hasDictionaryEncoding()) {
     complexNonDictionaryColumnCount++;
    } else {
     complexDictionaryColumnCount++;
    }
   } else if (!dataField.hasDictionaryEncoding()) {
    noDictionaryCount++;
   }
  }
  if (column.isMeasure()) {
   measureCount++;
  }
 }
}

filterMap = new int[storageColumns.length];
for (int i = 0; i < storageColumns.length; i++) {
 if (storageColumns[i].isDimension()) {
  if (isFiltlerDimensions[storageColumns[i].getOrdinal()]) {
   isRequired[i] = true;

 logHolder.getColumnMessageMap().put(dataField.getColumn().getColName(), message);
if (dataField.getColumn().isDimension()) {
 logHolder.setReason(message);
try {
 if (dataField.getColumn().isDimension()) {
  String dateFormat = null;
  if (dataField.getColumn().getDataType() == DataTypes.DATE) {

 throws IOException {
if (dataField.getColumn().isDimension()) {
 if (dataField.getColumn().hasEncoding(Encoding.DIRECT_DICTIONARY) &&
   !dataField.getColumn().isComplex()) {

for (int i = 0; i < carbonColumns.length; i++) {
 CarbonColumn carbonColumn = carbonColumns[i];
 if (carbonColumn.isDimension()) {
  if (carbonColumn.hasEncoding(Encoding.DIRECT_DICTIONARY)) {
   DirectDictionaryGenerator generator = DirectDictionaryKeyGeneratorFactory