Exemple #1
0
 public List<Type> guessTypes() throws SQLException {
   final ResultSetMetaData metaData = resultSet.getMetaData();
   final int columnCount = metaData.getColumnCount();
   assert this.types == null || this.types.size() == columnCount;
   List<Type> types = new ArrayList<Type>();
   for (int i = 0; i < columnCount; i++) {
     final Type suggestedType = this.types == null ? null : this.types.get(i);
     types.add(guessType(suggestedType, metaData, i));
   }
   return types;
 }
Exemple #2
0
 /**
  * Chooses the most appropriate type for accessing the values of a column in a result set.
  *
  * <p>NOTE: It is possible that this method is driver-dependent. If this is the case, move it to
  * {@link mondrian.spi.Dialect}.
  *
  * @param suggestedType Type suggested by Level.internalType attribute
  * @param metaData Result set metadata
  * @param i Column ordinal (0-based)
  * @return Best client type
  * @throws SQLException on error
  */
 public static Type guessType(Type suggestedType, ResultSetMetaData metaData, int i)
     throws SQLException {
   if (suggestedType != null) {
     return suggestedType;
   }
   final String typeName = metaData.getColumnTypeName(i + 1);
   final int columnType = metaData.getColumnType(i + 1);
   int precision;
   int scale;
   switch (columnType) {
     case Types.SMALLINT:
     case Types.INTEGER:
     case Types.BOOLEAN:
       return Type.INT;
     case Types.NUMERIC:
       precision = metaData.getPrecision(i + 1);
       scale = metaData.getScale(i + 1);
       if (precision == 0
           && (scale == 0 || scale == -127)
           && (typeName.equalsIgnoreCase("NUMBER") || (typeName.equalsIgnoreCase("NUMERIC")))) {
         // In Oracle and Greenplum the NUMBER/NUMERIC datatype with no
         // precision or scale (not NUMBER(p) or NUMBER(p, s)) means
         // floating point. Some drivers represent this with scale 0,
         // others scale -127.
         //
         // There is a further problem. In GROUPING SETS queries, Oracle
         // loosens the type of columns compared to mere GROUP BY
         // queries. We need integer GROUP BY columns to remain integers,
         // otherwise the segments won't be found; but if we convert
         // measure (whose column names are like "m0", "m1") to integers,
         // data loss will occur.
         final String columnName = metaData.getColumnName(i + 1);
         if (columnName.startsWith("m")) {
           return Type.OBJECT;
         } else {
           return Type.INT;
         }
       }
       return getDecimalType(precision, scale);
     case Types.DECIMAL:
       precision = metaData.getPrecision(i + 1);
       scale = metaData.getScale(i + 1);
       return getDecimalType(precision, scale);
     case Types.DOUBLE:
     case Types.FLOAT:
       return Type.DOUBLE;
     default:
       return Type.OBJECT;
   }
 }