Examples with RelDataType org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType used on opensource projects

Example 21 with RelDataType

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType in project herddb by diennea.

the class CalcitePlanner method planValues.

private PlannerOp planValues(EnumerableValues op) {
    List<List<CompiledSQLExpression>> tuples = new ArrayList<>(op.getTuples().size());
    RelDataType rowType = op.getRowType();
    List<RelDataTypeField> fieldList = rowType.getFieldList();
    Column[] columns = new Column[fieldList.size()];
    for (ImmutableList<RexLiteral> tuple : op.getTuples()) {
        List<CompiledSQLExpression> row = new ArrayList<>(tuple.size());
        for (RexLiteral node : tuple) {
            CompiledSQLExpression exp = SQLExpressionCompiler.compileExpression(node);
            row.add(exp);
        }
        tuples.add(row);
    }
    int i = 0;
    String[] fieldNames = new String[fieldList.size()];
    for (RelDataTypeField field : fieldList) {
        Column col = Column.column(field.getName(), convertToHerdType(field.getType()));
        fieldNames[i] = field.getName();
        columns[i++] = col;
    }
    return new ValuesOp(manager.getNodeId(), fieldNames, columns, tuples);
}

Example 22 with RelDataType

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType in project herddb by diennea.

the class CalcitePlanner method planEnumerableNestedLoopJoin.

private PlannerOp planEnumerableNestedLoopJoin(EnumerableNestedLoopJoin op, RelDataType rowType) {
    PlannerOp left = convertRelNode(op.getLeft(), null, false, false);
    PlannerOp right = convertRelNode(op.getRight(), null, false, false);
    CompiledSQLExpression condition = SQLExpressionCompiler.compileExpression(op.getCondition());
    final RelDataType _rowType = rowType == null ? op.getRowType() : rowType;
    List<RelDataTypeField> fieldList = _rowType.getFieldList();
    Column[] columns = new Column[fieldList.size()];
    String[] fieldNames = new String[columns.length];
    int i = 0;
    for (RelDataTypeField field : fieldList) {
        Column col = Column.column(field.getName().toLowerCase(), convertToHerdType(field.getType()));
        fieldNames[i] = col.name;
        columns[i++] = col;
    }
    return new NestedLoopJoinOp(fieldNames, columns, left, right, condition, op.getJoinType(), false);
}

Example 23 with RelDataType

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType in project calcite by apache.

the class CassandraTable method query.

/**
 * Executes a CQL query on the underlying table.
 *
 * @param session Cassandra session
 * @param fields List of fields to project
 * @param predicates A list of predicates which should be used in the query
 * @return Enumerator of results
 */
public Enumerable<Object> query(final Session session, List<Map.Entry<String, Class>> fields, final List<Map.Entry<String, String>> selectFields, List<String> predicates, List<String> order, final Integer offset, final Integer fetch) {
    // Build the type of the resulting row based on the provided fields
    final RelDataTypeFactory typeFactory = new SqlTypeFactoryImpl(RelDataTypeSystem.DEFAULT);
    final RelDataTypeFactory.Builder fieldInfo = typeFactory.builder();
    final RelDataType rowType = getRowType(typeFactory);
    Function1<String, Void> addField = new Function1<String, Void>() {

        public Void apply(String fieldName) {
            SqlTypeName typeName = rowType.getField(fieldName, true, false).getType().getSqlTypeName();
            fieldInfo.add(fieldName, typeFactory.createSqlType(typeName)).nullable(true);
            return null;
        }
    };
    if (selectFields.isEmpty()) {
        for (Map.Entry<String, Class> field : fields) {
            addField.apply(field.getKey());
        }
    } else {
        for (Map.Entry<String, String> field : selectFields) {
            addField.apply(field.getKey());
        }
    }
    final RelProtoDataType resultRowType = RelDataTypeImpl.proto(fieldInfo.build());
    // Construct the list of fields to project
    final String selectString;
    if (selectFields.isEmpty()) {
        selectString = "*";
    } else {
        selectString = Util.toString(new Iterable<String>() {

            public Iterator<String> iterator() {
                final Iterator<Map.Entry<String, String>> selectIterator = selectFields.iterator();
                return new Iterator<String>() {

                    @Override
                    public boolean hasNext() {
                        return selectIterator.hasNext();
                    }

                    @Override
                    public String next() {
                        Map.Entry<String, String> entry = selectIterator.next();
                        return entry.getKey() + " AS " + entry.getValue();
                    }

                    @Override
                    public void remove() {
                        throw new UnsupportedOperationException();
                    }
                };
            }
        }, "", ", ", "");
    }
    // Combine all predicates conjunctively
    String whereClause = "";
    if (!predicates.isEmpty()) {
        whereClause = " WHERE ";
        whereClause += Util.toString(predicates, "", " AND ", "");
    }
    // Build and issue the query and return an Enumerator over the results
    StringBuilder queryBuilder = new StringBuilder("SELECT ");
    queryBuilder.append(selectString);
    queryBuilder.append(" FROM \"" + columnFamily + "\"");
    queryBuilder.append(whereClause);
    if (!order.isEmpty()) {
        queryBuilder.append(Util.toString(order, " ORDER BY ", ", ", ""));
    }
    int limit = offset;
    if (fetch >= 0) {
        limit += fetch;
    }
    if (limit > 0) {
        queryBuilder.append(" LIMIT " + limit);
    }
    queryBuilder.append(" ALLOW FILTERING");
    final String query = queryBuilder.toString();
    return new AbstractEnumerable<Object>() {

        public Enumerator<Object> enumerator() {
            final ResultSet results = session.execute(query);
            // Skip results until we get to the right offset
            int skip = 0;
            Enumerator<Object> enumerator = new CassandraEnumerator(results, resultRowType);
            while (skip < offset && enumerator.moveNext()) {
                skip++;
            }
            return enumerator;
        }
    };
}

Example 24 with RelDataType

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType in project calcite by apache.

the class TableScanNode method createEnumerable.

private static TableScanNode createEnumerable(Compiler compiler, TableScan rel, Enumerable<Row> enumerable, final ImmutableIntList acceptedProjects, List<RexNode> rejectedFilters, final ImmutableIntList rejectedProjects) {
    if (!rejectedFilters.isEmpty()) {
        final RexNode filter = RexUtil.composeConjunction(rel.getCluster().getRexBuilder(), rejectedFilters, false);
        assert filter != null;
        // Re-map filter for the projects that have been applied already
        final RexNode filter2;
        final RelDataType inputRowType;
        if (acceptedProjects == null) {
            filter2 = filter;
            inputRowType = rel.getRowType();
        } else {
            final Mapping mapping = Mappings.target(acceptedProjects, rel.getTable().getRowType().getFieldCount());
            filter2 = RexUtil.apply(mapping, filter);
            final RelDataTypeFactory.Builder builder = rel.getCluster().getTypeFactory().builder();
            final List<RelDataTypeField> fieldList = rel.getTable().getRowType().getFieldList();
            for (int acceptedProject : acceptedProjects) {
                builder.add(fieldList.get(acceptedProject));
            }
            inputRowType = builder.build();
        }
        final Scalar condition = compiler.compile(ImmutableList.of(filter2), inputRowType);
        final Context context = compiler.createContext();
        enumerable = enumerable.where(new Predicate1<Row>() {

            @Override
            public boolean apply(Row row) {
                context.values = row.getValues();
                Boolean b = (Boolean) condition.execute(context);
                return b != null && b;
            }
        });
    }
    if (rejectedProjects != null) {
        enumerable = enumerable.select(new Function1<Row, Row>() {

            final Object[] values = new Object[rejectedProjects.size()];

            @Override
            public Row apply(Row row) {
                final Object[] inValues = row.getValues();
                for (int i = 0; i < rejectedProjects.size(); i++) {
                    values[i] = inValues[rejectedProjects.get(i)];
                }
                return Row.asCopy(values);
            }
        });
    }
    return new TableScanNode(compiler, rel, enumerable);
}

Example 25 with RelDataType

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.type.RelDataType in project calcite by apache.

the class JdbcSchema method getRelDataType.

RelProtoDataType getRelDataType(DatabaseMetaData metaData, String catalogName, String schemaName, String tableName) throws SQLException {
    final ResultSet resultSet = metaData.getColumns(catalogName, schemaName, tableName, null);
    // Temporary type factory, just for the duration of this method. Allowable
    // because we're creating a proto-type, not a type; before being used, the
    // proto-type will be copied into a real type factory.
    final RelDataTypeFactory typeFactory = new SqlTypeFactoryImpl(RelDataTypeSystem.DEFAULT);
    final RelDataTypeFactory.Builder fieldInfo = typeFactory.builder();
    while (resultSet.next()) {
        final String columnName = resultSet.getString(4);
        final int dataType = resultSet.getInt(5);
        final String typeString = resultSet.getString(6);
        final int precision;
        final int scale;
        switch(SqlType.valueOf(dataType)) {
            case TIMESTAMP:
            case TIME:
                // SCALE
                precision = resultSet.getInt(9);
                scale = 0;
                break;
            default:
                // SIZE
                precision = resultSet.getInt(7);
                // SCALE
                scale = resultSet.getInt(9);
                break;
        }
        RelDataType sqlType = sqlType(typeFactory, dataType, precision, scale, typeString);
        boolean nullable = resultSet.getInt(11) != DatabaseMetaData.columnNoNulls;
        fieldInfo.add(columnName, sqlType).nullable(nullable);
    }
    resultSet.close();
    return RelDataTypeImpl.proto(fieldInfo.build());
}