Examples with RelDataTypeField org.apache.calcite.rel.type.RelDataTypeField used on opensource projects

Example 6 with RelDataTypeField

use of org.apache.calcite.rel.type.RelDataTypeField in project druid by druid-io.

the class SqlResource method doPost.

@POST
@Produces(MediaType.APPLICATION_JSON)
@Consumes(MediaType.APPLICATION_JSON)
public Response doPost(final SqlQuery sqlQuery) throws SQLException, IOException {
    // This is not integrated with the experimental authorization framework.
    // (Non-trivial since we don't know the dataSources up-front)
    final PlannerResult plannerResult;
    final DateTimeZone timeZone;
    try (final DruidPlanner planner = plannerFactory.createPlanner(sqlQuery.getContext())) {
        plannerResult = planner.plan(sqlQuery.getQuery());
        timeZone = planner.getPlannerContext().getTimeZone();
        // Remember which columns are time-typed, so we can emit ISO8601 instead of millis values.
        final List<RelDataTypeField> fieldList = plannerResult.rowType().getFieldList();
        final boolean[] timeColumns = new boolean[fieldList.size()];
        final boolean[] dateColumns = new boolean[fieldList.size()];
        for (int i = 0; i < fieldList.size(); i++) {
            final SqlTypeName sqlTypeName = fieldList.get(i).getType().getSqlTypeName();
            timeColumns[i] = sqlTypeName == SqlTypeName.TIMESTAMP;
            dateColumns[i] = sqlTypeName == SqlTypeName.DATE;
        }
        final Yielder<Object[]> yielder0 = Yielders.each(plannerResult.run());
        try {
            return Response.ok(new StreamingOutput() {

                @Override
                public void write(final OutputStream outputStream) throws IOException, WebApplicationException {
                    Yielder<Object[]> yielder = yielder0;
                    try (final JsonGenerator jsonGenerator = jsonMapper.getFactory().createGenerator(outputStream)) {
                        jsonGenerator.writeStartArray();
                        while (!yielder.isDone()) {
                            final Object[] row = yielder.get();
                            jsonGenerator.writeStartObject();
                            for (int i = 0; i < fieldList.size(); i++) {
                                final Object value;
                                if (timeColumns[i]) {
                                    value = ISODateTimeFormat.dateTime().print(Calcites.calciteTimestampToJoda((long) row[i], timeZone));
                                } else if (dateColumns[i]) {
                                    value = ISODateTimeFormat.dateTime().print(Calcites.calciteDateToJoda((int) row[i], timeZone));
                                } else {
                                    value = row[i];
                                }
                                jsonGenerator.writeObjectField(fieldList.get(i).getName(), value);
                            }
                            jsonGenerator.writeEndObject();
                            yielder = yielder.next(null);
                        }
                        jsonGenerator.writeEndArray();
                        jsonGenerator.flush();
                        // End with CRLF
                        outputStream.write('\r');
                        outputStream.write('\n');
                    } finally {
                        yielder.close();
                    }
                }
            }).build();
        } catch (Throwable e) {
            // make sure to close yielder if anything happened before starting to serialize the response.
            yielder0.close();
            throw Throwables.propagate(e);
        }
    } catch (Exception e) {
        log.warn(e, "Failed to handle query: %s", sqlQuery);
        final Exception exceptionToReport;
        if (e instanceof RelOptPlanner.CannotPlanException) {
            exceptionToReport = new ISE("Cannot build plan for query: %s", sqlQuery.getQuery());
        } else {
            exceptionToReport = e;
        }
        return Response.serverError().type(MediaType.APPLICATION_JSON_TYPE).entity(jsonMapper.writeValueAsBytes(QueryInterruptedException.wrapIfNeeded(exceptionToReport))).build();
    }
}

Example 7 with RelDataTypeField

use of org.apache.calcite.rel.type.RelDataTypeField in project druid by druid-io.

the class QueryMaker method executeTimeseries.

private Sequence<Object[]> executeTimeseries(final DruidQueryBuilder queryBuilder, final TimeseriesQuery query) {
    final List<RelDataTypeField> fieldList = queryBuilder.getRowType().getFieldList();
    final List<DimensionSpec> dimensions = queryBuilder.getGrouping().getDimensions();
    final String timeOutputName = dimensions.isEmpty() ? null : Iterables.getOnlyElement(dimensions).getOutputName();
    Hook.QUERY_PLAN.run(query);
    return Sequences.map(query.run(walker, Maps.<String, Object>newHashMap()), new Function<Result<TimeseriesResultValue>, Object[]>() {

        @Override
        public Object[] apply(final Result<TimeseriesResultValue> result) {
            final Map<String, Object> row = result.getValue().getBaseObject();
            final Object[] retVal = new Object[fieldList.size()];
            for (final RelDataTypeField field : fieldList) {
                final String outputName = queryBuilder.getRowOrder().get(field.getIndex());
                if (outputName.equals(timeOutputName)) {
                    retVal[field.getIndex()] = coerce(result.getTimestamp(), field.getType().getSqlTypeName());
                } else {
                    retVal[field.getIndex()] = coerce(row.get(outputName), field.getType().getSqlTypeName());
                }
            }
            return retVal;
        }
    });
}

Example 8 with RelDataTypeField

use of org.apache.calcite.rel.type.RelDataTypeField in project druid by druid-io.

the class DruidStatement method createColumnMetaData.

public static List<ColumnMetaData> createColumnMetaData(final RelDataType rowType) {
    final List<ColumnMetaData> columns = new ArrayList<>();
    List<RelDataTypeField> fieldList = rowType.getFieldList();
    for (int i = 0; i < fieldList.size(); i++) {
        RelDataTypeField field = fieldList.get(i);
        final ColumnMetaData.Rep rep = QueryMaker.rep(field.getType().getSqlTypeName());
        final ColumnMetaData.ScalarType columnType = ColumnMetaData.scalar(field.getType().getSqlTypeName().getJdbcOrdinal(), field.getType().getSqlTypeName().getName(), rep);
        columns.add(new ColumnMetaData(// ordinal
        i, // auto increment
        false, // case sensitive
        true, // searchable
        false, // currency
        false, field.getType().isNullable() ? DatabaseMetaData.columnNullable : // nullable
        DatabaseMetaData.columnNoNulls, // signed
        true, // display size
        field.getType().getPrecision(), // label
        field.getName(), // column name
        null, // schema name
        null, // precision
        field.getType().getPrecision(), // scale
        field.getType().getScale(), // table name
        null, // catalog name
        null, // avatica type
        columnType, // read only
        true, // writable
        false, // definitely writable
        false, // column class name
        columnType.columnClassName()));
    }
    return columns;
}

Example 9 with RelDataTypeField

use of org.apache.calcite.rel.type.RelDataTypeField in project flink by apache.

the class FlinkRelDecorrelator method decorrelateRel.

/**
	 * Rewrite LogicalProject.
	 *
	 * @param rel the project rel to rewrite
	 */
public Frame decorrelateRel(LogicalProject rel) {
    //
    // Rewrite logic:
    //
    // 1. Pass along any correlated variables coming from the input.
    //
    final RelNode oldInput = rel.getInput();
    Frame frame = getInvoke(oldInput, rel);
    if (frame == null) {
        // If input has not been rewritten, do not rewrite this rel.
        return null;
    }
    final List<RexNode> oldProjects = rel.getProjects();
    final List<RelDataTypeField> relOutput = rel.getRowType().getFieldList();
    // LogicalProject projects the original expressions,
    // plus any correlated variables the input wants to pass along.
    final List<Pair<RexNode, String>> projects = Lists.newArrayList();
    // and produce the correlated variables in the new output.
    if (cm.mapRefRelToCorVar.containsKey(rel)) {
        decorrelateInputWithValueGenerator(rel);
        // The old input should be mapped to the LogicalJoin created by
        // rewriteInputWithValueGenerator().
        frame = map.get(oldInput);
    }
    // LogicalProject projects the original expressions
    final Map<Integer, Integer> mapOldToNewOutputPos = Maps.newHashMap();
    int newPos;
    for (newPos = 0; newPos < oldProjects.size(); newPos++) {
        projects.add(newPos, Pair.of(decorrelateExpr(oldProjects.get(newPos)), relOutput.get(newPos).getName()));
        mapOldToNewOutputPos.put(newPos, newPos);
    }
    // Project any correlated variables the input wants to pass along.
    final SortedMap<Correlation, Integer> mapCorVarToOutputPos = new TreeMap<>();
    for (Map.Entry<Correlation, Integer> entry : frame.corVarOutputPos.entrySet()) {
        projects.add(RexInputRef.of2(entry.getValue(), frame.r.getRowType().getFieldList()));
        mapCorVarToOutputPos.put(entry.getKey(), newPos);
        newPos++;
    }
    RelNode newProject = RelOptUtil.createProject(frame.r, projects, false);
    return register(rel, newProject, mapOldToNewOutputPos, mapCorVarToOutputPos);
}

Example 10 with RelDataTypeField

use of org.apache.calcite.rel.type.RelDataTypeField in project flink by apache.

the class FlinkRelDecorrelator method decorrelateRel.

/**
	 * Rewrite Correlator into a left outer join.
	 *
	 * @param rel Correlator
	 */
public Frame decorrelateRel(LogicalCorrelate rel) {
    //
    // Rewrite logic:
    //
    // The original left input will be joined with the new right input that
    // has generated correlated variables propagated up. For any generated
    // cor vars that are not used in the join key, pass them along to be
    // joined later with the CorrelatorRels that produce them.
    //
    // the right input to Correlator should produce correlated variables
    final RelNode oldLeft = rel.getInput(0);
    final RelNode oldRight = rel.getInput(1);
    final Frame leftFrame = getInvoke(oldLeft, rel);
    final Frame rightFrame = getInvoke(oldRight, rel);
    if (leftFrame == null || rightFrame == null) {
        // If any input has not been rewritten, do not rewrite this rel.
        return null;
    }
    if (rightFrame.corVarOutputPos.isEmpty()) {
        return null;
    }
    assert rel.getRequiredColumns().cardinality() <= rightFrame.corVarOutputPos.keySet().size();
    // Change correlator rel into a join.
    // Join all the correlated variables produced by this correlator rel
    // with the values generated and propagated from the right input
    final SortedMap<Correlation, Integer> corVarOutputPos = new TreeMap<>(rightFrame.corVarOutputPos);
    final List<RexNode> conditions = new ArrayList<>();
    final List<RelDataTypeField> newLeftOutput = leftFrame.r.getRowType().getFieldList();
    int newLeftFieldCount = newLeftOutput.size();
    final List<RelDataTypeField> newRightOutput = rightFrame.r.getRowType().getFieldList();
    for (Map.Entry<Correlation, Integer> rightOutputPos : Lists.newArrayList(corVarOutputPos.entrySet())) {
        final Correlation corVar = rightOutputPos.getKey();
        if (!corVar.corr.equals(rel.getCorrelationId())) {
            continue;
        }
        final int newLeftPos = leftFrame.oldToNewOutputPos.get(corVar.field);
        final int newRightPos = rightOutputPos.getValue();
        conditions.add(rexBuilder.makeCall(SqlStdOperatorTable.EQUALS, RexInputRef.of(newLeftPos, newLeftOutput), new RexInputRef(newLeftFieldCount + newRightPos, newRightOutput.get(newRightPos).getType())));
        // remove this cor var from output position mapping
        corVarOutputPos.remove(corVar);
    }
    // vars that are not used in the join key.
    for (Correlation corVar : corVarOutputPos.keySet()) {
        int newPos = corVarOutputPos.get(corVar) + newLeftFieldCount;
        corVarOutputPos.put(corVar, newPos);
    }
    // then add any cor var from the left input. Do not need to change
    // output positions.
    corVarOutputPos.putAll(leftFrame.corVarOutputPos);
    // Create the mapping between the output of the old correlation rel
    // and the new join rel
    final Map<Integer, Integer> mapOldToNewOutputPos = Maps.newHashMap();
    int oldLeftFieldCount = oldLeft.getRowType().getFieldCount();
    int oldRightFieldCount = oldRight.getRowType().getFieldCount();
    assert rel.getRowType().getFieldCount() == oldLeftFieldCount + oldRightFieldCount;
    // Left input positions are not changed.
    mapOldToNewOutputPos.putAll(leftFrame.oldToNewOutputPos);
    // Right input positions are shifted by newLeftFieldCount.
    for (int i = 0; i < oldRightFieldCount; i++) {
        mapOldToNewOutputPos.put(i + oldLeftFieldCount, rightFrame.oldToNewOutputPos.get(i) + newLeftFieldCount);
    }
    final RexNode condition = RexUtil.composeConjunction(rexBuilder, conditions, false);
    RelNode newJoin = LogicalJoin.create(leftFrame.r, rightFrame.r, condition, ImmutableSet.<CorrelationId>of(), rel.getJoinType().toJoinType());
    return register(rel, newJoin, mapOldToNewOutputPos, corVarOutputPos);
}