use of org.apache.druid.query.groupby.orderby.OrderByColumnSpec in project druid by druid-io.
the class GroupByQueryRunnerTest method testGroupByLimitPushDownPostAggNotSupported.
@Test
public void testGroupByLimitPushDownPostAggNotSupported() {
if (!config.getDefaultStrategy().equals(GroupByStrategySelector.STRATEGY_V2)) {
return;
}
expectedException.expect(UnsupportedOperationException.class);
expectedException.expectMessage("Limit push down when sorting by a post aggregator is not supported.");
GroupByQuery query = makeQueryBuilder().setDataSource(QueryRunnerTestHelper.DATA_SOURCE).setGranularity(QueryRunnerTestHelper.ALL_GRAN).setDimensions(new DefaultDimensionSpec(QueryRunnerTestHelper.MARKET_DIMENSION, "marketalias")).setInterval(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).setLimitSpec(new DefaultLimitSpec(Collections.singletonList(new OrderByColumnSpec("constant", OrderByColumnSpec.Direction.DESCENDING)), 2)).setAggregatorSpecs(QueryRunnerTestHelper.ROWS_COUNT).setPostAggregatorSpecs(Collections.singletonList(new ConstantPostAggregator("constant", 1))).overrideContext(ImmutableMap.of(GroupByQueryConfig.CTX_KEY_FORCE_LIMIT_PUSH_DOWN, true)).build();
GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
}
use of org.apache.druid.query.groupby.orderby.OrderByColumnSpec in project druid by druid-io.
the class GroupByQueryRunnerTest method testGroupByWithHavingOnHyperUnique.
@Test
public void testGroupByWithHavingOnHyperUnique() {
GroupByQuery query = makeQueryBuilder().setDataSource(QueryRunnerTestHelper.DATA_SOURCE).setGranularity(QueryRunnerTestHelper.ALL_GRAN).setDimensions(new DefaultDimensionSpec(QueryRunnerTestHelper.MARKET_DIMENSION, QueryRunnerTestHelper.MARKET_DIMENSION)).setInterval(QueryRunnerTestHelper.FULL_ON_INTERVAL_SPEC).setLimitSpec(new DefaultLimitSpec(Collections.singletonList(new OrderByColumnSpec(QueryRunnerTestHelper.UNIQUE_METRIC, OrderByColumnSpec.Direction.DESCENDING)), 3)).setHavingSpec(new GreaterThanHavingSpec(QueryRunnerTestHelper.UNIQUE_METRIC, 8)).setAggregatorSpecs(QueryRunnerTestHelper.QUALITY_UNIQUES).setPostAggregatorSpecs(Collections.singletonList(new HyperUniqueFinalizingPostAggregator(QueryRunnerTestHelper.HYPER_UNIQUE_FINALIZING_POST_AGG_METRIC, QueryRunnerTestHelper.UNIQUE_METRIC))).build();
List<ResultRow> expectedResults = Collections.singletonList(makeRow(query, "1970-01-01T00:00:00.000Z", "market", "spot", QueryRunnerTestHelper.UNIQUE_METRIC, QueryRunnerTestHelper.UNIQUES_9, QueryRunnerTestHelper.HYPER_UNIQUE_FINALIZING_POST_AGG_METRIC, QueryRunnerTestHelper.UNIQUES_9));
Iterable<ResultRow> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
TestHelper.assertExpectedObjects(expectedResults, results, "order-limit");
}
use of org.apache.druid.query.groupby.orderby.OrderByColumnSpec in project druid by druid-io.
the class GroupByQueryRunnerTest method testMultiValueDimensionAsArrayWithOtherDims.
@Test
public void testMultiValueDimensionAsArrayWithOtherDims() {
// array types don't work with group by v1
if (config.getDefaultStrategy().equals(GroupByStrategySelector.STRATEGY_V1)) {
expectedException.expect(UnsupportedOperationException.class);
expectedException.expectMessage("GroupBy v1 only supports dimensions with an outputType of STRING");
}
// Cannot vectorize due to multi-value dimensions.
cannotVectorize();
GroupByQuery query = makeQueryBuilder().setDataSource(QueryRunnerTestHelper.DATA_SOURCE).setQuerySegmentSpec(QueryRunnerTestHelper.FIRST_TO_THIRD).setVirtualColumns(new ExpressionVirtualColumn("v0", "mv_to_array(placementish)", ColumnType.STRING_ARRAY, ExprMacroTable.nil())).setDimensions(new DefaultDimensionSpec("v0", "alias", ColumnType.STRING_ARRAY), new DefaultDimensionSpec("quality", "quality")).setLimitSpec(new DefaultLimitSpec(ImmutableList.of(new OrderByColumnSpec("alias", OrderByColumnSpec.Direction.ASCENDING, StringComparators.LEXICOGRAPHIC), new OrderByColumnSpec("quality", OrderByColumnSpec.Direction.ASCENDING, StringComparators.LEXICOGRAPHIC)), Integer.MAX_VALUE - 1)).setAggregatorSpecs(QueryRunnerTestHelper.ROWS_COUNT, new LongSumAggregatorFactory("idx", "index")).setGranularity(QueryRunnerTestHelper.ALL_GRAN).build();
List<ResultRow> expectedResults = Arrays.asList(makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("a", "preferred"), "quality", "automotive", "rows", 2L, "idx", 282L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("b", "preferred"), "quality", "business", "rows", 2L, "idx", 230L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("e", "preferred"), "quality", "entertainment", "rows", 2L, "idx", 324L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("h", "preferred"), "quality", "health", "rows", 2L, "idx", 233L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("m", "preferred"), "quality", "mezzanine", "rows", 6L, "idx", 5317L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("n", "preferred"), "quality", "news", "rows", 2L, "idx", 235L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("p", "preferred"), "quality", "premium", "rows", 6L, "idx", 5405L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("preferred", "t"), "quality", "technology", "rows", 2L, "idx", 175L), makeRow(query, "2011-04-01", "alias", ComparableStringArray.of("preferred", "t"), "quality", "travel", "rows", 2L, "idx", 245L));
Iterable<ResultRow> results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
TestHelper.assertExpectedObjects(expectedResults, results, "multi-value-dims-groupby-arrays");
query = makeQueryBuilder().setDataSource(QueryRunnerTestHelper.DATA_SOURCE).setQuerySegmentSpec(QueryRunnerTestHelper.FIRST_TO_THIRD).setVirtualColumns(new ExpressionVirtualColumn("v0", "mv_to_array(placementish)", ColumnType.STRING_ARRAY, ExprMacroTable.nil())).setDimensions(new DefaultDimensionSpec("v0", "alias", ColumnType.STRING_ARRAY), new DefaultDimensionSpec("quality", "quality")).setLimitSpec(new DefaultLimitSpec(ImmutableList.of(new OrderByColumnSpec("alias", OrderByColumnSpec.Direction.DESCENDING, StringComparators.LEXICOGRAPHIC), new OrderByColumnSpec("quality", OrderByColumnSpec.Direction.DESCENDING, StringComparators.LEXICOGRAPHIC)), Integer.MAX_VALUE - 1)).setAggregatorSpecs(QueryRunnerTestHelper.ROWS_COUNT, new LongSumAggregatorFactory("idx", "index")).setGranularity(QueryRunnerTestHelper.ALL_GRAN).build();
Collections.reverse(expectedResults);
results = GroupByQueryRunnerTestHelper.runQuery(factory, runner, query);
TestHelper.assertExpectedObjects(expectedResults, results, "multi-value-dims-groupby-arrays-descending");
}
use of org.apache.druid.query.groupby.orderby.OrderByColumnSpec in project druid by druid-io.
the class DruidQuery method toTopNQuery.
/**
* Return this query as a TopN query, or null if this query is not compatible with TopN.
*
* @return query or null
*/
@Nullable
private TopNQuery toTopNQuery(final QueryFeatureInspector queryFeatureInspector) {
// Must be allowed by the QueryMaker.
if (!queryFeatureInspector.feature(QueryFeature.CAN_RUN_TOPN)) {
return null;
}
// Must have GROUP BY one column, no GROUPING SETS, ORDER BY ≤ 1 column, LIMIT > 0 and ≤ maxTopNLimit,
// no OFFSET, no HAVING.
final boolean topNOk = grouping != null && grouping.getDimensions().size() == 1 && !grouping.getSubtotals().hasEffect(grouping.getDimensionSpecs()) && sorting != null && (sorting.getOrderBys().size() <= 1 && sorting.getOffsetLimit().hasLimit() && sorting.getOffsetLimit().getLimit() > 0 && sorting.getOffsetLimit().getLimit() <= plannerContext.getPlannerConfig().getMaxTopNLimit() && !sorting.getOffsetLimit().hasOffset()) && grouping.getHavingFilter() == null;
if (!topNOk) {
return null;
}
final DimensionSpec dimensionSpec = Iterables.getOnlyElement(grouping.getDimensions()).toDimensionSpec();
// grouping col cannot be type array
if (dimensionSpec.getOutputType().isArray()) {
return null;
}
final OrderByColumnSpec limitColumn;
if (sorting.getOrderBys().isEmpty()) {
limitColumn = new OrderByColumnSpec(dimensionSpec.getOutputName(), OrderByColumnSpec.Direction.ASCENDING, Calcites.getStringComparatorForValueType(dimensionSpec.getOutputType()));
} else {
limitColumn = Iterables.getOnlyElement(sorting.getOrderBys());
}
final TopNMetricSpec topNMetricSpec;
if (limitColumn.getDimension().equals(dimensionSpec.getOutputName())) {
// DimensionTopNMetricSpec is exact; always return it even if allowApproximate is false.
final DimensionTopNMetricSpec baseMetricSpec = new DimensionTopNMetricSpec(null, limitColumn.getDimensionComparator());
topNMetricSpec = limitColumn.getDirection() == OrderByColumnSpec.Direction.ASCENDING ? baseMetricSpec : new InvertedTopNMetricSpec(baseMetricSpec);
} else if (plannerContext.getPlannerConfig().isUseApproximateTopN()) {
// ORDER BY metric
final NumericTopNMetricSpec baseMetricSpec = new NumericTopNMetricSpec(limitColumn.getDimension());
topNMetricSpec = limitColumn.getDirection() == OrderByColumnSpec.Direction.ASCENDING ? new InvertedTopNMetricSpec(baseMetricSpec) : baseMetricSpec;
} else {
return null;
}
final Pair<DataSource, Filtration> dataSourceFiltrationPair = getFiltration(dataSource, filter, virtualColumnRegistry);
final DataSource newDataSource = dataSourceFiltrationPair.lhs;
final Filtration filtration = dataSourceFiltrationPair.rhs;
final List<PostAggregator> postAggregators = new ArrayList<>(grouping.getPostAggregators());
if (sorting.getProjection() != null) {
postAggregators.addAll(sorting.getProjection().getPostAggregators());
}
return new TopNQuery(newDataSource, getVirtualColumns(true), dimensionSpec, topNMetricSpec, Ints.checkedCast(sorting.getOffsetLimit().getLimit()), filtration.getQuerySegmentSpec(), filtration.getDimFilter(), Granularities.ALL, grouping.getAggregatorFactories(), postAggregators, ImmutableSortedMap.copyOf(plannerContext.getQueryContext()));
}
use of org.apache.druid.query.groupby.orderby.OrderByColumnSpec in project druid by druid-io.
the class DruidQuery method computeSorting.
@Nonnull
private static Sorting computeSorting(final PartialDruidQuery partialQuery, final PlannerContext plannerContext, final RowSignature rowSignature, @Nullable final VirtualColumnRegistry virtualColumnRegistry) {
final Sort sort = Preconditions.checkNotNull(partialQuery.getSort(), "sort");
final Project sortProject = partialQuery.getSortProject();
// Extract limit and offset.
final OffsetLimit offsetLimit = OffsetLimit.fromSort(sort);
// Extract orderBy column specs.
final List<OrderByColumnSpec> orderBys = new ArrayList<>(sort.getChildExps().size());
for (int sortKey = 0; sortKey < sort.getChildExps().size(); sortKey++) {
final RexNode sortExpression = sort.getChildExps().get(sortKey);
final RelFieldCollation collation = sort.getCollation().getFieldCollations().get(sortKey);
final OrderByColumnSpec.Direction direction;
final StringComparator comparator;
if (collation.getDirection() == RelFieldCollation.Direction.ASCENDING) {
direction = OrderByColumnSpec.Direction.ASCENDING;
} else if (collation.getDirection() == RelFieldCollation.Direction.DESCENDING) {
direction = OrderByColumnSpec.Direction.DESCENDING;
} else {
throw new ISE("Don't know what to do with direction[%s]", collation.getDirection());
}
final SqlTypeName sortExpressionType = sortExpression.getType().getSqlTypeName();
if (SqlTypeName.NUMERIC_TYPES.contains(sortExpressionType) || SqlTypeName.TIMESTAMP == sortExpressionType || SqlTypeName.DATE == sortExpressionType) {
comparator = StringComparators.NUMERIC;
} else {
comparator = StringComparators.LEXICOGRAPHIC;
}
if (sortExpression.isA(SqlKind.INPUT_REF)) {
final RexInputRef ref = (RexInputRef) sortExpression;
final String fieldName = rowSignature.getColumnName(ref.getIndex());
orderBys.add(new OrderByColumnSpec(fieldName, direction, comparator));
} else {
// We don't support sorting by anything other than refs which actually appear in the query result.
throw new CannotBuildQueryException(sort, sortExpression);
}
}
// Extract any post-sort Projection.
final Projection projection;
if (sortProject == null) {
projection = null;
} else if (partialQuery.getAggregate() == null) {
if (virtualColumnRegistry == null) {
throw new ISE("Must provide 'virtualColumnRegistry' for pre-aggregation Projection!");
}
projection = Projection.preAggregation(sortProject, plannerContext, rowSignature, virtualColumnRegistry);
} else {
projection = Projection.postAggregation(sortProject, plannerContext, rowSignature, "s");
}
return Sorting.create(orderBys, offsetLimit, projection);
}
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