#include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include namespace DB { namespace ErrorCodes { extern const int TOO_DEEP_SUBQUERIES; extern const int SAMPLING_NOT_SUPPORTED; extern const int ILLEGAL_FINAL; extern const int ILLEGAL_PREWHERE; extern const int TOO_MANY_COLUMNS; extern const int LOGICAL_ERROR; extern const int NOT_IMPLEMENTED; extern const int PARAMETER_OUT_OF_BOUND; extern const int INVALID_LIMIT_EXPRESSION; extern const int INVALID_WITH_FILL_EXPRESSION; extern const int INVALID_SETTING_VALUE; } /// Assumes `storage` is set and the table filter (row-level security) is not empty. String InterpreterSelectQuery::generateFilterActions( ExpressionActionsPtr & actions, const ASTPtr & row_policy_filter, const Names & prerequisite_columns) const { const auto & db_name = table_id.getDatabaseName(); const auto & table_name = table_id.getTableName(); /// TODO: implement some AST builders for this kind of stuff ASTPtr query_ast = std::make_shared(); auto * select_ast = query_ast->as(); select_ast->setExpression(ASTSelectQuery::Expression::SELECT, std::make_shared()); auto expr_list = select_ast->select(); // The first column is our filter expression. expr_list->children.push_back(row_policy_filter); /// Keep columns that are required after the filter actions. for (const auto & column_str : prerequisite_columns) { ParserExpression expr_parser; expr_list->children.push_back(parseQuery(expr_parser, column_str, 0, context->getSettingsRef().max_parser_depth)); } select_ast->setExpression(ASTSelectQuery::Expression::TABLES, std::make_shared()); auto tables = select_ast->tables(); auto tables_elem = std::make_shared(); auto table_expr = std::make_shared(); tables->children.push_back(tables_elem); tables_elem->table_expression = table_expr; tables_elem->children.push_back(table_expr); table_expr->database_and_table_name = createTableIdentifier(db_name, table_name); table_expr->children.push_back(table_expr->database_and_table_name); /// Using separate expression analyzer to prevent any possible alias injection auto syntax_result = SyntaxAnalyzer(*context).analyzeSelect(query_ast, SyntaxAnalyzerResult({}, storage)); SelectQueryExpressionAnalyzer analyzer(query_ast, syntax_result, *context); actions = analyzer.simpleSelectActions(); return expr_list->children.at(0)->getColumnName(); } InterpreterSelectQuery::InterpreterSelectQuery( const ASTPtr & query_ptr_, const Context & context_, const SelectQueryOptions & options_, const Names & required_result_column_names_) : InterpreterSelectQuery(query_ptr_, context_, nullptr, std::nullopt, nullptr, options_, required_result_column_names_) { } InterpreterSelectQuery::InterpreterSelectQuery( const ASTPtr & query_ptr_, const Context & context_, const BlockInputStreamPtr & input_, const SelectQueryOptions & options_) : InterpreterSelectQuery(query_ptr_, context_, input_, std::nullopt, nullptr, options_.copy().noSubquery()) {} InterpreterSelectQuery::InterpreterSelectQuery( const ASTPtr & query_ptr_, const Context & context_, Pipe input_pipe_, const SelectQueryOptions & options_) : InterpreterSelectQuery(query_ptr_, context_, nullptr, std::move(input_pipe_), nullptr, options_.copy().noSubquery()) {} InterpreterSelectQuery::InterpreterSelectQuery( const ASTPtr & query_ptr_, const Context & context_, const StoragePtr & storage_, const SelectQueryOptions & options_) : InterpreterSelectQuery(query_ptr_, context_, nullptr, std::nullopt, storage_, options_.copy().noSubquery()) {} InterpreterSelectQuery::~InterpreterSelectQuery() = default; /** There are no limits on the maximum size of the result for the subquery. * Since the result of the query is not the result of the entire query. */ static Context getSubqueryContext(const Context & context) { Context subquery_context = context; Settings subquery_settings = context.getSettings(); subquery_settings.max_result_rows = 0; subquery_settings.max_result_bytes = 0; /// The calculation of extremes does not make sense and is not necessary (if you do it, then the extremes of the subquery can be taken for whole query). subquery_settings.extremes = false; subquery_context.setSettings(subquery_settings); return subquery_context; } static void rewriteMultipleJoins(ASTPtr & query, const TablesWithColumns & tables, const String & database, const Settings & settings) { ASTSelectQuery & select = query->as(); Aliases aliases; if (ASTPtr with = select.with()) QueryAliasesNoSubqueriesVisitor(aliases).visit(with); QueryAliasesNoSubqueriesVisitor(aliases).visit(select.select()); CrossToInnerJoinVisitor::Data cross_to_inner{tables, aliases, database}; CrossToInnerJoinVisitor(cross_to_inner).visit(query); size_t rewriter_version = settings.multiple_joins_rewriter_version; if (!rewriter_version || rewriter_version > 2) throw Exception("Bad multiple_joins_rewriter_version setting value: " + settings.multiple_joins_rewriter_version.toString(), ErrorCodes::INVALID_SETTING_VALUE); JoinToSubqueryTransformVisitor::Data join_to_subs_data{tables, aliases, rewriter_version}; JoinToSubqueryTransformVisitor(join_to_subs_data).visit(query); } InterpreterSelectQuery::InterpreterSelectQuery( const ASTPtr & query_ptr_, const Context & context_, const BlockInputStreamPtr & input_, std::optional input_pipe_, const StoragePtr & storage_, const SelectQueryOptions & options_, const Names & required_result_column_names) : options(options_) /// NOTE: the query almost always should be cloned because it will be modified during analysis. , query_ptr(options.modify_inplace ? query_ptr_ : query_ptr_->clone()) , context(std::make_shared(context_)) , storage(storage_) , input(input_) , input_pipe(std::move(input_pipe_)) , log(&Poco::Logger::get("InterpreterSelectQuery")) { checkStackSize(); initSettings(); const Settings & settings = context->getSettingsRef(); if (settings.max_subquery_depth && options.subquery_depth > settings.max_subquery_depth) throw Exception("Too deep subqueries. Maximum: " + settings.max_subquery_depth.toString(), ErrorCodes::TOO_DEEP_SUBQUERIES); bool has_input = input || input_pipe; if (input) { /// Read from prepared input. source_header = input->getHeader(); } else if (input_pipe) { /// Read from prepared input. source_header = input_pipe->getHeader(); } JoinedTables joined_tables(getSubqueryContext(*context), getSelectQuery()); if (!has_input && !storage) storage = joined_tables.getLeftTableStorage(); if (storage) { table_lock = storage->lockStructureForShare( false, context->getInitialQueryId(), context->getSettingsRef().lock_acquire_timeout); table_id = storage->getStorageID(); } if (has_input || !joined_tables.resolveTables()) joined_tables.makeFakeTable(storage, source_header); /// Rewrite JOINs if (!has_input && joined_tables.tablesCount() > 1) { rewriteMultipleJoins(query_ptr, joined_tables.tablesWithColumns(), context->getCurrentDatabase(), settings); joined_tables.reset(getSelectQuery()); joined_tables.resolveTables(); if (storage && joined_tables.isLeftTableSubquery()) { /// Rewritten with subquery. Free storage locks here. storage = {}; table_lock.release(); table_id = StorageID::createEmpty(); } } if (!has_input) { interpreter_subquery = joined_tables.makeLeftTableSubquery(options.subquery()); if (interpreter_subquery) source_header = interpreter_subquery->getSampleBlock(); } joined_tables.rewriteDistributedInAndJoins(query_ptr); max_streams = settings.max_threads; ASTSelectQuery & query = getSelectQuery(); std::shared_ptr table_join = joined_tables.makeTableJoin(query); ASTPtr row_policy_filter; if (storage) row_policy_filter = context->getRowPolicyCondition(table_id.getDatabaseName(), table_id.getTableName(), RowPolicy::SELECT_FILTER); StorageView * view = nullptr; if (storage) view = dynamic_cast(storage.get()); auto analyze = [&] (bool try_move_to_prewhere) { /// Allow push down and other optimizations for VIEW: replace with subquery and rewrite it. ASTPtr view_table; if (view) view->replaceWithSubquery(getSelectQuery(), view_table); syntax_analyzer_result = SyntaxAnalyzer(*context).analyzeSelect( query_ptr, SyntaxAnalyzerResult(source_header.getNamesAndTypesList(), storage), options, joined_tables.tablesWithColumns(), required_result_column_names, table_join); if (view) { /// Restore original view name. Save rewritten subquery for future usage in StorageView. query_info.view_query = view->restoreViewName(getSelectQuery(), view_table); view = nullptr; } if (try_move_to_prewhere && storage && !row_policy_filter && query.where() && !query.prewhere() && !query.final()) { /// PREWHERE optimization: transfer some condition from WHERE to PREWHERE if enabled and viable if (const auto * merge_tree = dynamic_cast(storage.get())) { SelectQueryInfo current_info; current_info.query = query_ptr; current_info.syntax_analyzer_result = syntax_analyzer_result; MergeTreeWhereOptimizer{current_info, *context, *merge_tree, syntax_analyzer_result->requiredSourceColumns(), log}; } } /// Save scalar sub queries's results in the query context if (!options.only_analyze && context->hasQueryContext()) for (const auto & it : syntax_analyzer_result->getScalars()) context->getQueryContext().addScalar(it.first, it.second); query_analyzer = std::make_unique( query_ptr, syntax_analyzer_result, *context, NameSet(required_result_column_names.begin(), required_result_column_names.end()), !options.only_analyze, options); if (!options.only_analyze) { if (query.sampleSize() && (input || input_pipe || !storage || !storage->supportsSampling())) throw Exception("Illegal SAMPLE: table doesn't support sampling", ErrorCodes::SAMPLING_NOT_SUPPORTED); if (query.final() && (input || input_pipe || !storage || !storage->supportsFinal())) throw Exception((!input && !input_pipe && storage) ? "Storage " + storage->getName() + " doesn't support FINAL" : "Illegal FINAL", ErrorCodes::ILLEGAL_FINAL); if (query.prewhere() && (input || input_pipe || !storage || !storage->supportsPrewhere())) throw Exception((!input && !input_pipe && storage) ? "Storage " + storage->getName() + " doesn't support PREWHERE" : "Illegal PREWHERE", ErrorCodes::ILLEGAL_PREWHERE); /// Save the new temporary tables in the query context for (const auto & it : query_analyzer->getExternalTables()) if (!context->tryResolveStorageID({"", it.first}, Context::ResolveExternal)) context->addExternalTable(it.first, std::move(*it.second)); } if (!options.only_analyze || options.modify_inplace) { if (syntax_analyzer_result->rewrite_subqueries) { /// remake interpreter_subquery when PredicateOptimizer rewrites subqueries and main table is subquery interpreter_subquery = joined_tables.makeLeftTableSubquery(options.subquery()); } } if (interpreter_subquery) { /// If there is an aggregation in the outer query, WITH TOTALS is ignored in the subquery. if (query_analyzer->hasAggregation()) interpreter_subquery->ignoreWithTotals(); } required_columns = syntax_analyzer_result->requiredSourceColumns(); if (storage) { source_header = storage->getSampleBlockForColumns(required_columns); /// Fix source_header for filter actions. if (row_policy_filter) { filter_info = std::make_shared(); filter_info->column_name = generateFilterActions(filter_info->actions, row_policy_filter, required_columns); source_header = storage->getSampleBlockForColumns(filter_info->actions->getRequiredColumns()); } } if (!options.only_analyze && storage && filter_info && query.prewhere()) throw Exception("PREWHERE is not supported if the table is filtered by row-level security expression", ErrorCodes::ILLEGAL_PREWHERE); /// Calculate structure of the result. result_header = getSampleBlockImpl(); }; analyze(settings.optimize_move_to_prewhere); bool need_analyze_again = false; if (analysis_result.prewhere_constant_filter_description.always_false || analysis_result.prewhere_constant_filter_description.always_true) { if (analysis_result.prewhere_constant_filter_description.always_true) query.setExpression(ASTSelectQuery::Expression::PREWHERE, {}); else query.setExpression(ASTSelectQuery::Expression::PREWHERE, std::make_shared(0u)); need_analyze_again = true; } if (analysis_result.where_constant_filter_description.always_false || analysis_result.where_constant_filter_description.always_true) { if (analysis_result.where_constant_filter_description.always_true) query.setExpression(ASTSelectQuery::Expression::WHERE, {}); else query.setExpression(ASTSelectQuery::Expression::WHERE, std::make_shared(0u)); need_analyze_again = true; } if (query.prewhere() && query.where()) { /// Filter block in WHERE instead to get better performance query.setExpression(ASTSelectQuery::Expression::WHERE, makeASTFunction("and", query.prewhere()->clone(), query.where()->clone())); need_analyze_again = true; } if (need_analyze_again) { /// Do not try move conditions to PREWHERE for the second time. /// Otherwise, we won't be able to fallback from inefficient PREWHERE to WHERE later. analyze(/* try_move_to_prewhere = */ false); } /// If there is no WHERE, filter blocks as usual if (query.prewhere() && !query.where()) analysis_result.prewhere_info->need_filter = true; const StorageID & left_table_id = joined_tables.leftTableID(); if (left_table_id) context->checkAccess(AccessType::SELECT, left_table_id, required_columns); /// Remove limits for some tables in the `system` database. if (left_table_id.database_name == "system") { static const boost::container::flat_set system_tables_ignoring_quota{"quotas", "quota_limits", "quota_usage", "quotas_usage", "one"}; if (system_tables_ignoring_quota.count(left_table_id.table_name)) { options.ignore_quota = true; options.ignore_limits = true; } } /// Blocks used in expression analysis contains size 1 const columns for constant folding and /// null non-const columns to avoid useless memory allocations. However, a valid block sample /// requires all columns to be of size 0, thus we need to sanitize the block here. sanitizeBlock(result_header); } Block InterpreterSelectQuery::getSampleBlock() { return result_header; } BlockIO InterpreterSelectQuery::execute() { BlockIO res; executeImpl(res.pipeline, input, std::move(input_pipe)); res.pipeline.addInterpreterContext(context); res.pipeline.addStorageHolder(storage); /// We must guarantee that result structure is the same as in getSampleBlock() if (!blocksHaveEqualStructure(res.pipeline.getHeader(), result_header)) { res.pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, result_header, ConvertingTransform::MatchColumnsMode::Name); }); } return res; } Block InterpreterSelectQuery::getSampleBlockImpl() { if (storage && !options.only_analyze) from_stage = storage->getQueryProcessingStage(*context, options.to_stage, query_ptr); /// Do I need to perform the first part of the pipeline - running on remote servers during distributed processing. bool first_stage = from_stage < QueryProcessingStage::WithMergeableState && options.to_stage >= QueryProcessingStage::WithMergeableState; /// Do I need to execute the second part of the pipeline - running on the initiating server during distributed processing. bool second_stage = from_stage <= QueryProcessingStage::WithMergeableState && options.to_stage > QueryProcessingStage::WithMergeableState; analysis_result = ExpressionAnalysisResult( *query_analyzer, first_stage, second_stage, options.only_analyze, filter_info, source_header); if (options.to_stage == QueryProcessingStage::Enum::FetchColumns) { auto header = source_header; if (analysis_result.prewhere_info) { analysis_result.prewhere_info->prewhere_actions->execute(header); header = materializeBlock(header); if (analysis_result.prewhere_info->remove_prewhere_column) header.erase(analysis_result.prewhere_info->prewhere_column_name); } return header; } if (options.to_stage == QueryProcessingStage::Enum::WithMergeableState) { if (!analysis_result.need_aggregate) return analysis_result.before_order_and_select->getSampleBlock(); auto header = analysis_result.before_aggregation->getSampleBlock(); Block res; for (const auto & key : query_analyzer->aggregationKeys()) res.insert({nullptr, header.getByName(key.name).type, key.name}); for (const auto & aggregate : query_analyzer->aggregates()) { size_t arguments_size = aggregate.argument_names.size(); DataTypes argument_types(arguments_size); for (size_t j = 0; j < arguments_size; ++j) argument_types[j] = header.getByName(aggregate.argument_names[j]).type; DataTypePtr type = std::make_shared(aggregate.function, argument_types, aggregate.parameters); res.insert({nullptr, type, aggregate.column_name}); } return res; } return analysis_result.final_projection->getSampleBlock(); } static Field getWithFillFieldValue(const ASTPtr & node, const Context & context) { const auto & [field, type] = evaluateConstantExpression(node, context); if (!isColumnedAsNumber(type)) throw Exception("Illegal type " + type->getName() + " of WITH FILL expression, must be numeric type", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); return field; } static FillColumnDescription getWithFillDescription(const ASTOrderByElement & order_by_elem, const Context & context) { FillColumnDescription descr; if (order_by_elem.fill_from) descr.fill_from = getWithFillFieldValue(order_by_elem.fill_from, context); if (order_by_elem.fill_to) descr.fill_to = getWithFillFieldValue(order_by_elem.fill_to, context); if (order_by_elem.fill_step) descr.fill_step = getWithFillFieldValue(order_by_elem.fill_step, context); else descr.fill_step = order_by_elem.direction; if (applyVisitor(FieldVisitorAccurateEquals(), descr.fill_step, Field{0})) throw Exception("WITH FILL STEP value cannot be zero", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); if (order_by_elem.direction == 1) { if (applyVisitor(FieldVisitorAccurateLess(), descr.fill_step, Field{0})) throw Exception("WITH FILL STEP value cannot be negative for sorting in ascending direction", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); if (!descr.fill_from.isNull() && !descr.fill_to.isNull() && applyVisitor(FieldVisitorAccurateLess(), descr.fill_to, descr.fill_from)) { throw Exception("WITH FILL TO value cannot be less than FROM value for sorting in ascending direction", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); } } else { if (applyVisitor(FieldVisitorAccurateLess(), Field{0}, descr.fill_step)) throw Exception("WITH FILL STEP value cannot be positive for sorting in descending direction", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); if (!descr.fill_from.isNull() && !descr.fill_to.isNull() && applyVisitor(FieldVisitorAccurateLess(), descr.fill_from, descr.fill_to)) { throw Exception("WITH FILL FROM value cannot be less than TO value for sorting in descending direction", ErrorCodes::INVALID_WITH_FILL_EXPRESSION); } } return descr; } static SortDescription getSortDescription(const ASTSelectQuery & query, const Context & context) { SortDescription order_descr; order_descr.reserve(query.orderBy()->children.size()); SpecialSort special_sort = context.getSettings().special_sort.value; for (const auto & elem : query.orderBy()->children) { String name = elem->children.front()->getColumnName(); const auto & order_by_elem = elem->as(); std::shared_ptr collator; if (order_by_elem.collation) collator = std::make_shared(order_by_elem.collation->as().value.get()); if (order_by_elem.with_fill) { FillColumnDescription fill_desc = getWithFillDescription(order_by_elem, context); order_descr.emplace_back(name, order_by_elem.direction, order_by_elem.nulls_direction, collator, special_sort, true, fill_desc); } else order_descr.emplace_back(name, order_by_elem.direction, order_by_elem.nulls_direction, collator, special_sort); } return order_descr; } static SortDescription getSortDescriptionFromGroupBy(const ASTSelectQuery & query) { SortDescription order_descr; order_descr.reserve(query.groupBy()->children.size()); for (const auto & elem : query.groupBy()->children) { String name = elem->getColumnName(); order_descr.emplace_back(name, 1, 1); } return order_descr; } static UInt64 getLimitUIntValue(const ASTPtr & node, const Context & context, const std::string & expr) { const auto & [field, type] = evaluateConstantExpression(node, context); if (!isNativeNumber(type)) throw Exception("Illegal type " + type->getName() + " of " + expr + " expression, must be numeric type", ErrorCodes::INVALID_LIMIT_EXPRESSION); Field converted = convertFieldToType(field, DataTypeUInt64()); if (converted.isNull()) throw Exception("The value " + applyVisitor(FieldVisitorToString(), field) + " of " + expr + " expression is not representable as UInt64", ErrorCodes::INVALID_LIMIT_EXPRESSION); return converted.safeGet(); } static std::pair getLimitLengthAndOffset(const ASTSelectQuery & query, const Context & context) { UInt64 length = 0; UInt64 offset = 0; if (query.limitLength()) { length = getLimitUIntValue(query.limitLength(), context, "LIMIT"); if (query.limitOffset() && length) offset = getLimitUIntValue(query.limitOffset(), context, "OFFSET"); } else if (query.limitOffset()) offset = getLimitUIntValue(query.limitOffset(), context, "OFFSET"); return {length, offset}; } static UInt64 getLimitForSorting(const ASTSelectQuery & query, const Context & context) { /// Partial sort can be done if there is LIMIT but no DISTINCT or LIMIT BY, neither ARRAY JOIN. if (!query.distinct && !query.limitBy() && !query.limit_with_ties && !query.arrayJoinExpressionList() && query.limitLength()) { auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, context); return limit_length + limit_offset; } return 0; } void InterpreterSelectQuery::executeImpl(QueryPipeline & pipeline, const BlockInputStreamPtr & prepared_input, std::optional prepared_pipe) { /** Streams of data. When the query is executed in parallel, we have several data streams. * If there is no GROUP BY, then perform all operations before ORDER BY and LIMIT in parallel, then * if there is an ORDER BY, then glue the streams using ResizeProcessor, and then MergeSorting transforms, * if not, then glue it using ResizeProcessor, * then apply LIMIT. * If there is GROUP BY, then we will perform all operations up to GROUP BY, inclusive, in parallel; * a parallel GROUP BY will glue streams into one, * then perform the remaining operations with one resulting stream. */ /// Now we will compose block streams that perform the necessary actions. auto & query = getSelectQuery(); const Settings & settings = context->getSettingsRef(); auto & expressions = analysis_result; const auto & subqueries_for_sets = query_analyzer->getSubqueriesForSets(); bool intermediate_stage = false; if (options.only_analyze) { ReadNothingStep read_nothing(DataStream{.header = source_header}); read_nothing.initializePipeline(pipeline); if (expressions.prewhere_info) { FilterStep prewhere_step( DataStream{.header = pipeline.getHeader()}, expressions.prewhere_info->prewhere_actions, expressions.prewhere_info->prewhere_column_name, expressions.prewhere_info->remove_prewhere_column); prewhere_step.setStepDescription("PREWHERE"); prewhere_step.transformPipeline(pipeline); // To remove additional columns in dry run // For example, sample column which can be removed in this stage if (expressions.prewhere_info->remove_columns_actions) { ExpressionStep remove_columns( DataStream{.header = pipeline.getHeader()}, expressions.prewhere_info->remove_columns_actions); remove_columns.setStepDescription("Remove unnecessary columns after PREWHERE"); remove_columns.transformPipeline(pipeline); } } } else { if (prepared_input) { ReadFromPreparedSource prepared_source_step(Pipe(std::make_shared(prepared_input))); prepared_source_step.initializePipeline(pipeline); } else if (prepared_pipe) { ReadFromPreparedSource prepared_source_step(std::move(*prepared_pipe)); prepared_source_step.initializePipeline(pipeline); } if (from_stage == QueryProcessingStage::WithMergeableState && options.to_stage == QueryProcessingStage::WithMergeableState) intermediate_stage = true; if (storage && expressions.filter_info && expressions.prewhere_info) throw Exception("PREWHERE is not supported if the table is filtered by row-level security expression", ErrorCodes::ILLEGAL_PREWHERE); /** Read the data from Storage. from_stage - to what stage the request was completed in Storage. */ executeFetchColumns(from_stage, pipeline, expressions.prewhere_info, expressions.columns_to_remove_after_prewhere); LOG_TRACE(log, "{} -> {}", QueryProcessingStage::toString(from_stage), QueryProcessingStage::toString(options.to_stage)); } if (options.to_stage > QueryProcessingStage::FetchColumns) { /// Do I need to aggregate in a separate row rows that have not passed max_rows_to_group_by. bool aggregate_overflow_row = expressions.need_aggregate && query.group_by_with_totals && settings.max_rows_to_group_by && settings.group_by_overflow_mode == OverflowMode::ANY && settings.totals_mode != TotalsMode::AFTER_HAVING_EXCLUSIVE; /// Do I need to immediately finalize the aggregate functions after the aggregation? bool aggregate_final = expressions.need_aggregate && options.to_stage > QueryProcessingStage::WithMergeableState && !query.group_by_with_totals && !query.group_by_with_rollup && !query.group_by_with_cube; auto preliminary_sort = [&]() { /** For distributed query processing, * if no GROUP, HAVING set, * but there is an ORDER or LIMIT, * then we will perform the preliminary sorting and LIMIT on the remote server. */ if (!expressions.second_stage && !expressions.need_aggregate && !expressions.hasHaving()) { if (expressions.has_order_by) executeOrder(pipeline, query_info.input_order_info); if (expressions.has_order_by && query.limitLength()) executeDistinct(pipeline, false, expressions.selected_columns); if (expressions.hasLimitBy()) { executeExpression(pipeline, expressions.before_limit_by, "Before LIMIT BY"); executeLimitBy(pipeline); } if (query.limitLength()) executePreLimit(pipeline, true); } }; if (intermediate_stage) { if (expressions.first_stage || expressions.second_stage) throw Exception("Query with intermediate stage cannot have any other stages", ErrorCodes::LOGICAL_ERROR); preliminary_sort(); if (expressions.need_aggregate) executeMergeAggregated(pipeline, aggregate_overflow_row, aggregate_final); } if (expressions.first_stage) { if (expressions.hasFilter()) { FilterStep row_level_security_step( DataStream{.header = pipeline.getHeader()}, expressions.filter_info->actions, expressions.filter_info->column_name, expressions.filter_info->do_remove_column); row_level_security_step.setStepDescription("Row-level security filter"); row_level_security_step.transformPipeline(pipeline); } if (expressions.hasJoin()) { Block join_result_sample; JoinPtr join = expressions.before_join->getTableJoinAlgo(); join_result_sample = ExpressionTransform::transformHeader(pipeline.getHeader(), expressions.before_join); /// In case joined subquery has totals, and we don't, add default chunk to totals. bool default_totals = false; if (!pipeline.hasTotals()) { pipeline.addDefaultTotals(); default_totals = true; } bool inflating_join = false; if (join) { inflating_join = true; if (auto * hash_join = typeid_cast(join.get())) inflating_join = isCross(hash_join->getKind()); } if (inflating_join) { InflatingExpressionStep before_join_step( DataStream{.header = pipeline.getHeader()}, expressions.before_join, default_totals); before_join_step.setStepDescription("JOIN"); before_join_step.transformPipeline(pipeline); } else { ExpressionStep before_join_step( DataStream{.header = pipeline.getHeader()}, expressions.before_join, default_totals); before_join_step.setStepDescription("JOIN"); before_join_step.transformPipeline(pipeline); } if (join) { if (auto stream = join->createStreamWithNonJoinedRows(join_result_sample, settings.max_block_size)) { auto source = std::make_shared(std::move(stream)); AddingDelayedStreamStep add_non_joined_rows_step( DataStream{.header = pipeline.getHeader()}, std::move(source)); add_non_joined_rows_step.setStepDescription("Add non-joined rows after JOIN"); add_non_joined_rows_step.transformPipeline(pipeline); } } } if (expressions.hasWhere()) executeWhere(pipeline, expressions.before_where, expressions.remove_where_filter); if (expressions.need_aggregate) { executeAggregation(pipeline, expressions.before_aggregation, aggregate_overflow_row, aggregate_final, query_info.input_order_info); /// We need to reset input order info, so that executeOrder can't use it query_info.input_order_info.reset(); } else { executeExpression(pipeline, expressions.before_order_and_select, "Before ORDER BY and SELECT"); executeDistinct(pipeline, true, expressions.selected_columns); } preliminary_sort(); // If there is no global subqueries, we can run subqueries only when receive them on server. if (!query_analyzer->hasGlobalSubqueries() && !subqueries_for_sets.empty()) executeSubqueriesInSetsAndJoins(pipeline, subqueries_for_sets); } if (expressions.second_stage) { bool need_second_distinct_pass = false; if (expressions.need_aggregate) { /// If you need to combine aggregated results from multiple servers if (!expressions.first_stage) executeMergeAggregated(pipeline, aggregate_overflow_row, aggregate_final); if (!aggregate_final) { if (query.group_by_with_totals) { bool final = !query.group_by_with_rollup && !query.group_by_with_cube; executeTotalsAndHaving(pipeline, expressions.hasHaving(), expressions.before_having, aggregate_overflow_row, final); } if (query.group_by_with_rollup) executeRollupOrCube(pipeline, Modificator::ROLLUP); else if (query.group_by_with_cube) executeRollupOrCube(pipeline, Modificator::CUBE); if ((query.group_by_with_rollup || query.group_by_with_cube) && expressions.hasHaving()) { if (query.group_by_with_totals) throw Exception("WITH TOTALS and WITH ROLLUP or CUBE are not supported together in presence of HAVING", ErrorCodes::NOT_IMPLEMENTED); executeHaving(pipeline, expressions.before_having); } } else if (expressions.hasHaving()) executeHaving(pipeline, expressions.before_having); executeExpression(pipeline, expressions.before_order_and_select, "Before ORDER BY and SELECT"); executeDistinct(pipeline, true, expressions.selected_columns); } else if (query.group_by_with_totals || query.group_by_with_rollup || query.group_by_with_cube) throw Exception("WITH TOTALS, ROLLUP or CUBE are not supported without aggregation", ErrorCodes::NOT_IMPLEMENTED); need_second_distinct_pass = query.distinct && pipeline.hasMixedStreams(); if (expressions.has_order_by) { /** If there is an ORDER BY for distributed query processing, * but there is no aggregation, then on the remote servers ORDER BY was made * - therefore, we merge the sorted streams from remote servers. */ if (!expressions.first_stage && !expressions.need_aggregate && !(query.group_by_with_totals && !aggregate_final)) executeMergeSorted(pipeline, "before ORDER BY"); else /// Otherwise, just sort. executeOrder(pipeline, query_info.input_order_info); } /** Optimization - if there are several sources and there is LIMIT, then first apply the preliminary LIMIT, * limiting the number of rows in each up to `offset + limit`. */ bool has_prelimit = false; if (query.limitLength() && !query.limit_with_ties && pipeline.hasMoreThanOneStream() && !query.distinct && !expressions.hasLimitBy() && !settings.extremes) { executePreLimit(pipeline, false); has_prelimit = true; } bool need_merge_streams = need_second_distinct_pass || query.limitBy(); if (need_merge_streams) pipeline.resize(1); /** If there was more than one stream, * then DISTINCT needs to be performed once again after merging all streams. */ if (need_second_distinct_pass) executeDistinct(pipeline, false, expressions.selected_columns); if (expressions.hasLimitBy()) { executeExpression(pipeline, expressions.before_limit_by, "Before LIMIT BY"); executeLimitBy(pipeline); } executeWithFill(pipeline); /** We must do projection after DISTINCT because projection may remove some columns. */ executeProjection(pipeline, expressions.final_projection); /** Extremes are calculated before LIMIT, but after LIMIT BY. This is Ok. */ executeExtremes(pipeline); if (!has_prelimit) /// Limit is no longer needed if there is prelimit. executeLimit(pipeline); executeOffset(pipeline); } } if (query_analyzer->hasGlobalSubqueries() && !subqueries_for_sets.empty()) executeSubqueriesInSetsAndJoins(pipeline, subqueries_for_sets); } void InterpreterSelectQuery::executeFetchColumns( QueryProcessingStage::Enum processing_stage, QueryPipeline & pipeline, const PrewhereInfoPtr & prewhere_info, const Names & columns_to_remove_after_prewhere) { auto & query = getSelectQuery(); const Settings & settings = context->getSettingsRef(); /// Optimization for trivial query like SELECT count() FROM table. bool optimize_trivial_count = syntax_analyzer_result->optimize_trivial_count && storage && !filter_info && processing_stage == QueryProcessingStage::FetchColumns && query_analyzer->hasAggregation() && (query_analyzer->aggregates().size() == 1) && typeid_cast(query_analyzer->aggregates()[0].function.get()); if (optimize_trivial_count) { const auto & desc = query_analyzer->aggregates()[0]; const auto & func = desc.function; std::optional num_rows = storage->totalRows(); if (num_rows) { AggregateFunctionCount & agg_count = static_cast(*func); /// We will process it up to "WithMergeableState". std::vector state(agg_count.sizeOfData()); AggregateDataPtr place = state.data(); agg_count.create(place); SCOPE_EXIT(agg_count.destroy(place)); agg_count.set(place, *num_rows); auto column = ColumnAggregateFunction::create(func); column->insertFrom(place); auto header = analysis_result.before_aggregation->getSampleBlock(); size_t arguments_size = desc.argument_names.size(); DataTypes argument_types(arguments_size); for (size_t j = 0; j < arguments_size; ++j) argument_types[j] = header.getByName(desc.argument_names[j]).type; Block block_with_count{ {std::move(column), std::make_shared(func, argument_types, desc.parameters), desc.column_name}}; auto istream = std::make_shared(block_with_count); ReadFromPreparedSource prepared_count(Pipe(std::make_shared(istream))); prepared_count.setStepDescription("Optimized trivial count"); prepared_count.initializePipeline(pipeline); from_stage = QueryProcessingStage::WithMergeableState; analysis_result.first_stage = false; return; } } /// Actions to calculate ALIAS if required. ExpressionActionsPtr alias_actions; if (storage) { /// Append columns from the table filter to required auto row_policy_filter = context->getRowPolicyCondition(table_id.getDatabaseName(), table_id.getTableName(), RowPolicy::SELECT_FILTER); if (row_policy_filter) { auto initial_required_columns = required_columns; ExpressionActionsPtr actions; generateFilterActions(actions, row_policy_filter, initial_required_columns); auto required_columns_from_filter = actions->getRequiredColumns(); for (const auto & column : required_columns_from_filter) { if (required_columns.end() == std::find(required_columns.begin(), required_columns.end(), column)) required_columns.push_back(column); } } /// Detect, if ALIAS columns are required for query execution auto alias_columns_required = false; const ColumnsDescription & storage_columns = storage->getColumns(); for (const auto & column_name : required_columns) { auto column_default = storage_columns.getDefault(column_name); if (column_default && column_default->kind == ColumnDefaultKind::Alias) { alias_columns_required = true; break; } } /// There are multiple sources of required columns: /// - raw required columns, /// - columns deduced from ALIAS columns, /// - raw required columns from PREWHERE, /// - columns deduced from ALIAS columns from PREWHERE. /// PREWHERE is a special case, since we need to resolve it and pass directly to `IStorage::read()` /// before any other executions. if (alias_columns_required) { NameSet required_columns_from_prewhere; /// Set of all (including ALIAS) required columns for PREWHERE NameSet required_aliases_from_prewhere; /// Set of ALIAS required columns for PREWHERE if (prewhere_info) { /// Get some columns directly from PREWHERE expression actions auto prewhere_required_columns = prewhere_info->prewhere_actions->getRequiredColumns(); required_columns_from_prewhere.insert(prewhere_required_columns.begin(), prewhere_required_columns.end()); } /// Expression, that contains all raw required columns ASTPtr required_columns_all_expr = std::make_shared(); /// Expression, that contains raw required columns for PREWHERE ASTPtr required_columns_from_prewhere_expr = std::make_shared(); /// Sort out already known required columns between expressions, /// also populate `required_aliases_from_prewhere`. for (const auto & column : required_columns) { ASTPtr column_expr; const auto column_default = storage_columns.getDefault(column); bool is_alias = column_default && column_default->kind == ColumnDefaultKind::Alias; if (is_alias) { auto column_decl = storage_columns.get(column); /// TODO: can make CAST only if the type is different (but requires SyntaxAnalyzer). auto cast_column_default = addTypeConversionToAST(column_default->expression->clone(), column_decl.type->getName()); column_expr = setAlias(cast_column_default->clone(), column); } else column_expr = std::make_shared(column); if (required_columns_from_prewhere.count(column)) { required_columns_from_prewhere_expr->children.emplace_back(std::move(column_expr)); if (is_alias) required_aliases_from_prewhere.insert(column); } else required_columns_all_expr->children.emplace_back(std::move(column_expr)); } /// Columns, which we will get after prewhere and filter executions. NamesAndTypesList required_columns_after_prewhere; NameSet required_columns_after_prewhere_set; /// Collect required columns from prewhere expression actions. if (prewhere_info) { NameSet columns_to_remove(columns_to_remove_after_prewhere.begin(), columns_to_remove_after_prewhere.end()); Block prewhere_actions_result = prewhere_info->prewhere_actions->getSampleBlock(); /// Populate required columns with the columns, added by PREWHERE actions and not removed afterwards. /// XXX: looks hacky that we already know which columns after PREWHERE we won't need for sure. for (const auto & column : prewhere_actions_result) { if (prewhere_info->remove_prewhere_column && column.name == prewhere_info->prewhere_column_name) continue; if (columns_to_remove.count(column.name)) continue; required_columns_all_expr->children.emplace_back(std::make_shared(column.name)); required_columns_after_prewhere.emplace_back(column.name, column.type); } required_columns_after_prewhere_set = ext::map(required_columns_after_prewhere, [](const auto & it) { return it.name; }); } auto syntax_result = SyntaxAnalyzer(*context).analyze(required_columns_all_expr, required_columns_after_prewhere, storage); alias_actions = ExpressionAnalyzer(required_columns_all_expr, syntax_result, *context).getActions(true); /// The set of required columns could be added as a result of adding an action to calculate ALIAS. required_columns = alias_actions->getRequiredColumns(); /// Do not remove prewhere filter if it is a column which is used as alias. if (prewhere_info && prewhere_info->remove_prewhere_column) if (required_columns.end() != std::find(required_columns.begin(), required_columns.end(), prewhere_info->prewhere_column_name)) prewhere_info->remove_prewhere_column = false; /// Remove columns which will be added by prewhere. required_columns.erase(std::remove_if(required_columns.begin(), required_columns.end(), [&](const String & name) { return required_columns_after_prewhere_set.count(name) != 0; }), required_columns.end()); if (prewhere_info) { /// Don't remove columns which are needed to be aliased. auto new_actions = std::make_shared(prewhere_info->prewhere_actions->getRequiredColumnsWithTypes(), *context); for (const auto & action : prewhere_info->prewhere_actions->getActions()) { if (action.type != ExpressionAction::REMOVE_COLUMN || required_columns.end() == std::find(required_columns.begin(), required_columns.end(), action.source_name)) new_actions->add(action); } prewhere_info->prewhere_actions = std::move(new_actions); auto analyzed_result = SyntaxAnalyzer(*context).analyze(required_columns_from_prewhere_expr, storage->getColumns().getAllPhysical()); prewhere_info->alias_actions = ExpressionAnalyzer(required_columns_from_prewhere_expr, analyzed_result, *context).getActions(true, false); /// Add (physical?) columns required by alias actions. auto required_columns_from_alias = prewhere_info->alias_actions->getRequiredColumns(); Block prewhere_actions_result = prewhere_info->prewhere_actions->getSampleBlock(); for (auto & column : required_columns_from_alias) if (!prewhere_actions_result.has(column)) if (required_columns.end() == std::find(required_columns.begin(), required_columns.end(), column)) required_columns.push_back(column); /// Add physical columns required by prewhere actions. for (const auto & column : required_columns_from_prewhere) if (required_aliases_from_prewhere.count(column) == 0) if (required_columns.end() == std::find(required_columns.begin(), required_columns.end(), column)) required_columns.push_back(column); } } } /// Limitation on the number of columns to read. /// It's not applied in 'only_analyze' mode, because the query could be analyzed without removal of unnecessary columns. if (!options.only_analyze && settings.max_columns_to_read && required_columns.size() > settings.max_columns_to_read) throw Exception("Limit for number of columns to read exceeded. " "Requested: " + toString(required_columns.size()) + ", maximum: " + settings.max_columns_to_read.toString(), ErrorCodes::TOO_MANY_COLUMNS); /** With distributed query processing, almost no computations are done in the threads, * but wait and receive data from remote servers. * If we have 20 remote servers, and max_threads = 8, then it would not be very good * connect and ask only 8 servers at a time. * To simultaneously query more remote servers, * instead of max_threads, max_distributed_connections is used. */ bool is_remote = false; if (storage && storage->isRemote()) { is_remote = true; max_streams = settings.max_distributed_connections; pipeline.setMaxThreads(max_streams); } UInt64 max_block_size = settings.max_block_size; auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context); /** Optimization - if not specified DISTINCT, WHERE, GROUP, HAVING, ORDER, LIMIT BY, WITH TIES but LIMIT is specified, and limit + offset < max_block_size, * then as the block size we will use limit + offset (not to read more from the table than requested), * and also set the number of threads to 1. */ if (!query.distinct && !query.limit_with_ties && !query.prewhere() && !query.where() && !query.groupBy() && !query.having() && !query.orderBy() && !query.limitBy() && query.limitLength() && !query_analyzer->hasAggregation() && limit_length + limit_offset < max_block_size) { max_block_size = std::max(UInt64(1), limit_length + limit_offset); max_streams = 1; pipeline.setMaxThreads(max_streams); } if (!max_block_size) throw Exception("Setting 'max_block_size' cannot be zero", ErrorCodes::PARAMETER_OUT_OF_BOUND); /// Initialize the initial data streams to which the query transforms are superimposed. Table or subquery or prepared input? if (pipeline.initialized()) { /// Prepared input. } else if (interpreter_subquery) { /// Subquery. /// If we need less number of columns that subquery have - update the interpreter. if (required_columns.size() < source_header.columns()) { ASTPtr subquery = extractTableExpression(query, 0); if (!subquery) throw Exception("Subquery expected", ErrorCodes::LOGICAL_ERROR); interpreter_subquery = std::make_unique( subquery, getSubqueryContext(*context), options.copy().subquery().noModify(), required_columns); if (query_analyzer->hasAggregation()) interpreter_subquery->ignoreWithTotals(); } pipeline = interpreter_subquery->execute().pipeline; } else if (storage) { /// Table. if (max_streams == 0) throw Exception("Logical error: zero number of streams requested", ErrorCodes::LOGICAL_ERROR); /// If necessary, we request more sources than the number of threads - to distribute the work evenly over the threads. if (max_streams > 1 && !is_remote) max_streams *= settings.max_streams_to_max_threads_ratio; query_info.query = query_ptr; query_info.syntax_analyzer_result = syntax_analyzer_result; query_info.sets = query_analyzer->getPreparedSets(); query_info.prewhere_info = prewhere_info; /// Create optimizer with prepared actions. /// Maybe we will need to calc input_order_info later, e.g. while reading from StorageMerge. if (analysis_result.optimize_read_in_order || analysis_result.optimize_aggregation_in_order) { if (analysis_result.optimize_read_in_order) query_info.order_optimizer = std::make_shared( analysis_result.order_by_elements_actions, getSortDescription(query, *context), query_info.syntax_analyzer_result); else query_info.order_optimizer = std::make_shared( analysis_result.group_by_elements_actions, getSortDescriptionFromGroupBy(query), query_info.syntax_analyzer_result); query_info.input_order_info = query_info.order_optimizer->getInputOrder(storage); } ReadFromStorageStep read_step( table_lock, options, storage, required_columns, query_info, *context, processing_stage, max_block_size, max_streams); read_step.setStepDescription("Read from " + storage->getName()); pipeline = std::move(*read_step.updatePipeline({})); } else throw Exception("Logical error in InterpreterSelectQuery: nowhere to read", ErrorCodes::LOGICAL_ERROR); /// Aliases in table declaration. if (processing_stage == QueryProcessingStage::FetchColumns && alias_actions) { ExpressionStep table_aliases(DataStream{.header = pipeline.getHeader()}, alias_actions); table_aliases.setStepDescription("Add table aliases"); table_aliases.transformPipeline(pipeline); } } void InterpreterSelectQuery::executeWhere(QueryPipeline & pipeline, const ExpressionActionsPtr & expression, bool remove_filter) { FilterStep where_step( DataStream{.header = pipeline.getHeader()}, expression, getSelectQuery().where()->getColumnName(), remove_filter); where_step.setStepDescription("WHERE"); where_step.transformPipeline(pipeline); } void InterpreterSelectQuery::executeAggregation(QueryPipeline & pipeline, const ExpressionActionsPtr & expression, bool overflow_row, bool final, InputOrderInfoPtr group_by_info) { pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, expression); }); Block header_before_aggregation = pipeline.getHeader(); ColumnNumbers keys; for (const auto & key : query_analyzer->aggregationKeys()) keys.push_back(header_before_aggregation.getPositionByName(key.name)); AggregateDescriptions aggregates = query_analyzer->aggregates(); for (auto & descr : aggregates) if (descr.arguments.empty()) for (const auto & name : descr.argument_names) descr.arguments.push_back(header_before_aggregation.getPositionByName(name)); const Settings & settings = context->getSettingsRef(); /** Two-level aggregation is useful in two cases: * 1. Parallel aggregation is done, and the results should be merged in parallel. * 2. An aggregation is done with store of temporary data on the disk, and they need to be merged in a memory efficient way. */ bool allow_to_use_two_level_group_by = pipeline.getNumStreams() > 1 || settings.max_bytes_before_external_group_by != 0; Aggregator::Params params(header_before_aggregation, keys, aggregates, overflow_row, settings.max_rows_to_group_by, settings.group_by_overflow_mode, allow_to_use_two_level_group_by ? settings.group_by_two_level_threshold : SettingUInt64(0), allow_to_use_two_level_group_by ? settings.group_by_two_level_threshold_bytes : SettingUInt64(0), settings.max_bytes_before_external_group_by, settings.empty_result_for_aggregation_by_empty_set, context->getTemporaryVolume(), settings.max_threads, settings.min_free_disk_space_for_temporary_data); auto transform_params = std::make_shared(params, final); /// Forget about current totals and extremes. They will be calculated again after aggregation if needed. pipeline.dropTotalsAndExtremes(); if (group_by_info && settings.optimize_aggregation_in_order) { auto & query = getSelectQuery(); SortDescription group_by_descr = getSortDescriptionFromGroupBy(query); bool need_finish_sorting = (group_by_info->order_key_prefix_descr.size() < group_by_descr.size()); if (need_finish_sorting) { /// TOO SLOW } else { if (pipeline.getNumStreams() > 1) { auto many_data = std::make_shared(pipeline.getNumStreams()); size_t counter = 0; pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, transform_params, group_by_descr, settings.max_block_size, many_data, counter++); }); for (auto & column_description : group_by_descr) { if (!column_description.column_name.empty()) { column_description.column_number = pipeline.getHeader().getPositionByName(column_description.column_name); column_description.column_name.clear(); } } auto transform = std::make_shared( pipeline.getHeader(), pipeline.getNumStreams(), group_by_descr, settings.max_block_size); pipeline.addPipe({ std::move(transform) }); } else { pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, transform_params, group_by_descr, settings.max_block_size); }); } pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, transform_params); }); pipeline.enableQuotaForCurrentStreams(); return; } } /// If there are several sources, then we perform parallel aggregation if (pipeline.getNumStreams() > 1) { /// Add resize transform to uniformly distribute data between aggregating streams. if (!(storage && storage->hasEvenlyDistributedRead())) pipeline.resize(pipeline.getNumStreams(), true, true); auto many_data = std::make_shared(pipeline.getNumStreams()); auto merge_threads = settings.aggregation_memory_efficient_merge_threads ? static_cast(settings.aggregation_memory_efficient_merge_threads) : static_cast(settings.max_threads); size_t counter = 0; pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, transform_params, many_data, counter++, max_streams, merge_threads); }); pipeline.resize(1); } else { pipeline.resize(1); pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, transform_params); }); } pipeline.enableQuotaForCurrentStreams(); } void InterpreterSelectQuery::executeMergeAggregated(QueryPipeline & pipeline, bool overflow_row, bool final) { Block header_before_merge = pipeline.getHeader(); ColumnNumbers keys; for (const auto & key : query_analyzer->aggregationKeys()) keys.push_back(header_before_merge.getPositionByName(key.name)); /** There are two modes of distributed aggregation. * * 1. In different threads read from the remote servers blocks. * Save all the blocks in the RAM. Merge blocks. * If the aggregation is two-level - parallelize to the number of buckets. * * 2. In one thread, read blocks from different servers in order. * RAM stores only one block from each server. * If the aggregation is a two-level aggregation, we consistently merge the blocks of each next level. * * The second option consumes less memory (up to 256 times less) * in the case of two-level aggregation, which is used for large results after GROUP BY, * but it can work more slowly. */ const Settings & settings = context->getSettingsRef(); Aggregator::Params params(header_before_merge, keys, query_analyzer->aggregates(), overflow_row, settings.max_threads); auto transform_params = std::make_shared(params, final); MergingAggregatedStep merging_aggregated( DataStream{.header = pipeline.getHeader()}, transform_params, settings.distributed_aggregation_memory_efficient, settings.max_threads, settings.aggregation_memory_efficient_merge_threads); merging_aggregated.transformPipeline(pipeline); } void InterpreterSelectQuery::executeHaving(QueryPipeline & pipeline, const ExpressionActionsPtr & expression) { pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr { bool on_totals = stream_type == QueryPipeline::StreamType::Totals; /// TODO: do we need to save filter there? return std::make_shared(header, expression, getSelectQuery().having()->getColumnName(), false, on_totals); }); } void InterpreterSelectQuery::executeTotalsAndHaving(QueryPipeline & pipeline, bool has_having, const ExpressionActionsPtr & expression, bool overflow_row, bool final) { const Settings & settings = context->getSettingsRef(); auto totals_having = std::make_shared( pipeline.getHeader(), overflow_row, expression, has_having ? getSelectQuery().having()->getColumnName() : "", settings.totals_mode, settings.totals_auto_threshold, final); pipeline.addTotalsHavingTransform(std::move(totals_having)); } void InterpreterSelectQuery::executeRollupOrCube(QueryPipeline & pipeline, Modificator modificator) { pipeline.resize(1); Block header_before_transform = pipeline.getHeader(); ColumnNumbers keys; for (const auto & key : query_analyzer->aggregationKeys()) keys.push_back(header_before_transform.getPositionByName(key.name)); const Settings & settings = context->getSettingsRef(); Aggregator::Params params(header_before_transform, keys, query_analyzer->aggregates(), false, settings.max_rows_to_group_by, settings.group_by_overflow_mode, SettingUInt64(0), SettingUInt64(0), settings.max_bytes_before_external_group_by, settings.empty_result_for_aggregation_by_empty_set, context->getTemporaryVolume(), settings.max_threads, settings.min_free_disk_space_for_temporary_data); auto transform_params = std::make_shared(params, true); pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr { if (stream_type == QueryPipeline::StreamType::Totals) return nullptr; if (modificator == Modificator::ROLLUP) return std::make_shared(header, std::move(transform_params)); else return std::make_shared(header, std::move(transform_params)); }); } void InterpreterSelectQuery::executeExpression(QueryPipeline & pipeline, const ExpressionActionsPtr & expression, const std::string & description) { ExpressionStep expression_step( DataStream{.header = pipeline.getHeader()}, expression); expression_step.setStepDescription(description); expression_step.transformPipeline(pipeline); } void InterpreterSelectQuery::executeOrderOptimized(QueryPipeline & pipeline, InputOrderInfoPtr input_sorting_info, UInt64 limit, SortDescription & output_order_descr) { const Settings & settings = context->getSettingsRef(); bool need_finish_sorting = (input_sorting_info->order_key_prefix_descr.size() < output_order_descr.size()); if (pipeline.getNumStreams() > 1) { UInt64 limit_for_merging = (need_finish_sorting ? 0 : limit); auto transform = std::make_shared( pipeline.getHeader(), pipeline.getNumStreams(), input_sorting_info->order_key_prefix_descr, settings.max_block_size, limit_for_merging); pipeline.addPipe({ std::move(transform) }); } pipeline.enableQuotaForCurrentStreams(); if (need_finish_sorting) { pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr { if (stream_type != QueryPipeline::StreamType::Main) return nullptr; return std::make_shared(header, output_order_descr, limit); }); /// NOTE limits are not applied to the size of temporary sets in FinishSortingTransform pipeline.addSimpleTransform([&](const Block & header) -> ProcessorPtr { return std::make_shared( header, input_sorting_info->order_key_prefix_descr, output_order_descr, settings.max_block_size, limit); }); } } void InterpreterSelectQuery::executeOrder(QueryPipeline & pipeline, InputOrderInfoPtr input_sorting_info) { auto & query = getSelectQuery(); SortDescription output_order_descr = getSortDescription(query, *context); UInt64 limit = getLimitForSorting(query, *context); if (input_sorting_info) { /* Case of sorting with optimization using sorting key. * We have several threads, each of them reads batch of parts in direct * or reverse order of sorting key using one input stream per part * and then merge them into one sorted stream. * At this stage we merge per-thread streams into one. */ executeOrderOptimized(pipeline, input_sorting_info, limit, output_order_descr); return; } const Settings & settings = context->getSettingsRef(); PartialSortingStep partial_sorting( DataStream{.header = pipeline.getHeader()}, output_order_descr, limit, SizeLimits(settings.max_rows_to_sort, settings.max_bytes_to_sort, settings.sort_overflow_mode)); partial_sorting.setStepDescription("Sort each block before ORDER BY"); partial_sorting.transformPipeline(pipeline); /// Merge the sorted blocks. MergeSortingStep merge_sorting_step( DataStream{.header = pipeline.getHeader()}, output_order_descr, settings.max_block_size, limit, settings.max_bytes_before_remerge_sort / pipeline.getNumStreams(), settings.max_bytes_before_external_sort, context->getTemporaryVolume(), settings.min_free_disk_space_for_temporary_data); merge_sorting_step.setStepDescription("Merge sorted blocks before ORDER BY"); merge_sorting_step.transformPipeline(pipeline); /// If there are several streams, we merge them into one executeMergeSorted(pipeline, output_order_descr, limit, "before ORDER BY"); } void InterpreterSelectQuery::executeMergeSorted(QueryPipeline & pipeline, const std::string & description) { auto & query = getSelectQuery(); SortDescription order_descr = getSortDescription(query, *context); UInt64 limit = getLimitForSorting(query, *context); executeMergeSorted(pipeline, order_descr, limit, description); } void InterpreterSelectQuery::executeMergeSorted(QueryPipeline & pipeline, const SortDescription & sort_description, UInt64 limit, const std::string & description) { const Settings & settings = context->getSettingsRef(); MergingSortedStep merging_sorted( DataStream{.header = pipeline.getHeader()}, sort_description, settings.max_block_size, limit); merging_sorted.setStepDescription("Merge sorted streams " + description); merging_sorted.transformPipeline(pipeline); } void InterpreterSelectQuery::executeProjection(QueryPipeline & pipeline, const ExpressionActionsPtr & expression) { pipeline.addSimpleTransform([&](const Block & header) -> ProcessorPtr { return std::make_shared(header, expression); }); } void InterpreterSelectQuery::executeDistinct(QueryPipeline & pipeline, bool before_order, Names columns) { auto & query = getSelectQuery(); if (query.distinct) { const Settings & settings = context->getSettingsRef(); auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context); UInt64 limit_for_distinct = 0; /// If after this stage of DISTINCT ORDER BY is not executed, then you can get no more than limit_length + limit_offset of different rows. if (!query.orderBy() || !before_order) limit_for_distinct = limit_length + limit_offset; SizeLimits limits(settings.max_rows_in_distinct, settings.max_bytes_in_distinct, settings.distinct_overflow_mode); DistinctStep distinct_step( DataStream{.header = pipeline.getHeader()}, limits, limit_for_distinct, columns); distinct_step.transformPipeline(pipeline); } } /// Preliminary LIMIT - is used in every source, if there are several sources, before they are combined. void InterpreterSelectQuery::executePreLimit(QueryPipeline & pipeline, bool do_not_skip_offset) { auto & query = getSelectQuery(); /// If there is LIMIT if (query.limitLength()) { auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context); if (do_not_skip_offset) { limit_length += limit_offset; limit_offset = 0; } LimitStep limit(DataStream{.header = pipeline.getHeader()}, limit_length, limit_offset); limit.setStepDescription("preliminary LIMIT"); limit.transformPipeline(pipeline); } } void InterpreterSelectQuery::executeLimitBy(QueryPipeline & pipeline) { auto & query = getSelectQuery(); if (!query.limitByLength() || !query.limitBy()) return; Names columns; for (const auto & elem : query.limitBy()->children) columns.emplace_back(elem->getColumnName()); UInt64 length = getLimitUIntValue(query.limitByLength(), *context, "LIMIT"); UInt64 offset = (query.limitByOffset() ? getLimitUIntValue(query.limitByOffset(), *context, "OFFSET") : 0); LimitByStep limit_by(DataStream{.header = pipeline.getHeader()}, length, offset, columns); limit_by.transformPipeline(pipeline); } namespace { bool hasWithTotalsInAnySubqueryInFromClause(const ASTSelectQuery & query) { if (query.group_by_with_totals) return true; /** NOTE You can also check that the table in the subquery is distributed, and that it only looks at one shard. * In other cases, totals will be computed on the initiating server of the query, and it is not necessary to read the data to the end. */ if (auto query_table = extractTableExpression(query, 0)) { if (const auto * ast_union = query_table->as()) { for (const auto & elem : ast_union->list_of_selects->children) if (hasWithTotalsInAnySubqueryInFromClause(elem->as())) return true; } } return false; } } void InterpreterSelectQuery::executeWithFill(QueryPipeline & pipeline) { auto & query = getSelectQuery(); if (query.orderBy()) { SortDescription order_descr = getSortDescription(query, *context); SortDescription fill_descr; for (auto & desc : order_descr) { if (desc.with_fill) fill_descr.push_back(desc); } if (fill_descr.empty()) return; pipeline.addSimpleTransform([&](const Block & header) { return std::make_shared(header, fill_descr); }); } } void InterpreterSelectQuery::executeLimit(QueryPipeline & pipeline) { auto & query = getSelectQuery(); /// If there is LIMIT if (query.limitLength()) { /** Rare case: * if there is no WITH TOTALS and there is a subquery in FROM, and there is WITH TOTALS on one of the levels, * then when using LIMIT, you should read the data to the end, rather than cancel the query earlier, * because if you cancel the query, we will not get `totals` data from the remote server. * * Another case: * if there is WITH TOTALS and there is no ORDER BY, then read the data to the end, * otherwise TOTALS is counted according to incomplete data. */ bool always_read_till_end = false; if (query.group_by_with_totals && !query.orderBy()) always_read_till_end = true; if (!query.group_by_with_totals && hasWithTotalsInAnySubqueryInFromClause(query)) always_read_till_end = true; UInt64 limit_length; UInt64 limit_offset; std::tie(limit_length, limit_offset) = getLimitLengthAndOffset(query, *context); SortDescription order_descr; if (query.limit_with_ties) { if (!query.orderBy()) throw Exception("LIMIT WITH TIES without ORDER BY", ErrorCodes::LOGICAL_ERROR); order_descr = getSortDescription(query, *context); } LimitStep limit( DataStream{.header = pipeline.getHeader()}, limit_length, limit_offset, always_read_till_end, query.limit_with_ties, order_descr); if (query.limit_with_ties) limit.setStepDescription("LIMIT WITH TIES"); limit.transformPipeline(pipeline); } } void InterpreterSelectQuery::executeOffset(QueryPipeline & pipeline) { auto & query = getSelectQuery(); /// If there is not a LIMIT but an offset if (!query.limitLength() && query.limitOffset()) { UInt64 limit_length; UInt64 limit_offset; std::tie(limit_length, limit_offset) = getLimitLengthAndOffset(query, *context); pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr { if (stream_type != QueryPipeline::StreamType::Main) return nullptr; return std::make_shared(header, limit_offset, 1); }); } } void InterpreterSelectQuery::executeExtremes(QueryPipeline & pipeline) { if (!context->getSettingsRef().extremes) return; pipeline.addExtremesTransform(); } void InterpreterSelectQuery::executeSubqueriesInSetsAndJoins(QueryPipeline & pipeline, const SubqueriesForSets & subqueries_for_sets) { if (query_info.input_order_info) executeMergeSorted(pipeline, query_info.input_order_info->order_key_prefix_descr, 0, "before creating sets for subqueries and joins"); const Settings & settings = context->getSettingsRef(); auto creating_sets = std::make_shared( pipeline.getHeader(), subqueries_for_sets, SizeLimits(settings.max_rows_to_transfer, settings.max_bytes_to_transfer, settings.transfer_overflow_mode), *context); pipeline.addCreatingSetsTransform(std::move(creating_sets)); } void InterpreterSelectQuery::ignoreWithTotals() { getSelectQuery().group_by_with_totals = false; } void InterpreterSelectQuery::initSettings() { auto & query = getSelectQuery(); if (query.settings()) InterpreterSetQuery(query.settings(), *context).executeForCurrentContext(); } }