ClickHouse/dbms/Interpreters/InterpreterSelectQuery.cpp

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#include <DataStreams/ExpressionBlockInputStream.h>
#include <DataStreams/FilterBlockInputStream.h>
#include <DataStreams/FinishSortingBlockInputStream.h>
#include <DataStreams/LimitBlockInputStream.h>
#include <DataStreams/LimitByBlockInputStream.h>
#include <DataStreams/PartialSortingBlockInputStream.h>
#include <DataStreams/MergeSortingBlockInputStream.h>
#include <DataStreams/MergingSortedBlockInputStream.h>
#include <DataStreams/AggregatingBlockInputStream.h>
#include <DataStreams/MergingAggregatedBlockInputStream.h>
#include <DataStreams/MergingAggregatedMemoryEfficientBlockInputStream.h>
#include <DataStreams/AsynchronousBlockInputStream.h>
#include <DataStreams/UnionBlockInputStream.h>
#include <DataStreams/ParallelAggregatingBlockInputStream.h>
#include <DataStreams/DistinctBlockInputStream.h>
#include <DataStreams/NullBlockInputStream.h>
#include <DataStreams/TotalsHavingBlockInputStream.h>
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#include <DataStreams/OneBlockInputStream.h>
#include <DataStreams/copyData.h>
#include <DataStreams/CreatingSetsBlockInputStream.h>
#include <DataStreams/MaterializingBlockInputStream.h>
#include <DataStreams/ConcatBlockInputStream.h>
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#include <DataStreams/RollupBlockInputStream.h>
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#include <DataStreams/CubeBlockInputStream.h>
#include <DataStreams/ConvertColumnLowCardinalityToFullBlockInputStream.h>
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#include <DataStreams/ConvertingBlockInputStream.h>
#include <DataStreams/ReverseBlockInputStream.h>
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#include <DataStreams/FillingBlockInputStream.h>
#include <Parsers/ASTFunction.h>
#include <Parsers/ASTIdentifier.h>
#include <Parsers/ASTLiteral.h>
#include <Parsers/ASTOrderByElement.h>
#include <Parsers/ASTSelectWithUnionQuery.h>
#include <Parsers/ASTTablesInSelectQuery.h>
#include <Parsers/ParserSelectQuery.h>
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#include <Parsers/ExpressionListParsers.h>
#include <Parsers/parseQuery.h>
#include <Access/AccessFlags.h>
#include <Interpreters/InterpreterSelectQuery.h>
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#include <Interpreters/InterpreterSelectWithUnionQuery.h>
#include <Interpreters/InterpreterSetQuery.h>
#include <Interpreters/evaluateConstantExpression.h>
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#include <Interpreters/convertFieldToType.h>
#include <Interpreters/ExpressionAnalyzer.h>
#include <Interpreters/getTableExpressions.h>
#include <Interpreters/JoinToSubqueryTransformVisitor.h>
#include <Interpreters/CrossToInnerJoinVisitor.h>
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#include <Interpreters/AnalyzedJoin.h>
#include <Interpreters/Join.h>
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#include <Interpreters/JoinedTables.h>
#include <Interpreters/QueryAliasesVisitor.h>
#include <Storages/MergeTree/MergeTreeData.h>
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#include <Storages/MergeTree/MergeTreeWhereOptimizer.h>
#include <Storages/IStorage.h>
#include <TableFunctions/ITableFunction.h>
#include <TableFunctions/TableFunctionFactory.h>
#include <Functions/IFunction.h>
#include <Core/Field.h>
#include <Core/Types.h>
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#include <Columns/Collator.h>
#include <Common/FieldVisitors.h>
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#include <Common/typeid_cast.h>
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#include <Common/checkStackSize.h>
#include <Parsers/queryToString.h>
#include <ext/map.h>
#include <ext/scope_guard.h>
#include <memory>
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#include <Processors/Sources/NullSource.h>
#include <Processors/Sources/SourceFromInputStream.h>
#include <Processors/Transforms/FilterTransform.h>
#include <Processors/Transforms/ExpressionTransform.h>
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#include <Processors/Transforms/InflatingExpressionTransform.h>
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#include <Processors/Transforms/AggregatingTransform.h>
#include <Processors/Transforms/MergingAggregatedTransform.h>
#include <Processors/Transforms/MergingAggregatedMemoryEfficientTransform.h>
#include <Processors/Transforms/TotalsHavingTransform.h>
#include <Processors/Transforms/PartialSortingTransform.h>
#include <Processors/Transforms/LimitsCheckingTransform.h>
#include <Processors/Transforms/MergeSortingTransform.h>
#include <Processors/Transforms/MergingSortedTransform.h>
#include <Processors/Transforms/DistinctTransform.h>
#include <Processors/Transforms/LimitByTransform.h>
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#include <Processors/Transforms/ExtremesTransform.h>
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#include <Processors/Transforms/CreatingSetsTransform.h>
#include <Processors/Transforms/RollupTransform.h>
#include <Processors/Transforms/CubeTransform.h>
#include <Processors/Transforms/FillingTransform.h>
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#include <Processors/LimitTransform.h>
#include <Processors/Transforms/FinishSortingTransform.h>
#include <DataTypes/DataTypeAggregateFunction.h>
#include <DataStreams/materializeBlock.h>
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#include <Processors/Pipe.h>
#include <Processors/Executors/TreeExecutorBlockInputStream.h>
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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;
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extern const int TOO_MANY_COLUMNS;
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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;
}
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/// 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
{
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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<ASTSelectQuery>();
auto * select_ast = query_ast->as<ASTSelectQuery>();
select_ast->setExpression(ASTSelectQuery::Expression::SELECT, std::make_shared<ASTExpressionList>());
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));
}
select_ast->setExpression(ASTSelectQuery::Expression::TABLES, std::make_shared<ASTTablesInSelectQuery>());
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auto tables = select_ast->tables();
auto tables_elem = std::make_shared<ASTTablesInSelectQueryElement>();
auto table_expr = std::make_shared<ASTTableExpression>();
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
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auto syntax_result = SyntaxAnalyzer(*context).analyzeSelect(query_ast, SyntaxAnalyzerResult({}, storage));
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SelectQueryExpressionAnalyzer analyzer(query_ast, syntax_result, *context);
actions = analyzer.simpleSelectActions();
return expr_list->children.at(0)->getColumnName();
}
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InterpreterSelectQuery::InterpreterSelectQuery(
const ASTPtr & query_ptr_,
const Context & context_,
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const SelectQueryOptions & options_,
const Names & required_result_column_names_)
: InterpreterSelectQuery(query_ptr_, context_, nullptr, std::nullopt, nullptr, options_, required_result_column_names_)
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{
}
InterpreterSelectQuery::InterpreterSelectQuery(
const ASTPtr & query_ptr_,
const Context & context_,
const BlockInputStreamPtr & input_,
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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())
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{}
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InterpreterSelectQuery::InterpreterSelectQuery(
const ASTPtr & query_ptr_,
const Context & context_,
const StoragePtr & storage_,
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const SelectQueryOptions & options_)
: InterpreterSelectQuery(query_ptr_, context_, nullptr, std::nullopt, storage_, options_.copy().noSubquery())
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{}
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)
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{
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).
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subquery_settings.extremes = false;
subquery_context.setSettings(subquery_settings);
return subquery_context;
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}
InterpreterSelectQuery::InterpreterSelectQuery(
const ASTPtr & query_ptr_,
const Context & context_,
const BlockInputStreamPtr & input_,
std::optional<Pipe> input_pipe_,
const StoragePtr & storage_,
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const SelectQueryOptions & options_,
const Names & required_result_column_names)
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: options(options_)
/// NOTE: the query almost always should be cloned because it will be modified during analysis.
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, query_ptr(options.modify_inplace ? query_ptr_ : query_ptr_->clone())
, context(std::make_shared<Context>(context_))
, storage(storage_)
, input(input_)
, input_pipe(std::move(input_pipe_))
, log(&Logger::get("InterpreterSelectQuery"))
{
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checkStackSize();
initSettings();
const Settings & settings = context->getSettingsRef();
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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)
{
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/// Read from prepared input.
source_header = input->getHeader();
}
else if (input_pipe)
{
/// Read from prepared input.
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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());
table_id = storage->getStorageID();
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}
if (has_input || !joined_tables.resolveTables())
joined_tables.makeFakeTable(storage, source_header);
/// Rewrite JOINs
if (!has_input && joined_tables.tablesCount() > 1)
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{
ASTSelectQuery & select = getSelectQuery();
Aliases aliases;
if (ASTPtr with = select.with())
QueryAliasesNoSubqueriesVisitor(aliases).visit(with);
QueryAliasesNoSubqueriesVisitor(aliases).visit(select.select());
CrossToInnerJoinVisitor::Data cross_to_inner{joined_tables.tablesWithColumns(), aliases, context->getCurrentDatabase()};
CrossToInnerJoinVisitor(cross_to_inner).visit(query_ptr);
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);
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JoinToSubqueryTransformVisitor::Data join_to_subs_data{joined_tables.tablesWithColumns(), aliases, rewriter_version};
JoinToSubqueryTransformVisitor(join_to_subs_data).visit(query_ptr);
joined_tables.reset(select);
joined_tables.resolveTables();
if (storage && joined_tables.isLeftTableSubquery())
{
/// Rewritten with subquery. Free storage here locks here.
storage = {};
table_lock.release();
table_id = StorageID::createEmpty();
}
}
if (!has_input)
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{
interpreter_subquery = joined_tables.makeLeftTableSubquery(options.subquery());
if (interpreter_subquery)
source_header = interpreter_subquery->getSampleBlock();
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}
joined_tables.rewriteDistributedInAndJoins(query_ptr);
max_streams = settings.max_threads;
ASTSelectQuery & query = getSelectQuery();
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auto analyze = [&] (bool try_move_to_prewhere = true)
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{
syntax_analyzer_result = SyntaxAnalyzer(*context).analyzeSelect(
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query_ptr, SyntaxAnalyzerResult(source_header.getNamesAndTypesList(), storage),
options, joined_tables.tablesWithColumns(), required_result_column_names);
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/// Save scalar sub queries's results in the query context
if (context->hasQueryContext())
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for (const auto & it : syntax_analyzer_result->getScalars())
context->getQueryContext().addScalar(it.first, it.second);
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query_analyzer = std::make_unique<SelectQueryExpressionAnalyzer>(
query_ptr, syntax_analyzer_result, *context,
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NameSet(required_result_column_names.begin(), required_result_column_names.end()),
!options.only_analyze, options);
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if (!options.only_analyze)
{
if (query.sampleSize() && (input || input_pipe || !storage || !storage->supportsSampling()))
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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);
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/// Save the new temporary tables in the query context
for (const auto & it : query_analyzer->getExternalTables())
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if (!context->tryResolveStorageID({"", it.first}, Context::ResolveExternal))
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context->addExternalTable(it.first, std::move(*it.second));
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}
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if (!options.only_analyze || options.modify_inplace)
{
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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());
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}
}
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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();
}
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required_columns = syntax_analyzer_result->requiredSourceColumns();
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if (storage)
{
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source_header = storage->getSampleBlockForColumns(required_columns);
/// Fix source_header for filter actions.
auto row_policy_filter = context->getRowPolicyCondition(table_id.getDatabaseName(), table_id.getTableName(), RowPolicy::SELECT_FILTER);
if (row_policy_filter)
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{
filter_info = std::make_shared<FilterInfo>();
filter_info->column_name = generateFilterActions(filter_info->actions, row_policy_filter, required_columns);
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source_header = storage->getSampleBlockForColumns(filter_info->actions->getRequiredColumns());
}
}
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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);
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/// Calculate structure of the result.
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result_header = getSampleBlockImpl(try_move_to_prewhere);
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};
analyze();
bool need_analyze_again = false;
if (analysis_result.prewhere_constant_filter_description.always_false || analysis_result.prewhere_constant_filter_description.always_true)
{
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if (analysis_result.prewhere_constant_filter_description.always_true)
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query.setExpression(ASTSelectQuery::Expression::PREWHERE, {});
else
query.setExpression(ASTSelectQuery::Expression::PREWHERE, std::make_shared<ASTLiteral>(0u));
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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)
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query.setExpression(ASTSelectQuery::Expression::WHERE, {});
else
query.setExpression(ASTSelectQuery::Expression::WHERE, std::make_shared<ASTLiteral>(0u));
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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;
}
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if (need_analyze_again)
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{
/// 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);
}
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/// If there is no WHERE, filter blocks as usual
if (query.prewhere() && !query.where())
analysis_result.prewhere_info->need_filter = true;
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const StorageID & left_table_id = joined_tables.leftTableID();
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if (left_table_id)
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context->checkAccess(AccessType::SELECT, left_table_id, required_columns);
/// Remove limits for some tables in the `system` database.
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if (left_table_id.database_name == "system" &&
((left_table_id.table_name == "quotas") || (left_table_id.table_name == "quota_usage") || (left_table_id.table_name == "one")))
{
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options.ignore_quota = true;
options.ignore_limits = true;
}
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/// 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);
}
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Block InterpreterSelectQuery::getSampleBlock()
{
return result_header;
}
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BlockIO InterpreterSelectQuery::execute()
{
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Pipeline pipeline;
BlockIO res;
executeImpl(pipeline, input, std::move(input_pipe), res.pipeline);
executeUnion(pipeline, getSampleBlock());
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res.in = pipeline.firstStream();
res.pipeline.addInterpreterContext(context);
res.pipeline.addStorageHolder(storage);
return res;
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}
BlockInputStreams InterpreterSelectQuery::executeWithMultipleStreams(QueryPipeline & parent_pipeline)
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{
///FIXME pipeline must be alive until query is finished
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Pipeline pipeline;
executeImpl(pipeline, input, std::move(input_pipe), parent_pipeline);
unifyStreams(pipeline, getSampleBlock());
parent_pipeline.addInterpreterContext(context);
parent_pipeline.addStorageHolder(storage);
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return pipeline.streams;
}
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QueryPipeline InterpreterSelectQuery::executeWithProcessors()
{
QueryPipeline query_pipeline;
executeImpl(query_pipeline, input, std::move(input_pipe), query_pipeline);
query_pipeline.addInterpreterContext(context);
query_pipeline.addStorageHolder(storage);
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return query_pipeline;
}
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Block InterpreterSelectQuery::getSampleBlockImpl(bool try_move_to_prewhere)
{
auto & query = getSelectQuery();
const Settings & settings = context->getSettingsRef();
/// Do all AST changes here, because actions from analysis_result will be used later in readImpl.
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if (storage)
{
query_analyzer->makeSetsForIndex(query.where());
query_analyzer->makeSetsForIndex(query.prewhere());
/// PREWHERE optimization.
/// Turn off, if the table filter (row-level security) is applied.
if (!context->getRowPolicyCondition(table_id.getDatabaseName(), table_id.getTableName(), RowPolicy::SELECT_FILTER))
{
auto optimize_prewhere = [&](auto & merge_tree)
{
SelectQueryInfo current_info;
current_info.query = query_ptr;
current_info.syntax_analyzer_result = syntax_analyzer_result;
current_info.sets = query_analyzer->getPreparedSets();
/// Try transferring some condition from WHERE to PREWHERE if enabled and viable
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if (settings.optimize_move_to_prewhere && try_move_to_prewhere && query.where() && !query.prewhere() && !query.final())
MergeTreeWhereOptimizer{current_info, *context, merge_tree,
syntax_analyzer_result->requiredSourceColumns(), log};
};
if (const auto * merge_tree_data = dynamic_cast<const MergeTreeData *>(storage.get()))
optimize_prewhere(*merge_tree_data);
}
}
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if (storage && !options.only_analyze)
from_stage = storage->getQueryProcessingStage(*context, query_ptr);
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/// 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,
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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 (auto & key : query_analyzer->aggregationKeys())
res.insert({nullptr, header.getByName(key.name).type, key.name});
for (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<DataTypeAggregateFunction>(aggregate.function, argument_types, aggregate.parameters);
res.insert({nullptr, type, aggregate.column_name});
}
return res;
}
return analysis_result.final_projection->getSampleBlock();
}
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static Field getWithFillFieldValue(const ASTPtr & node, const Context & context)
{
const auto & [field, type] = evaluateConstantExpression(node, context);
if (!isColumnedAsNumber(type))
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throw Exception("Illegal type " + type->getName() + " of WITH FILL expression, must be numeric type", ErrorCodes::INVALID_WITH_FILL_EXPRESSION);
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return field;
}
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static FillColumnDescription getWithFillDescription(const ASTOrderByElement & order_by_elem, const Context & context)
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{
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);
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else
descr.fill_step = order_by_elem.direction;
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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);
}
}
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return descr;
}
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static SortDescription getSortDescription(const ASTSelectQuery & query, const Context & context)
{
SortDescription order_descr;
order_descr.reserve(query.orderBy()->children.size());
for (const auto & elem : query.orderBy()->children)
{
String name = elem->children.front()->getColumnName();
const auto & order_by_elem = elem->as<ASTOrderByElement &>();
std::shared_ptr<Collator> collator;
if (order_by_elem.collation)
collator = std::make_shared<Collator>(order_by_elem.collation->as<ASTLiteral &>().value.get<String>());
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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, true, fill_desc);
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}
else
order_descr.emplace_back(name, order_by_elem.direction, order_by_elem.nulls_direction, collator);
}
return order_descr;
}
static UInt64 getLimitUIntValue(const ASTPtr & node, const Context & context)
{
const auto & [field, type] = evaluateConstantExpression(node, context);
if (!isNativeNumber(type))
throw Exception("Illegal type " + type->getName() + " of LIMIT 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 LIMIT expression is not representable as UInt64", ErrorCodes::INVALID_LIMIT_EXPRESSION);
return converted.safeGet<UInt64>();
}
static std::pair<UInt64, UInt64> getLimitLengthAndOffset(const ASTSelectQuery & query, const Context & context)
{
UInt64 length = 0;
UInt64 offset = 0;
if (query.limitLength())
{
length = getLimitUIntValue(query.limitLength(), context);
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if (query.limitOffset() && length)
offset = getLimitUIntValue(query.limitOffset(), context);
}
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.
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if (!query.distinct && !query.limitBy() && !query.limit_with_ties)
{
auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, context);
return limit_length + limit_offset;
}
return 0;
}
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template <typename TPipeline>
void InterpreterSelectQuery::executeImpl(TPipeline & pipeline, const BlockInputStreamPtr & prepared_input, std::optional<Pipe> prepared_pipe, QueryPipeline & save_context_and_storage)
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{
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/** 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 UnionBlockInputStream, and then MergeSortingBlockInputStream,
* if not, then glue it using UnionBlockInputStream,
* 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.
*/
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constexpr bool pipeline_with_processors = std::is_same<TPipeline, QueryPipeline>::value;
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/// Now we will compose block streams that perform the necessary actions.
auto & query = getSelectQuery();
const Settings & settings = context->getSettingsRef();
auto & expressions = analysis_result;
auto & subqueries_for_sets = query_analyzer->getSubqueriesForSets();
bool intermediate_stage = false;
if (options.only_analyze)
{
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if constexpr (pipeline_with_processors)
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pipeline.init(Pipe(std::make_shared<NullSource>(source_header)));
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else
pipeline.streams.emplace_back(std::make_shared<NullBlockInputStream>(source_header));
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if (expressions.prewhere_info)
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{
if constexpr (pipeline_with_processors)
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pipeline.addSimpleTransform([&](const Block & header)
{
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return std::make_shared<FilterTransform>(
header,
expressions.prewhere_info->prewhere_actions,
expressions.prewhere_info->prewhere_column_name,
expressions.prewhere_info->remove_prewhere_column);
});
else
pipeline.streams.back() = std::make_shared<FilterBlockInputStream>(
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pipeline.streams.back(), expressions.prewhere_info->prewhere_actions,
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expressions.prewhere_info->prewhere_column_name, expressions.prewhere_info->remove_prewhere_column);
// 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)
{
if constexpr (pipeline_with_processors)
{
pipeline.addSimpleTransform([&](const Block & header)
{
return std::make_shared<ExpressionTransform>(header, expressions.prewhere_info->remove_columns_actions);
});
}
else
pipeline.streams.back() = std::make_shared<ExpressionBlockInputStream>(pipeline.streams.back(), expressions.prewhere_info->remove_columns_actions);
}
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}
}
else
{
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if (prepared_input)
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{
if constexpr (pipeline_with_processors)
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pipeline.init(Pipe(std::make_shared<SourceFromInputStream>(prepared_input)));
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else
pipeline.streams.push_back(prepared_input);
}
else if (prepared_pipe)
{
if constexpr (pipeline_with_processors)
pipeline.init(std::move(*prepared_pipe));
else
pipeline.streams.push_back(std::make_shared<TreeExecutorBlockInputStream>(std::move(*prepared_pipe)));
}
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if (from_stage == QueryProcessingStage::WithMergeableState &&
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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);
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/** Read the data from Storage. from_stage - to what stage the request was completed in Storage. */
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executeFetchColumns(from_stage, pipeline, expressions.prewhere_info, expressions.columns_to_remove_after_prewhere, save_context_and_storage);
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LOG_TRACE(log, QueryProcessingStage::toString(from_stage) << " -> " << QueryProcessingStage::toString(options.to_stage));
}
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if (options.to_stage > QueryProcessingStage::FetchColumns)
{
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/// Do I need to aggregate in a separate row rows that have not passed max_rows_to_group_by.
bool aggregate_overflow_row =
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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;
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/// Do I need to immediately finalize the aggregate functions after the aggregation?
bool aggregate_final =
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expressions.need_aggregate &&
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options.to_stage > QueryProcessingStage::WithMergeableState &&
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!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_sorting_info);
if (expressions.has_order_by && query.limitLength())
executeDistinct(pipeline, false, expressions.selected_columns);
if (expressions.hasLimitBy())
{
executeExpression(pipeline, expressions.before_limit_by);
executeLimitBy(pipeline);
}
if (query.limitLength())
{
if constexpr (pipeline_with_processors)
executePreLimit(pipeline, true);
else
executePreLimit(pipeline);
}
}
};
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);
}
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if (expressions.first_stage)
{
if (expressions.hasFilter())
{
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if constexpr (pipeline_with_processors)
{
pipeline.addSimpleTransform([&](const Block & block, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type == QueryPipeline::StreamType::Totals)
return nullptr;
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return std::make_shared<FilterTransform>(
block,
expressions.filter_info->actions,
expressions.filter_info->column_name,
expressions.filter_info->do_remove_column);
});
}
else
{
pipeline.transform([&](auto & stream)
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{
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stream = std::make_shared<FilterBlockInputStream>(
stream,
expressions.filter_info->actions,
expressions.filter_info->column_name,
expressions.filter_info->do_remove_column);
});
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}
}
if (expressions.hasJoin())
{
Block join_result_sample;
JoinPtr join = expressions.before_join->getTableJoinAlgo();
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if constexpr (pipeline_with_processors)
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{
join_result_sample = ExpressionBlockInputStream(
std::make_shared<OneBlockInputStream>(pipeline.getHeader()), expressions.before_join).getHeader();
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/// In case joined subquery has totals, and we don't, add default chunk to totals.
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bool default_totals = false;
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if (!pipeline.hasTotals())
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{
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pipeline.addDefaultTotals();
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default_totals = true;
}
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bool inflating_join = join && !typeid_cast<Join *>(join.get());
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pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType type)
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{
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bool on_totals = type == QueryPipeline::StreamType::Totals;
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std::shared_ptr<IProcessor> ret;
if (inflating_join)
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ret = std::make_shared<InflatingExpressionTransform>(header, expressions.before_join, on_totals, default_totals);
else
ret = std::make_shared<ExpressionTransform>(header, expressions.before_join, on_totals, default_totals);
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return ret;
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});
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}
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else
{
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/// Applies to all sources except stream_with_non_joined_data.
for (auto & stream : pipeline.streams)
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stream = std::make_shared<InflatingExpressionBlockInputStream>(stream, expressions.before_join);
join_result_sample = pipeline.firstStream()->getHeader();
}
if (join)
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{
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if (auto stream = join->createStreamWithNonJoinedRows(join_result_sample, settings.max_block_size))
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{
if constexpr (pipeline_with_processors)
{
auto source = std::make_shared<SourceFromInputStream>(std::move(stream));
pipeline.addDelayedStream(source);
}
else
pipeline.stream_with_non_joined_data = std::move(stream);
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}
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}
}
if (expressions.hasWhere())
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executeWhere(pipeline, expressions.before_where, expressions.remove_where_filter);
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if (expressions.need_aggregate)
executeAggregation(pipeline, expressions.before_aggregation, aggregate_overflow_row, aggregate_final);
else
{
executeExpression(pipeline, expressions.before_order_and_select);
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executeDistinct(pipeline, true, expressions.selected_columns);
}
preliminary_sort();
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// 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);
}
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if (expressions.second_stage)
{
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bool need_second_distinct_pass = false;
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if (expressions.need_aggregate)
{
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/// If you need to combine aggregated results from multiple servers
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if (!expressions.first_stage)
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executeMergeAggregated(pipeline, aggregate_overflow_row, aggregate_final);
if (!aggregate_final)
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{
if (query.group_by_with_totals)
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{
bool final = !query.group_by_with_rollup && !query.group_by_with_cube;
executeTotalsAndHaving(pipeline, expressions.hasHaving(), expressions.before_having, aggregate_overflow_row, final);
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}
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if (query.group_by_with_rollup)
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executeRollupOrCube(pipeline, Modificator::ROLLUP);
else if (query.group_by_with_cube)
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executeRollupOrCube(pipeline, Modificator::CUBE);
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if ((query.group_by_with_rollup || query.group_by_with_cube) && expressions.hasHaving())
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{
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);
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}
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}
else if (expressions.hasHaving())
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executeHaving(pipeline, expressions.before_having);
executeExpression(pipeline, expressions.before_order_and_select);
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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();
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if (expressions.has_order_by)
{
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/** 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.
*/
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if (!expressions.first_stage && !expressions.need_aggregate && !(query.group_by_with_totals && !aggregate_final))
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executeMergeSorted(pipeline);
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else /// Otherwise, just sort.
executeOrder(pipeline, query_info.input_sorting_info);
}
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/** Optimization - if there are several sources and there is LIMIT, then first apply the preliminary LIMIT,
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* 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)
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{
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if constexpr (pipeline_with_processors)
executePreLimit(pipeline, false);
else
executePreLimit(pipeline);
has_prelimit = true;
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}
bool need_merge_streams = need_second_distinct_pass || query.limitBy()
|| (!pipeline_with_processors && query.limitLength()); /// Don't merge streams for pre-limit more.
if constexpr (!pipeline_with_processors)
if (pipeline.hasDelayedStream())
need_merge_streams = true;
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if (need_merge_streams)
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{
if constexpr (pipeline_with_processors)
pipeline.resize(1);
else
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executeUnion(pipeline, {});
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}
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/** If there was more than one stream,
* then DISTINCT needs to be performed once again after merging all streams.
*/
if (need_second_distinct_pass)
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executeDistinct(pipeline, false, expressions.selected_columns);
if (expressions.hasLimitBy())
{
executeExpression(pipeline, expressions.before_limit_by);
executeLimitBy(pipeline);
}
executeWithFill(pipeline);
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/** 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 (!(pipeline_with_processors && has_prelimit)) /// Limit is no longer needed if there is prelimit.
executeLimit(pipeline);
}
}
if (query_analyzer->hasGlobalSubqueries() && !subqueries_for_sets.empty())
executeSubqueriesInSetsAndJoins(pipeline, subqueries_for_sets);
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}
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template <typename TPipeline>
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void InterpreterSelectQuery::executeFetchColumns(
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QueryProcessingStage::Enum processing_stage, TPipeline & pipeline,
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const PrewhereInfoPtr & prewhere_info, const Names & columns_to_remove_after_prewhere,
QueryPipeline & save_context_and_storage)
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{
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constexpr bool pipeline_with_processors = std::is_same<TPipeline, QueryPipeline>::value;
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auto & query = getSelectQuery();
const Settings & settings = context->getSettingsRef();
/// Optimization for trivial query like SELECT count() FROM table.
auto check_trivial_count_query = [&]() -> std::optional<AggregateDescription>
{
if (!settings.optimize_trivial_count_query || !syntax_analyzer_result->maybe_optimize_trivial_count || !storage
|| query.sampleSize() || query.sampleOffset() || query.final() || query.prewhere() || query.where() || query.groupBy()
|| !query_analyzer->hasAggregation() || processing_stage != QueryProcessingStage::FetchColumns)
return {};
const AggregateDescriptions & aggregates = query_analyzer->aggregates();
if (aggregates.size() != 1)
return {};
const AggregateDescription & desc = aggregates[0];
if (typeid_cast<AggregateFunctionCount *>(desc.function.get()))
return desc;
return {};
};
if (auto desc = check_trivial_count_query())
{
auto func = desc->function;
std::optional<UInt64> num_rows = storage->totalRows();
if (num_rows)
{
AggregateFunctionCount & agg_count = static_cast<AggregateFunctionCount &>(*func);
/// We will process it up to "WithMergeableState".
std::vector<char> state(agg_count.sizeOfData());
AggregateDataPtr place = state.data();
agg_count.create(place);
SCOPE_EXIT(agg_count.destroy(place));
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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<DataTypeAggregateFunction>(func, argument_types, desc->parameters), desc->column_name}};
auto istream = std::make_shared<OneBlockInputStream>(block_with_count);
if constexpr (pipeline_with_processors)
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pipeline.init(Pipe(std::make_shared<SourceFromInputStream>(istream)));
else
pipeline.streams.emplace_back(istream);
from_stage = QueryProcessingStage::WithMergeableState;
analysis_result.first_stage = false;
return;
}
}
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/// 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<ASTExpressionList>();
/// Expression, that contains raw required columns for PREWHERE
ASTPtr required_columns_from_prewhere_expr = std::make_shared<ASTExpressionList>();
/// 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)
column_expr = setAlias(column_default->expression->clone(), column);
else
column_expr = std::make_shared<ASTIdentifier>(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<ASTIdentifier>(column.name));
required_columns_after_prewhere.emplace_back(column.name, column.type);
}
required_columns_after_prewhere_set
= ext::map<NameSet>(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);
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/// The set of required columns could be added as a result of adding an action to calculate ALIAS.
required_columns = alias_actions->getRequiredColumns();
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/// 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;
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/// 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);
}), required_columns.end());
if (prewhere_info)
{
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/// Don't remove columns which are needed to be aliased.
auto new_actions = std::make_shared<ExpressionActions>(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);
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/// 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.
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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(),
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ErrorCodes::TOO_MANY_COLUMNS);
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/** 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);
}
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UInt64 max_block_size = settings.max_block_size;
auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context);
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/** Optimization - if not specified DISTINCT, WHERE, GROUP, HAVING, ORDER, LIMIT BY, WITH TIES but LIMIT is specified, and limit + offset < max_block_size,
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* 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
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&& !query.limit_with_ties
&& !query.prewhere()
&& !query.where()
&& !query.groupBy()
&& !query.having()
&& !query.orderBy()
&& !query.limitBy()
&& query.limitLength()
&& !query_analyzer->hasAggregation()
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&& limit_length + limit_offset < max_block_size)
{
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max_block_size = std::max(UInt64(1), limit_length + limit_offset);
max_streams = 1;
pipeline.setMaxThreads(max_streams);
}
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if (!max_block_size)
throw Exception("Setting 'max_block_size' cannot be zero", ErrorCodes::PARAMETER_OUT_OF_BOUND);
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/// Initialize the initial data streams to which the query transforms are superimposed. Table or subquery or prepared input?
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if (pipeline.initialized())
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{
/// Prepared input.
}
else if (interpreter_subquery)
{
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/// Subquery.
/// If we need less number of columns that subquery have - update the interpreter.
if (required_columns.size() < source_header.columns())
{
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ASTPtr subquery = extractTableExpression(query, 0);
if (!subquery)
throw Exception("Subquery expected", ErrorCodes::LOGICAL_ERROR);
interpreter_subquery = std::make_unique<InterpreterSelectWithUnionQuery>(
subquery, getSubqueryContext(*context),
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options.copy().subquery().noModify(), required_columns);
if (query_analyzer->hasAggregation())
interpreter_subquery->ignoreWithTotals();
}
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if constexpr (pipeline_with_processors)
/// Just use pipeline from subquery.
pipeline = interpreter_subquery->executeWithProcessors();
else
pipeline.streams = interpreter_subquery->executeWithMultipleStreams(save_context_and_storage);
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}
else if (storage)
{
/// Table.
if (max_streams == 0)
throw Exception("Logical error: zero number of streams requested", ErrorCodes::LOGICAL_ERROR);
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/// 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;
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/// Create optimizer with prepared actions.
/// Maybe we will need to calc input_sorting_info later, e.g. while reading from StorageMerge.
if (analysis_result.optimize_read_in_order)
{
query_info.order_by_optimizer = std::make_shared<ReadInOrderOptimizer>(
analysis_result.order_by_elements_actions,
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getSortDescription(query, *context),
query_info.syntax_analyzer_result);
query_info.input_sorting_info = query_info.order_by_optimizer->getInputOrder(storage);
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}
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BlockInputStreams streams;
Pipes pipes;
if (pipeline_with_processors)
pipes = storage->read(required_columns, query_info, *context, processing_stage, max_block_size, max_streams);
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else
streams = storage->readStreams(required_columns, query_info, *context, processing_stage, max_block_size, max_streams);
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if (streams.empty() && !pipeline_with_processors)
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{
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streams = {std::make_shared<NullBlockInputStream>(storage->getSampleBlockForColumns(required_columns))};
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if (query_info.prewhere_info)
{
if (query_info.prewhere_info->alias_actions)
{
streams.back() = std::make_shared<ExpressionBlockInputStream>(
streams.back(),
query_info.prewhere_info->alias_actions);
}
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streams.back() = std::make_shared<FilterBlockInputStream>(
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streams.back(),
prewhere_info->prewhere_actions,
prewhere_info->prewhere_column_name,
prewhere_info->remove_prewhere_column);
// To remove additional columns
// In some cases, we did not read any marks so that the pipeline.streams is empty
// Thus, some columns in prewhere are not removed as expected
// This leads to mismatched header in distributed table
if (query_info.prewhere_info->remove_columns_actions)
{
streams.back() = std::make_shared<ExpressionBlockInputStream>(streams.back(), query_info.prewhere_info->remove_columns_actions);
}
}
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}
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/// Copy-paste from prev if.
/// Code is temporarily copy-pasted while moving to new pipeline.
if (pipes.empty() && pipeline_with_processors)
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{
Pipe pipe(std::make_shared<NullSource>(storage->getSampleBlockForColumns(required_columns)));
if (query_info.prewhere_info)
{
if (query_info.prewhere_info->alias_actions)
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(
pipe.getHeader(), query_info.prewhere_info->alias_actions));
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pipe.addSimpleTransform(std::make_shared<FilterTransform>(
pipe.getHeader(),
prewhere_info->prewhere_actions,
prewhere_info->prewhere_column_name,
prewhere_info->remove_prewhere_column));
if (query_info.prewhere_info->remove_columns_actions)
pipe.addSimpleTransform(std::make_shared<ExpressionTransform>(pipe.getHeader(), query_info.prewhere_info->remove_columns_actions));
}
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pipes.emplace_back(std::move(pipe));
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}
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for (auto & stream : streams)
stream->addTableLock(table_lock);
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if constexpr (pipeline_with_processors)
{
/// Table lock is stored inside pipeline here.
pipeline.addTableLock(table_lock);
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}
/// Set the limits and quota for reading data, the speed and time of the query.
{
IBlockInputStream::LocalLimits limits;
limits.mode = IBlockInputStream::LIMITS_TOTAL;
limits.size_limits = SizeLimits(settings.max_rows_to_read, settings.max_bytes_to_read, settings.read_overflow_mode);
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limits.speed_limits.max_execution_time = settings.max_execution_time;
limits.timeout_overflow_mode = settings.timeout_overflow_mode;
/** Quota and minimal speed restrictions are checked on the initiating server of the request, and not on remote servers,
* because the initiating server has a summary of the execution of the request on all servers.
*
* But limits on data size to read and maximum execution time are reasonable to check both on initiator and
* additionally on each remote server, because these limits are checked per block of data processed,
* and remote servers may process way more blocks of data than are received by initiator.
*/
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if (options.to_stage == QueryProcessingStage::Complete)
{
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limits.speed_limits.min_execution_rps = settings.min_execution_speed;
limits.speed_limits.max_execution_rps = settings.max_execution_speed;
limits.speed_limits.min_execution_bps = settings.min_execution_speed_bytes;
limits.speed_limits.max_execution_bps = settings.max_execution_speed_bytes;
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limits.speed_limits.timeout_before_checking_execution_speed = settings.timeout_before_checking_execution_speed;
}
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auto quota = context->getQuota();
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for (auto & stream : streams)
{
if (!options.ignore_limits)
stream->setLimits(limits);
if (!options.ignore_quota && (options.to_stage == QueryProcessingStage::Complete))
stream->setQuota(quota);
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}
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/// Copy-paste
for (auto & pipe : pipes)
{
if (!options.ignore_limits)
pipe.setLimits(limits);
if (!options.ignore_quota && (options.to_stage == QueryProcessingStage::Complete))
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pipe.setQuota(quota);
}
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}
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if constexpr (pipeline_with_processors)
{
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if (streams.size() == 1 || pipes.size() == 1)
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pipeline.setMaxThreads(streams.size());
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/// Unify streams. They must have same headers.
if (streams.size() > 1)
{
/// Unify streams in case they have different headers.
auto first_header = streams.at(0)->getHeader();
if (first_header.columns() > 1 && first_header.has("_dummy"))
first_header.erase("_dummy");
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for (auto & stream : streams)
{
auto header = stream->getHeader();
auto mode = ConvertingBlockInputStream::MatchColumnsMode::Name;
if (!blocksHaveEqualStructure(first_header, header))
stream = std::make_shared<ConvertingBlockInputStream>(*context, stream, first_header, mode);
}
}
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for (auto & stream : streams)
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{
bool force_add_agg_info = processing_stage == QueryProcessingStage::WithMergeableState;
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auto source = std::make_shared<SourceFromInputStream>(stream, force_add_agg_info);
if (processing_stage == QueryProcessingStage::Complete)
source->addTotalsPort();
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pipes.emplace_back(std::move(source));
}
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for (auto & pipe : pipes)
pipe.enableQuota();
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pipeline.init(std::move(pipes));
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}
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else
pipeline.streams = std::move(streams);
}
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else
throw Exception("Logical error in InterpreterSelectQuery: nowhere to read", ErrorCodes::LOGICAL_ERROR);
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/// Aliases in table declaration.
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if (processing_stage == QueryProcessingStage::FetchColumns && alias_actions)
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{
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if constexpr (pipeline_with_processors)
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{
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pipeline.addSimpleTransform([&](const Block & header)
{
return std::make_shared<ExpressionTransform>(header, alias_actions);
});
}
else
{
pipeline.transform([&](auto & stream)
{
stream = std::make_shared<ExpressionBlockInputStream>(stream, alias_actions);
});
}
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}
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}
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void InterpreterSelectQuery::executeWhere(Pipeline & pipeline, const ExpressionActionsPtr & expression, bool remove_filter)
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{
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pipeline.transform([&](auto & stream)
{
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stream = std::make_shared<FilterBlockInputStream>(stream, expression, getSelectQuery().where()->getColumnName(), remove_filter);
});
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}
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void InterpreterSelectQuery::executeWhere(QueryPipeline & pipeline, const ExpressionActionsPtr & expression, bool remove_filter)
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{
pipeline.addSimpleTransform([&](const Block & block)
{
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return std::make_shared<FilterTransform>(block, expression, getSelectQuery().where()->getColumnName(), remove_filter);
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});
}
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void InterpreterSelectQuery::executeAggregation(Pipeline & pipeline, const ExpressionActionsPtr & expression, bool overflow_row, bool final)
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{
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pipeline.transform([&](auto & stream)
{
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stream = std::make_shared<ExpressionBlockInputStream>(stream, expression);
});
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Block header = pipeline.firstStream()->getHeader();
ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header.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.getPositionByName(name));
const Settings & settings = context->getSettingsRef();
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/** 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.streams.size() > 1 || settings.max_bytes_before_external_group_by != 0;
Aggregator::Params params(header, 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);
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/// If there are several sources, then we perform parallel aggregation
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if (pipeline.streams.size() > 1)
{
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pipeline.firstStream() = std::make_shared<ParallelAggregatingBlockInputStream>(
pipeline.streams, pipeline.stream_with_non_joined_data, params, final,
max_streams,
settings.aggregation_memory_efficient_merge_threads
? static_cast<size_t>(settings.aggregation_memory_efficient_merge_threads)
: static_cast<size_t>(settings.max_threads));
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pipeline.stream_with_non_joined_data = nullptr;
pipeline.streams.resize(1);
}
else
{
BlockInputStreams inputs;
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if (!pipeline.streams.empty())
inputs.push_back(pipeline.firstStream());
else
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pipeline.streams.resize(1);
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if (pipeline.stream_with_non_joined_data)
inputs.push_back(pipeline.stream_with_non_joined_data);
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pipeline.firstStream() = std::make_shared<AggregatingBlockInputStream>(std::make_shared<ConcatBlockInputStream>(inputs), params, final);
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pipeline.stream_with_non_joined_data = nullptr;
}
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}
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void InterpreterSelectQuery::executeAggregation(QueryPipeline & pipeline, const ExpressionActionsPtr & expression, bool overflow_row, bool final)
{
pipeline.addSimpleTransform([&](const Block & header)
{
return std::make_shared<ExpressionTransform>(header, expression);
});
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Block header_before_aggregation = pipeline.getHeader();
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ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header_before_aggregation.getPositionByName(key.name));
AggregateDescriptions aggregates = query_analyzer->aggregates();
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for (auto & descr : aggregates)
if (descr.arguments.empty())
for (const auto & name : descr.argument_names)
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descr.arguments.push_back(header_before_aggregation.getPositionByName(name));
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const Settings & settings = context->getSettingsRef();
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/** 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;
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Aggregator::Params params(header_before_aggregation, keys, aggregates,
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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);
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auto transform_params = std::make_shared<AggregatingTransformParams>(params, final);
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pipeline.dropTotalsIfHas();
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/// If there are several sources, then we perform parallel aggregation
if (pipeline.getNumStreams() > 1)
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{
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/// Add resize transform to uniformly distribute data between aggregating streams.
if (!(storage && storage->hasEvenlyDistributedRead()))
pipeline.resize(pipeline.getNumStreams(), true, true);
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auto many_data = std::make_shared<ManyAggregatedData>(pipeline.getNumStreams());
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auto merge_threads = settings.aggregation_memory_efficient_merge_threads
? static_cast<size_t>(settings.aggregation_memory_efficient_merge_threads)
: static_cast<size_t>(settings.max_threads);
size_t counter = 0;
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pipeline.addSimpleTransform([&](const Block & header)
{
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return std::make_shared<AggregatingTransform>(header, transform_params, many_data, counter++, max_streams, merge_threads);
});
pipeline.resize(1);
}
else
{
pipeline.resize(1);
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pipeline.addSimpleTransform([&](const Block & header)
{
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return std::make_shared<AggregatingTransform>(header, transform_params);
});
}
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pipeline.enableQuotaForCurrentStreams();
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}
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void InterpreterSelectQuery::executeMergeAggregated(Pipeline & pipeline, bool overflow_row, bool final)
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{
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Block header = pipeline.firstStream()->getHeader();
ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header.getPositionByName(key.name));
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/** There are two modes of distributed aggregation.
*
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* 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.
*
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* 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.
*
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* 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();
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Aggregator::Params params(header, keys, query_analyzer->aggregates(), overflow_row, settings.max_threads);
if (!settings.distributed_aggregation_memory_efficient)
{
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/// We union several sources into one, parallelizing the work.
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executeUnion(pipeline, {});
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/// Now merge the aggregated blocks
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pipeline.firstStream() = std::make_shared<MergingAggregatedBlockInputStream>(pipeline.firstStream(), params, final, settings.max_threads);
}
else
{
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pipeline.firstStream() = std::make_shared<MergingAggregatedMemoryEfficientBlockInputStream>(pipeline.streams, params, final,
max_streams,
settings.aggregation_memory_efficient_merge_threads
? static_cast<size_t>(settings.aggregation_memory_efficient_merge_threads)
: static_cast<size_t>(settings.max_threads));
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pipeline.streams.resize(1);
}
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}
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void InterpreterSelectQuery::executeMergeAggregated(QueryPipeline & pipeline, bool overflow_row, bool final)
{
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Block header_before_merge = pipeline.getHeader();
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ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header_before_merge.getPositionByName(key.name));
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/** 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();
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Aggregator::Params params(header_before_merge, keys, query_analyzer->aggregates(), overflow_row, settings.max_threads);
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auto transform_params = std::make_shared<AggregatingTransformParams>(params, final);
if (!settings.distributed_aggregation_memory_efficient)
{
/// We union several sources into one, parallelizing the work.
pipeline.resize(1);
/// Now merge the aggregated blocks
pipeline.addSimpleTransform([&](const Block & header)
{
return std::make_shared<MergingAggregatedTransform>(header, transform_params, settings.max_threads);
});
}
else
{
/// pipeline.resize(max_streams); - Seem we don't need it.
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auto num_merge_threads = settings.aggregation_memory_efficient_merge_threads
? static_cast<size_t>(settings.aggregation_memory_efficient_merge_threads)
: static_cast<size_t>(settings.max_threads);
auto pipe = createMergingAggregatedMemoryEfficientPipe(
pipeline.getHeader(),
transform_params,
pipeline.getNumStreams(),
num_merge_threads);
pipeline.addPipe(std::move(pipe));
}
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pipeline.enableQuotaForCurrentStreams();
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}
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void InterpreterSelectQuery::executeHaving(Pipeline & pipeline, const ExpressionActionsPtr & expression)
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{
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pipeline.transform([&](auto & stream)
{
stream = std::make_shared<FilterBlockInputStream>(stream, expression, getSelectQuery().having()->getColumnName());
});
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}
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void InterpreterSelectQuery::executeHaving(QueryPipeline & pipeline, const ExpressionActionsPtr & expression)
{
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pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
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if (stream_type == QueryPipeline::StreamType::Totals)
return nullptr;
/// TODO: do we need to save filter there?
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return std::make_shared<FilterTransform>(header, expression, getSelectQuery().having()->getColumnName(), false);
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});
}
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void InterpreterSelectQuery::executeTotalsAndHaving(Pipeline & pipeline, bool has_having, const ExpressionActionsPtr & expression, bool overflow_row, bool final)
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{
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executeUnion(pipeline, {});
const Settings & settings = context->getSettingsRef();
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pipeline.firstStream() = std::make_shared<TotalsHavingBlockInputStream>(
pipeline.firstStream(),
overflow_row,
expression,
has_having ? getSelectQuery().having()->getColumnName() : "",
settings.totals_mode,
settings.totals_auto_threshold,
final);
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}
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void InterpreterSelectQuery::executeTotalsAndHaving(QueryPipeline & pipeline, bool has_having, const ExpressionActionsPtr & expression, bool overflow_row, bool final)
{
const Settings & settings = context->getSettingsRef();
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auto totals_having = std::make_shared<TotalsHavingTransform>(
pipeline.getHeader(), overflow_row, expression,
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has_having ? getSelectQuery().having()->getColumnName() : "",
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settings.totals_mode, settings.totals_auto_threshold, final);
pipeline.addTotalsHavingTransform(std::move(totals_having));
}
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void InterpreterSelectQuery::executeRollupOrCube(Pipeline & pipeline, Modificator modificator)
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{
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executeUnion(pipeline, {});
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Block header = pipeline.firstStream()->getHeader();
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ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header.getPositionByName(key.name));
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const Settings & settings = context->getSettingsRef();
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Aggregator::Params params(header, keys, query_analyzer->aggregates(),
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false, settings.max_rows_to_group_by, settings.group_by_overflow_mode,
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SettingUInt64(0), SettingUInt64(0),
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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);
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2018-09-20 17:51:42 +00:00
if (modificator == Modificator::ROLLUP)
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pipeline.firstStream() = std::make_shared<RollupBlockInputStream>(pipeline.firstStream(), params);
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else
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pipeline.firstStream() = std::make_shared<CubeBlockInputStream>(pipeline.firstStream(), params);
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}
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void InterpreterSelectQuery::executeRollupOrCube(QueryPipeline & pipeline, Modificator modificator)
{
pipeline.resize(1);
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Block header_before_transform = pipeline.getHeader();
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ColumnNumbers keys;
for (const auto & key : query_analyzer->aggregationKeys())
keys.push_back(header_before_transform.getPositionByName(key.name));
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const Settings & settings = context->getSettingsRef();
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Aggregator::Params params(header_before_transform, keys, query_analyzer->aggregates(),
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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);
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auto transform_params = std::make_shared<AggregatingTransformParams>(params, true);
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pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
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if (stream_type == QueryPipeline::StreamType::Totals)
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return nullptr;
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if (modificator == Modificator::ROLLUP)
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return std::make_shared<RollupTransform>(header, std::move(transform_params));
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else
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return std::make_shared<CubeTransform>(header, std::move(transform_params));
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});
}
2014-02-27 12:49:21 +00:00
2018-02-21 03:26:06 +00:00
void InterpreterSelectQuery::executeExpression(Pipeline & pipeline, const ExpressionActionsPtr & expression)
2012-05-09 13:12:38 +00:00
{
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pipeline.transform([&](auto & stream)
{
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stream = std::make_shared<ExpressionBlockInputStream>(stream, expression);
});
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}
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void InterpreterSelectQuery::executeExpression(QueryPipeline & pipeline, const ExpressionActionsPtr & expression)
{
pipeline.addSimpleTransform([&](const Block & header) -> ProcessorPtr
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{
return std::make_shared<ExpressionTransform>(header, expression);
});
}
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void InterpreterSelectQuery::executeOrder(Pipeline & pipeline, InputSortingInfoPtr input_sorting_info)
{
2019-03-12 14:07:02 +00:00
auto & query = getSelectQuery();
SortDescription output_order_descr = getSortDescription(query, *context);
const Settings & settings = context->getSettingsRef();
UInt64 limit = getLimitForSorting(query, *context);
2017-05-24 20:13:04 +00:00
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.
* If the input is sorted by some prefix of the sorting key required for output,
* we have to finish sorting after the merge.
*/
bool need_finish_sorting = (input_sorting_info->order_key_prefix_descr.size() < output_order_descr.size());
2019-11-13 14:57:45 +00:00
UInt64 limit_for_merging = (need_finish_sorting ? 0 : limit);
executeMergeSorted(pipeline, input_sorting_info->order_key_prefix_descr, limit_for_merging);
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if (need_finish_sorting)
{
pipeline.transform([&](auto & stream)
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{
stream = std::make_shared<PartialSortingBlockInputStream>(stream, output_order_descr, limit);
});
pipeline.firstStream() = std::make_shared<FinishSortingBlockInputStream>(
pipeline.firstStream(), input_sorting_info->order_key_prefix_descr,
output_order_descr, settings.max_block_size, limit);
}
}
else
{
pipeline.transform([&](auto & stream)
{
auto sorting_stream = std::make_shared<PartialSortingBlockInputStream>(stream, output_order_descr, limit);
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/// Limits on sorting
IBlockInputStream::LocalLimits limits;
limits.mode = IBlockInputStream::LIMITS_TOTAL;
limits.size_limits = SizeLimits(settings.max_rows_to_sort, settings.max_bytes_to_sort, settings.sort_overflow_mode);
sorting_stream->setLimits(limits);
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2020-01-06 12:43:27 +00:00
auto merging_stream = std::make_shared<MergeSortingBlockInputStream>(
sorting_stream, output_order_descr, settings.max_block_size, limit,
settings.max_bytes_before_remerge_sort,
settings.max_bytes_before_external_sort / pipeline.streams.size(),
context->getTemporaryVolume(), settings.min_free_disk_space_for_temporary_data);
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stream = merging_stream;
});
/// If there are several streams, we merge them into one
2020-01-06 12:43:27 +00:00
executeMergeSorted(pipeline, output_order_descr, limit);
}
}
2012-02-27 06:28:20 +00:00
void InterpreterSelectQuery::executeOrder(QueryPipeline & pipeline, InputSortingInfoPtr input_sorting_info)
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{
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auto & query = getSelectQuery();
SortDescription output_order_descr = getSortDescription(query, *context);
UInt64 limit = getLimitForSorting(query, *context);
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const Settings & settings = context->getSettingsRef();
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/// TODO: Limits on sorting
// IBlockInputStream::LocalLimits limits;
// limits.mode = IBlockInputStream::LIMITS_TOTAL;
// limits.size_limits = SizeLimits(settings.max_rows_to_sort, settings.max_bytes_to_sort, settings.sort_overflow_mode);
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.
*/
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<MergingSortedTransform>(
pipeline.getHeader(),
pipeline.getNumStreams(),
input_sorting_info->order_key_prefix_descr,
settings.max_block_size, limit_for_merging);
pipeline.addPipe({ std::move(transform) });
}
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pipeline.enableQuotaForCurrentStreams();
if (need_finish_sorting)
{
pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type != QueryPipeline::StreamType::Main)
return nullptr;
return std::make_shared<PartialSortingTransform>(header, output_order_descr, limit);
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});
pipeline.addSimpleTransform([&](const Block & header) -> ProcessorPtr
{
return std::make_shared<FinishSortingTransform>(
header, input_sorting_info->order_key_prefix_descr,
output_order_descr, settings.max_block_size, limit);
});
}
return;
}
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pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type != QueryPipeline::StreamType::Main)
return nullptr;
return std::make_shared<PartialSortingTransform>(header, output_order_descr, limit);
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});
/// Merge the sorted blocks.
pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type == QueryPipeline::StreamType::Totals)
return nullptr;
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return std::make_shared<MergeSortingTransform>(
header, output_order_descr, settings.max_block_size, limit,
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settings.max_bytes_before_remerge_sort / pipeline.getNumStreams(),
settings.max_bytes_before_external_sort, context->getTemporaryVolume(),
settings.min_free_disk_space_for_temporary_data);
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});
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/// If there are several streams, we merge them into one
executeMergeSorted(pipeline, output_order_descr, limit);
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}
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void InterpreterSelectQuery::executeMergeSorted(Pipeline & pipeline)
{
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auto & query = getSelectQuery();
SortDescription order_descr = getSortDescription(query, *context);
UInt64 limit = getLimitForSorting(query, *context);
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/// If there are several streams, then we merge them into one
2018-02-21 03:26:06 +00:00
if (pipeline.hasMoreThanOneStream())
{
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unifyStreams(pipeline, pipeline.firstStream()->getHeader());
executeMergeSorted(pipeline, order_descr, limit);
}
}
void InterpreterSelectQuery::executeMergeSorted(Pipeline & pipeline, const SortDescription & sort_description, UInt64 limit)
{
if (pipeline.hasMoreThanOneStream())
{
const Settings & settings = context->getSettingsRef();
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/** MergingSortedBlockInputStream reads the sources sequentially.
* To make the data on the remote servers prepared in parallel, we wrap it in AsynchronousBlockInputStream.
*/
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pipeline.transform([&](auto & stream)
{
stream = std::make_shared<AsynchronousBlockInputStream>(stream);
});
pipeline.firstStream() = std::make_shared<MergingSortedBlockInputStream>(
pipeline.streams, sort_description, settings.max_block_size, limit);
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pipeline.streams.resize(1);
}
}
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void InterpreterSelectQuery::executeMergeSorted(QueryPipeline & pipeline)
{
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auto & query = getSelectQuery();
SortDescription order_descr = getSortDescription(query, *context);
UInt64 limit = getLimitForSorting(query, *context);
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executeMergeSorted(pipeline, order_descr, limit);
}
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void InterpreterSelectQuery::executeMergeSorted(QueryPipeline & pipeline, const SortDescription & sort_description, UInt64 limit)
{
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/// If there are several streams, then we merge them into one
if (pipeline.getNumStreams() > 1)
{
const Settings & settings = context->getSettingsRef();
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auto transform = std::make_shared<MergingSortedTransform>(
pipeline.getHeader(),
pipeline.getNumStreams(),
sort_description,
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settings.max_block_size, limit);
pipeline.addPipe({ std::move(transform) });
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pipeline.enableQuotaForCurrentStreams();
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}
}
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void InterpreterSelectQuery::executeProjection(Pipeline & pipeline, const ExpressionActionsPtr & expression)
{
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pipeline.transform([&](auto & stream)
{
stream = std::make_shared<ExpressionBlockInputStream>(stream, expression);
});
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}
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void InterpreterSelectQuery::executeProjection(QueryPipeline & pipeline, const ExpressionActionsPtr & expression)
{
pipeline.addSimpleTransform([&](const Block & header) -> ProcessorPtr
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{
return std::make_shared<ExpressionTransform>(header, expression);
});
}
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void InterpreterSelectQuery::executeDistinct(Pipeline & pipeline, bool before_order, Names columns)
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{
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auto & query = getSelectQuery();
if (query.distinct)
{
const Settings & settings = context->getSettingsRef();
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auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context);
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UInt64 limit_for_distinct = 0;
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/// 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.
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if ((!query.orderBy() || !before_order) && !query.limit_with_ties)
limit_for_distinct = limit_length + limit_offset;
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pipeline.transform([&](auto & stream)
{
SizeLimits limits(settings.max_rows_in_distinct, settings.max_bytes_in_distinct, settings.distinct_overflow_mode);
stream = std::make_shared<DistinctBlockInputStream>(stream, limits, limit_for_distinct, columns);
});
}
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}
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void InterpreterSelectQuery::executeDistinct(QueryPipeline & pipeline, bool before_order, Names columns)
{
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auto & query = getSelectQuery();
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if (query.distinct)
{
const Settings & settings = context->getSettingsRef();
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auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context);
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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.
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if (!query.orderBy() || !before_order)
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limit_for_distinct = limit_length + limit_offset;
SizeLimits limits(settings.max_rows_in_distinct, settings.max_bytes_in_distinct, settings.distinct_overflow_mode);
pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type == QueryPipeline::StreamType::Totals)
return nullptr;
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return std::make_shared<DistinctTransform>(header, limits, limit_for_distinct, columns);
});
}
}
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void InterpreterSelectQuery::executeUnion(Pipeline & pipeline, Block header)
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{
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/// If there are still several streams, then we combine them into one
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if (pipeline.hasMoreThanOneStream())
{
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if (!header)
header = pipeline.firstStream()->getHeader();
unifyStreams(pipeline, std::move(header));
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pipeline.firstStream() = std::make_shared<UnionBlockInputStream>(pipeline.streams, pipeline.stream_with_non_joined_data, max_streams);
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pipeline.stream_with_non_joined_data = nullptr;
pipeline.streams.resize(1);
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pipeline.union_stream = true;
}
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else if (pipeline.stream_with_non_joined_data)
{
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pipeline.streams.push_back(pipeline.stream_with_non_joined_data);
pipeline.stream_with_non_joined_data = nullptr;
}
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}
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/// Preliminary LIMIT - is used in every source, if there are several sources, before they are combined.
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void InterpreterSelectQuery::executePreLimit(Pipeline & pipeline)
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{
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auto & query = getSelectQuery();
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/// If there is LIMIT
if (query.limitLength())
{
auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context);
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SortDescription sort_descr;
if (query.limit_with_ties)
{
if (!query.orderBy())
throw Exception("LIMIT WITH TIES without ORDER BY", ErrorCodes::LOGICAL_ERROR);
sort_descr = getSortDescription(query, *context);
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}
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pipeline.transform([&, limit = limit_length + limit_offset](auto & stream)
{
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stream = std::make_shared<LimitBlockInputStream>(stream, limit, 0, false, false, query.limit_with_ties, sort_descr);
});
}
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}
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/// Preliminary LIMIT - is used in every source, if there are several sources, before they are combined.
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void InterpreterSelectQuery::executePreLimit(QueryPipeline & pipeline, bool do_not_skip_offset)
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{
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auto & query = getSelectQuery();
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/// If there is LIMIT
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if (query.limitLength())
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{
auto [limit_length, limit_offset] = getLimitLengthAndOffset(query, *context);
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if (do_not_skip_offset)
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{
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limit_length += limit_offset;
limit_offset = 0;
}
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auto limit = std::make_shared<LimitTransform>(pipeline.getHeader(), limit_length, limit_offset, pipeline.getNumStreams());
pipeline.addPipe({std::move(limit)});
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}
}
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void InterpreterSelectQuery::executeLimitBy(Pipeline & pipeline)
{
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auto & query = getSelectQuery();
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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);
UInt64 offset = (query.limitByOffset() ? getLimitUIntValue(query.limitByOffset(), *context) : 0);
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pipeline.transform([&](auto & stream)
{
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stream = std::make_shared<LimitByBlockInputStream>(stream, length, offset, columns);
});
}
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void InterpreterSelectQuery::executeLimitBy(QueryPipeline & pipeline)
{
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auto & query = getSelectQuery();
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if (!query.limitByLength() || !query.limitBy())
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return;
Names columns;
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for (const auto & elem : query.limitBy()->children)
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columns.emplace_back(elem->getColumnName());
UInt64 length = getLimitUIntValue(query.limitByLength(), *context);
UInt64 offset = (query.limitByOffset() ? getLimitUIntValue(query.limitByOffset(), *context) : 0);
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pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type == QueryPipeline::StreamType::Totals)
return nullptr;
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return std::make_shared<LimitByTransform>(header, length, offset, columns);
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});
}
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namespace
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{
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bool hasWithTotalsInAnySubqueryInFromClause(const ASTSelectQuery & query)
{
if (query.group_by_with_totals)
return true;
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/** NOTE You can also check that the table in the subquery is distributed, and that it only looks at one shard.
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* 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.
*/
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if (auto query_table = extractTableExpression(query, 0))
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{
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if (const auto * ast_union = query_table->as<ASTSelectWithUnionQuery>())
{
for (const auto & elem : ast_union->list_of_selects->children)
if (hasWithTotalsInAnySubqueryInFromClause(elem->as<ASTSelectQuery &>()))
return true;
}
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}
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return false;
}
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}
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void InterpreterSelectQuery::executeLimit(Pipeline & pipeline)
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{
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auto & query = getSelectQuery();
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/// If there is LIMIT
if (query.limitLength())
{
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/** 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.
*
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* 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;
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if (!query.group_by_with_totals && hasWithTotalsInAnySubqueryInFromClause(query))
always_read_till_end = true;
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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);
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}
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UInt64 limit_length;
UInt64 limit_offset;
std::tie(limit_length, limit_offset) = getLimitLengthAndOffset(query, *context);
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pipeline.transform([&](auto & stream)
{
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stream = std::make_shared<LimitBlockInputStream>(stream, limit_length, limit_offset, always_read_till_end, false, query.limit_with_ties, order_descr);
});
}
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}
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void InterpreterSelectQuery::executeWithFill(Pipeline & pipeline)
{
auto & query = getSelectQuery();
if (query.orderBy())
{
SortDescription order_descr = getSortDescription(query, *context);
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SortDescription fill_descr;
for (auto & desc : order_descr)
{
if (desc.with_fill)
fill_descr.push_back(desc);
}
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if (fill_descr.empty())
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return;
pipeline.transform([&](auto & stream)
{
stream = std::make_shared<FillingBlockInputStream>(stream, fill_descr);
});
}
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}
void InterpreterSelectQuery::executeWithFill(QueryPipeline & pipeline)
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{
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<FillingTransform>(header, fill_descr);
});
}
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}
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void InterpreterSelectQuery::executeLimit(QueryPipeline & pipeline)
{
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auto & query = getSelectQuery();
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/// If there is LIMIT
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if (query.limitLength())
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{
/** 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;
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if (query.group_by_with_totals && !query.orderBy())
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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);
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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);
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}
pipeline.addSimpleTransform([&](const Block & header, QueryPipeline::StreamType stream_type) -> ProcessorPtr
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{
if (stream_type != QueryPipeline::StreamType::Main)
return nullptr;
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return std::make_shared<LimitTransform>(
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header, limit_length, limit_offset, 1, always_read_till_end, query.limit_with_ties, order_descr);
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});
}
}
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void InterpreterSelectQuery::executeExtremes(Pipeline & pipeline)
{
if (!context->getSettingsRef().extremes)
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return;
pipeline.transform([&](auto & stream)
{
stream->enableExtremes();
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});
}
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void InterpreterSelectQuery::executeExtremes(QueryPipeline & pipeline)
{
if (!context->getSettingsRef().extremes)
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return;
auto transform = std::make_shared<ExtremesTransform>(pipeline.getHeader());
pipeline.addExtremesTransform(std::move(transform));
}
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void InterpreterSelectQuery::executeSubqueriesInSetsAndJoins(Pipeline & pipeline, const SubqueriesForSets & subqueries_for_sets)
{
/// Merge streams to one. Use MergeSorting if data was read in sorted order, Union otherwise.
if (query_info.input_sorting_info)
{
if (pipeline.stream_with_non_joined_data)
throw Exception("Using read in order optimization, but has stream with non-joined data in pipeline", ErrorCodes::LOGICAL_ERROR);
executeMergeSorted(pipeline, query_info.input_sorting_info->order_key_prefix_descr, 0);
}
else
executeUnion(pipeline, {});
pipeline.firstStream() = std::make_shared<CreatingSetsBlockInputStream>(
pipeline.firstStream(), subqueries_for_sets, *context);
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}
void InterpreterSelectQuery::executeSubqueriesInSetsAndJoins(QueryPipeline & pipeline, const SubqueriesForSets & subqueries_for_sets)
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{
if (query_info.input_sorting_info)
executeMergeSorted(pipeline, query_info.input_sorting_info->order_key_prefix_descr, 0);
const Settings & settings = context->getSettingsRef();
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auto creating_sets = std::make_shared<CreatingSetsTransform>(
pipeline.getHeader(), subqueries_for_sets,
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SizeLimits(settings.max_rows_to_transfer, settings.max_bytes_to_transfer, settings.transfer_overflow_mode),
*context);
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pipeline.addCreatingSetsTransform(std::move(creating_sets));
}
void InterpreterSelectQuery::unifyStreams(Pipeline & pipeline, Block header)
{
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/// Unify streams in case they have different headers.
/// TODO: remove previous addition of _dummy column.
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if (header.columns() > 1 && header.has("_dummy"))
header.erase("_dummy");
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for (auto & stream : pipeline.streams)
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{
auto stream_header = stream->getHeader();
auto mode = ConvertingBlockInputStream::MatchColumnsMode::Name;
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if (!blocksHaveEqualStructure(header, stream_header))
stream = std::make_shared<ConvertingBlockInputStream>(*context, stream, header, mode);
}
}
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void InterpreterSelectQuery::ignoreWithTotals()
{
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getSelectQuery().group_by_with_totals = false;
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}
void InterpreterSelectQuery::initSettings()
{
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auto & query = getSelectQuery();
if (query.settings())
InterpreterSetQuery(query.settings(), *context).executeForCurrentContext();
}
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}