mirror of
https://github.com/ClickHouse/ClickHouse.git
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fbe7df73a2
CONTRIB-254
2413 lines
84 KiB
C++
2413 lines
84 KiB
C++
#include <iomanip>
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#include <thread>
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#include <future>
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#include <Common/Stopwatch.h>
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#include <Common/setThreadName.h>
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#include <DataTypes/DataTypeAggregateFunction.h>
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#include <DataTypes/DataTypeNullable.h>
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#include <Columns/ColumnsNumber.h>
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#include <Columns/ColumnArray.h>
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#include <Columns/ColumnTuple.h>
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#include <AggregateFunctions/AggregateFunctionCount.h>
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#include <DataStreams/IProfilingBlockInputStream.h>
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#include <DataStreams/NativeBlockOutputStream.h>
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#include <DataStreams/NullBlockInputStream.h>
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#include <DataStreams/materializeBlock.h>
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#include <IO/WriteBufferFromFile.h>
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#include <IO/CompressedWriteBuffer.h>
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#include <Interpreters/Aggregator.h>
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#include <Common/ClickHouseRevision.h>
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#include <Common/MemoryTracker.h>
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#include <Common/typeid_cast.h>
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#include <common/demangle.h>
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#if __has_include(<Interpreters/config_compile.h>)
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#include <Interpreters/config_compile.h>
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#endif
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namespace ProfileEvents
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{
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extern const Event ExternalAggregationWritePart;
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extern const Event ExternalAggregationCompressedBytes;
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extern const Event ExternalAggregationUncompressedBytes;
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}
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namespace CurrentMetrics
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{
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extern const Metric QueryThread;
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}
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int CANNOT_COMPILE_CODE;
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extern const int TOO_MANY_ROWS;
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extern const int EMPTY_DATA_PASSED;
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extern const int CANNOT_MERGE_DIFFERENT_AGGREGATED_DATA_VARIANTS;
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}
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AggregatedDataVariants::~AggregatedDataVariants()
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{
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if (aggregator && !aggregator->all_aggregates_has_trivial_destructor)
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{
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try
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{
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aggregator->destroyAllAggregateStates(*this);
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}
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catch (...)
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{
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tryLogCurrentException(__PRETTY_FUNCTION__);
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}
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}
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}
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void AggregatedDataVariants::convertToTwoLevel()
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{
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if (aggregator)
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LOG_TRACE(aggregator->log, "Converting aggregation data to two-level.");
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switch (type)
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{
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#define M(NAME) \
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case Type::NAME: \
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NAME ## _two_level = std::make_unique<decltype(NAME ## _two_level)::element_type>(*NAME); \
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NAME.reset(); \
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type = Type::NAME ## _two_level; \
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break;
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APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M)
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#undef M
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default:
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throw Exception("Wrong data variant passed.", ErrorCodes::LOGICAL_ERROR);
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}
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}
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Block Aggregator::getHeader(bool final) const
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{
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Block res;
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if (params.src_header)
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{
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for (size_t i = 0; i < params.keys_size; ++i)
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res.insert(params.src_header.safeGetByPosition(params.keys[i]).cloneEmpty());
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for (size_t i = 0; i < params.aggregates_size; ++i)
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{
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size_t arguments_size = params.aggregates[i].arguments.size();
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DataTypes argument_types(arguments_size);
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for (size_t j = 0; j < arguments_size; ++j)
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argument_types[j] = params.src_header.safeGetByPosition(params.aggregates[i].arguments[j]).type;
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DataTypePtr type;
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if (final)
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type = params.aggregates[i].function->getReturnType();
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else
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type = std::make_shared<DataTypeAggregateFunction>(params.aggregates[i].function, argument_types, params.aggregates[i].parameters);
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res.insert({ type, params.aggregates[i].column_name });
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}
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}
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else if (params.intermediate_header)
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{
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res = params.intermediate_header.cloneEmpty();
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if (final)
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{
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for (size_t i = 0; i < params.aggregates_size; ++i)
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{
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auto & elem = res.getByPosition(params.keys_size + i);
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elem.type = params.aggregates[i].function->getReturnType();
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elem.column = elem.type->createColumn();
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}
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}
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}
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return materializeBlock(res);
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}
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Aggregator::Aggregator(const Params & params_)
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: params(params_),
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isCancelled([]() { return false; })
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{
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if (current_memory_tracker)
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memory_usage_before_aggregation = current_memory_tracker->get();
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aggregate_functions.resize(params.aggregates_size);
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for (size_t i = 0; i < params.aggregates_size; ++i)
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aggregate_functions[i] = params.aggregates[i].function.get();
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/// Initialize sizes of aggregation states and its offsets.
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offsets_of_aggregate_states.resize(params.aggregates_size);
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total_size_of_aggregate_states = 0;
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all_aggregates_has_trivial_destructor = true;
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for (size_t i = 0; i < params.aggregates_size; ++i)
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{
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offsets_of_aggregate_states[i] = total_size_of_aggregate_states;
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total_size_of_aggregate_states += params.aggregates[i].function->sizeOfData();
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if (!params.aggregates[i].function->hasTrivialDestructor())
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all_aggregates_has_trivial_destructor = false;
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}
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method = chooseAggregationMethod();
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}
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void Aggregator::compileIfPossible(AggregatedDataVariants::Type type)
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{
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std::lock_guard<std::mutex> lock(mutex);
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if (compiled_if_possible)
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return;
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compiled_if_possible = true;
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#if !defined(INTERNAL_COMPILER_HEADERS)
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throw Exception("Cannot compile code: Compiler disabled", ErrorCodes::CANNOT_COMPILE_CODE);
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#else
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std::string method_typename;
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std::string method_typename_two_level;
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if (false) {}
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#define M(NAME) \
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else if (type == AggregatedDataVariants::Type::NAME) \
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{ \
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method_typename = "decltype(AggregatedDataVariants::" #NAME ")::element_type"; \
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method_typename_two_level = "decltype(AggregatedDataVariants::" #NAME "_two_level)::element_type"; \
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}
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APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M)
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#undef M
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#define M(NAME) \
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else if (type == AggregatedDataVariants::Type::NAME) \
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method_typename = "decltype(AggregatedDataVariants::" #NAME ")::element_type";
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APPLY_FOR_VARIANTS_NOT_CONVERTIBLE_TO_TWO_LEVEL(M)
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#undef M
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else if (type == AggregatedDataVariants::Type::without_key) {}
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else
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throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
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/// List of types of aggregate functions.
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std::stringstream aggregate_functions_typenames_str;
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std::stringstream aggregate_functions_headers_args;
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for (size_t i = 0; i < params.aggregates_size; ++i)
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{
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IAggregateFunction & func = *aggregate_functions[i];
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int status = 0;
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std::string type_name = demangle(typeid(func).name(), status);
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if (status)
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throw Exception("Cannot compile code: cannot demangle name " + String(typeid(func).name())
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+ ", status: " + toString(status), ErrorCodes::CANNOT_COMPILE_CODE);
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aggregate_functions_typenames_str << ((i != 0) ? ", " : "") << type_name;
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std::string header_path = func.getHeaderFilePath();
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auto pos = header_path.find("/AggregateFunctions/");
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if (pos == std::string::npos)
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throw Exception("Cannot compile code: unusual path of header file for aggregate function: " + header_path,
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ErrorCodes::CANNOT_COMPILE_CODE);
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aggregate_functions_headers_args << "-include '" INTERNAL_COMPILER_HEADERS "/dbms/src";
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aggregate_functions_headers_args.write(&header_path[pos], header_path.size() - pos);
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aggregate_functions_headers_args << "' ";
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}
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aggregate_functions_headers_args << "-include '" INTERNAL_COMPILER_HEADERS "/dbms/src/Interpreters/SpecializedAggregator.h'";
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std::string aggregate_functions_typenames = aggregate_functions_typenames_str.str();
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std::stringstream key_str;
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key_str << "Aggregate: ";
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if (!method_typename.empty())
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key_str << method_typename + ", ";
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key_str << aggregate_functions_typenames;
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std::string key = key_str.str();
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auto get_code = [method_typename, method_typename_two_level, aggregate_functions_typenames]
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{
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/// A short piece of code, which is an explicit instantiation of the template.
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std::stringstream code;
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code << /// No explicit inclusion of the header file. It is included using the -include compiler option.
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"namespace DB\n"
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"{\n"
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"\n";
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/// There can be up to two instantiations for the template - for normal and two_level options.
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auto append_code_for_specialization =
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[&code, &aggregate_functions_typenames] (const std::string & method_typename, const std::string & suffix)
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{
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code <<
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"template void Aggregator::executeSpecialized<\n"
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" " << method_typename << ", TypeList<" << aggregate_functions_typenames << ">>(\n"
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" " << method_typename << " &, Arena *, size_t, ColumnRawPtrs &,\n"
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" AggregateColumns &, const Sizes &, StringRefs &, bool, AggregateDataPtr) const;\n"
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"\n"
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"static void wrapper" << suffix << "(\n"
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" const Aggregator & aggregator,\n"
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" " << method_typename << " & method,\n"
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" Arena * arena,\n"
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" size_t rows,\n"
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" ColumnRawPtrs & key_columns,\n"
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" Aggregator::AggregateColumns & aggregate_columns,\n"
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" const Sizes & key_sizes,\n"
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" StringRefs & keys,\n"
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" bool no_more_keys,\n"
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" AggregateDataPtr overflow_row)\n"
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"{\n"
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" aggregator.executeSpecialized<\n"
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" " << method_typename << ", TypeList<" << aggregate_functions_typenames << ">>(\n"
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" method, arena, rows, key_columns, aggregate_columns, key_sizes, keys, no_more_keys, overflow_row);\n"
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"}\n"
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"\n"
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"void * getPtr" << suffix << "() __attribute__((__visibility__(\"default\")));\n"
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"void * getPtr" << suffix << "()\n" /// Without this wrapper, it's not clear how to get the desired symbol from the compiled library.
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"{\n"
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" return reinterpret_cast<void *>(&wrapper" << suffix << ");\n"
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"}\n";
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};
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if (!method_typename.empty())
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append_code_for_specialization(method_typename, "");
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else
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{
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/// For `without_key` method.
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code <<
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"template void Aggregator::executeSpecializedWithoutKey<\n"
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" " << "TypeList<" << aggregate_functions_typenames << ">>(\n"
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" AggregatedDataWithoutKey &, size_t, AggregateColumns &, Arena *) const;\n"
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"\n"
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"static void wrapper(\n"
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" const Aggregator & aggregator,\n"
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" AggregatedDataWithoutKey & method,\n"
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" size_t rows,\n"
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" Aggregator::AggregateColumns & aggregate_columns,\n"
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" Arena * arena)\n"
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"{\n"
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" aggregator.executeSpecializedWithoutKey<\n"
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" TypeList<" << aggregate_functions_typenames << ">>(\n"
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" method, rows, aggregate_columns, arena);\n"
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"}\n"
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"\n"
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"void * getPtr() __attribute__((__visibility__(\"default\")));\n"
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"void * getPtr()\n"
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"{\n"
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" return reinterpret_cast<void *>(&wrapper);\n"
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"}\n";
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}
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if (!method_typename_two_level.empty())
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append_code_for_specialization(method_typename_two_level, "TwoLevel");
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else
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{
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/// The stub.
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code <<
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"void * getPtrTwoLevel() __attribute__((__visibility__(\"default\")));\n"
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"void * getPtrTwoLevel()\n"
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"{\n"
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" return nullptr;\n"
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"}\n";
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}
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code <<
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"}\n";
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return code.str();
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};
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auto compiled_data_owned_by_callback = compiled_data;
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auto on_ready = [compiled_data_owned_by_callback] (SharedLibraryPtr & lib)
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{
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if (compiled_data_owned_by_callback.unique()) /// Aggregator is already destroyed.
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return;
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compiled_data_owned_by_callback->compiled_aggregator = lib;
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compiled_data_owned_by_callback->compiled_method_ptr = lib->get<void * (*) ()>("_ZN2DB6getPtrEv")();
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compiled_data_owned_by_callback->compiled_two_level_method_ptr = lib->get<void * (*) ()>("_ZN2DB14getPtrTwoLevelEv")();
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};
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/** If the library has already been compiled, a non-zero SharedLibraryPtr is returned.
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* If the library was not compiled, then the counter is incremented, and nullptr is returned.
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* If the counter has reached the value min_count_to_compile, then the compilation starts asynchronously (in a separate thread)
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* at the end of which `on_ready` callback is called.
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*/
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aggregate_functions_headers_args << " -Wno-unused-function";
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SharedLibraryPtr lib = params.compiler->getOrCount(key, params.min_count_to_compile,
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aggregate_functions_headers_args.str(),
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get_code, on_ready);
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/// If the result is already ready.
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if (lib)
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on_ready(lib);
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#endif
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}
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AggregatedDataVariants::Type Aggregator::chooseAggregationMethod()
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{
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/// If no keys. All aggregating to single row.
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if (params.keys_size == 0)
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return AggregatedDataVariants::Type::without_key;
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/// Check if at least one of the specified keys is nullable.
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DataTypes types_removed_nullable;
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types_removed_nullable.reserve(params.keys.size());
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bool has_nullable_key = false;
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for (const auto & pos : params.keys)
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{
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const auto & type = (params.src_header ? params.src_header : params.intermediate_header).safeGetByPosition(pos).type;
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if (type->isNullable())
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{
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has_nullable_key = true;
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types_removed_nullable.push_back(removeNullable(type));
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}
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else
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types_removed_nullable.push_back(type);
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}
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/** Returns ordinary (not two-level) methods, because we start from them.
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* Later, during aggregation process, data may be converted (partitioned) to two-level structure, if cardinality is high.
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*/
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size_t keys_bytes = 0;
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size_t num_contiguous_keys = 0;
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size_t num_fixed_contiguous_keys = 0;
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size_t num_string_keys = 0;
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key_sizes.resize(params.keys_size);
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for (size_t j = 0; j < params.keys_size; ++j)
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{
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if (types_removed_nullable[j]->isValueUnambiguouslyRepresentedInContiguousMemoryRegion())
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{
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++num_contiguous_keys;
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if (types_removed_nullable[j]->isValueUnambiguouslyRepresentedInFixedSizeContiguousMemoryRegion())
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{
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++num_fixed_contiguous_keys;
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key_sizes[j] = types_removed_nullable[j]->getSizeOfValueInMemory();
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keys_bytes += key_sizes[j];
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}
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if (types_removed_nullable[j]->isString())
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{
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++num_string_keys;
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}
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}
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}
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if (has_nullable_key)
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{
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if (params.keys_size == num_fixed_contiguous_keys)
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{
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/// Pack if possible all the keys along with information about which key values are nulls
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/// into a fixed 16- or 32-byte blob.
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if (std::tuple_size<KeysNullMap<UInt128>>::value + keys_bytes <= 16)
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return AggregatedDataVariants::Type::nullable_keys128;
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if (std::tuple_size<KeysNullMap<UInt256>>::value + keys_bytes <= 32)
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return AggregatedDataVariants::Type::nullable_keys256;
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}
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/// Fallback case.
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return AggregatedDataVariants::Type::serialized;
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}
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/// No key has been found to be nullable.
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/// Single numeric key.
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if (params.keys_size == 1 && types_removed_nullable[0]->isValueRepresentedByNumber())
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{
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size_t size_of_field = types_removed_nullable[0]->getSizeOfValueInMemory();
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if (size_of_field == 1)
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return AggregatedDataVariants::Type::key8;
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if (size_of_field == 2)
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return AggregatedDataVariants::Type::key16;
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if (size_of_field == 4)
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return AggregatedDataVariants::Type::key32;
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if (size_of_field == 8)
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return AggregatedDataVariants::Type::key64;
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if (size_of_field == 16)
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return AggregatedDataVariants::Type::keys128;
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throw Exception("Logical error: numeric column has sizeOfField not in 1, 2, 4, 8, 16.", ErrorCodes::LOGICAL_ERROR);
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}
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/// If all keys fits in N bits, will use hash table with all keys packed (placed contiguously) to single N-bit key.
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if (params.keys_size == num_fixed_contiguous_keys)
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{
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if (keys_bytes <= 16)
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return AggregatedDataVariants::Type::keys128;
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if (keys_bytes <= 32)
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return AggregatedDataVariants::Type::keys256;
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}
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/// If single string key - will use hash table with references to it. Strings itself are stored separately in Arena.
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if (params.keys_size == 1 && types_removed_nullable[0]->isString())
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return AggregatedDataVariants::Type::key_string;
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if (params.keys_size == 1 && types_removed_nullable[0]->isFixedString())
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return AggregatedDataVariants::Type::key_fixed_string;
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/** If it is possible to use 'concat' method due to one-to-one correspondense. Otherwise the method will be 'serialized'.
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*/
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if (params.keys_size == num_contiguous_keys && num_fixed_contiguous_keys + 1 >= num_contiguous_keys)
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return AggregatedDataVariants::Type::concat;
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/** For case with multiple strings, we use 'concat' method despite the fact, that correspondense is not one-to-one.
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* Concat will concatenate strings including its zero terminators.
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* But if strings contains zero bytes in between, different keys may clash.
|
|
* For example, keys ('a\0b', 'c') and ('a', 'b\0c') will be aggregated as one key.
|
|
* This is documented behaviour. It may be avoided by just switching to 'serialized' method, which is less efficient.
|
|
*/
|
|
if (params.keys_size == num_fixed_contiguous_keys + num_string_keys)
|
|
return AggregatedDataVariants::Type::concat;
|
|
|
|
return AggregatedDataVariants::Type::serialized;
|
|
|
|
/// NOTE AggregatedDataVariants::Type::hashed is not used. It's proven to be less efficient than 'serialized' in most cases.
|
|
}
|
|
|
|
|
|
void Aggregator::createAggregateStates(AggregateDataPtr & aggregate_data) const
|
|
{
|
|
for (size_t j = 0; j < params.aggregates_size; ++j)
|
|
{
|
|
try
|
|
{
|
|
/** An exception may occur if there is a shortage of memory.
|
|
* In order that then everything is properly destroyed, we "roll back" some of the created states.
|
|
* The code is not very convenient.
|
|
*/
|
|
aggregate_functions[j]->create(aggregate_data + offsets_of_aggregate_states[j]);
|
|
}
|
|
catch (...)
|
|
{
|
|
for (size_t rollback_j = 0; rollback_j < j; ++rollback_j)
|
|
aggregate_functions[rollback_j]->destroy(aggregate_data + offsets_of_aggregate_states[rollback_j]);
|
|
|
|
throw;
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
/** It's interesting - if you remove `noinline`, then gcc for some reason will inline this function, and the performance decreases (~ 10%).
|
|
* (Probably because after the inline of this function, more internal functions no longer be inlined.)
|
|
* Inline does not make sense, since the inner loop is entirely inside this function.
|
|
*/
|
|
template <typename Method>
|
|
void NO_INLINE Aggregator::executeImpl(
|
|
Method & method,
|
|
Arena * aggregates_pool,
|
|
size_t rows,
|
|
ColumnRawPtrs & key_columns,
|
|
AggregateFunctionInstruction * aggregate_instructions,
|
|
const Sizes & key_sizes,
|
|
StringRefs & keys,
|
|
bool no_more_keys,
|
|
AggregateDataPtr overflow_row) const
|
|
{
|
|
typename Method::State state;
|
|
state.init(key_columns);
|
|
|
|
if (!no_more_keys)
|
|
executeImplCase<false>(method, state, aggregates_pool, rows, key_columns, aggregate_instructions, key_sizes, keys, overflow_row);
|
|
else
|
|
executeImplCase<true>(method, state, aggregates_pool, rows, key_columns, aggregate_instructions, key_sizes, keys, overflow_row);
|
|
}
|
|
|
|
#ifndef __clang__
|
|
#pragma GCC diagnostic push
|
|
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
|
|
#endif
|
|
|
|
template <bool no_more_keys, typename Method>
|
|
void NO_INLINE Aggregator::executeImplCase(
|
|
Method & method,
|
|
typename Method::State & state,
|
|
Arena * aggregates_pool,
|
|
size_t rows,
|
|
ColumnRawPtrs & key_columns,
|
|
AggregateFunctionInstruction * aggregate_instructions,
|
|
const Sizes & key_sizes,
|
|
StringRefs & keys,
|
|
AggregateDataPtr overflow_row) const
|
|
{
|
|
/// NOTE When editing this code, also pay attention to SpecializedAggregator.h.
|
|
|
|
/// For all rows.
|
|
typename Method::iterator it;
|
|
typename Method::Key prev_key;
|
|
for (size_t i = 0; i < rows; ++i)
|
|
{
|
|
bool inserted; /// Inserted a new key, or was this key already?
|
|
bool overflow = false; /// The new key did not fit in the hash table because of no_more_keys.
|
|
|
|
/// Get the key to insert into the hash table.
|
|
typename Method::Key key = state.getKey(key_columns, params.keys_size, i, key_sizes, keys, *aggregates_pool);
|
|
|
|
if (!no_more_keys) /// Insert.
|
|
{
|
|
/// Optimization for consecutive identical keys.
|
|
if (!Method::no_consecutive_keys_optimization)
|
|
{
|
|
if (i != 0 && key == prev_key)
|
|
{
|
|
/// Add values to the aggregate functions.
|
|
AggregateDataPtr value = Method::getAggregateData(it->second);
|
|
for (AggregateFunctionInstruction * inst = aggregate_instructions; inst->that; ++inst)
|
|
(*inst->func)(inst->that, value + inst->state_offset, inst->arguments, i, aggregates_pool);
|
|
|
|
method.onExistingKey(key, keys, *aggregates_pool);
|
|
continue;
|
|
}
|
|
else
|
|
prev_key = key;
|
|
}
|
|
|
|
method.data.emplace(key, it, inserted);
|
|
}
|
|
else
|
|
{
|
|
/// Add only if the key already exists.
|
|
inserted = false;
|
|
it = method.data.find(key);
|
|
if (method.data.end() == it)
|
|
overflow = true;
|
|
}
|
|
|
|
/// If the key does not fit, and the data does not need to be aggregated in a separate row, then there's nothing to do.
|
|
if (no_more_keys && overflow && !overflow_row)
|
|
{
|
|
method.onExistingKey(key, keys, *aggregates_pool);
|
|
continue;
|
|
}
|
|
|
|
/// If a new key is inserted, initialize the states of the aggregate functions, and possibly something related to the key.
|
|
if (inserted)
|
|
{
|
|
AggregateDataPtr & aggregate_data = Method::getAggregateData(it->second);
|
|
|
|
/// exception-safety - if you can not allocate memory or create states, then destructors will not be called.
|
|
aggregate_data = nullptr;
|
|
|
|
method.onNewKey(*it, params.keys_size, keys, *aggregates_pool);
|
|
|
|
AggregateDataPtr place = aggregates_pool->alloc(total_size_of_aggregate_states);
|
|
createAggregateStates(place);
|
|
aggregate_data = place;
|
|
}
|
|
else
|
|
method.onExistingKey(key, keys, *aggregates_pool);
|
|
|
|
AggregateDataPtr value = (!no_more_keys || !overflow) ? Method::getAggregateData(it->second) : overflow_row;
|
|
|
|
/// Add values to the aggregate functions.
|
|
for (AggregateFunctionInstruction * inst = aggregate_instructions; inst->that; ++inst)
|
|
(*inst->func)(inst->that, value + inst->state_offset, inst->arguments, i, aggregates_pool);
|
|
}
|
|
}
|
|
|
|
#ifndef __clang__
|
|
#pragma GCC diagnostic pop
|
|
#endif
|
|
|
|
void NO_INLINE Aggregator::executeWithoutKeyImpl(
|
|
AggregatedDataWithoutKey & res,
|
|
size_t rows,
|
|
AggregateFunctionInstruction * aggregate_instructions,
|
|
Arena * arena) const
|
|
{
|
|
/// Optimization in the case of a single aggregate function `count`.
|
|
AggregateFunctionCount * agg_count = params.aggregates_size == 1
|
|
? typeid_cast<AggregateFunctionCount *>(aggregate_functions[0])
|
|
: nullptr;
|
|
|
|
if (agg_count)
|
|
agg_count->addDelta(res, rows);
|
|
else
|
|
{
|
|
for (size_t i = 0; i < rows; ++i)
|
|
{
|
|
/// Adding values
|
|
for (AggregateFunctionInstruction * inst = aggregate_instructions; inst->that; ++inst)
|
|
(*inst->func)(inst->that, res + inst->state_offset, inst->arguments, i, arena);
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
bool Aggregator::executeOnBlock(const Block & block, AggregatedDataVariants & result,
|
|
ColumnRawPtrs & key_columns, AggregateColumns & aggregate_columns, StringRefs & key,
|
|
bool & no_more_keys)
|
|
{
|
|
if (isCancelled())
|
|
return true;
|
|
|
|
/// `result` will destroy the states of aggregate functions in the destructor
|
|
result.aggregator = this;
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_columns[i].resize(params.aggregates[i].arguments.size());
|
|
|
|
/** Constant columns are not supported directly during aggregation.
|
|
* To make them work anyway, we materialize them.
|
|
*/
|
|
Columns materialized_columns;
|
|
|
|
/// Remember the columns we will work with
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
{
|
|
key_columns[i] = block.safeGetByPosition(params.keys[i]).column.get();
|
|
|
|
if (ColumnPtr converted = key_columns[i]->convertToFullColumnIfConst())
|
|
{
|
|
materialized_columns.push_back(converted);
|
|
key_columns[i] = materialized_columns.back().get();
|
|
}
|
|
}
|
|
|
|
AggregateFunctionInstructions aggregate_functions_instructions(params.aggregates_size + 1);
|
|
aggregate_functions_instructions[params.aggregates_size].that = nullptr;
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
{
|
|
for (size_t j = 0; j < aggregate_columns[i].size(); ++j)
|
|
{
|
|
aggregate_columns[i][j] = block.safeGetByPosition(params.aggregates[i].arguments[j]).column.get();
|
|
|
|
if (ColumnPtr converted = aggregate_columns[i][j]->convertToFullColumnIfConst())
|
|
{
|
|
materialized_columns.push_back(converted);
|
|
aggregate_columns[i][j] = materialized_columns.back().get();
|
|
}
|
|
}
|
|
|
|
aggregate_functions_instructions[i].that = aggregate_functions[i];
|
|
aggregate_functions_instructions[i].func = aggregate_functions[i]->getAddressOfAddFunction();
|
|
aggregate_functions_instructions[i].state_offset = offsets_of_aggregate_states[i];
|
|
aggregate_functions_instructions[i].arguments = aggregate_columns[i].data();
|
|
}
|
|
|
|
if (isCancelled())
|
|
return true;
|
|
|
|
size_t rows = block.rows();
|
|
|
|
/// How to perform the aggregation?
|
|
if (result.empty())
|
|
{
|
|
result.init(method);
|
|
result.keys_size = params.keys_size;
|
|
result.key_sizes = key_sizes;
|
|
LOG_TRACE(log, "Aggregation method: " << result.getMethodName());
|
|
|
|
if (params.compiler)
|
|
compileIfPossible(result.type);
|
|
}
|
|
|
|
if (isCancelled())
|
|
return true;
|
|
|
|
if ((params.overflow_row || result.type == AggregatedDataVariants::Type::without_key) && !result.without_key)
|
|
{
|
|
AggregateDataPtr place = result.aggregates_pool->alloc(total_size_of_aggregate_states);
|
|
createAggregateStates(place);
|
|
result.without_key = place;
|
|
}
|
|
|
|
/// We select one of the aggregation methods and call it.
|
|
|
|
/// For the case when there are no keys (all aggregate into one row).
|
|
if (result.type == AggregatedDataVariants::Type::without_key)
|
|
{
|
|
/// If there is a dynamically compiled code.
|
|
if (compiled_data->compiled_method_ptr)
|
|
{
|
|
reinterpret_cast<
|
|
void (*)(const Aggregator &, AggregatedDataWithoutKey &, size_t, AggregateColumns &, Arena *)>
|
|
(compiled_data->compiled_method_ptr)(*this, result.without_key, rows, aggregate_columns, result.aggregates_pool);
|
|
}
|
|
else
|
|
executeWithoutKeyImpl(result.without_key, rows, &aggregate_functions_instructions[0], result.aggregates_pool);
|
|
}
|
|
else
|
|
{
|
|
/// This is where data is written that does not fit in `max_rows_to_group_by` with `group_by_overflow_mode = any`.
|
|
AggregateDataPtr overflow_row_ptr = params.overflow_row ? result.without_key : nullptr;
|
|
|
|
bool is_two_level = result.isTwoLevel();
|
|
|
|
/// Compiled code, for the normal structure.
|
|
if (!is_two_level && compiled_data->compiled_method_ptr)
|
|
{
|
|
#define M(NAME, IS_TWO_LEVEL) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
reinterpret_cast<void (*)( \
|
|
const Aggregator &, decltype(result.NAME)::element_type &, \
|
|
Arena *, size_t, ColumnRawPtrs &, AggregateColumns &, \
|
|
const Sizes &, StringRefs &, bool, AggregateDataPtr)>(compiled_data->compiled_method_ptr) \
|
|
(*this, *result.NAME, result.aggregates_pool, rows, key_columns, aggregate_columns, \
|
|
result.key_sizes, key, no_more_keys, overflow_row_ptr);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_AGGREGATED_VARIANTS(M)
|
|
#undef M
|
|
}
|
|
/// Compiled code, for a two-level structure.
|
|
else if (is_two_level && compiled_data->compiled_two_level_method_ptr)
|
|
{
|
|
#define M(NAME) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
reinterpret_cast<void (*)( \
|
|
const Aggregator &, decltype(result.NAME)::element_type &, \
|
|
Arena *, size_t, ColumnRawPtrs &, AggregateColumns &, \
|
|
const Sizes &, StringRefs &, bool, AggregateDataPtr)>(compiled_data->compiled_two_level_method_ptr) \
|
|
(*this, *result.NAME, result.aggregates_pool, rows, key_columns, aggregate_columns, \
|
|
result.key_sizes, key, no_more_keys, overflow_row_ptr);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
}
|
|
/// When there is no dynamically compiled code.
|
|
else
|
|
{
|
|
#define M(NAME, IS_TWO_LEVEL) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
executeImpl(*result.NAME, result.aggregates_pool, rows, key_columns, &aggregate_functions_instructions[0], \
|
|
result.key_sizes, key, no_more_keys, overflow_row_ptr);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_AGGREGATED_VARIANTS(M)
|
|
#undef M
|
|
}
|
|
}
|
|
|
|
size_t result_size = result.sizeWithoutOverflowRow();
|
|
Int64 current_memory_usage = 0;
|
|
if (current_memory_tracker)
|
|
current_memory_usage = current_memory_tracker->get();
|
|
|
|
auto result_size_bytes = current_memory_usage - memory_usage_before_aggregation; /// Here all the results in the sum are taken into account, from different threads.
|
|
|
|
bool worth_convert_to_two_level
|
|
= (params.group_by_two_level_threshold && result_size >= params.group_by_two_level_threshold)
|
|
|| (params.group_by_two_level_threshold_bytes && result_size_bytes >= static_cast<Int64>(params.group_by_two_level_threshold_bytes));
|
|
|
|
/** Converting to a two-level data structure.
|
|
* It allows you to make, in the subsequent, an effective merge - either economical from memory or parallel.
|
|
*/
|
|
if (result.isConvertibleToTwoLevel() && worth_convert_to_two_level)
|
|
result.convertToTwoLevel();
|
|
|
|
/// Checking the constraints.
|
|
if (!checkLimits(result_size, no_more_keys))
|
|
return false;
|
|
|
|
/** Flush data to disk if too much RAM is consumed.
|
|
* Data can only be flushed to disk if a two-level aggregation structure is used.
|
|
*/
|
|
if (params.max_bytes_before_external_group_by
|
|
&& result.isTwoLevel()
|
|
&& current_memory_usage > static_cast<Int64>(params.max_bytes_before_external_group_by)
|
|
&& worth_convert_to_two_level)
|
|
{
|
|
writeToTemporaryFile(result);
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
|
|
void Aggregator::writeToTemporaryFile(AggregatedDataVariants & data_variants)
|
|
{
|
|
Stopwatch watch;
|
|
size_t rows = data_variants.size();
|
|
|
|
Poco::File(params.tmp_path).createDirectories();
|
|
auto file = std::make_unique<Poco::TemporaryFile>(params.tmp_path);
|
|
const std::string & path = file->path();
|
|
WriteBufferFromFile file_buf(path);
|
|
CompressedWriteBuffer compressed_buf(file_buf);
|
|
NativeBlockOutputStream block_out(compressed_buf, ClickHouseRevision::get(), getHeader(false));
|
|
|
|
LOG_DEBUG(log, "Writing part of aggregation data into temporary file " << path << ".");
|
|
ProfileEvents::increment(ProfileEvents::ExternalAggregationWritePart);
|
|
|
|
/// Flush only two-level data and possibly overflow data.
|
|
|
|
#define M(NAME) \
|
|
else if (data_variants.type == AggregatedDataVariants::Type::NAME) \
|
|
writeToTemporaryFileImpl(data_variants, *data_variants.NAME, block_out);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
|
|
/// NOTE Instead of freeing up memory and creating new hash tables and arenas, you can re-use the old ones.
|
|
data_variants.init(data_variants.type);
|
|
data_variants.aggregates_pools = Arenas(1, std::make_shared<Arena>());
|
|
data_variants.aggregates_pool = data_variants.aggregates_pools.back().get();
|
|
data_variants.without_key = nullptr;
|
|
|
|
block_out.flush();
|
|
compressed_buf.next();
|
|
file_buf.next();
|
|
|
|
double elapsed_seconds = watch.elapsedSeconds();
|
|
double compressed_bytes = file_buf.count();
|
|
double uncompressed_bytes = compressed_buf.count();
|
|
|
|
{
|
|
std::lock_guard<std::mutex> lock(temporary_files.mutex);
|
|
temporary_files.files.emplace_back(std::move(file));
|
|
temporary_files.sum_size_uncompressed += uncompressed_bytes;
|
|
temporary_files.sum_size_compressed += compressed_bytes;
|
|
}
|
|
|
|
ProfileEvents::increment(ProfileEvents::ExternalAggregationCompressedBytes, compressed_bytes);
|
|
ProfileEvents::increment(ProfileEvents::ExternalAggregationUncompressedBytes, uncompressed_bytes);
|
|
|
|
LOG_TRACE(log, std::fixed << std::setprecision(3)
|
|
<< "Written part in " << elapsed_seconds << " sec., "
|
|
<< rows << " rows, "
|
|
<< (uncompressed_bytes / 1048576.0) << " MiB uncompressed, "
|
|
<< (compressed_bytes / 1048576.0) << " MiB compressed, "
|
|
<< (uncompressed_bytes / rows) << " uncompressed bytes per row, "
|
|
<< (compressed_bytes / rows) << " compressed bytes per row, "
|
|
<< "compression rate: " << (uncompressed_bytes / compressed_bytes)
|
|
<< " (" << (rows / elapsed_seconds) << " rows/sec., "
|
|
<< (uncompressed_bytes / elapsed_seconds / 1048576.0) << " MiB/sec. uncompressed, "
|
|
<< (compressed_bytes / elapsed_seconds / 1048576.0) << " MiB/sec. compressed)");
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
Block Aggregator::convertOneBucketToBlock(
|
|
AggregatedDataVariants & data_variants,
|
|
Method & method,
|
|
bool final,
|
|
size_t bucket) const
|
|
{
|
|
Block block = prepareBlockAndFill(data_variants, final, method.data.impls[bucket].size(),
|
|
[bucket, &method, this] (
|
|
MutableColumns & key_columns,
|
|
AggregateColumnsData & aggregate_columns,
|
|
MutableColumns & final_aggregate_columns,
|
|
const Sizes & key_sizes,
|
|
bool final)
|
|
{
|
|
convertToBlockImpl(method, method.data.impls[bucket],
|
|
key_columns, aggregate_columns, final_aggregate_columns, key_sizes, final);
|
|
});
|
|
|
|
block.info.bucket_num = bucket;
|
|
return block;
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
void Aggregator::writeToTemporaryFileImpl(
|
|
AggregatedDataVariants & data_variants,
|
|
Method & method,
|
|
IBlockOutputStream & out)
|
|
{
|
|
size_t max_temporary_block_size_rows = 0;
|
|
size_t max_temporary_block_size_bytes = 0;
|
|
|
|
auto update_max_sizes = [&](const Block & block)
|
|
{
|
|
size_t block_size_rows = block.rows();
|
|
size_t block_size_bytes = block.bytes();
|
|
|
|
if (block_size_rows > max_temporary_block_size_rows)
|
|
max_temporary_block_size_rows = block_size_rows;
|
|
if (block_size_bytes > max_temporary_block_size_bytes)
|
|
max_temporary_block_size_bytes = block_size_bytes;
|
|
};
|
|
|
|
for (size_t bucket = 0; bucket < Method::Data::NUM_BUCKETS; ++bucket)
|
|
{
|
|
Block block = convertOneBucketToBlock(data_variants, method, false, bucket);
|
|
out.write(block);
|
|
update_max_sizes(block);
|
|
}
|
|
|
|
if (params.overflow_row)
|
|
{
|
|
Block block = prepareBlockAndFillWithoutKey(data_variants, false, true);
|
|
out.write(block);
|
|
update_max_sizes(block);
|
|
}
|
|
|
|
/// Pass ownership of the aggregate functions states:
|
|
/// `data_variants` will not destroy them in the destructor, they are now owned by ColumnAggregateFunction objects.
|
|
data_variants.aggregator = nullptr;
|
|
|
|
LOG_TRACE(log, std::fixed << std::setprecision(3)
|
|
<< "Max size of temporary block: " << max_temporary_block_size_rows << " rows, "
|
|
<< (max_temporary_block_size_bytes / 1048576.0) << " MiB.");
|
|
}
|
|
|
|
|
|
bool Aggregator::checkLimits(size_t result_size, bool & no_more_keys) const
|
|
{
|
|
if (!no_more_keys && params.max_rows_to_group_by && result_size > params.max_rows_to_group_by)
|
|
{
|
|
switch (params.group_by_overflow_mode)
|
|
{
|
|
case OverflowMode::THROW:
|
|
throw Exception("Limit for rows to GROUP BY exceeded: has " + toString(result_size)
|
|
+ " rows, maximum: " + toString(params.max_rows_to_group_by),
|
|
ErrorCodes::TOO_MANY_ROWS);
|
|
|
|
case OverflowMode::BREAK:
|
|
return false;
|
|
|
|
case OverflowMode::ANY:
|
|
no_more_keys = true;
|
|
break;
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
|
|
void Aggregator::execute(const BlockInputStreamPtr & stream, AggregatedDataVariants & result)
|
|
{
|
|
if (isCancelled())
|
|
return;
|
|
|
|
StringRefs key(params.keys_size);
|
|
ColumnRawPtrs key_columns(params.keys_size);
|
|
AggregateColumns aggregate_columns(params.aggregates_size);
|
|
|
|
/** Used if there is a limit on the maximum number of rows in the aggregation,
|
|
* and if group_by_overflow_mode == ANY.
|
|
* In this case, new keys are not added to the set, but aggregation is performed only by
|
|
* keys that have already managed to get into the set.
|
|
*/
|
|
bool no_more_keys = false;
|
|
|
|
LOG_TRACE(log, "Aggregating");
|
|
|
|
Stopwatch watch;
|
|
|
|
size_t src_rows = 0;
|
|
size_t src_bytes = 0;
|
|
|
|
/// Read all the data
|
|
while (Block block = stream->read())
|
|
{
|
|
if (isCancelled())
|
|
return;
|
|
|
|
src_rows += block.rows();
|
|
src_bytes += block.bytes();
|
|
|
|
if (!executeOnBlock(block, result, key_columns, aggregate_columns, key, no_more_keys))
|
|
break;
|
|
}
|
|
|
|
/// If there was no data, and we aggregate without keys, and we must return single row with the result of empty aggregation.
|
|
/// To do this, we pass a block with zero rows to aggregate.
|
|
if (result.empty() && params.keys_size == 0 && !params.empty_result_for_aggregation_by_empty_set)
|
|
executeOnBlock(stream->getHeader(), result, key_columns, aggregate_columns, key, no_more_keys);
|
|
|
|
double elapsed_seconds = watch.elapsedSeconds();
|
|
size_t rows = result.sizeWithoutOverflowRow();
|
|
LOG_TRACE(log, std::fixed << std::setprecision(3)
|
|
<< "Aggregated. " << src_rows << " to " << rows << " rows (from " << src_bytes / 1048576.0 << " MiB)"
|
|
<< " in " << elapsed_seconds << " sec."
|
|
<< " (" << src_rows / elapsed_seconds << " rows/sec., " << src_bytes / elapsed_seconds / 1048576.0 << " MiB/sec.)");
|
|
}
|
|
|
|
|
|
template <typename Method, typename Table>
|
|
void Aggregator::convertToBlockImpl(
|
|
Method & method,
|
|
Table & data,
|
|
MutableColumns & key_columns,
|
|
AggregateColumnsData & aggregate_columns,
|
|
MutableColumns & final_aggregate_columns,
|
|
const Sizes & key_sizes,
|
|
bool final) const
|
|
{
|
|
if (data.empty())
|
|
return;
|
|
|
|
if (final)
|
|
convertToBlockImplFinal(method, data, key_columns, final_aggregate_columns, key_sizes);
|
|
else
|
|
convertToBlockImplNotFinal(method, data, key_columns, aggregate_columns, key_sizes);
|
|
|
|
/// In order to release memory early.
|
|
data.clearAndShrink();
|
|
}
|
|
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::convertToBlockImplFinal(
|
|
Method & method,
|
|
Table & data,
|
|
MutableColumns & key_columns,
|
|
MutableColumns & final_aggregate_columns,
|
|
const Sizes & key_sizes) const
|
|
{
|
|
for (const auto & value : data)
|
|
{
|
|
method.insertKeyIntoColumns(value, key_columns, params.keys_size, key_sizes);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->insertResultInto(
|
|
Method::getAggregateData(value.second) + offsets_of_aggregate_states[i],
|
|
*final_aggregate_columns[i]);
|
|
}
|
|
|
|
destroyImpl<Method>(data); /// NOTE You can do better.
|
|
}
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::convertToBlockImplNotFinal(
|
|
Method & method,
|
|
Table & data,
|
|
MutableColumns & key_columns,
|
|
AggregateColumnsData & aggregate_columns,
|
|
const Sizes & key_sizes) const
|
|
{
|
|
|
|
for (auto & value : data)
|
|
{
|
|
method.insertKeyIntoColumns(value, key_columns, params.keys_size, key_sizes);
|
|
|
|
/// reserved, so push_back does not throw exceptions
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_columns[i]->push_back(Method::getAggregateData(value.second) + offsets_of_aggregate_states[i]);
|
|
|
|
Method::getAggregateData(value.second) = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
template <typename Filler>
|
|
Block Aggregator::prepareBlockAndFill(
|
|
AggregatedDataVariants & data_variants,
|
|
bool final,
|
|
size_t rows,
|
|
Filler && filler) const
|
|
{
|
|
MutableColumns key_columns(params.keys_size);
|
|
MutableColumns aggregate_columns(params.aggregates_size);
|
|
MutableColumns final_aggregate_columns(params.aggregates_size);
|
|
AggregateColumnsData aggregate_columns_data(params.aggregates_size);
|
|
|
|
Block header = getHeader(final);
|
|
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
{
|
|
key_columns[i] = header.safeGetByPosition(i).type->createColumn();
|
|
key_columns[i]->reserve(rows);
|
|
}
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
{
|
|
if (!final)
|
|
{
|
|
aggregate_columns[i] = header.safeGetByPosition(i + params.keys_size).type->createColumn();
|
|
|
|
/// The ColumnAggregateFunction column captures the shared ownership of the arena with the aggregate function states.
|
|
ColumnAggregateFunction & column_aggregate_func = static_cast<ColumnAggregateFunction &>(*aggregate_columns[i]);
|
|
|
|
for (size_t j = 0; j < data_variants.aggregates_pools.size(); ++j)
|
|
column_aggregate_func.addArena(data_variants.aggregates_pools[j]);
|
|
|
|
aggregate_columns_data[i] = &column_aggregate_func.getData();
|
|
aggregate_columns_data[i]->reserve(rows);
|
|
}
|
|
else
|
|
{
|
|
final_aggregate_columns[i] = aggregate_functions[i]->getReturnType()->createColumn();
|
|
final_aggregate_columns[i]->reserve(rows);
|
|
|
|
if (aggregate_functions[i]->isState())
|
|
{
|
|
/// The ColumnAggregateFunction column captures the shared ownership of the arena with aggregate function states.
|
|
ColumnAggregateFunction & column_aggregate_func = static_cast<ColumnAggregateFunction &>(*final_aggregate_columns[i]);
|
|
|
|
for (size_t j = 0; j < data_variants.aggregates_pools.size(); ++j)
|
|
column_aggregate_func.addArena(data_variants.aggregates_pools[j]);
|
|
}
|
|
}
|
|
}
|
|
|
|
filler(key_columns, aggregate_columns_data, final_aggregate_columns, data_variants.key_sizes, final);
|
|
|
|
Block res = header.cloneEmpty();
|
|
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
res.getByPosition(i).column = std::move(key_columns[i]);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
{
|
|
if (final)
|
|
res.getByPosition(i + params.keys_size).column = std::move(final_aggregate_columns[i]);
|
|
else
|
|
res.getByPosition(i + params.keys_size).column = std::move(aggregate_columns[i]);
|
|
}
|
|
|
|
/// Change the size of the columns-constants in the block.
|
|
size_t columns = header.columns();
|
|
for (size_t i = 0; i < columns; ++i)
|
|
if (res.getByPosition(i).column->isColumnConst())
|
|
res.getByPosition(i).column = res.getByPosition(i).column->cut(0, rows);
|
|
|
|
return res;
|
|
}
|
|
|
|
|
|
Block Aggregator::prepareBlockAndFillWithoutKey(AggregatedDataVariants & data_variants, bool final, bool is_overflows) const
|
|
{
|
|
size_t rows = 1;
|
|
|
|
auto filler = [&data_variants, this](
|
|
MutableColumns & key_columns,
|
|
AggregateColumnsData & aggregate_columns,
|
|
MutableColumns & final_aggregate_columns,
|
|
const Sizes & /*key_sizes*/,
|
|
bool final)
|
|
{
|
|
if (data_variants.type == AggregatedDataVariants::Type::without_key || params.overflow_row)
|
|
{
|
|
AggregatedDataWithoutKey & data = data_variants.without_key;
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
{
|
|
if (!final)
|
|
aggregate_columns[i]->push_back(data + offsets_of_aggregate_states[i]);
|
|
else
|
|
aggregate_functions[i]->insertResultInto(data + offsets_of_aggregate_states[i], *final_aggregate_columns[i]);
|
|
}
|
|
|
|
if (!final)
|
|
data = nullptr;
|
|
|
|
if (params.overflow_row)
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
key_columns[i]->insertDefault();
|
|
}
|
|
};
|
|
|
|
Block block = prepareBlockAndFill(data_variants, final, rows, filler);
|
|
|
|
if (is_overflows)
|
|
block.info.is_overflows = true;
|
|
|
|
if (final)
|
|
destroyWithoutKey(data_variants);
|
|
|
|
return block;
|
|
}
|
|
|
|
Block Aggregator::prepareBlockAndFillSingleLevel(AggregatedDataVariants & data_variants, bool final) const
|
|
{
|
|
size_t rows = data_variants.sizeWithoutOverflowRow();
|
|
|
|
auto filler = [&data_variants, this](
|
|
MutableColumns & key_columns,
|
|
AggregateColumnsData & aggregate_columns,
|
|
MutableColumns & final_aggregate_columns,
|
|
const Sizes & /*key_sizes*/,
|
|
bool final)
|
|
{
|
|
#define M(NAME) \
|
|
else if (data_variants.type == AggregatedDataVariants::Type::NAME) \
|
|
convertToBlockImpl(*data_variants.NAME, data_variants.NAME->data, \
|
|
key_columns, aggregate_columns, final_aggregate_columns, data_variants.key_sizes, final);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_SINGLE_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
};
|
|
|
|
return prepareBlockAndFill(data_variants, final, rows, filler);
|
|
}
|
|
|
|
|
|
BlocksList Aggregator::prepareBlocksAndFillTwoLevel(AggregatedDataVariants & data_variants, bool final, ThreadPool * thread_pool) const
|
|
{
|
|
#define M(NAME) \
|
|
else if (data_variants.type == AggregatedDataVariants::Type::NAME) \
|
|
return prepareBlocksAndFillTwoLevelImpl(data_variants, *data_variants.NAME, final, thread_pool);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
BlocksList Aggregator::prepareBlocksAndFillTwoLevelImpl(
|
|
AggregatedDataVariants & data_variants,
|
|
Method & method,
|
|
bool final,
|
|
ThreadPool * thread_pool) const
|
|
{
|
|
auto converter = [&](size_t bucket, MemoryTracker * memory_tracker)
|
|
{
|
|
current_memory_tracker = memory_tracker;
|
|
return convertOneBucketToBlock(data_variants, method, final, bucket);
|
|
};
|
|
|
|
/// packaged_task is used to ensure that exceptions are automatically thrown into the main stream.
|
|
|
|
std::vector<std::packaged_task<Block()>> tasks(Method::Data::NUM_BUCKETS);
|
|
|
|
try
|
|
{
|
|
for (size_t bucket = 0; bucket < Method::Data::NUM_BUCKETS; ++bucket)
|
|
{
|
|
if (method.data.impls[bucket].empty())
|
|
continue;
|
|
|
|
tasks[bucket] = std::packaged_task<Block()>(std::bind(converter, bucket, current_memory_tracker));
|
|
|
|
if (thread_pool)
|
|
thread_pool->schedule([bucket, &tasks] { tasks[bucket](); });
|
|
else
|
|
tasks[bucket]();
|
|
}
|
|
}
|
|
catch (...)
|
|
{
|
|
/// If this is not done, then in case of an exception, tasks will be destroyed before the threads are completed, and it will be bad.
|
|
if (thread_pool)
|
|
thread_pool->wait();
|
|
|
|
throw;
|
|
}
|
|
|
|
if (thread_pool)
|
|
thread_pool->wait();
|
|
|
|
BlocksList blocks;
|
|
|
|
for (auto & task : tasks)
|
|
{
|
|
if (!task.valid())
|
|
continue;
|
|
|
|
blocks.emplace_back(task.get_future().get());
|
|
}
|
|
|
|
return blocks;
|
|
}
|
|
|
|
|
|
BlocksList Aggregator::convertToBlocks(AggregatedDataVariants & data_variants, bool final, size_t max_threads) const
|
|
{
|
|
if (isCancelled())
|
|
return BlocksList();
|
|
|
|
LOG_TRACE(log, "Converting aggregated data to blocks");
|
|
|
|
Stopwatch watch;
|
|
|
|
BlocksList blocks;
|
|
|
|
/// In what data structure is the data aggregated?
|
|
if (data_variants.empty())
|
|
return blocks;
|
|
|
|
std::unique_ptr<ThreadPool> thread_pool;
|
|
if (max_threads > 1 && data_variants.sizeWithoutOverflowRow() > 100000 /// TODO Make a custom threshold.
|
|
&& data_variants.isTwoLevel()) /// TODO Use the shared thread pool with the `merge` function.
|
|
thread_pool = std::make_unique<ThreadPool>(max_threads);
|
|
|
|
if (isCancelled())
|
|
return BlocksList();
|
|
|
|
if (data_variants.without_key)
|
|
blocks.emplace_back(prepareBlockAndFillWithoutKey(
|
|
data_variants, final, data_variants.type != AggregatedDataVariants::Type::without_key));
|
|
|
|
if (isCancelled())
|
|
return BlocksList();
|
|
|
|
if (data_variants.type != AggregatedDataVariants::Type::without_key)
|
|
{
|
|
if (!data_variants.isTwoLevel())
|
|
blocks.emplace_back(prepareBlockAndFillSingleLevel(data_variants, final));
|
|
else
|
|
blocks.splice(blocks.end(), prepareBlocksAndFillTwoLevel(data_variants, final, thread_pool.get()));
|
|
}
|
|
|
|
if (!final)
|
|
{
|
|
/// data_variants will not destroy the states of aggregate functions in the destructor.
|
|
/// Now ColumnAggregateFunction owns the states.
|
|
data_variants.aggregator = nullptr;
|
|
}
|
|
|
|
if (isCancelled())
|
|
return BlocksList();
|
|
|
|
size_t rows = 0;
|
|
size_t bytes = 0;
|
|
|
|
for (const auto & block : blocks)
|
|
{
|
|
rows += block.rows();
|
|
bytes += block.bytes();
|
|
}
|
|
|
|
double elapsed_seconds = watch.elapsedSeconds();
|
|
LOG_TRACE(log, std::fixed << std::setprecision(3)
|
|
<< "Converted aggregated data to blocks. "
|
|
<< rows << " rows, " << bytes / 1048576.0 << " MiB"
|
|
<< " in " << elapsed_seconds << " sec."
|
|
<< " (" << rows / elapsed_seconds << " rows/sec., " << bytes / elapsed_seconds / 1048576.0 << " MiB/sec.)");
|
|
|
|
return blocks;
|
|
}
|
|
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::mergeDataImpl(
|
|
Table & table_dst,
|
|
Table & table_src,
|
|
Arena * arena) const
|
|
{
|
|
for (auto it = table_src.begin(); it != table_src.end(); ++it)
|
|
{
|
|
decltype(it) res_it;
|
|
bool inserted;
|
|
table_dst.emplace(it->first, res_it, inserted, it.getHash());
|
|
|
|
if (!inserted)
|
|
{
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->merge(
|
|
Method::getAggregateData(res_it->second) + offsets_of_aggregate_states[i],
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i],
|
|
arena);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->destroy(
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i]);
|
|
}
|
|
else
|
|
{
|
|
res_it->second = it->second;
|
|
}
|
|
|
|
Method::getAggregateData(it->second) = nullptr;
|
|
}
|
|
|
|
table_src.clearAndShrink();
|
|
}
|
|
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::mergeDataNoMoreKeysImpl(
|
|
Table & table_dst,
|
|
AggregatedDataWithoutKey & overflows,
|
|
Table & table_src,
|
|
Arena * arena) const
|
|
{
|
|
for (auto it = table_src.begin(); it != table_src.end(); ++it)
|
|
{
|
|
decltype(it) res_it = table_dst.find(it->first, it.getHash());
|
|
|
|
AggregateDataPtr res_data = table_dst.end() == res_it
|
|
? overflows
|
|
: Method::getAggregateData(res_it->second);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->merge(
|
|
res_data + offsets_of_aggregate_states[i],
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i],
|
|
arena);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->destroy(
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i]);
|
|
|
|
Method::getAggregateData(it->second) = nullptr;
|
|
}
|
|
|
|
table_src.clearAndShrink();
|
|
}
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::mergeDataOnlyExistingKeysImpl(
|
|
Table & table_dst,
|
|
Table & table_src,
|
|
Arena * arena) const
|
|
{
|
|
for (auto it = table_src.begin(); it != table_src.end(); ++it)
|
|
{
|
|
decltype(it) res_it = table_dst.find(it->first, it.getHash());
|
|
|
|
if (table_dst.end() == res_it)
|
|
continue;
|
|
|
|
AggregateDataPtr res_data = Method::getAggregateData(res_it->second);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->merge(
|
|
res_data + offsets_of_aggregate_states[i],
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i],
|
|
arena);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->destroy(
|
|
Method::getAggregateData(it->second) + offsets_of_aggregate_states[i]);
|
|
|
|
Method::getAggregateData(it->second) = nullptr;
|
|
}
|
|
|
|
table_src.clearAndShrink();
|
|
}
|
|
|
|
|
|
void NO_INLINE Aggregator::mergeWithoutKeyDataImpl(
|
|
ManyAggregatedDataVariants & non_empty_data) const
|
|
{
|
|
AggregatedDataVariantsPtr & res = non_empty_data[0];
|
|
|
|
/// We connect all aggregation results to the first.
|
|
for (size_t i = 1, size = non_empty_data.size(); i < size; ++i)
|
|
{
|
|
AggregatedDataWithoutKey & res_data = res->without_key;
|
|
AggregatedDataWithoutKey & current_data = non_empty_data[i]->without_key;
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->merge(res_data + offsets_of_aggregate_states[i], current_data + offsets_of_aggregate_states[i], res->aggregates_pool);
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->destroy(current_data + offsets_of_aggregate_states[i]);
|
|
|
|
current_data = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
void NO_INLINE Aggregator::mergeSingleLevelDataImpl(
|
|
ManyAggregatedDataVariants & non_empty_data) const
|
|
{
|
|
AggregatedDataVariantsPtr & res = non_empty_data[0];
|
|
bool no_more_keys = false;
|
|
|
|
/// We connect all aggregation results to the first.
|
|
for (size_t i = 1, size = non_empty_data.size(); i < size; ++i)
|
|
{
|
|
if (!checkLimits(res->sizeWithoutOverflowRow(), no_more_keys))
|
|
break;
|
|
|
|
AggregatedDataVariants & current = *non_empty_data[i];
|
|
|
|
if (!no_more_keys)
|
|
mergeDataImpl<Method>(
|
|
getDataVariant<Method>(*res).data,
|
|
getDataVariant<Method>(current).data,
|
|
res->aggregates_pool);
|
|
else if (res->without_key)
|
|
mergeDataNoMoreKeysImpl<Method>(
|
|
getDataVariant<Method>(*res).data,
|
|
res->without_key,
|
|
getDataVariant<Method>(current).data,
|
|
res->aggregates_pool);
|
|
else
|
|
mergeDataOnlyExistingKeysImpl<Method>(
|
|
getDataVariant<Method>(*res).data,
|
|
getDataVariant<Method>(current).data,
|
|
res->aggregates_pool);
|
|
|
|
/// `current` will not destroy the states of aggregate functions in the destructor
|
|
current.aggregator = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
void NO_INLINE Aggregator::mergeBucketImpl(
|
|
ManyAggregatedDataVariants & data, Int32 bucket, Arena * arena) const
|
|
{
|
|
/// We connect all aggregation results to the first.
|
|
AggregatedDataVariantsPtr & res = data[0];
|
|
for (size_t i = 1, size = data.size(); i < size; ++i)
|
|
{
|
|
AggregatedDataVariants & current = *data[i];
|
|
|
|
mergeDataImpl<Method>(
|
|
getDataVariant<Method>(*res).data.impls[bucket],
|
|
getDataVariant<Method>(current).data.impls[bucket],
|
|
arena);
|
|
}
|
|
}
|
|
|
|
|
|
/** Combines aggregation states together, turns them into blocks, and outputs streams.
|
|
* If the aggregation states are two-level, then it produces blocks strictly in order of 'bucket_num'.
|
|
* (This is important for distributed processing.)
|
|
* In doing so, it can handle different buckets in parallel, using up to `threads` threads.
|
|
*/
|
|
class MergingAndConvertingBlockInputStream : public IProfilingBlockInputStream
|
|
{
|
|
public:
|
|
/** The input is a set of non-empty sets of partially aggregated data,
|
|
* which are all either single-level, or are two-level.
|
|
*/
|
|
MergingAndConvertingBlockInputStream(const Aggregator & aggregator_, ManyAggregatedDataVariants & data_, bool final_, size_t threads_)
|
|
: aggregator(aggregator_), data(data_), final(final_), threads(threads_)
|
|
{
|
|
/// At least we need one arena in first data item per thread
|
|
if (!data.empty() && threads > data[0]->aggregates_pools.size())
|
|
{
|
|
Arenas & first_pool = data[0]->aggregates_pools;
|
|
for (size_t j = first_pool.size(); j < threads; j++)
|
|
first_pool.emplace_back(std::make_shared<Arena>());
|
|
}
|
|
}
|
|
|
|
String getName() const override { return "MergingAndConverting"; }
|
|
|
|
Block getHeader() const override { return aggregator.getHeader(final); }
|
|
|
|
~MergingAndConvertingBlockInputStream()
|
|
{
|
|
LOG_TRACE(&Logger::get(__PRETTY_FUNCTION__), "Waiting for threads to finish");
|
|
|
|
/// We need to wait for threads to finish before destructor of 'parallel_merge_data',
|
|
/// because the threads access 'parallel_merge_data'.
|
|
if (parallel_merge_data)
|
|
parallel_merge_data->pool.wait();
|
|
}
|
|
|
|
protected:
|
|
Block readImpl() override
|
|
{
|
|
if (data.empty())
|
|
return {};
|
|
|
|
if (current_bucket_num >= NUM_BUCKETS)
|
|
return {};
|
|
|
|
AggregatedDataVariantsPtr & first = data[0];
|
|
|
|
if (current_bucket_num == -1)
|
|
{
|
|
++current_bucket_num;
|
|
|
|
if (first->type == AggregatedDataVariants::Type::without_key || aggregator.params.overflow_row)
|
|
{
|
|
aggregator.mergeWithoutKeyDataImpl(data);
|
|
return aggregator.prepareBlockAndFillWithoutKey(
|
|
*first, final, first->type != AggregatedDataVariants::Type::without_key);
|
|
}
|
|
}
|
|
|
|
if (!first->isTwoLevel())
|
|
{
|
|
if (current_bucket_num > 0)
|
|
return {};
|
|
|
|
if (first->type == AggregatedDataVariants::Type::without_key)
|
|
return {};
|
|
|
|
++current_bucket_num;
|
|
|
|
#define M(NAME) \
|
|
else if (first->type == AggregatedDataVariants::Type::NAME) \
|
|
aggregator.mergeSingleLevelDataImpl<decltype(first->NAME)::element_type>(data);
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_SINGLE_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
|
|
return aggregator.prepareBlockAndFillSingleLevel(*first, final);
|
|
}
|
|
else
|
|
{
|
|
if (!parallel_merge_data)
|
|
{
|
|
parallel_merge_data = std::make_unique<ParallelMergeData>(threads);
|
|
for (size_t i = 0; i < threads; ++i)
|
|
scheduleThreadForNextBucket();
|
|
}
|
|
|
|
Block res;
|
|
|
|
while (true)
|
|
{
|
|
std::unique_lock<std::mutex> lock(parallel_merge_data->mutex);
|
|
|
|
if (parallel_merge_data->exception)
|
|
std::rethrow_exception(parallel_merge_data->exception);
|
|
|
|
auto it = parallel_merge_data->ready_blocks.find(current_bucket_num);
|
|
if (it != parallel_merge_data->ready_blocks.end())
|
|
{
|
|
++current_bucket_num;
|
|
scheduleThreadForNextBucket();
|
|
|
|
if (it->second)
|
|
{
|
|
res.swap(it->second);
|
|
break;
|
|
}
|
|
else if (current_bucket_num >= NUM_BUCKETS)
|
|
break;
|
|
}
|
|
|
|
parallel_merge_data->condvar.wait(lock);
|
|
}
|
|
|
|
return res;
|
|
}
|
|
}
|
|
|
|
private:
|
|
const Aggregator & aggregator;
|
|
ManyAggregatedDataVariants data;
|
|
bool final;
|
|
size_t threads;
|
|
|
|
Int32 current_bucket_num = -1;
|
|
Int32 max_scheduled_bucket_num = -1;
|
|
static constexpr Int32 NUM_BUCKETS = 256;
|
|
|
|
struct ParallelMergeData
|
|
{
|
|
std::map<Int32, Block> ready_blocks;
|
|
std::exception_ptr exception;
|
|
std::mutex mutex;
|
|
std::condition_variable condvar;
|
|
ThreadPool pool;
|
|
|
|
explicit ParallelMergeData(size_t threads) : pool(threads) {}
|
|
};
|
|
|
|
std::unique_ptr<ParallelMergeData> parallel_merge_data;
|
|
|
|
void scheduleThreadForNextBucket()
|
|
{
|
|
++max_scheduled_bucket_num;
|
|
if (max_scheduled_bucket_num >= NUM_BUCKETS)
|
|
return;
|
|
|
|
parallel_merge_data->pool.schedule(std::bind(&MergingAndConvertingBlockInputStream::thread, this,
|
|
max_scheduled_bucket_num, current_memory_tracker));
|
|
}
|
|
|
|
void thread(Int32 bucket_num, MemoryTracker * memory_tracker)
|
|
{
|
|
current_memory_tracker = memory_tracker;
|
|
setThreadName("MergingAggregtd");
|
|
CurrentMetrics::Increment metric_increment{CurrentMetrics::QueryThread};
|
|
|
|
try
|
|
{
|
|
/// TODO: add no_more_keys support maybe
|
|
|
|
auto & merged_data = *data[0];
|
|
auto method = merged_data.type;
|
|
Block block;
|
|
|
|
/// Select Arena to avoid race conditions
|
|
size_t thread_number = static_cast<size_t>(bucket_num) % threads;
|
|
Arena * arena = merged_data.aggregates_pools.at(thread_number).get();
|
|
|
|
if (false) {}
|
|
#define M(NAME) \
|
|
else if (method == AggregatedDataVariants::Type::NAME) \
|
|
{ \
|
|
aggregator.mergeBucketImpl<decltype(merged_data.NAME)::element_type>(data, bucket_num, arena); \
|
|
block = aggregator.convertOneBucketToBlock(merged_data, *merged_data.NAME, final, bucket_num); \
|
|
}
|
|
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
|
|
std::lock_guard<std::mutex> lock(parallel_merge_data->mutex);
|
|
parallel_merge_data->ready_blocks[bucket_num] = std::move(block);
|
|
}
|
|
catch (...)
|
|
{
|
|
std::lock_guard<std::mutex> lock(parallel_merge_data->mutex);
|
|
if (!parallel_merge_data->exception)
|
|
parallel_merge_data->exception = std::current_exception();
|
|
}
|
|
|
|
parallel_merge_data->condvar.notify_all();
|
|
}
|
|
};
|
|
|
|
|
|
std::unique_ptr<IBlockInputStream> Aggregator::mergeAndConvertToBlocks(
|
|
ManyAggregatedDataVariants & data_variants, bool final, size_t max_threads) const
|
|
{
|
|
if (data_variants.empty())
|
|
throw Exception("Empty data passed to Aggregator::mergeAndConvertToBlocks.", ErrorCodes::EMPTY_DATA_PASSED);
|
|
|
|
LOG_TRACE(log, "Merging aggregated data");
|
|
|
|
ManyAggregatedDataVariants non_empty_data;
|
|
non_empty_data.reserve(data_variants.size());
|
|
for (auto & data : data_variants)
|
|
if (!data->empty())
|
|
non_empty_data.push_back(data);
|
|
|
|
if (non_empty_data.empty())
|
|
return std::make_unique<NullBlockInputStream>(getHeader(final));
|
|
|
|
if (non_empty_data.size() > 1)
|
|
{
|
|
/// Sort the states in descending order so that the merge is more efficient (since all states are merged into the first).
|
|
std::sort(non_empty_data.begin(), non_empty_data.end(),
|
|
[](const AggregatedDataVariantsPtr & lhs, const AggregatedDataVariantsPtr & rhs)
|
|
{
|
|
return lhs->sizeWithoutOverflowRow() > rhs->sizeWithoutOverflowRow();
|
|
});
|
|
}
|
|
|
|
/// If at least one of the options is two-level, then convert all the options into two-level ones, if there are not such.
|
|
/// Note - perhaps it would be more optimal not to convert single-level versions before the merge, but merge them separately, at the end.
|
|
|
|
bool has_at_least_one_two_level = false;
|
|
for (const auto & variant : non_empty_data)
|
|
{
|
|
if (variant->isTwoLevel())
|
|
{
|
|
has_at_least_one_two_level = true;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (has_at_least_one_two_level)
|
|
for (auto & variant : non_empty_data)
|
|
if (!variant->isTwoLevel())
|
|
variant->convertToTwoLevel();
|
|
|
|
AggregatedDataVariantsPtr & first = non_empty_data[0];
|
|
|
|
for (size_t i = 1, size = non_empty_data.size(); i < size; ++i)
|
|
{
|
|
if (first->type != non_empty_data[i]->type)
|
|
throw Exception("Cannot merge different aggregated data variants.", ErrorCodes::CANNOT_MERGE_DIFFERENT_AGGREGATED_DATA_VARIANTS);
|
|
|
|
/** Elements from the remaining sets can be moved to the first data set.
|
|
* Therefore, it must own all the arenas of all other sets.
|
|
*/
|
|
first->aggregates_pools.insert(first->aggregates_pools.end(),
|
|
non_empty_data[i]->aggregates_pools.begin(), non_empty_data[i]->aggregates_pools.end());
|
|
}
|
|
|
|
return std::make_unique<MergingAndConvertingBlockInputStream>(*this, non_empty_data, final, max_threads);
|
|
}
|
|
|
|
|
|
template <bool no_more_keys, typename Method, typename Table>
|
|
void NO_INLINE Aggregator::mergeStreamsImplCase(
|
|
Block & block,
|
|
const Sizes & key_sizes,
|
|
Arena * aggregates_pool,
|
|
Method & method,
|
|
Table & data,
|
|
AggregateDataPtr overflow_row) const
|
|
{
|
|
ColumnRawPtrs key_columns(params.keys_size);
|
|
AggregateColumnsConstData aggregate_columns(params.aggregates_size);
|
|
|
|
/// Remember the columns we will work with
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
key_columns[i] = block.safeGetByPosition(i).column.get();
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_columns[i] = &typeid_cast<const ColumnAggregateFunction &>(*block.safeGetByPosition(params.keys_size + i).column).getData();
|
|
|
|
typename Method::State state;
|
|
state.init(key_columns);
|
|
|
|
/// For all rows.
|
|
StringRefs keys(params.keys_size);
|
|
size_t rows = block.rows();
|
|
for (size_t i = 0; i < rows; ++i)
|
|
{
|
|
typename Table::iterator it;
|
|
|
|
bool inserted; /// Inserted a new key, or was this key already?
|
|
bool overflow = false; /// The new key did not fit in the hash table because of no_more_keys.
|
|
|
|
/// Get the key to insert into the hash table.
|
|
auto key = state.getKey(key_columns, params.keys_size, i, key_sizes, keys, *aggregates_pool);
|
|
|
|
if (!no_more_keys)
|
|
{
|
|
data.emplace(key, it, inserted);
|
|
}
|
|
else
|
|
{
|
|
inserted = false;
|
|
it = data.find(key);
|
|
if (data.end() == it)
|
|
overflow = true;
|
|
}
|
|
|
|
/// If the key does not fit, and the data does not need to be aggregated into a separate row, then there's nothing to do.
|
|
if (no_more_keys && overflow && !overflow_row)
|
|
{
|
|
method.onExistingKey(key, keys, *aggregates_pool);
|
|
continue;
|
|
}
|
|
|
|
/// If a new key is inserted, initialize the states of the aggregate functions, and possibly something related to the key.
|
|
if (inserted)
|
|
{
|
|
AggregateDataPtr & aggregate_data = Method::getAggregateData(it->second);
|
|
aggregate_data = nullptr;
|
|
|
|
method.onNewKey(*it, params.keys_size, keys, *aggregates_pool);
|
|
|
|
AggregateDataPtr place = aggregates_pool->alloc(total_size_of_aggregate_states);
|
|
createAggregateStates(place);
|
|
aggregate_data = place;
|
|
}
|
|
else
|
|
method.onExistingKey(key, keys, *aggregates_pool);
|
|
|
|
AggregateDataPtr value = (!no_more_keys || !overflow) ? Method::getAggregateData(it->second) : overflow_row;
|
|
|
|
/// Merge state of aggregate functions.
|
|
for (size_t j = 0; j < params.aggregates_size; ++j)
|
|
aggregate_functions[j]->merge(
|
|
value + offsets_of_aggregate_states[j],
|
|
(*aggregate_columns[j])[i],
|
|
aggregates_pool);
|
|
}
|
|
|
|
/// Early release memory.
|
|
block.clear();
|
|
}
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::mergeStreamsImpl(
|
|
Block & block,
|
|
const Sizes & key_sizes,
|
|
Arena * aggregates_pool,
|
|
Method & method,
|
|
Table & data,
|
|
AggregateDataPtr overflow_row,
|
|
bool no_more_keys) const
|
|
{
|
|
if (!no_more_keys)
|
|
mergeStreamsImplCase<false>(block, key_sizes, aggregates_pool, method, data, overflow_row);
|
|
else
|
|
mergeStreamsImplCase<true>(block, key_sizes, aggregates_pool, method, data, overflow_row);
|
|
}
|
|
|
|
|
|
void NO_INLINE Aggregator::mergeWithoutKeyStreamsImpl(
|
|
Block & block,
|
|
AggregatedDataVariants & result) const
|
|
{
|
|
AggregateColumnsConstData aggregate_columns(params.aggregates_size);
|
|
|
|
/// Remember the columns we will work with
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_columns[i] = &typeid_cast<const ColumnAggregateFunction &>(*block.safeGetByPosition(params.keys_size + i).column).getData();
|
|
|
|
AggregatedDataWithoutKey & res = result.without_key;
|
|
if (!res)
|
|
{
|
|
AggregateDataPtr place = result.aggregates_pool->alloc(total_size_of_aggregate_states);
|
|
createAggregateStates(place);
|
|
res = place;
|
|
}
|
|
|
|
/// Adding Values
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
aggregate_functions[i]->merge(res + offsets_of_aggregate_states[i], (*aggregate_columns[i])[0], result.aggregates_pool);
|
|
|
|
/// Early release memory.
|
|
block.clear();
|
|
}
|
|
|
|
|
|
void Aggregator::mergeStream(const BlockInputStreamPtr & stream, AggregatedDataVariants & result, size_t max_threads)
|
|
{
|
|
if (isCancelled())
|
|
return;
|
|
|
|
/** If the remote servers used a two-level aggregation method,
|
|
* then blocks will contain information about the number of the bucket.
|
|
* Then the calculations can be parallelized by buckets.
|
|
* We decompose the blocks to the bucket numbers indicated in them.
|
|
*/
|
|
using BucketToBlocks = std::map<Int32, BlocksList>;
|
|
BucketToBlocks bucket_to_blocks;
|
|
|
|
/// Read all the data.
|
|
LOG_TRACE(log, "Reading blocks of partially aggregated data.");
|
|
|
|
size_t total_input_rows = 0;
|
|
size_t total_input_blocks = 0;
|
|
while (Block block = stream->read())
|
|
{
|
|
if (isCancelled())
|
|
return;
|
|
|
|
total_input_rows += block.rows();
|
|
++total_input_blocks;
|
|
bucket_to_blocks[block.info.bucket_num].emplace_back(std::move(block));
|
|
}
|
|
|
|
LOG_TRACE(log, "Read " << total_input_blocks << " blocks of partially aggregated data, total " << total_input_rows << " rows.");
|
|
|
|
if (bucket_to_blocks.empty())
|
|
return;
|
|
|
|
/** `minus one` means the absence of information about the bucket
|
|
* - in the case of single-level aggregation, as well as for blocks with "overflowing" values.
|
|
* If there is at least one block with a bucket number greater than zero, then there was a two-level aggregation.
|
|
*/
|
|
auto max_bucket = bucket_to_blocks.rbegin()->first;
|
|
size_t has_two_level = max_bucket > 0;
|
|
|
|
if (has_two_level)
|
|
{
|
|
#define M(NAME) \
|
|
if (method == AggregatedDataVariants::Type::NAME) \
|
|
method = AggregatedDataVariants::Type::NAME ## _two_level;
|
|
|
|
APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M)
|
|
|
|
#undef M
|
|
}
|
|
|
|
if (isCancelled())
|
|
return;
|
|
|
|
/// result will destroy the states of aggregate functions in the destructor
|
|
result.aggregator = this;
|
|
|
|
result.init(method);
|
|
result.keys_size = params.keys_size;
|
|
result.key_sizes = key_sizes;
|
|
|
|
bool has_blocks_with_unknown_bucket = bucket_to_blocks.count(-1);
|
|
|
|
/// First, parallel the merge for the individual buckets. Then we continue merge the data not allocated to the buckets.
|
|
if (has_two_level)
|
|
{
|
|
/** In this case, no_more_keys is not supported due to the fact that
|
|
* from different threads it is difficult to update the general state for "other" keys (overflows).
|
|
* That is, the keys in the end can be significantly larger than max_rows_to_group_by.
|
|
*/
|
|
|
|
LOG_TRACE(log, "Merging partially aggregated two-level data.");
|
|
|
|
auto merge_bucket = [&bucket_to_blocks, &result, this](Int32 bucket, Arena * aggregates_pool, MemoryTracker * memory_tracker)
|
|
{
|
|
current_memory_tracker = memory_tracker;
|
|
|
|
for (Block & block : bucket_to_blocks[bucket])
|
|
{
|
|
if (isCancelled())
|
|
return;
|
|
|
|
#define M(NAME) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
mergeStreamsImpl(block, result.key_sizes, aggregates_pool, *result.NAME, result.NAME->data.impls[bucket], nullptr, false);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
}
|
|
};
|
|
|
|
std::unique_ptr<ThreadPool> thread_pool;
|
|
if (max_threads > 1 && total_input_rows > 100000) /// TODO Make a custom threshold.
|
|
thread_pool = std::make_unique<ThreadPool>(max_threads);
|
|
|
|
for (const auto & bucket_blocks : bucket_to_blocks)
|
|
{
|
|
const auto bucket = bucket_blocks.first;
|
|
|
|
if (bucket == -1)
|
|
continue;
|
|
|
|
result.aggregates_pools.push_back(std::make_shared<Arena>());
|
|
Arena * aggregates_pool = result.aggregates_pools.back().get();
|
|
|
|
auto task = std::bind(merge_bucket, bucket, aggregates_pool, current_memory_tracker);
|
|
|
|
if (thread_pool)
|
|
thread_pool->schedule(task);
|
|
else
|
|
task();
|
|
}
|
|
|
|
if (thread_pool)
|
|
thread_pool->wait();
|
|
|
|
LOG_TRACE(log, "Merged partially aggregated two-level data.");
|
|
}
|
|
|
|
if (isCancelled())
|
|
{
|
|
result.invalidate();
|
|
return;
|
|
}
|
|
|
|
if (has_blocks_with_unknown_bucket)
|
|
{
|
|
LOG_TRACE(log, "Merging partially aggregated single-level data.");
|
|
|
|
bool no_more_keys = false;
|
|
|
|
BlocksList & blocks = bucket_to_blocks[-1];
|
|
for (Block & block : blocks)
|
|
{
|
|
if (isCancelled())
|
|
{
|
|
result.invalidate();
|
|
return;
|
|
}
|
|
|
|
if (!checkLimits(result.sizeWithoutOverflowRow(), no_more_keys))
|
|
break;
|
|
|
|
if (result.type == AggregatedDataVariants::Type::without_key || block.info.is_overflows)
|
|
mergeWithoutKeyStreamsImpl(block, result);
|
|
|
|
#define M(NAME, IS_TWO_LEVEL) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
mergeStreamsImpl(block, result.key_sizes, result.aggregates_pool, *result.NAME, result.NAME->data, result.without_key, no_more_keys);
|
|
|
|
APPLY_FOR_AGGREGATED_VARIANTS(M)
|
|
#undef M
|
|
else if (result.type != AggregatedDataVariants::Type::without_key)
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
}
|
|
|
|
LOG_TRACE(log, "Merged partially aggregated single-level data.");
|
|
}
|
|
}
|
|
|
|
|
|
Block Aggregator::mergeBlocks(BlocksList & blocks, bool final)
|
|
{
|
|
if (blocks.empty())
|
|
return {};
|
|
|
|
auto bucket_num = blocks.front().info.bucket_num;
|
|
bool is_overflows = blocks.front().info.is_overflows;
|
|
|
|
LOG_TRACE(log, "Merging partially aggregated blocks (bucket = " << bucket_num << ").");
|
|
Stopwatch watch;
|
|
|
|
/** If possible, change 'method' to some_hash64. Otherwise, leave as is.
|
|
* Better hash function is needed because during external aggregation,
|
|
* we may merge partitions of data with total number of keys far greater than 4 billion.
|
|
*/
|
|
auto merge_method = method;
|
|
|
|
#define APPLY_FOR_VARIANTS_THAT_MAY_USE_BETTER_HASH_FUNCTION(M) \
|
|
M(key64) \
|
|
M(key_string) \
|
|
M(key_fixed_string) \
|
|
M(keys128) \
|
|
M(keys256) \
|
|
M(concat) \
|
|
M(serialized) \
|
|
|
|
#define M(NAME) \
|
|
if (merge_method == AggregatedDataVariants::Type::NAME) \
|
|
merge_method = AggregatedDataVariants::Type::NAME ## _hash64; \
|
|
|
|
APPLY_FOR_VARIANTS_THAT_MAY_USE_BETTER_HASH_FUNCTION(M)
|
|
#undef M
|
|
|
|
#undef APPLY_FOR_VARIANTS_THAT_MAY_USE_BETTER_HASH_FUNCTION
|
|
|
|
/// Temporary data for aggregation.
|
|
AggregatedDataVariants result;
|
|
|
|
/// result will destroy the states of aggregate functions in the destructor
|
|
result.aggregator = this;
|
|
|
|
result.init(merge_method);
|
|
result.keys_size = params.keys_size;
|
|
result.key_sizes = key_sizes;
|
|
|
|
for (Block & block : blocks)
|
|
{
|
|
if (isCancelled())
|
|
return {};
|
|
|
|
if (bucket_num >= 0 && block.info.bucket_num != bucket_num)
|
|
bucket_num = -1;
|
|
|
|
if (result.type == AggregatedDataVariants::Type::without_key || is_overflows)
|
|
mergeWithoutKeyStreamsImpl(block, result);
|
|
|
|
#define M(NAME, IS_TWO_LEVEL) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
mergeStreamsImpl(block, key_sizes, result.aggregates_pool, *result.NAME, result.NAME->data, nullptr, false);
|
|
|
|
APPLY_FOR_AGGREGATED_VARIANTS(M)
|
|
#undef M
|
|
else if (result.type != AggregatedDataVariants::Type::without_key)
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
}
|
|
|
|
if (isCancelled())
|
|
return {};
|
|
|
|
Block block;
|
|
if (result.type == AggregatedDataVariants::Type::without_key || is_overflows)
|
|
block = prepareBlockAndFillWithoutKey(result, final, is_overflows);
|
|
else
|
|
block = prepareBlockAndFillSingleLevel(result, final);
|
|
/// NOTE: two-level data is not possible here - chooseAggregationMethod chooses only among single-level methods.
|
|
|
|
if (!final)
|
|
{
|
|
/// Pass ownership of aggregate function states from result to ColumnAggregateFunction objects in the resulting block.
|
|
result.aggregator = nullptr;
|
|
}
|
|
|
|
size_t rows = block.rows();
|
|
size_t bytes = block.bytes();
|
|
double elapsed_seconds = watch.elapsedSeconds();
|
|
LOG_TRACE(log, std::fixed << std::setprecision(3)
|
|
<< "Merged partially aggregated blocks. "
|
|
<< rows << " rows, " << bytes / 1048576.0 << " MiB."
|
|
<< " in " << elapsed_seconds << " sec."
|
|
<< " (" << rows / elapsed_seconds << " rows/sec., " << bytes / elapsed_seconds / 1048576.0 << " MiB/sec.)");
|
|
|
|
if (isCancelled())
|
|
return {};
|
|
|
|
block.info.bucket_num = bucket_num;
|
|
return block;
|
|
}
|
|
|
|
|
|
template <typename Method>
|
|
void NO_INLINE Aggregator::convertBlockToTwoLevelImpl(
|
|
Method & method,
|
|
Arena * pool,
|
|
ColumnRawPtrs & key_columns,
|
|
const Sizes & key_sizes,
|
|
StringRefs & keys,
|
|
const Block & source,
|
|
std::vector<Block> & destinations) const
|
|
{
|
|
typename Method::State state;
|
|
state.init(key_columns);
|
|
|
|
size_t rows = source.rows();
|
|
size_t columns = source.columns();
|
|
|
|
/// Create a 'selector' that will contain bucket index for every row. It will be used to scatter rows to buckets.
|
|
IColumn::Selector selector(rows);
|
|
|
|
/// For every row.
|
|
for (size_t i = 0; i < rows; ++i)
|
|
{
|
|
/// Obtain a key. Calculate bucket number from it.
|
|
typename Method::Key key = state.getKey(key_columns, params.keys_size, i, key_sizes, keys, *pool);
|
|
|
|
auto hash = method.data.hash(key);
|
|
auto bucket = method.data.getBucketFromHash(hash);
|
|
|
|
selector[i] = bucket;
|
|
|
|
/// We don't need to store this key in pool.
|
|
method.onExistingKey(key, keys, *pool);
|
|
}
|
|
|
|
size_t num_buckets = destinations.size();
|
|
|
|
for (size_t column_idx = 0; column_idx < columns; ++column_idx)
|
|
{
|
|
const ColumnWithTypeAndName & src_col = source.getByPosition(column_idx);
|
|
MutableColumns scattered_columns = src_col.column->scatter(num_buckets, selector);
|
|
|
|
for (size_t bucket = 0, size = num_buckets; bucket < size; ++bucket)
|
|
{
|
|
if (!scattered_columns[bucket]->empty())
|
|
{
|
|
Block & dst = destinations[bucket];
|
|
dst.info.bucket_num = bucket;
|
|
dst.insert({std::move(scattered_columns[bucket]), src_col.type, src_col.name});
|
|
}
|
|
|
|
/** Inserted columns of type ColumnAggregateFunction will own states of aggregate functions
|
|
* by holding shared_ptr to source column. See ColumnAggregateFunction.h
|
|
*/
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
std::vector<Block> Aggregator::convertBlockToTwoLevel(const Block & block)
|
|
{
|
|
if (!block)
|
|
return {};
|
|
|
|
AggregatedDataVariants data;
|
|
|
|
StringRefs key(params.keys_size);
|
|
ColumnRawPtrs key_columns(params.keys_size);
|
|
|
|
/// Remember the columns we will work with
|
|
for (size_t i = 0; i < params.keys_size; ++i)
|
|
key_columns[i] = block.safeGetByPosition(i).column.get();
|
|
|
|
AggregatedDataVariants::Type type = method;
|
|
data.keys_size = params.keys_size;
|
|
data.key_sizes = key_sizes;
|
|
|
|
#define M(NAME) \
|
|
else if (type == AggregatedDataVariants::Type::NAME) \
|
|
type = AggregatedDataVariants::Type::NAME ## _two_level;
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
|
|
data.init(type);
|
|
|
|
size_t num_buckets = 0;
|
|
|
|
#define M(NAME) \
|
|
else if (data.type == AggregatedDataVariants::Type::NAME) \
|
|
num_buckets = data.NAME->data.NUM_BUCKETS;
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
|
|
std::vector<Block> splitted_blocks(num_buckets);
|
|
|
|
#define M(NAME) \
|
|
else if (data.type == AggregatedDataVariants::Type::NAME) \
|
|
convertBlockToTwoLevelImpl(*data.NAME, data.aggregates_pool, \
|
|
key_columns, data.key_sizes, key, block, splitted_blocks);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_VARIANTS_TWO_LEVEL(M)
|
|
#undef M
|
|
else
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
|
|
return splitted_blocks;
|
|
}
|
|
|
|
|
|
template <typename Method, typename Table>
|
|
void NO_INLINE Aggregator::destroyImpl(Table & table) const
|
|
{
|
|
for (auto elem : table)
|
|
{
|
|
AggregateDataPtr & data = Method::getAggregateData(elem.second);
|
|
|
|
/** If an exception (usually a lack of memory, the MemoryTracker throws) arose
|
|
* after inserting the key into a hash table, but before creating all states of aggregate functions,
|
|
* then data will be equal nullptr.
|
|
*/
|
|
if (nullptr == data)
|
|
continue;
|
|
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
if (!aggregate_functions[i]->isState())
|
|
aggregate_functions[i]->destroy(data + offsets_of_aggregate_states[i]);
|
|
|
|
data = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
void Aggregator::destroyWithoutKey(AggregatedDataVariants & result) const
|
|
{
|
|
AggregatedDataWithoutKey & res_data = result.without_key;
|
|
|
|
if (nullptr != res_data)
|
|
{
|
|
for (size_t i = 0; i < params.aggregates_size; ++i)
|
|
if (!aggregate_functions[i]->isState())
|
|
aggregate_functions[i]->destroy(res_data + offsets_of_aggregate_states[i]);
|
|
|
|
res_data = nullptr;
|
|
}
|
|
}
|
|
|
|
|
|
void Aggregator::destroyAllAggregateStates(AggregatedDataVariants & result)
|
|
{
|
|
if (result.size() == 0)
|
|
return;
|
|
|
|
LOG_TRACE(log, "Destroying aggregate states");
|
|
|
|
/// In what data structure is the data aggregated?
|
|
if (result.type == AggregatedDataVariants::Type::without_key || params.overflow_row)
|
|
destroyWithoutKey(result);
|
|
|
|
#define M(NAME, IS_TWO_LEVEL) \
|
|
else if (result.type == AggregatedDataVariants::Type::NAME) \
|
|
destroyImpl<decltype(result.NAME)::element_type>(result.NAME->data);
|
|
|
|
if (false) {}
|
|
APPLY_FOR_AGGREGATED_VARIANTS(M)
|
|
#undef M
|
|
else if (result.type != AggregatedDataVariants::Type::without_key)
|
|
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
|
|
}
|
|
|
|
|
|
void Aggregator::setCancellationHook(const CancellationHook cancellation_hook)
|
|
{
|
|
isCancelled = cancellation_hook;
|
|
}
|
|
|
|
|
|
}
|