ClickHouse/dbms/src/Interpreters/Aggregator.h

1427 lines
55 KiB
C++

#pragma once
#include <mutex>
#include <memory>
#include <functional>
#include <Poco/TemporaryFile.h>
#include <common/logger_useful.h>
#include <common/StringRef.h>
#include <Common/Arena.h>
#include <Common/HashTable/HashMap.h>
#include <Common/HashTable/TwoLevelHashMap.h>
#include <common/ThreadPool.h>
#include <DataStreams/IBlockInputStream.h>
#include <Interpreters/AggregateDescription.h>
#include <Interpreters/AggregationCommon.h>
#include <Interpreters/Limits.h>
#include <Interpreters/Compiler.h>
#include <Columns/ColumnString.h>
#include <Columns/ColumnFixedString.h>
#include <Columns/ColumnAggregateFunction.h>
#include <Columns/ColumnVector.h>
#include <Columns/ColumnNullable.h>
namespace DB
{
namespace ErrorCodes
{
extern const int UNKNOWN_AGGREGATED_DATA_VARIANT;
}
class IBlockOutputStream;
/** Different data structures that can be used for aggregation
* For efficiency, the aggregation data itself is put into the pool.
* Data and pool ownership (states of aggregate functions)
* is acquired later - in `convertToBlocks` function, by the ColumnAggregateFunction object.
*
* Most data structures exist in two versions: normal and two-level (TwoLevel).
* A two-level hash table works a little slower with a small number of different keys,
* but with a large number of different keys scales better, because it allows
* parallelize some operations (merging, post-processing) in a natural way.
*
* To ensure efficient work over a wide range of conditions,
* first single-level hash tables are used,
* and when the number of different keys is large enough,
* they are converted to two-level ones.
*
* PS. There are many different approaches to the effective implementation of parallel and distributed aggregation,
* best suited for different cases, and this approach is just one of them, chosen for a combination of reasons.
*/
using AggregatedDataWithoutKey = AggregateDataPtr;
using AggregatedDataWithUInt8Key = HashMap<UInt64, AggregateDataPtr, TrivialHash, HashTableFixedGrower<8>>;
using AggregatedDataWithUInt16Key = HashMap<UInt64, AggregateDataPtr, TrivialHash, HashTableFixedGrower<16>>;
using AggregatedDataWithUInt64Key = HashMap<UInt64, AggregateDataPtr, HashCRC32<UInt64>>;
using AggregatedDataWithStringKey = HashMapWithSavedHash<StringRef, AggregateDataPtr>;
using AggregatedDataWithKeys128 = HashMap<UInt128, AggregateDataPtr, UInt128HashCRC32>;
using AggregatedDataWithKeys256 = HashMap<UInt256, AggregateDataPtr, UInt256HashCRC32>;
using AggregatedDataHashed = HashMap<UInt128, std::pair<StringRef*, AggregateDataPtr>, UInt128TrivialHash>;
using AggregatedDataWithUInt64KeyTwoLevel = TwoLevelHashMap<UInt64, AggregateDataPtr, HashCRC32<UInt64>>;
using AggregatedDataWithStringKeyTwoLevel = TwoLevelHashMapWithSavedHash<StringRef, AggregateDataPtr>;
using AggregatedDataWithKeys128TwoLevel = TwoLevelHashMap<UInt128, AggregateDataPtr, UInt128HashCRC32>;
using AggregatedDataWithKeys256TwoLevel = TwoLevelHashMap<UInt256, AggregateDataPtr, UInt256HashCRC32>;
using AggregatedDataHashedTwoLevel = TwoLevelHashMap<UInt128, std::pair<StringRef*, AggregateDataPtr>, UInt128TrivialHash>;
/** Variants with better hash function, using more than 32 bits for hash.
* Using for merging phase of external aggregation, where number of keys may be far greater than 4 billion,
* but we keep in memory and merge only sub-partition of them simultaneously.
* TODO We need to switch for better hash function not only for external aggregation,
* but also for huge aggregation results on machines with terabytes of RAM.
*/
using AggregatedDataWithUInt64KeyHash64 = HashMap<UInt64, AggregateDataPtr, DefaultHash<UInt64>>;
using AggregatedDataWithStringKeyHash64 = HashMapWithSavedHash<StringRef, AggregateDataPtr, StringRefHash64>;
using AggregatedDataWithKeys128Hash64 = HashMap<UInt128, AggregateDataPtr, UInt128Hash>;
using AggregatedDataWithKeys256Hash64 = HashMap<UInt256, AggregateDataPtr, UInt256Hash>;
/// For the case where there is one numeric key.
template <typename FieldType, typename TData> /// UInt8/16/32/64 for any type with corresponding bit width.
struct AggregationMethodOneNumber
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodOneNumber() {}
template <typename Other>
AggregationMethodOneNumber(const Other & other) : data(other.data) {}
/// To use one `Method` in different threads, use different `State`.
struct State
{
const FieldType * vec;
/** Called at the start of each block processing.
* Sets the variables needed for the other methods called in internal loops.
*/
void init(ConstColumnPlainPtrs & key_columns)
{
vec = &static_cast<const ColumnVector<FieldType> *>(key_columns[0])->getData()[0];
}
/// Get the key from the key columns for insertion into the hash table.
Key getKey(
const ConstColumnPlainPtrs & key_columns, /// Key columns.
size_t keys_size, /// Number of key columns.
size_t i, /// From which row of the block, get the key.
const Sizes & key_sizes, /// If the keys of a fixed length - their lengths. It is not used in aggregation methods for variable length keys.
StringRefs & keys, /// Here references to key data in columns can be written. They can be used in the future.
Arena & pool) const
{
return unionCastToUInt64(vec[i]);
}
};
/// From the value in the hash table, get AggregateDataPtr.
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
/** Place additional data, if necessary, in case a new key was inserted into the hash table.
*/
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
}
/** The action to be taken if the key is not new. For example, roll back the memory allocation in the pool.
*/
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool) {}
/** Do not use optimization for consecutive keys.
*/
static const bool no_consecutive_keys_optimization = false;
/** Insert the key from the hash table into columns.
*/
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
static_cast<ColumnVector<FieldType> *>(key_columns[0])->insertData(reinterpret_cast<const char *>(&value.first), sizeof(value.first));
}
};
/// For the case where there is one string key.
template <typename TData>
struct AggregationMethodString
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodString() {}
template <typename Other>
AggregationMethodString(const Other & other) : data(other.data) {}
struct State
{
const ColumnString::Offsets_t * offsets;
const ColumnString::Chars_t * chars;
void init(ConstColumnPlainPtrs & key_columns)
{
const IColumn & column = *key_columns[0];
const ColumnString & column_string = static_cast<const ColumnString &>(column);
offsets = &column_string.getOffsets();
chars = &column_string.getChars();
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
return StringRef(
&(*chars)[i == 0 ? 0 : (*offsets)[i - 1]],
(i == 0 ? (*offsets)[i] : ((*offsets)[i] - (*offsets)[i - 1])) - 1);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
value.first.data = pool.insert(value.first.data, value.first.size);
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool) {}
static const bool no_consecutive_keys_optimization = false;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
key_columns[0]->insertData(value.first.data, value.first.size);
}
};
/// For the case where there is one fixed-length string key.
template <typename TData>
struct AggregationMethodFixedString
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodFixedString() {}
template <typename Other>
AggregationMethodFixedString(const Other & other) : data(other.data) {}
struct State
{
size_t n;
const ColumnFixedString::Chars_t * chars;
void init(ConstColumnPlainPtrs & key_columns)
{
const IColumn & column = *key_columns[0];
const ColumnFixedString & column_string = static_cast<const ColumnFixedString &>(column);
n = column_string.getN();
chars = &column_string.getChars();
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
return StringRef(&(*chars)[i * n], n);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
value.first.data = pool.insert(value.first.data, value.first.size);
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool) {}
static const bool no_consecutive_keys_optimization = false;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
key_columns[0]->insertData(value.first.data, value.first.size);
}
};
namespace aggregator_impl
{
/// This class is designed to provide the functionality that is required for
/// supporting nullable keys in AggregationMethodKeysFixed. If there are
/// no nullable keys, this class is merely implemented as an empty shell.
template <typename Key, bool has_nullable_keys>
class BaseStateKeysFixed;
/// Case where nullable keys are supported.
template <typename Key>
class BaseStateKeysFixed<Key, true>
{
protected:
void init(const ConstColumnPlainPtrs & key_columns)
{
null_maps.reserve(key_columns.size());
actual_columns.reserve(key_columns.size());
for (const auto & col : key_columns)
{
if (col->isNullable())
{
const auto & nullable_col = static_cast<const ColumnNullable &>(*col);
actual_columns.push_back(nullable_col.getNestedColumn().get());
null_maps.push_back(nullable_col.getNullMapColumn().get());
}
else
{
actual_columns.push_back(col);
null_maps.push_back(nullptr);
}
}
}
/// Return the columns which actually contain the values of the keys.
/// For a given key column, if it is nullable, we return its nested
/// column. Otherwise we return the key column itself.
inline const ConstColumnPlainPtrs & getActualColumns() const
{
return actual_columns;
}
/// Create a bitmap that indicates whether, for a particular row,
/// a key column bears a null value or not.
KeysNullMap<Key> createBitmap(size_t row) const
{
KeysNullMap<Key> bitmap{};
for (size_t k = 0; k < null_maps.size(); ++k)
{
if (null_maps[k] != nullptr)
{
const auto & null_map = static_cast<const ColumnUInt8 &>(*null_maps[k]).getData();
if (null_map[row] == 1)
{
size_t bucket = k / 8;
size_t offset = k % 8;
bitmap[bucket] |= UInt8(1) << offset;
}
}
}
return bitmap;
}
private:
ConstColumnPlainPtrs actual_columns;
ConstColumnPlainPtrs null_maps;
};
/// Case where nullable keys are not supported.
template <typename Key>
class BaseStateKeysFixed<Key, false>
{
protected:
void init(const ConstColumnPlainPtrs & key_columns)
{
throw Exception{"Internal error: calling init() for non-nullable"
" keys is forbidden", ErrorCodes::LOGICAL_ERROR};
}
const ConstColumnPlainPtrs & getActualColumns() const
{
throw Exception{"Internal error: calling getActualColumns() for non-nullable"
" keys is forbidden", ErrorCodes::LOGICAL_ERROR};
}
KeysNullMap<Key> createBitmap(size_t row) const
{
throw Exception{"Internal error: calling createBitmap() for non-nullable keys"
" is forbidden", ErrorCodes::LOGICAL_ERROR};
}
};
}
/// For the case where all keys are of fixed length, and they fit in N (for example, 128) bits.
template <typename TData, bool has_nullable_keys_ = false>
struct AggregationMethodKeysFixed
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
static constexpr bool has_nullable_keys = has_nullable_keys_;
Data data;
AggregationMethodKeysFixed() {}
template <typename Other>
AggregationMethodKeysFixed(const Other & other) : data(other.data) {}
class State final : private aggregator_impl::BaseStateKeysFixed<Key, has_nullable_keys>
{
public:
using Base = aggregator_impl::BaseStateKeysFixed<Key, has_nullable_keys>;
void init(ConstColumnPlainPtrs & key_columns)
{
if (has_nullable_keys)
Base::init(key_columns);
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
if (has_nullable_keys)
{
auto bitmap = Base::createBitmap(i);
return packFixed<Key>(i, keys_size, Base::getActualColumns(), key_sizes, bitmap);
}
else
return packFixed<Key>(i, keys_size, key_columns, key_sizes);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool) {}
static const bool no_consecutive_keys_optimization = false;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
static constexpr auto bitmap_size = has_nullable_keys ? std::tuple_size<KeysNullMap<Key>>::value : 0;
/// In any hash key value, column values to be read start just after the bitmap, if it exists.
size_t pos = bitmap_size;
for (size_t i = 0; i < keys_size; ++i)
{
IColumn * observed_column;
ColumnUInt8 * null_map;
/// If we have a nullable column, get its nested column and its null map.
if (has_nullable_keys && key_columns[i]->isNullable())
{
ColumnNullable & nullable_col = static_cast<ColumnNullable &>(*key_columns[i]);
observed_column = nullable_col.getNestedColumn().get();
null_map = static_cast<ColumnUInt8 *>(nullable_col.getNullMapColumn().get());
}
else
{
observed_column = key_columns[i];
null_map = nullptr;
}
bool is_null;
if (has_nullable_keys && key_columns[i]->isNullable())
{
/// The current column is nullable. Check if the value of the
/// corresponding key is nullable. Update the null map accordingly.
size_t bucket = i / 8;
size_t offset = i % 8;
UInt8 val = (reinterpret_cast<const UInt8 *>(&value.first)[bucket] >> offset) & 1;
null_map->insert(val);
is_null = val == 1;
}
else
is_null = false;
if (has_nullable_keys && is_null)
observed_column->insertDefault();
else
{
size_t size = key_sizes[i];
observed_column->insertData(reinterpret_cast<const char *>(&value.first) + pos, size);
pos += size;
}
}
}
};
/// Aggregates by key concatenation. (In this case, strings containing zeros in the middle can stick together.)
template <typename TData>
struct AggregationMethodConcat
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodConcat() {}
template <typename Other>
AggregationMethodConcat(const Other & other) : data(other.data) {}
struct State
{
void init(ConstColumnPlainPtrs & key_columns)
{
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
return extractKeysAndPlaceInPoolContiguous(i, keys_size, key_columns, keys, pool);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool)
{
pool.rollback(key.size + keys.size() * sizeof(keys[0]));
}
/// If the key already was, then it is removed from the pool (overwritten), and the next key can not be compared with it.
static const bool no_consecutive_keys_optimization = true;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
insertKeyIntoColumnsImpl(value, key_columns, keys_size, key_sizes);
}
private:
/// Insert the values of the specified keys into the corresponding columns.
static void insertKeyIntoColumnsImpl(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
/// See function extractKeysAndPlaceInPoolContiguous.
const StringRef * key_refs = reinterpret_cast<const StringRef *>(value.first.data + value.first.size);
if (unlikely(0 == value.first.size))
{
/** Fix if all keys are empty arrays. For them, a zero-length StringRef is written to the hash table, but with a non-zero pointer.
* But when inserted into a hash table, this StringRef occurs equal to another key of zero length,
* whose data pointer can be any garbage and can not be used.
*/
for (size_t i = 0; i < keys_size; ++i)
key_columns[i]->insertDefault();
}
else
{
for (size_t i = 0; i < keys_size; ++i)
key_columns[i]->insertDataWithTerminatingZero(key_refs[i].data, key_refs[i].size);
}
}
};
/** Aggregates by concatenating serialized key values.
* Similar to AggregationMethodConcat, but it is suitable, for example, for arrays of strings or multiple arrays.
* The serialized value differs in that it uniquely allows to deserialize it, having only the position with which it starts.
* That is, for example, for strings, it contains first the serialized length of the string, and then the bytes.
* Therefore, when aggregating by several strings, there is no ambiguity.
*/
template <typename TData>
struct AggregationMethodSerialized
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodSerialized() {}
template <typename Other>
AggregationMethodSerialized(const Other & other) : data(other.data) {}
struct State
{
void init(ConstColumnPlainPtrs & key_columns)
{
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
return serializeKeysToPoolContiguous(i, keys_size, key_columns, keys, pool);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool)
{
pool.rollback(key.size);
}
/// If the key already was, it is removed from the pool (overwritten), and the next key can not be compared with it.
static const bool no_consecutive_keys_optimization = true;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
auto pos = value.first.data;
for (size_t i = 0; i < keys_size; ++i)
pos = key_columns[i]->deserializeAndInsertFromArena(pos);
}
};
/// For other cases. Aggregates by 128-bit hash from the key.
template <typename TData>
struct AggregationMethodHashed
{
using Data = TData;
using Key = typename Data::key_type;
using Mapped = typename Data::mapped_type;
using iterator = typename Data::iterator;
using const_iterator = typename Data::const_iterator;
Data data;
AggregationMethodHashed() {}
template <typename Other>
AggregationMethodHashed(const Other & other) : data(other.data) {}
struct State
{
void init(ConstColumnPlainPtrs & key_columns)
{
}
Key getKey(
const ConstColumnPlainPtrs & key_columns,
size_t keys_size,
size_t i,
const Sizes & key_sizes,
StringRefs & keys,
Arena & pool) const
{
return hash128(i, keys_size, key_columns, keys);
}
};
static AggregateDataPtr & getAggregateData(Mapped & value) { return value.second; }
static const AggregateDataPtr & getAggregateData(const Mapped & value) { return value.second; }
static void onNewKey(typename Data::value_type & value, size_t keys_size, size_t i, StringRefs & keys, Arena & pool)
{
value.second.first = placeKeysInPool(i, keys_size, keys, pool);
}
static void onExistingKey(const Key & key, StringRefs & keys, Arena & pool) {}
static const bool no_consecutive_keys_optimization = false;
static void insertKeyIntoColumns(const typename Data::value_type & value, ColumnPlainPtrs & key_columns, size_t keys_size, const Sizes & key_sizes)
{
for (size_t i = 0; i < keys_size; ++i)
key_columns[i]->insertDataWithTerminatingZero(value.second.first[i].data, value.second.first[i].size);
}
};
class Aggregator;
struct AggregatedDataVariants : private boost::noncopyable
{
/** Working with states of aggregate functions in the pool is arranged in the following (inconvenient) way:
* - when aggregating, states are created in the pool using IAggregateFunction::create (inside - `placement new` of arbitrary structure);
* - they must then be destroyed using IAggregateFunction::destroy (inside - calling the destructor of arbitrary structure);
* - if aggregation is complete, then, in the Aggregator::convertToBlocks function, pointers to the states of aggregate functions
* are written to ColumnAggregateFunction; ColumnAggregateFunction "acquires ownership" of them, that is - calls `destroy` in its destructor.
* - if during the aggregation, before call to Aggregator::convertToBlocks, an exception was thrown,
* then the states of aggregate functions must still be destroyed,
* otherwise, for complex states (eg, AggregateFunctionUniq), there will be memory leaks;
* - in this case, to destroy states, the destructor calls Aggregator::destroyAggregateStates method,
* but only if the variable aggregator (see below) is not nullptr;
* - that is, until you transfer ownership of the aggregate function states in the ColumnAggregateFunction, set the variable `aggregator`,
* so that when an exception occurs, the states are correctly destroyed.
*
* PS. This can be corrected by making a pool that knows about which states of aggregate functions and in which order are put in it, and knows how to destroy them.
* But this can hardly be done simply because it is planned to put variable-length strings into the same pool.
* In this case, the pool will not be able to know with what offsets objects are stored.
*/
Aggregator * aggregator = nullptr;
size_t keys_size; /// Number of keys. NOTE do we need this field?
Sizes key_sizes; /// Dimensions of keys, if keys of fixed length
/// Pools for states of aggregate functions. Ownership will be later transferred to ColumnAggregateFunction.
Arenas aggregates_pools;
Arena * aggregates_pool; /// The pool that is currently used for allocation.
/** Specialization for the case when there are no keys, and for keys not fitted into max_rows_to_group_by.
*/
AggregatedDataWithoutKey without_key = nullptr;
std::unique_ptr<AggregationMethodOneNumber<UInt8, AggregatedDataWithUInt8Key>> key8;
std::unique_ptr<AggregationMethodOneNumber<UInt16, AggregatedDataWithUInt16Key>> key16;
std::unique_ptr<AggregationMethodOneNumber<UInt32, AggregatedDataWithUInt64Key>> key32;
std::unique_ptr<AggregationMethodOneNumber<UInt64, AggregatedDataWithUInt64Key>> key64;
std::unique_ptr<AggregationMethodString<AggregatedDataWithStringKey>> key_string;
std::unique_ptr<AggregationMethodFixedString<AggregatedDataWithStringKey>> key_fixed_string;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys128>> keys128;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys256>> keys256;
std::unique_ptr<AggregationMethodHashed<AggregatedDataHashed>> hashed;
std::unique_ptr<AggregationMethodConcat<AggregatedDataWithStringKey>> concat;
std::unique_ptr<AggregationMethodSerialized<AggregatedDataWithStringKey>> serialized;
std::unique_ptr<AggregationMethodOneNumber<UInt32, AggregatedDataWithUInt64KeyTwoLevel>> key32_two_level;
std::unique_ptr<AggregationMethodOneNumber<UInt64, AggregatedDataWithUInt64KeyTwoLevel>> key64_two_level;
std::unique_ptr<AggregationMethodString<AggregatedDataWithStringKeyTwoLevel>> key_string_two_level;
std::unique_ptr<AggregationMethodFixedString<AggregatedDataWithStringKeyTwoLevel>> key_fixed_string_two_level;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys128TwoLevel>> keys128_two_level;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys256TwoLevel>> keys256_two_level;
std::unique_ptr<AggregationMethodHashed<AggregatedDataHashedTwoLevel>> hashed_two_level;
std::unique_ptr<AggregationMethodConcat<AggregatedDataWithStringKeyTwoLevel>> concat_two_level;
std::unique_ptr<AggregationMethodSerialized<AggregatedDataWithStringKeyTwoLevel>> serialized_two_level;
std::unique_ptr<AggregationMethodOneNumber<UInt64, AggregatedDataWithUInt64KeyHash64>> key64_hash64;
std::unique_ptr<AggregationMethodString<AggregatedDataWithStringKeyHash64>> key_string_hash64;
std::unique_ptr<AggregationMethodFixedString<AggregatedDataWithStringKeyHash64>> key_fixed_string_hash64;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys128Hash64>> keys128_hash64;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys256Hash64>> keys256_hash64;
std::unique_ptr<AggregationMethodConcat<AggregatedDataWithStringKeyHash64>> concat_hash64;
std::unique_ptr<AggregationMethodSerialized<AggregatedDataWithStringKeyHash64>> serialized_hash64;
/// Support for nullable keys.
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys128, true>> nullable_keys128;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys256, true>> nullable_keys256;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys128TwoLevel, true>> nullable_keys128_two_level;
std::unique_ptr<AggregationMethodKeysFixed<AggregatedDataWithKeys256TwoLevel, true>> nullable_keys256_two_level;
/// In this and similar macros, the option without_key is not considered.
#define APPLY_FOR_AGGREGATED_VARIANTS(M) \
M(key8, false) \
M(key16, false) \
M(key32, false) \
M(key64, false) \
M(key_string, false) \
M(key_fixed_string, false) \
M(keys128, false) \
M(keys256, false) \
M(hashed, false) \
M(concat, false) \
M(serialized, false) \
M(key32_two_level, true) \
M(key64_two_level, true) \
M(key_string_two_level, true) \
M(key_fixed_string_two_level, true) \
M(keys128_two_level, true) \
M(keys256_two_level, true) \
M(hashed_two_level, true) \
M(concat_two_level, true) \
M(serialized_two_level, true) \
M(key64_hash64, false) \
M(key_string_hash64, false) \
M(key_fixed_string_hash64, false) \
M(keys128_hash64, false) \
M(keys256_hash64, false) \
M(concat_hash64, false) \
M(serialized_hash64, false) \
M(nullable_keys128, false) \
M(nullable_keys256, false) \
M(nullable_keys128_two_level, true) \
M(nullable_keys256_two_level, true) \
enum class Type
{
EMPTY = 0,
without_key,
#define M(NAME, IS_TWO_LEVEL) NAME,
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
};
Type type = Type::EMPTY;
AggregatedDataVariants() : aggregates_pools(1, std::make_shared<Arena>()), aggregates_pool(aggregates_pools.back().get()) {}
bool empty() const { return type == Type::EMPTY; }
void invalidate() { type = Type::EMPTY; }
~AggregatedDataVariants();
void init(Type type_)
{
switch (type_)
{
case Type::EMPTY: break;
case Type::without_key: break;
#define M(NAME, IS_TWO_LEVEL) \
case Type::NAME: NAME = std::make_unique<decltype(NAME)::element_type>(); break;
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
default:
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
}
type = type_;
}
/// Number of rows (different keys).
size_t size() const
{
switch (type)
{
case Type::EMPTY: return 0;
case Type::without_key: return 1;
#define M(NAME, IS_TWO_LEVEL) \
case Type::NAME: return NAME->data.size() + (without_key != nullptr);
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
default:
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
}
}
/// The size without taking into account the row in which data is written for the calculation of TOTALS.
size_t sizeWithoutOverflowRow() const
{
switch (type)
{
case Type::EMPTY: return 0;
case Type::without_key: return 1;
#define M(NAME, IS_TWO_LEVEL) \
case Type::NAME: return NAME->data.size();
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
default:
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
}
}
const char * getMethodName() const
{
switch (type)
{
case Type::EMPTY: return "EMPTY";
case Type::without_key: return "without_key";
#define M(NAME, IS_TWO_LEVEL) \
case Type::NAME: return #NAME;
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
default:
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
}
}
bool isTwoLevel() const
{
switch (type)
{
case Type::EMPTY: return false;
case Type::without_key: return false;
#define M(NAME, IS_TWO_LEVEL) \
case Type::NAME: return IS_TWO_LEVEL;
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
default:
throw Exception("Unknown aggregated data variant.", ErrorCodes::UNKNOWN_AGGREGATED_DATA_VARIANT);
}
}
#define APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M) \
M(key32) \
M(key64) \
M(key_string) \
M(key_fixed_string) \
M(keys128) \
M(keys256) \
M(hashed) \
M(concat) \
M(serialized) \
M(nullable_keys128) \
M(nullable_keys256) \
#define APPLY_FOR_VARIANTS_NOT_CONVERTIBLE_TO_TWO_LEVEL(M) \
M(key8) \
M(key16) \
M(key64_hash64) \
M(key_string_hash64) \
M(key_fixed_string_hash64) \
M(keys128_hash64) \
M(keys256_hash64) \
M(concat_hash64) \
M(serialized_hash64) \
#define APPLY_FOR_VARIANTS_SINGLE_LEVEL(M) \
APPLY_FOR_VARIANTS_NOT_CONVERTIBLE_TO_TWO_LEVEL(M) \
APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M) \
bool isConvertibleToTwoLevel() const
{
switch (type)
{
#define M(NAME) \
case Type::NAME: return true;
APPLY_FOR_VARIANTS_CONVERTIBLE_TO_TWO_LEVEL(M)
#undef M
default:
return false;
}
}
void convertToTwoLevel();
#define APPLY_FOR_VARIANTS_TWO_LEVEL(M) \
M(key32_two_level) \
M(key64_two_level) \
M(key_string_two_level) \
M(key_fixed_string_two_level) \
M(keys128_two_level) \
M(keys256_two_level) \
M(hashed_two_level) \
M(concat_two_level) \
M(serialized_two_level) \
M(nullable_keys128_two_level) \
M(nullable_keys256_two_level)
};
using AggregatedDataVariantsPtr = std::shared_ptr<AggregatedDataVariants>;
using ManyAggregatedDataVariants = std::vector<AggregatedDataVariantsPtr>;
/** How are "total" values calculated with WITH TOTALS?
* (For more details, see TotalsHavingBlockInputStream.)
*
* In the absence of group_by_overflow_mode = 'any', the data is aggregated as usual, but the states of the aggregate functions are not finalized.
* Later, the aggregate function states for all rows (passed through HAVING) are merged into one - this will be TOTALS.
*
* If there is group_by_overflow_mode = 'any', the data is aggregated as usual, except for the keys that did not fit in max_rows_to_group_by.
* For these keys, the data is aggregated into one additional row - see below under the names `overflow_row`, `overflows`...
* Later, the aggregate function states for all rows (passed through HAVING) are merged into one,
* also overflow_row is added or not added (depending on the totals_mode setting) also - this will be TOTALS.
*/
/** Aggregates the source of the blocks.
*/
class Aggregator
{
public:
struct Params
{
/// What to count.
Names key_names;
ColumnNumbers keys; /// The column numbers are computed later.
AggregateDescriptions aggregates;
size_t keys_size;
size_t aggregates_size;
/// The settings of approximate calculation of GROUP BY.
const bool overflow_row; /// Do we need to put into AggregatedDataVariants::without_key aggregates for keys that are not in max_rows_to_group_by.
const size_t max_rows_to_group_by;
const OverflowMode group_by_overflow_mode;
/// For dynamic compilation.
Compiler * compiler;
const UInt32 min_count_to_compile;
/// Two-level aggregation settings (used for a large number of keys).
/** With how many keys or the size of the aggregation state in bytes,
* two-level aggregation begins to be used. Enough to reach of at least one of the thresholds.
* 0 - the corresponding threshold is not specified.
*/
const size_t group_by_two_level_threshold;
const size_t group_by_two_level_threshold_bytes;
/// Settings to flush temporary data to the filesystem (external aggregation).
const size_t max_bytes_before_external_group_by; /// 0 - do not use external aggregation.
const std::string tmp_path;
Params(
const Names & key_names_, const AggregateDescriptions & aggregates_,
bool overflow_row_, size_t max_rows_to_group_by_, OverflowMode group_by_overflow_mode_,
Compiler * compiler_, UInt32 min_count_to_compile_,
size_t group_by_two_level_threshold_, size_t group_by_two_level_threshold_bytes_,
size_t max_bytes_before_external_group_by_, const std::string & tmp_path_)
: key_names(key_names_), aggregates(aggregates_), aggregates_size(aggregates.size()),
overflow_row(overflow_row_), max_rows_to_group_by(max_rows_to_group_by_), group_by_overflow_mode(group_by_overflow_mode_),
compiler(compiler_), min_count_to_compile(min_count_to_compile_),
group_by_two_level_threshold(group_by_two_level_threshold_), group_by_two_level_threshold_bytes(group_by_two_level_threshold_bytes_),
max_bytes_before_external_group_by(max_bytes_before_external_group_by_), tmp_path(tmp_path_)
{
std::sort(key_names.begin(), key_names.end());
key_names.erase(std::unique(key_names.begin(), key_names.end()), key_names.end());
keys_size = key_names.size();
}
/// Only parameters that matter during merge.
Params(const Names & key_names_, const AggregateDescriptions & aggregates_, bool overflow_row_)
: Params(key_names_, aggregates_, overflow_row_, 0, OverflowMode::THROW, nullptr, 0, 0, 0, 0, "") {}
/// Compute the column numbers in `keys` and `aggregates`.
void calculateColumnNumbers(const Block & block);
};
Aggregator(const Params & params_)
: params(params_),
isCancelled([]() { return false; })
{
}
/// Aggregate the source. Get the result in the form of one of the data structures.
void execute(BlockInputStreamPtr stream, AggregatedDataVariants & result);
using AggregateColumns = std::vector<ConstColumnPlainPtrs>;
using AggregateColumnsData = std::vector<ColumnAggregateFunction::Container_t *>;
using AggregateFunctionsPlainPtrs = std::vector<IAggregateFunction *>;
/// Process one block. Return false if the processing should be aborted (with group_by_overflow_mode = 'break').
bool executeOnBlock(Block & block, AggregatedDataVariants & result,
ConstColumnPlainPtrs & key_columns, AggregateColumns & aggregate_columns, /// Passed to not create them anew for each block
Sizes & key_sizes, StringRefs & keys, /// - pass the corresponding objects that are initially empty.
bool & no_more_keys);
/** Convert the aggregation data structure into a block.
* If overflow_row = true, then aggregates for rows that are not included in max_rows_to_group_by are put in the first block.
*
* If final = false, then ColumnAggregateFunction is created as the aggregation columns with the state of the calculations,
* which can then be combined with other states (for distributed query processing).
* If final = true, then columns with ready values are created as aggregate columns.
*/
BlocksList convertToBlocks(AggregatedDataVariants & data_variants, bool final, size_t max_threads) const;
/** Merge several aggregation data structures and output the result as a block stream.
*/
std::unique_ptr<IBlockInputStream> mergeAndConvertToBlocks(ManyAggregatedDataVariants & data_variants, bool final, size_t max_threads) const;
/** Merge the stream of partially aggregated blocks into one data structure.
* (Pre-aggregate several blocks that represent the result of independent aggregations from remote servers.)
*/
void mergeStream(BlockInputStreamPtr stream, AggregatedDataVariants & result, size_t max_threads);
/// Merge several partially aggregated blocks into one.
/// Precondition: for all blocks block.info.is_overflows flag must be the same.
/// (either all blocks are from overflow data or none blocks are).
/// The resulting block has the same value of is_overflows flag.
Block mergeBlocks(BlocksList & blocks, bool final);
/** Split block with partially-aggregated data to many blocks, as if two-level method of aggregation was used.
* This is needed to simplify merging of that data with other results, that are already two-level.
*/
std::vector<Block> convertBlockToTwoLevel(const Block & block);
using CancellationHook = std::function<bool()>;
/** Set a function that checks whether the current task can be aborted.
*/
void setCancellationHook(const CancellationHook cancellation_hook);
/// For IBlockInputStream.
String getID() const;
/// For external aggregation.
void writeToTemporaryFile(AggregatedDataVariants & data_variants);
bool hasTemporaryFiles() const { return !temporary_files.empty(); }
struct TemporaryFiles
{
std::vector<std::unique_ptr<Poco::TemporaryFile>> files;
size_t sum_size_uncompressed = 0;
size_t sum_size_compressed = 0;
mutable std::mutex mutex;
bool empty() const
{
std::lock_guard<std::mutex> lock(mutex);
return files.empty();
}
};
const TemporaryFiles & getTemporaryFiles() const { return temporary_files; }
protected:
friend struct AggregatedDataVariants;
friend class MergingAndConvertingBlockInputStream;
Params params;
AggregateFunctionsPlainPtrs aggregate_functions;
/** This array serves two purposes.
*
* 1. Function arguments are collected side by side, and they do not need to be collected from different places. Also the array is made zero-terminated.
* The inner loop (for the case without_key) is almost twice as compact; performance gain of about 30%.
*
* 2. Calling a function by pointer is better than a virtual call, because in the case of a virtual call,
* GCC 5.1.2 generates code that, at each iteration of the loop, reloads the function address from memory into the register
* (the offset value in the virtual function table).
*/
struct AggregateFunctionInstruction
{
const IAggregateFunction * that;
IAggregateFunction::AddFunc func;
size_t state_offset;
const IColumn ** arguments;
};
using AggregateFunctionInstructions = std::vector<AggregateFunctionInstruction>;
Sizes offsets_of_aggregate_states; /// The offset to the n-th aggregate function in a row of aggregate functions.
size_t total_size_of_aggregate_states = 0; /// The total size of the row from the aggregate functions.
bool all_aggregates_has_trivial_destructor = false;
/// How many RAM were used to process the query before processing the first block.
Int64 memory_usage_before_aggregation = 0;
/// To initialize from the first block when used concurrently.
bool initialized = false;
std::mutex mutex;
Block sample;
Logger * log = &Logger::get("Aggregator");
/** Dynamically compiled library for aggregation, if any.
* The meaning of dynamic compilation is to specialize code
* for a specific list of aggregate functions.
* This allows you to expand the loop to create and update states of aggregate functions,
* and also use inline-code instead of virtual calls.
*/
struct CompiledData
{
SharedLibraryPtr compiled_aggregator;
/// Obtained with dlsym. It is still necessary to make reinterpret_cast to the function pointer.
void * compiled_method_ptr = nullptr;
void * compiled_two_level_method_ptr = nullptr;
};
/// shared_ptr - to pass into a callback, that can survive Aggregator.
std::shared_ptr<CompiledData> compiled_data { new CompiledData };
bool compiled_if_possible = false;
void compileIfPossible(AggregatedDataVariants::Type type);
/// Returns true if you can abort the current task.
CancellationHook isCancelled;
/// For external aggregation.
TemporaryFiles temporary_files;
/** If only the column names (key_names, and also aggregates[i].column_name) are specified, then calculate the column numbers.
* Generate block - sample of the result. It is used in the convertToBlocks, mergeAndConvertToBlocks methods.
*/
void initialize(const Block & block);
/** Set the block - sample of the result,
* only if it has not already been set.
*/
void setSampleBlock(const Block & block);
/** Select the aggregation method based on the number and types of keys. */
AggregatedDataVariants::Type chooseAggregationMethod(const ConstColumnPlainPtrs & key_columns, Sizes & key_sizes) const;
/** Create states of aggregate functions for one key.
*/
void createAggregateStates(AggregateDataPtr & aggregate_data) const;
/** Call `destroy` methods for states of aggregate functions.
* Used in the exception handler for aggregation, since RAII in this case is not applicable.
*/
void destroyAllAggregateStates(AggregatedDataVariants & result);
/// Process one data block, aggregate the data into a hash table.
template <typename Method>
void executeImpl(
Method & method,
Arena * aggregates_pool,
size_t rows,
ConstColumnPlainPtrs & key_columns,
AggregateFunctionInstruction * aggregate_instructions,
const Sizes & key_sizes,
StringRefs & keys,
bool no_more_keys,
AggregateDataPtr overflow_row) const;
/// Specialization for a particular value no_more_keys.
template <bool no_more_keys, typename Method>
void executeImplCase(
Method & method,
typename Method::State & state,
Arena * aggregates_pool,
size_t rows,
ConstColumnPlainPtrs & key_columns,
AggregateFunctionInstruction * aggregate_instructions,
const Sizes & key_sizes,
StringRefs & keys,
AggregateDataPtr overflow_row) const;
/// For case when there are no keys (all aggregate into one row).
void executeWithoutKeyImpl(
AggregatedDataWithoutKey & res,
size_t rows,
AggregateFunctionInstruction * aggregate_instructions,
Arena * arena) const;
template <typename Method>
void writeToTemporaryFileImpl(
AggregatedDataVariants & data_variants,
Method & method,
IBlockOutputStream & out,
const String & path);
public:
/// Templates that are instantiated by dynamic code compilation - see SpecializedAggregator.h
template <typename Method, typename AggregateFunctionsList>
void executeSpecialized(
Method & method,
Arena * aggregates_pool,
size_t rows,
ConstColumnPlainPtrs & key_columns,
AggregateColumns & aggregate_columns,
const Sizes & key_sizes,
StringRefs & keys,
bool no_more_keys,
AggregateDataPtr overflow_row) const;
template <bool no_more_keys, typename Method, typename AggregateFunctionsList>
void executeSpecializedCase(
Method & method,
typename Method::State & state,
Arena * aggregates_pool,
size_t rows,
ConstColumnPlainPtrs & key_columns,
AggregateColumns & aggregate_columns,
const Sizes & key_sizes,
StringRefs & keys,
AggregateDataPtr overflow_row) const;
template <typename AggregateFunctionsList>
void executeSpecializedWithoutKey(
AggregatedDataWithoutKey & res,
size_t rows,
AggregateColumns & aggregate_columns,
Arena * arena) const;
protected:
/// Merge data from hash table `src` into `dst`.
template <typename Method, typename Table>
void mergeDataImpl(
Table & table_dst,
Table & table_src,
Arena * arena) const;
/// Merge data from hash table `src` into `dst`, but only for keys that already exist in dst. In other cases, merge the data into `overflows`.
template <typename Method, typename Table>
void mergeDataNoMoreKeysImpl(
Table & table_dst,
AggregatedDataWithoutKey & overflows,
Table & table_src,
Arena * arena) const;
/// Same, but ignores the rest of the keys.
template <typename Method, typename Table>
void mergeDataOnlyExistingKeysImpl(
Table & table_dst,
Table & table_src,
Arena * arena) const;
void mergeWithoutKeyDataImpl(
ManyAggregatedDataVariants & non_empty_data) const;
template <typename Method>
void mergeSingleLevelDataImpl(
ManyAggregatedDataVariants & non_empty_data) const;
template <typename Method, typename Table>
void convertToBlockImpl(
Method & method,
Table & data,
ColumnPlainPtrs & key_columns,
AggregateColumnsData & aggregate_columns,
ColumnPlainPtrs & final_aggregate_columns,
const Sizes & key_sizes,
bool final) const;
template <typename Method, typename Table>
void convertToBlockImplFinal(
Method & method,
Table & data,
ColumnPlainPtrs & key_columns,
ColumnPlainPtrs & final_aggregate_columns,
const Sizes & key_sizes) const;
template <typename Method, typename Table>
void convertToBlockImplNotFinal(
Method & method,
Table & data,
ColumnPlainPtrs & key_columns,
AggregateColumnsData & aggregate_columns,
const Sizes & key_sizes) const;
template <typename Filler>
Block prepareBlockAndFill(
AggregatedDataVariants & data_variants,
bool final,
size_t rows,
Filler && filler) const;
template <typename Method>
Block convertOneBucketToBlock(
AggregatedDataVariants & data_variants,
Method & method,
bool final,
size_t bucket) const;
Block prepareBlockAndFillWithoutKey(AggregatedDataVariants & data_variants, bool final, bool is_overflows) const;
Block prepareBlockAndFillSingleLevel(AggregatedDataVariants & data_variants, bool final) const;
BlocksList prepareBlocksAndFillTwoLevel(AggregatedDataVariants & data_variants, bool final, ThreadPool * thread_pool) const;
template <typename Method>
BlocksList prepareBlocksAndFillTwoLevelImpl(
AggregatedDataVariants & data_variants,
Method & method,
bool final,
ThreadPool * thread_pool) const;
template <bool no_more_keys, typename Method, typename Table>
void mergeStreamsImplCase(
Block & block,
const Sizes & key_sizes,
Arena * aggregates_pool,
Method & method,
Table & data,
AggregateDataPtr overflow_row) const;
template <typename Method, typename Table>
void mergeStreamsImpl(
Block & block,
const Sizes & key_sizes,
Arena * aggregates_pool,
Method & method,
Table & data,
AggregateDataPtr overflow_row,
bool no_more_keys) const;
void mergeWithoutKeyStreamsImpl(
Block & block,
AggregatedDataVariants & result) const;
template <typename Method>
void mergeBucketImpl(
ManyAggregatedDataVariants & data, Int32 bucket, Arena * arena) const;
template <typename Method>
void convertBlockToTwoLevelImpl(
Method & method,
Arena * pool,
ConstColumnPlainPtrs & key_columns,
const Sizes & key_sizes,
StringRefs & keys,
const Block & source,
std::vector<Block> & destinations) const;
template <typename Method, typename Table>
void destroyImpl(
Method & method,
Table & table) const;
void destroyWithoutKey(
AggregatedDataVariants & result) const;
/** Checks constraints on the maximum number of keys for aggregation.
* If it is exceeded, then, depending on the group_by_overflow_mode, either
* - throws an exception;
* - returns false, which means that execution must be aborted;
* - sets the variable no_more_keys to true.
*/
bool checkLimits(size_t result_size, bool & no_more_keys) const;
};
/** Get the aggregation variant by its type. */
template <typename Method> Method & getDataVariant(AggregatedDataVariants & variants);
#define M(NAME, IS_TWO_LEVEL) \
template <> inline decltype(AggregatedDataVariants::NAME)::element_type & getDataVariant<decltype(AggregatedDataVariants::NAME)::element_type>(AggregatedDataVariants & variants) { return *variants.NAME; }
APPLY_FOR_AGGREGATED_VARIANTS(M)
#undef M
}