Files
doris/be/src/vec/columns/column.h
Pxl 5e4bb98900 [Chore](build) enable -Wpedantic and update lowest gcc version to 11.1 (#16290)
enable -Wpedantic and update lowest gcc version to 11.1
2023-02-03 11:28:48 +08:00

710 lines
32 KiB
C++

// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
// This file is copied from
// https://github.com/ClickHouse/ClickHouse/blob/master/src/Columns/IColumn.h
// and modified by Doris
#pragma once
#include "olap/olap_common.h"
#include "runtime/define_primitive_type.h"
#include "vec/common/cow.h"
#include "vec/common/pod_array_fwd.h"
#include "vec/common/string_ref.h"
#include "vec/common/typeid_cast.h"
#include "vec/core/field.h"
#include "vec/core/types.h"
class SipHash;
#define SIP_HASHES_FUNCTION_COLUMN_IMPL() \
auto s = hashes.size(); \
DCHECK(s == size()); \
if (null_data == nullptr) { \
for (size_t i = 0; i < s; i++) { \
update_hash_with_value(i, hashes[i]); \
} \
} else { \
for (size_t i = 0; i < s; i++) { \
if (null_data[i] == 0) update_hash_with_value(i, hashes[i]); \
} \
}
#define DO_CRC_HASHES_FUNCTION_COLUMN_IMPL() \
if (null_data == nullptr) { \
for (size_t i = 0; i < s; i++) { \
hashes[i] = HashUtil::zlib_crc_hash(&data[i], sizeof(T), hashes[i]); \
} \
} else { \
for (size_t i = 0; i < s; i++) { \
if (null_data[i] == 0) \
hashes[i] = HashUtil::zlib_crc_hash(&data[i], sizeof(T), hashes[i]); \
} \
}
namespace doris::vectorized {
class Arena;
class Field;
class ColumnSorter;
using EqualFlags = std::vector<uint8_t>;
using EqualRange = std::pair<int, int>;
/// Declares interface to store columns in memory.
class IColumn : public COW<IColumn> {
private:
friend class COW<IColumn>;
/// Creates the same column with the same data.
/// This is internal method to use from COW.
/// It performs shallow copy with copy-ctor and not useful from outside.
/// If you want to copy column for modification, look at 'mutate' method.
virtual MutablePtr clone() const = 0;
protected:
// 64bit offsets now only Array type used, so we make it protected
// to avoid use IColumn::Offset64 directly.
// please use ColumnArray::Offset64 instead if we need.
using Offset64 = UInt64;
using Offsets64 = PaddedPODArray<Offset64>;
public:
// 32bit offsets for string
using Offset = UInt32;
using Offsets = PaddedPODArray<Offset>;
/// Name of a Column. It is used in info messages.
virtual std::string get_name() const { return get_family_name(); }
/// Name of a Column kind, without parameters (example: FixedString, Array).
virtual const char* get_family_name() const = 0;
/** If column isn't constant, returns nullptr (or itself).
* If column is constant, transforms constant to full column (if column type allows such transform) and return it.
*/
virtual Ptr convert_to_full_column_if_const() const { return get_ptr(); }
/// If column isn't ColumnLowCardinality, return itself.
/// If column is ColumnLowCardinality, transforms is to full column.
virtual Ptr convert_to_full_column_if_low_cardinality() const { return get_ptr(); }
/// If column isn't ColumnDictionary, return itself.
/// If column is ColumnDictionary, transforms is to predicate column.
virtual MutablePtr convert_to_predicate_column_if_dictionary() { return get_ptr(); }
/// If column is ColumnDictionary, and is a range comparison predicate, convert dict encoding
virtual void convert_dict_codes_if_necessary() {}
/// If column is ColumnDictionary, and is a bloom filter predicate, generate_hash_values
virtual void generate_hash_values_for_runtime_filter() {}
/// Creates empty column with the same type.
virtual MutablePtr clone_empty() const { return clone_resized(0); }
/// Creates column with the same type and specified size.
/// If size is less current size, then data is cut.
/// If size is greater, than default values are appended.
virtual MutablePtr clone_resized(size_t s) const {
LOG(FATAL) << "Cannot clone_resized() column " << get_name();
return nullptr;
}
// shrink the end zeros for CHAR type or ARRAY<CHAR> type
virtual MutablePtr get_shrinked_column() {
LOG(FATAL) << "Cannot clone_resized() column " << get_name();
return nullptr;
}
// Only used on ColumnDictionary
virtual void set_rowset_segment_id(std::pair<RowsetId, uint32_t> rowset_segment_id) {}
virtual std::pair<RowsetId, uint32_t> get_rowset_segment_id() const { return {}; }
/// Returns number of values in column.
virtual size_t size() const = 0;
/// There are no values in columns.
bool empty() const { return size() == 0; }
/// Returns value of n-th element in universal Field representation.
/// Is used in rare cases, since creation of Field instance is expensive usually.
virtual Field operator[](size_t n) const = 0;
/// Like the previous one, but avoids extra copying if Field is in a container, for example.
virtual void get(size_t n, Field& res) const = 0;
/// If possible, returns pointer to memory chunk which contains n-th element (if it isn't possible, throws an exception)
/// Is used to optimize some computations (in aggregation, for example).
virtual StringRef get_data_at(size_t n) const = 0;
/// If column stores integers, it returns n-th element transformed to UInt64 using static_cast.
/// If column stores floating point numbers, bits of n-th elements are copied to lower bits of UInt64, the remaining bits are zeros.
/// Is used to optimize some computations (in aggregation, for example).
virtual UInt64 get64(size_t /*n*/) const {
LOG(FATAL) << "Method get64 is not supported for ";
return 0;
}
/// If column stores native numeric type, it returns n-th element casted to Float64
/// Is used in regression methods to cast each features into uniform type
virtual Float64 get_float64(size_t /*n*/) const {
LOG(FATAL) << "Method get_float64 is not supported for " << get_name();
return 0;
}
/** If column is numeric, return value of n-th element, casted to UInt64.
* For NULL values of Nullable column it is allowed to return arbitrary value.
* Otherwise throw an exception.
*/
virtual UInt64 get_uint(size_t /*n*/) const {
LOG(FATAL) << "Method get_uint is not supported for " << get_name();
return 0;
}
virtual Int64 get_int(size_t /*n*/) const {
LOG(FATAL) << "Method get_int is not supported for " << get_name();
return 0;
}
virtual bool is_default_at(size_t n) const { return get64(n) == 0; }
virtual bool is_null_at(size_t /*n*/) const { return false; }
/** If column is numeric, return value of n-th element, casted to bool.
* For NULL values of Nullable column returns false.
* Otherwise throw an exception.
*/
virtual bool get_bool(size_t /*n*/) const {
LOG(FATAL) << "Method get_bool is not supported for " << get_name();
return false;
}
/// Removes all elements outside of specified range.
/// Is used in LIMIT operation, for example.
virtual Ptr cut(size_t start, size_t length) const {
MutablePtr res = clone_empty();
res->insert_range_from(*this, start, length);
return res;
}
/// Appends new value at the end of column (column's size is increased by 1).
/// Is used to transform raw strings to Blocks (for example, inside input format parsers)
virtual void insert(const Field& x) = 0;
/// Appends n-th element from other column with the same type.
/// Is used in merge-sort and merges. It could be implemented in inherited classes more optimally than default implementation.
virtual void insert_from(const IColumn& src, size_t n);
/// Appends range of elements from other column with the same type.
/// Could be used to concatenate columns.
virtual void insert_range_from(const IColumn& src, size_t start, size_t length) = 0;
/// Appends one element from other column with the same type multiple times.
virtual void insert_many_from(const IColumn& src, size_t position, size_t length) {
for (size_t i = 0; i < length; ++i) {
insert_from(src, position);
}
}
/// Appends a batch elements from other column with the same type
/// indices_begin + indices_end represent the row indices of column src
/// Warning:
/// if *indices == -1 means the row is null, only use in outer join, do not use in any other place
virtual void insert_indices_from(const IColumn& src, const int* indices_begin,
const int* indices_end) = 0;
/// Appends data located in specified memory chunk if it is possible (throws an exception if it cannot be implemented).
/// Is used to optimize some computations (in aggregation, for example).
/// Parameter length could be ignored if column values have fixed size.
/// All data will be inserted as single element
virtual void insert_data(const char* pos, size_t length) = 0;
virtual void insert_many_fix_len_data(const char* pos, size_t num) {
LOG(FATAL) << "Method insert_many_fix_len_data is not supported for " << get_name();
}
// todo(zeno) Use dict_args temp object to cover all arguments
virtual void insert_many_dict_data(const int32_t* data_array, size_t start_index,
const StringRef* dict, size_t data_num,
uint32_t dict_num = 0) {
LOG(FATAL) << "Method insert_many_dict_data is not supported for " << get_name();
}
virtual void insert_many_binary_data(char* data_array, uint32_t* len_array,
uint32_t* start_offset_array, size_t num) {
LOG(FATAL) << "Method insert_many_binary_data is not supported for " << get_name();
}
/// Insert binary data into column from a continuous buffer, the implementation maybe copy all binary data
/// in one single time.
virtual void insert_many_continuous_binary_data(const char* data, const uint32_t* offsets,
const size_t num) {
LOG(FATAL) << "Method insert_many_continuous_binary_data is not supported for "
<< get_name();
}
virtual void insert_many_strings(const StringRef* strings, size_t num) {
LOG(FATAL) << "Method insert_many_binary_data is not supported for " << get_name();
}
// Here `pos` points to the memory data type is the same as the data type of the column.
// This function is used by `insert_keys_into_columns` in AggregationNode.
virtual void insert_many_raw_data(const char* pos, size_t num) {
LOG(FATAL) << "Method insert_many_raw_data is not supported for " << get_name();
}
void insert_many_data(const char* pos, size_t length, size_t data_num) {
for (size_t i = 0; i < data_num; ++i) {
insert_data(pos, length);
}
}
/// Appends "default value".
/// Is used when there are need to increase column size, but inserting value doesn't make sense.
/// For example, ColumnNullable(Nested) absolutely ignores values of nested column if it is marked as NULL.
virtual void insert_default() = 0;
/// Appends "default value" multiple times.
virtual void insert_many_defaults(size_t length) {
for (size_t i = 0; i < length; ++i) {
insert_default();
}
}
/** Removes last n elements.
* Is used to support exception-safety of several operations.
* For example, sometimes insertion should be reverted if we catch an exception during operation processing.
* If column has less than n elements or n == 0 - undefined behavior.
*/
virtual void pop_back(size_t n) = 0;
/** Serializes n-th element. Serialized element should be placed continuously inside Arena's memory.
* Serialized value can be deserialized to reconstruct original object. Is used in aggregation.
* The method is similar to get_data_at(), but can work when element's value cannot be mapped to existing continuous memory chunk,
* For example, to obtain unambiguous representation of Array of strings, strings data should be interleaved with their sizes.
* Parameter begin should be used with Arena::alloc_continue.
*/
virtual StringRef serialize_value_into_arena(size_t n, Arena& arena,
char const*& begin) const = 0;
/// Deserializes a value that was serialized using IColumn::serialize_value_into_arena method.
/// Returns pointer to the position after the read data.
virtual const char* deserialize_and_insert_from_arena(const char* pos) = 0;
/// Return the size of largest row.
/// This is for calculating the memory size for vectorized serialization of aggregation keys.
virtual size_t get_max_row_byte_size() const {
LOG(FATAL) << "get_max_row_byte_size not supported";
return 0;
}
virtual void serialize_vec(std::vector<StringRef>& keys, size_t num_rows,
size_t max_row_byte_size) const {
LOG(FATAL) << "serialize_vec not supported";
}
virtual void serialize_vec_with_null_map(std::vector<StringRef>& keys, size_t num_rows,
const uint8_t* null_map,
size_t max_row_byte_size) const {
LOG(FATAL) << "serialize_vec_with_null_map not supported";
}
// This function deserializes group-by keys into column in the vectorized way.
virtual void deserialize_vec(std::vector<StringRef>& keys, const size_t num_rows) {
LOG(FATAL) << "deserialize_vec not supported";
}
// Used in ColumnNullable::deserialize_vec
virtual void deserialize_vec_with_null_map(std::vector<StringRef>& keys, const size_t num_rows,
const uint8_t* null_map) {
LOG(FATAL) << "deserialize_vec_with_null_map not supported";
}
/// TODO: SipHash is slower than city or xx hash, rethink we should have a new interface
/// Update state of hash function with value of n-th element.
/// On subsequent calls of this method for sequence of column values of arbitrary types,
/// passed bytes to hash must identify sequence of values unambiguously.
virtual void update_hash_with_value(size_t n, SipHash& hash) const {
LOG(FATAL) << "update_hash_with_value siphash not supported";
}
/// Update state of hash function with value of n elements to avoid the virtual function call
/// null_data to mark whether need to do hash compute, null_data == nullptr
/// means all element need to do hash function, else only *null_data != 0 need to do hash func
/// do xxHash here, faster than other hash method
virtual void update_hashes_with_value(std::vector<SipHash>& hashes,
const uint8_t* __restrict null_data = nullptr) const {
LOG(FATAL) << "update_hashes_with_value siphash not supported";
}
/// Update state of hash function with value of n elements to avoid the virtual function call
/// null_data to mark whether need to do hash compute, null_data == nullptr
/// means all element need to do hash function, else only *null_data != 0 need to do hash func
/// do xxHash here, faster than other sip hash
virtual void update_hashes_with_value(uint64_t* __restrict hashes,
const uint8_t* __restrict null_data = nullptr) const {
LOG(FATAL) << "update_hashes_with_value xxhash not supported";
}
/// Update state of crc32 hash function with value of n elements to avoid the virtual function call
/// null_data to mark whether need to do hash compute, null_data == nullptr
/// means all element need to do hash function, else only *null_data != 0 need to do hash func
virtual void update_crcs_with_value(std::vector<uint64_t>& hash, PrimitiveType type,
const uint8_t* __restrict null_data = nullptr) const {
LOG(FATAL) << "update_crcs_with_value not supported";
}
/** Removes elements that don't match the filter.
* Is used in WHERE and HAVING operations.
* If result_size_hint > 0, then makes advance reserve(result_size_hint) for the result column;
* if 0, then don't makes reserve(),
* otherwise (i.e. < 0), makes reserve() using size of source column.
*/
using Filter = PaddedPODArray<UInt8>;
virtual Ptr filter(const Filter& filt, ssize_t result_size_hint) const = 0;
/**
* used by lazy materialization to filter column by selected rowids
* Q: Why use IColumn* as args type instead of MutablePtr or ImmutablePtr ?
* A: If use MutablePtr/ImmutablePtr as col_ptr's type, which means there could be many
* convert(convert MutablePtr to ImmutablePtr or convert ImmutablePtr to MutablePtr)
* happends in filter_by_selector because of mem-reuse logic or ColumnNullable, I think this is meaningless;
* So using raw ptr directly here.
*/
virtual Status filter_by_selector(const uint16_t* sel, size_t sel_size, IColumn* col_ptr) {
LOG(FATAL) << "column not support filter_by_selector";
__builtin_unreachable();
}
/// Permutes elements using specified permutation. Is used in sortings.
/// limit - if it isn't 0, puts only first limit elements in the result.
using Permutation = PaddedPODArray<size_t>;
virtual Ptr permute(const Permutation& perm, size_t limit) const = 0;
/// Creates new column with values column[indexes[:limit]]. If limit is 0, all indexes are used.
/// Indexes must be one of the ColumnUInt. For default implementation, see select_index_impl from ColumnsCommon.h
// virtual Ptr index(const IColumn & indexes, size_t limit) const = 0;
/** Compares (*this)[n] and rhs[m]. Column rhs should have the same type.
* Returns negative number, 0, or positive number (*this)[n] is less, equal, greater than rhs[m] respectively.
* Is used in sortings.
*
* If one of element's value is NaN or NULLs, then:
* - if nan_direction_hint == -1, NaN and NULLs are considered as least than everything other;
* - if nan_direction_hint == 1, NaN and NULLs are considered as greatest than everything other.
* For example, if nan_direction_hint == -1 is used by descending sorting, NaNs will be at the end.
*
* For non Nullable and non floating point types, nan_direction_hint is ignored.
*/
virtual int compare_at(size_t n, size_t m, const IColumn& rhs,
int nan_direction_hint) const = 0;
/**
* To compare all rows in this column with another row (with row_id = rhs_row_id in column rhs)
* @param nan_direction_hint and direction indicates the ordering.
* @param cmp_res if we already has a comparison result for row i, e.g. cmp_res[i] = 1, we can skip row i
* @param filter this stores comparison results for all rows. filter[i] = 1 means row i is less than row rhs_row_id in rhs
*/
virtual void compare_internal(size_t rhs_row_id, const IColumn& rhs, int nan_direction_hint,
int direction, std::vector<uint8>& cmp_res,
uint8* __restrict filter) const;
/** Returns a permutation that sorts elements of this column,
* i.e. perm[i]-th element of source column should be i-th element of sorted column.
* reverse - reverse ordering (ascending).
* limit - if isn't 0, then only first limit elements of the result column could be sorted.
* nan_direction_hint - see above.
*/
virtual void get_permutation(bool reverse, size_t limit, int nan_direction_hint,
Permutation& res) const = 0;
/** Copies each element according offsets parameter.
* (i-th element should be copied offsets[i] - offsets[i - 1] times.)
* It is necessary in ARRAY JOIN operation.
*/
virtual Ptr replicate(const Offsets& offsets) const = 0;
/** Copies each element according offsets parameter.
* (i-th element should be copied counts[i] times.)
* If `begin` and `count_sz` specified, it means elements in range [`begin`, `begin` + `count_sz`) will be replicated.
* If `count_sz` is -1, `begin` must be 0.
*/
virtual void replicate(const uint32_t* counts, size_t target_size, IColumn& column,
size_t begin = 0, int count_sz = -1) const {
LOG(FATAL) << "not support";
}
/** Split column to smaller columns. Each value goes to column index, selected by corresponding element of 'selector'.
* Selector must contain values from 0 to num_columns - 1.
* For default implementation, see scatter_impl.
*/
using ColumnIndex = UInt64;
using Selector = PaddedPODArray<ColumnIndex>;
virtual std::vector<MutablePtr> scatter(ColumnIndex num_columns,
const Selector& selector) const = 0;
virtual void append_data_by_selector(MutablePtr& res, const Selector& selector) const = 0;
/// Insert data from several other columns according to source mask (used in vertical merge).
/// For now it is a helper to de-virtualize calls to insert*() functions inside gather loop
/// (descendants should call gatherer_stream.gather(*this) to implement this function.)
/// TODO: interface decoupled from ColumnGathererStream that allows non-generic specializations.
// virtual void gather(ColumnGathererStream & gatherer_stream) = 0;
/** Computes minimum and maximum element of the column.
* In addition to numeric types, the function is completely implemented for Date and DateTime.
* For strings and arrays function should return default value.
* (except for constant columns; they should return value of the constant).
* If column is empty function should return default value.
*/
virtual void get_extremes(Field& min, Field& max) const = 0;
/// Reserves memory for specified amount of elements. If reservation isn't possible, does nothing.
/// It affects performance only (not correctness).
virtual void reserve(size_t /*n*/) {}
/// Resize memory for specified amount of elements. If reservation isn't possible, does nothing.
/// It affects performance only (not correctness).
virtual void resize(size_t /*n*/) {}
/// Size of column data in memory (may be approximate) - for profiling. Zero, if could not be determined.
virtual size_t byte_size() const = 0;
/// Size of memory, allocated for column.
/// This is greater or equals to byte_size due to memory reservation in containers.
/// Zero, if could not be determined.
virtual size_t allocated_bytes() const = 0;
/// Make memory region readonly with mprotect if it is large enough.
/// The operation is slow and performed only for debug builds.
virtual void protect() {}
/// If the column contains subcolumns (such as Array, Nullable, etc), do callback on them.
/// Shallow: doesn't do recursive calls; don't do call for itself.
using ColumnCallback = std::function<void(WrappedPtr&)>;
virtual void for_each_subcolumn(ColumnCallback) {}
/// Columns have equal structure.
/// If true - you can use "compare_at", "insert_from", etc. methods.
virtual bool structure_equals(const IColumn&) const {
LOG(FATAL) << "Method structure_equals is not supported for " << get_name();
return false;
}
MutablePtr mutate() const&& {
MutablePtr res = shallow_mutate();
res->for_each_subcolumn(
[](WrappedPtr& subcolumn) { subcolumn = std::move(*subcolumn).mutate(); });
return res;
}
/** Some columns can contain another columns inside.
* So, we have a tree of columns. But not all combinations are possible.
* There are the following rules:
*
* ColumnConst may be only at top. It cannot be inside any column.
* ColumnNullable can contain only simple columns.
*/
/// Various properties on behaviour of column type.
/// True if column contains something nullable inside. It's true for ColumnNullable, can be true or false for ColumnConst, etc.
virtual bool is_nullable() const { return false; }
virtual bool is_bitmap() const { return false; }
virtual bool is_hll() const { return false; }
// true if column has null element
virtual bool has_null() const { return false; }
// true if column has null element [0,size)
virtual bool has_null(size_t size) const { return false; }
/// It's a special kind of column, that contain single value, but is not a ColumnConst.
virtual bool is_dummy() const { return false; }
/// Clear data of column, just like vector clear
virtual void clear() {}
/** Memory layout properties.
*
* Each value of a column can be placed in memory contiguously or not.
*
* Example: simple columns like UInt64 or FixedString store their values contiguously in single memory buffer.
*
* Example: Tuple store values of each component in separate subcolumn, so the values of Tuples with at least two components are not contiguous.
* Another example is Nullable. Each value have null flag, that is stored separately, so the value is not contiguous in memory.
*
* There are some important cases, when values are not stored contiguously, but for each value, you can get contiguous memory segment,
* that will unambiguously identify the value. In this case, methods get_data_at and insert_data are implemented.
* Example: String column: bytes of strings are stored concatenated in one memory buffer
* and offsets to that buffer are stored in another buffer. The same is for Array of fixed-size contiguous elements.
*
* To avoid confusion between these cases, we don't have isContiguous method.
*/
/// Values in column have fixed size (including the case when values span many memory segments).
virtual bool values_have_fixed_size() const { return is_fixed_and_contiguous(); }
/// Values in column are represented as continuous memory segment of fixed size. Implies values_have_fixed_size.
virtual bool is_fixed_and_contiguous() const { return false; }
/// If is_fixed_and_contiguous, returns the underlying data array, otherwise throws an exception.
virtual StringRef get_raw_data() const {
LOG(FATAL) << fmt::format("Column {} is not a contiguous block of memory", get_name());
return StringRef {};
}
/// If values_have_fixed_size, returns size of value, otherwise throw an exception.
virtual size_t size_of_value_if_fixed() const {
LOG(FATAL) << fmt::format("Values of column {} are not fixed size.", get_name());
return 0;
}
/// Column is ColumnVector of numbers or ColumnConst of it. Note that Nullable columns are not numeric.
/// Implies is_fixed_and_contiguous.
virtual bool is_numeric() const { return false; }
virtual bool is_column_string() const { return false; }
virtual bool is_column_decimal() const { return false; }
virtual bool is_predicate_column() const { return false; }
virtual bool is_column_dictionary() const { return false; }
virtual bool is_column_array() const { return false; }
/// If the only value column can contain is NULL.
/// Does not imply type of object, because it can be ColumnNullable(ColumnNothing) or ColumnConst(ColumnNullable(ColumnNothing))
virtual bool only_null() const { return false; }
/// Can be inside ColumnNullable.
virtual bool can_be_inside_nullable() const { return false; }
virtual bool low_cardinality() const { return false; }
virtual void sort_column(const ColumnSorter* sorter, EqualFlags& flags,
IColumn::Permutation& perms, EqualRange& range,
bool last_column) const;
virtual ~IColumn() = default;
IColumn() = default;
IColumn(const IColumn&) = default;
/** Print column name, size, and recursively print all subcolumns.
*/
String dump_structure() const;
// only used in agg value replace
// ColumnString should replace according to 0,1,2... ,size,0,1,2...
virtual void replace_column_data(const IColumn&, size_t row, size_t self_row = 0) = 0;
// only used in ColumnNullable replace_column_data
virtual void replace_column_data_default(size_t self_row = 0) = 0;
virtual bool is_date_type() const { return is_date; }
virtual bool is_datetime_type() const { return is_date_time; }
virtual bool is_decimalv2_type() const { return is_decimalv2; }
virtual void set_date_type() { is_date = true; }
virtual void set_datetime_type() { is_date_time = true; }
virtual void set_decimalv2_type() { is_decimalv2 = true; }
void copy_date_types(const IColumn& col) {
if (col.is_date_type()) {
set_date_type();
}
if (col.is_datetime_type()) {
set_datetime_type();
}
}
// todo(wb): a temporary implemention, need re-abstract here
bool is_date = false;
bool is_date_time = false;
bool is_decimalv2 = false;
protected:
/// Template is to devirtualize calls to insert_from method.
/// In derived classes (that use final keyword), implement scatter method as call to scatter_impl.
template <typename Derived>
std::vector<MutablePtr> scatter_impl(ColumnIndex num_columns, const Selector& selector) const;
template <typename Derived>
void append_data_by_selector_impl(MutablePtr& res, const Selector& selector) const;
};
using ColumnPtr = IColumn::Ptr;
using MutableColumnPtr = IColumn::MutablePtr;
using Columns = std::vector<ColumnPtr>;
using MutableColumns = std::vector<MutableColumnPtr>;
using ColumnRawPtrs = std::vector<const IColumn*>;
//using MutableColumnRawPtrs = std::vector<IColumn *>;
template <typename... Args>
struct IsMutableColumns;
template <typename Arg, typename... Args>
struct IsMutableColumns<Arg, Args...> {
static const bool value =
std::is_assignable<MutableColumnPtr&&, Arg>::value && IsMutableColumns<Args...>::value;
};
template <>
struct IsMutableColumns<> {
static const bool value = true;
};
template <typename Type>
const Type* check_and_get_column(const IColumn& column) {
return typeid_cast<const Type*>(&column);
}
template <typename Type>
const Type* check_and_get_column(const IColumn* column) {
return typeid_cast<const Type*>(column);
}
template <typename Type>
bool check_column(const IColumn& column) {
return check_and_get_column<Type>(&column);
}
template <typename Type>
bool check_column(const IColumn* column) {
return check_and_get_column<Type>(column);
}
/// True if column's an ColumnConst instance. It's just a syntax sugar for type check.
bool is_column_const(const IColumn& column);
/// True if column's an ColumnNullable instance. It's just a syntax sugar for type check.
bool is_column_nullable(const IColumn& column);
} // namespace doris::vectorized
// Wrap `ColumnPtr` because `ColumnPtr` can't be used in forward declaration.
namespace doris {
struct ColumnPtrWrapper {
vectorized::ColumnPtr column_ptr;
ColumnPtrWrapper(vectorized::ColumnPtr col) : column_ptr(col) {}
};
} // namespace doris