/root/doris/be/src/vec/columns/column.h
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1 | | // Licensed to the Apache Software Foundation (ASF) under one |
2 | | // or more contributor license agreements. See the NOTICE file |
3 | | // distributed with this work for additional information |
4 | | // regarding copyright ownership. The ASF licenses this file |
5 | | // to you under the Apache License, Version 2.0 (the |
6 | | // "License"); you may not use this file except in compliance |
7 | | // with the License. You may obtain a copy of the License at |
8 | | // |
9 | | // http://www.apache.org/licenses/LICENSE-2.0 |
10 | | // |
11 | | // Unless required by applicable law or agreed to in writing, |
12 | | // software distributed under the License is distributed on an |
13 | | // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
14 | | // KIND, either express or implied. See the License for the |
15 | | // specific language governing permissions and limitations |
16 | | // under the License. |
17 | | // This file is copied from |
18 | | // https://github.com/ClickHouse/ClickHouse/blob/master/src/Columns/IColumn.h |
19 | | // and modified by Doris |
20 | | |
21 | | #pragma once |
22 | | |
23 | | #include <fmt/format.h> |
24 | | #include <glog/logging.h> |
25 | | #include <stdint.h> |
26 | | #include <sys/types.h> |
27 | | |
28 | | #include <algorithm> |
29 | | #include <functional> |
30 | | #include <ostream> |
31 | | #include <string> |
32 | | #include <type_traits> |
33 | | #include <utility> |
34 | | #include <vector> |
35 | | |
36 | | #include "common/status.h" |
37 | | #include "gutil/integral_types.h" |
38 | | #include "olap/olap_common.h" |
39 | | #include "runtime/define_primitive_type.h" |
40 | | #include "vec/common/cow.h" |
41 | | #include "vec/common/pod_array_fwd.h" |
42 | | #include "vec/common/string_ref.h" |
43 | | #include "vec/common/typeid_cast.h" |
44 | | #include "vec/core/field.h" |
45 | | #include "vec/core/types.h" |
46 | | |
47 | | class SipHash; |
48 | | |
49 | | #define DO_CRC_HASHES_FUNCTION_COLUMN_IMPL() \ |
50 | 5 | if (null_data == nullptr) { \ |
51 | 0 | for (size_t i = 0; i < s; i++) { \ |
52 | 0 | hashes[i] = HashUtil::zlib_crc_hash(&data[i], sizeof(T), hashes[i]); \ |
53 | 0 | } \ |
54 | 5 | } else { \ |
55 | 10 | for (size_t i = 0; i < s; i++) { \ |
56 | 5 | if (null_data[i] == 0) \ |
57 | 5 | hashes[i] = HashUtil::zlib_crc_hash(&data[i], sizeof(T), hashes[i]); \ |
58 | 5 | } \ |
59 | 5 | } |
60 | | |
61 | | namespace doris::vectorized { |
62 | | |
63 | | class Arena; |
64 | | class ColumnSorter; |
65 | | |
66 | | using EqualFlags = std::vector<uint8_t>; |
67 | | using EqualRange = std::pair<int, int>; |
68 | | |
69 | | /// Declares interface to store columns in memory. |
70 | | class IColumn : public COW<IColumn> { |
71 | | private: |
72 | | friend class COW<IColumn>; |
73 | | |
74 | | /// Creates the same column with the same data. |
75 | | /// This is internal method to use from COW. |
76 | | /// It performs shallow copy with copy-ctor and not useful from outside. |
77 | | /// If you want to copy column for modification, look at 'mutate' method. |
78 | | virtual MutablePtr clone() const = 0; |
79 | | |
80 | | public: |
81 | | // 64bit offsets now only Array type used, so we make it protected |
82 | | // to avoid use IColumn::Offset64 directly. |
83 | | // please use ColumnArray::Offset64 instead if we need. |
84 | | using Offset64 = UInt64; |
85 | | using Offsets64 = PaddedPODArray<Offset64>; |
86 | | |
87 | | // 32bit offsets for string |
88 | | using Offset = UInt32; |
89 | | using Offsets = PaddedPODArray<Offset>; |
90 | | |
91 | | /// Name of a Column. It is used in info messages. |
92 | 118 | virtual std::string get_name() const { return get_family_name(); } |
93 | | |
94 | | /// Name of a Column kind, without parameters (example: FixedString, Array). |
95 | | virtual const char* get_family_name() const = 0; |
96 | | |
97 | | /** If column isn't constant, returns nullptr (or itself). |
98 | | * If column is constant, transforms constant to full column (if column type allows such transform) and return it. |
99 | | */ |
100 | 17.0k | virtual Ptr convert_to_full_column_if_const() const { return get_ptr(); } |
101 | | |
102 | | /** If in join. the StringColumn size may overflow uint32_t, we need convert to uint64_t to ColumnString64 |
103 | | * The Column: ColumnString, ColumnNullable, ColumnArray, ColumnStruct need impl the code |
104 | | */ |
105 | 0 | virtual Ptr convert_column_if_overflow() { return get_ptr(); } |
106 | | |
107 | | /// If column isn't ColumnLowCardinality, return itself. |
108 | | /// If column is ColumnLowCardinality, transforms is to full column. |
109 | 191 | virtual Ptr convert_to_full_column_if_low_cardinality() const { return get_ptr(); } |
110 | | |
111 | | /// If column isn't ColumnDictionary, return itself. |
112 | | /// If column is ColumnDictionary, transforms is to predicate column. |
113 | 0 | virtual MutablePtr convert_to_predicate_column_if_dictionary() { return get_ptr(); } |
114 | | |
115 | | /// If column is ColumnDictionary, and is a range comparison predicate, convert dict encoding |
116 | 4.05k | virtual void convert_dict_codes_if_necessary() {} |
117 | | |
118 | | /// If column is ColumnDictionary, and is a bloom filter predicate, generate_hash_values |
119 | 0 | virtual void initialize_hash_values_for_runtime_filter() {} |
120 | | |
121 | | /// Creates empty column with the same type. |
122 | 94 | virtual MutablePtr clone_empty() const { return clone_resized(0); } |
123 | | |
124 | | /// Creates column with the same type and specified size. |
125 | | /// If size is less current size, then data is cut. |
126 | | /// If size is greater, than default values are appended. |
127 | 0 | virtual MutablePtr clone_resized(size_t s) const { |
128 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
129 | 0 | "Method clone_resized is not supported for " + get_name()); |
130 | 0 | return nullptr; |
131 | 0 | } |
132 | | |
133 | | // shrink the end zeros for CHAR type or ARRAY<CHAR> type |
134 | 0 | virtual MutablePtr get_shrinked_column() { |
135 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
136 | 0 | "Method get_shrinked_column is not supported for " + get_name()); |
137 | 0 | return nullptr; |
138 | 0 | } |
139 | | |
140 | | // check the column whether could shrinked |
141 | | // now support only in char type, or the nested type in complex type: array{char}, struct{char}, map{char} |
142 | 0 | virtual bool could_shrinked_column() { return false; } |
143 | | |
144 | | /// Some columns may require finalization before using of other operations. |
145 | 0 | virtual void finalize() {} |
146 | | |
147 | | // Only used on ColumnDictionary |
148 | 347 | virtual void set_rowset_segment_id(std::pair<RowsetId, uint32_t> rowset_segment_id) {} |
149 | | |
150 | 0 | virtual std::pair<RowsetId, uint32_t> get_rowset_segment_id() const { return {}; } |
151 | | |
152 | | /// Returns number of values in column. |
153 | | virtual size_t size() const = 0; |
154 | | |
155 | | /// There are no values in columns. |
156 | 10.8k | bool empty() const { return size() == 0; } |
157 | | |
158 | | /// Returns value of n-th element in universal Field representation. |
159 | | /// Is used in rare cases, since creation of Field instance is expensive usually. |
160 | | virtual Field operator[](size_t n) const = 0; |
161 | | |
162 | | /// Like the previous one, but avoids extra copying if Field is in a container, for example. |
163 | | virtual void get(size_t n, Field& res) const = 0; |
164 | | |
165 | | /// If possible, returns pointer to memory chunk which contains n-th element (if it isn't possible, throws an exception) |
166 | | /// Is used to optimize some computations (in aggregation, for example). |
167 | | virtual StringRef get_data_at(size_t n) const = 0; |
168 | | |
169 | | /// If column stores integers, it returns n-th element transformed to UInt64 using static_cast. |
170 | | /// If column stores floating point numbers, bits of n-th elements are copied to lower bits of UInt64, the remaining bits are zeros. |
171 | | /// Is used to optimize some computations (in aggregation, for example). |
172 | 0 | virtual UInt64 get64(size_t /*n*/) const { |
173 | 0 | LOG(FATAL) << "Method get64 is not supported for "; |
174 | 0 | return 0; |
175 | 0 | } |
176 | | |
177 | | /// If column stores native numeric type, it returns n-th element casted to Float64 |
178 | | /// Is used in regression methods to cast each features into uniform type |
179 | 0 | virtual Float64 get_float64(size_t /*n*/) const { |
180 | 0 | LOG(FATAL) << "Method get_float64 is not supported for " << get_name(); |
181 | 0 | return 0; |
182 | 0 | } |
183 | | |
184 | | /** If column is numeric, return value of n-th element, casted to UInt64. |
185 | | * For NULL values of Nullable column it is allowed to return arbitrary value. |
186 | | * Otherwise throw an exception. |
187 | | */ |
188 | 0 | virtual UInt64 get_uint(size_t /*n*/) const { |
189 | 0 | LOG(FATAL) << "Method get_uint is not supported for " << get_name(); |
190 | 0 | return 0; |
191 | 0 | } |
192 | | |
193 | 0 | virtual Int64 get_int(size_t /*n*/) const { |
194 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
195 | 0 | "Method get_int is not supported for " + get_name()); |
196 | 0 | return 0; |
197 | 0 | } |
198 | | |
199 | 0 | virtual bool is_default_at(size_t n) const { return get64(n) == 0; } |
200 | 1.66k | virtual bool is_null_at(size_t /*n*/) const { return false; } |
201 | | |
202 | | /** If column is numeric, return value of n-th element, casted to bool. |
203 | | * For NULL values of Nullable column returns false. |
204 | | * Otherwise throw an exception. |
205 | | */ |
206 | 0 | virtual bool get_bool(size_t /*n*/) const { |
207 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
208 | 0 | "Method get_bool is not supported for " + get_name()); |
209 | 0 | return false; |
210 | 0 | } |
211 | | |
212 | | /// Removes all elements outside of specified range. |
213 | | /// Is used in LIMIT operation, for example. |
214 | 0 | virtual Ptr cut(size_t start, size_t length) const { |
215 | 0 | MutablePtr res = clone_empty(); |
216 | 0 | res->insert_range_from(*this, start, length); |
217 | 0 | return res; |
218 | 0 | } |
219 | | |
220 | | /// Appends new value at the end of column (column's size is increased by 1). |
221 | | /// Is used to transform raw strings to Blocks (for example, inside input format parsers) |
222 | | virtual void insert(const Field& x) = 0; |
223 | | |
224 | | /// Appends n-th element from other column with the same type. |
225 | | /// Is used in merge-sort and merges. It could be implemented in inherited classes more optimally than default implementation. |
226 | | virtual void insert_from(const IColumn& src, size_t n); |
227 | | |
228 | | /// Appends range of elements from other column with the same type. |
229 | | /// Could be used to concatenate columns. |
230 | | /// TODO: we need `insert_range_from_const` for every column type. |
231 | | virtual void insert_range_from(const IColumn& src, size_t start, size_t length) = 0; |
232 | | |
233 | | /// Appends range of elements from other column with the same type. |
234 | | /// Do not need throw execption in ColumnString overflow uint32, only |
235 | | /// use in join |
236 | | virtual void insert_range_from_ignore_overflow(const IColumn& src, size_t start, |
237 | 0 | size_t length) { |
238 | 0 | insert_range_from(src, start, length); |
239 | 0 | } |
240 | | |
241 | | /// Appends one element from other column with the same type multiple times. |
242 | 18 | virtual void insert_many_from(const IColumn& src, size_t position, size_t length) { |
243 | 36 | for (size_t i = 0; i < length; ++i) { |
244 | 18 | insert_from(src, position); |
245 | 18 | } |
246 | 18 | } |
247 | | |
248 | | virtual void insert_from_multi_column(const std::vector<const IColumn*>& srcs, |
249 | | std::vector<size_t> positions); |
250 | | |
251 | | /// Appends a batch elements from other column with the same type |
252 | | /// indices_begin + indices_end represent the row indices of column src |
253 | | virtual void insert_indices_from(const IColumn& src, const uint32_t* indices_begin, |
254 | | const uint32_t* indices_end) = 0; |
255 | | |
256 | | /// Appends data located in specified memory chunk if it is possible (throws an exception if it cannot be implemented). |
257 | | /// Is used to optimize some computations (in aggregation, for example). |
258 | | /// Parameter length could be ignored if column values have fixed size. |
259 | | /// All data will be inserted as single element |
260 | | virtual void insert_data(const char* pos, size_t length) = 0; |
261 | | |
262 | 0 | virtual void insert_many_fix_len_data(const char* pos, size_t num) { |
263 | 0 | throw doris::Exception( |
264 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
265 | 0 | "Method insert_many_fix_len_data is not supported for " + get_name()); |
266 | 0 | } |
267 | | |
268 | | // todo(zeno) Use dict_args temp object to cover all arguments |
269 | | virtual void insert_many_dict_data(const int32_t* data_array, size_t start_index, |
270 | | const StringRef* dict, size_t data_num, |
271 | 0 | uint32_t dict_num = 0) { |
272 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
273 | 0 | "Method insert_many_dict_data is not supported for " + get_name()); |
274 | 0 | } |
275 | | |
276 | | virtual void insert_many_binary_data(char* data_array, uint32_t* len_array, |
277 | 0 | uint32_t* start_offset_array, size_t num) { |
278 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
279 | 0 | "Method insert_many_binary_data is not supported for " + get_name()); |
280 | 0 | } |
281 | | |
282 | | /// Insert binary data into column from a continuous buffer, the implementation maybe copy all binary data |
283 | | /// in one single time. |
284 | | virtual void insert_many_continuous_binary_data(const char* data, const uint32_t* offsets, |
285 | 0 | const size_t num) { |
286 | 0 | throw doris::Exception( |
287 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
288 | 0 | "Method insert_many_continuous_binary_data is not supported for " + get_name()); |
289 | 0 | } |
290 | | |
291 | 0 | virtual void insert_many_strings(const StringRef* strings, size_t num) { |
292 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
293 | 0 | "Method insert_many_strings is not supported for " + get_name()); |
294 | 0 | } |
295 | | |
296 | | virtual void insert_many_strings_overflow(const StringRef* strings, size_t num, |
297 | 0 | size_t max_length) { |
298 | 0 | throw doris::Exception( |
299 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
300 | 0 | "Method insert_many_strings_overflow is not supported for " + get_name()); |
301 | 0 | } |
302 | | |
303 | | // Here `pos` points to the memory data type is the same as the data type of the column. |
304 | | // This function is used by `insert_keys_into_columns` in AggregationNode. |
305 | 0 | virtual void insert_many_raw_data(const char* pos, size_t num) { |
306 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
307 | 0 | "Method insert_many_raw_data is not supported for " + get_name()); |
308 | 0 | } |
309 | | |
310 | 6 | void insert_many_data(const char* pos, size_t length, size_t data_num) { |
311 | 12 | for (size_t i = 0; i < data_num; ++i) { |
312 | 6 | insert_data(pos, length); |
313 | 6 | } |
314 | 6 | } |
315 | | |
316 | | /// Appends "default value". |
317 | | /// Is used when there are need to increase column size, but inserting value doesn't make sense. |
318 | | /// For example, ColumnNullable(Nested) absolutely ignores values of nested column if it is marked as NULL. |
319 | | virtual void insert_default() = 0; |
320 | | |
321 | | /// Appends "default value" multiple times. |
322 | 3 | virtual void insert_many_defaults(size_t length) { |
323 | 26 | for (size_t i = 0; i < length; ++i) { |
324 | 23 | insert_default(); |
325 | 23 | } |
326 | 3 | } |
327 | | |
328 | | /** Removes last n elements. |
329 | | * Is used to support exception-safety of several operations. |
330 | | * For example, sometimes insertion should be reverted if we catch an exception during operation processing. |
331 | | * If column has less than n elements or n == 0 - undefined behavior. |
332 | | */ |
333 | | virtual void pop_back(size_t n) = 0; |
334 | | |
335 | | /** Serializes n-th element. Serialized element should be placed continuously inside Arena's memory. |
336 | | * Serialized value can be deserialized to reconstruct original object. Is used in aggregation. |
337 | | * The method is similar to get_data_at(), but can work when element's value cannot be mapped to existing continuous memory chunk, |
338 | | * For example, to obtain unambiguous representation of Array of strings, strings data should be interleaved with their sizes. |
339 | | * Parameter begin should be used with Arena::alloc_continue. |
340 | | */ |
341 | | virtual StringRef serialize_value_into_arena(size_t n, Arena& arena, |
342 | | char const*& begin) const = 0; |
343 | | |
344 | | /// Deserializes a value that was serialized using IColumn::serialize_value_into_arena method. |
345 | | /// Returns pointer to the position after the read data. |
346 | | virtual const char* deserialize_and_insert_from_arena(const char* pos) = 0; |
347 | | |
348 | | /// Return the size of largest row. |
349 | | /// This is for calculating the memory size for vectorized serialization of aggregation keys. |
350 | 0 | virtual size_t get_max_row_byte_size() const { |
351 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
352 | 0 | "Method get_max_row_byte_size is not supported for " + get_name()); |
353 | 0 | return 0; |
354 | 0 | } |
355 | | |
356 | | virtual void serialize_vec(std::vector<StringRef>& keys, size_t num_rows, |
357 | 0 | size_t max_row_byte_size) const { |
358 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
359 | 0 | "Method serialize_vec is not supported for " + get_name()); |
360 | 0 | __builtin_unreachable(); |
361 | 0 | } |
362 | | |
363 | | virtual void serialize_vec_with_null_map(std::vector<StringRef>& keys, size_t num_rows, |
364 | 0 | const uint8_t* null_map) const { |
365 | 0 | throw doris::Exception( |
366 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
367 | 0 | "Method serialize_vec_with_null_map is not supported for " + get_name()); |
368 | 0 | __builtin_unreachable(); |
369 | 0 | } |
370 | | |
371 | | // This function deserializes group-by keys into column in the vectorized way. |
372 | 0 | virtual void deserialize_vec(std::vector<StringRef>& keys, const size_t num_rows) { |
373 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
374 | 0 | "Method deserialize_vec is not supported for " + get_name()); |
375 | 0 | __builtin_unreachable(); |
376 | 0 | } |
377 | | |
378 | | // Used in ColumnNullable::deserialize_vec |
379 | | virtual void deserialize_vec_with_null_map(std::vector<StringRef>& keys, const size_t num_rows, |
380 | 0 | const uint8_t* null_map) { |
381 | 0 | throw doris::Exception( |
382 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
383 | 0 | "Method deserialize_vec_with_null_map is not supported for " + get_name()); |
384 | 0 | __builtin_unreachable(); |
385 | 0 | } |
386 | | |
387 | | /// TODO: SipHash is slower than city or xx hash, rethink we should have a new interface |
388 | | /// Update state of hash function with value of n-th element. |
389 | | /// On subsequent calls of this method for sequence of column values of arbitrary types, |
390 | | /// passed bytes to hash must identify sequence of values unambiguously. |
391 | 0 | virtual void update_hash_with_value(size_t n, SipHash& hash) const { |
392 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
393 | 0 | "Method update_hash_with_value is not supported for " + get_name()); |
394 | 0 | } |
395 | | |
396 | | /// Update state of hash function with value of n elements to avoid the virtual function call |
397 | | /// null_data to mark whether need to do hash compute, null_data == nullptr |
398 | | /// means all element need to do hash function, else only *null_data != 0 need to do hash func |
399 | | /// do xxHash here, faster than other sip hash |
400 | | virtual void update_hashes_with_value(uint64_t* __restrict hashes, |
401 | 0 | const uint8_t* __restrict null_data = nullptr) const { |
402 | 0 | throw doris::Exception( |
403 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
404 | 0 | "Method update_hashes_with_value is not supported for " + get_name()); |
405 | 0 | } |
406 | | |
407 | | // use range for one hash value to avoid virtual function call in loop |
408 | | virtual void update_xxHash_with_value(size_t start, size_t end, uint64_t& hash, |
409 | 0 | const uint8_t* __restrict null_data) const { |
410 | 0 | throw doris::Exception( |
411 | 0 | ErrorCode::NOT_IMPLEMENTED_ERROR, |
412 | 0 | "Method update_xxHash_with_value is not supported for " + get_name()); |
413 | 0 | } |
414 | | |
415 | | /// Update state of crc32 hash function with value of n elements to avoid the virtual function call |
416 | | /// null_data to mark whether need to do hash compute, null_data == nullptr |
417 | | /// means all element need to do hash function, else only *null_data != 0 need to do hash func |
418 | | virtual void update_crcs_with_value(uint32_t* __restrict hash, PrimitiveType type, |
419 | | uint32_t rows, uint32_t offset = 0, |
420 | 0 | const uint8_t* __restrict null_data = nullptr) const { |
421 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
422 | 0 | "Method update_crcs_with_value is not supported for " + get_name()); |
423 | 0 | } |
424 | | |
425 | | // use range for one hash value to avoid virtual function call in loop |
426 | | virtual void update_crc_with_value(size_t start, size_t end, uint32_t& hash, |
427 | 0 | const uint8_t* __restrict null_data) const { |
428 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
429 | 0 | "Method update_crc_with_value is not supported for " + get_name()); |
430 | 0 | } |
431 | | |
432 | | /** Removes elements that don't match the filter. |
433 | | * Is used in WHERE and HAVING operations. |
434 | | * If result_size_hint > 0, then makes advance reserve(result_size_hint) for the result column; |
435 | | * if 0, then don't makes reserve(), |
436 | | * otherwise (i.e. < 0), makes reserve() using size of source column. |
437 | | */ |
438 | | using Filter = PaddedPODArray<UInt8>; |
439 | | virtual Ptr filter(const Filter& filt, ssize_t result_size_hint) const = 0; |
440 | | |
441 | | /// This function will modify the original table. |
442 | | /// Return rows number after filtered. |
443 | | virtual size_t filter(const Filter& filter) = 0; |
444 | | |
445 | | /** |
446 | | * used by lazy materialization to filter column by selected rowids |
447 | | * Q: Why use IColumn* as args type instead of MutablePtr or ImmutablePtr ? |
448 | | * A: If use MutablePtr/ImmutablePtr as col_ptr's type, which means there could be many |
449 | | * convert(convert MutablePtr to ImmutablePtr or convert ImmutablePtr to MutablePtr) |
450 | | * happends in filter_by_selector because of mem-reuse logic or ColumnNullable, I think this is meaningless; |
451 | | * So using raw ptr directly here. |
452 | | * NOTICE: only column_nullable and predict_column, column_dictionary now support filter_by_selector |
453 | | */ |
454 | 0 | virtual Status filter_by_selector(const uint16_t* sel, size_t sel_size, IColumn* col_ptr) { |
455 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
456 | 0 | "Method filter_by_selector is not supported for {}, only " |
457 | 0 | "column_nullable, column_dictionary and predict_column support", |
458 | 0 | get_name()); |
459 | 0 | __builtin_unreachable(); |
460 | 0 | } |
461 | | |
462 | | /// Permutes elements using specified permutation. Is used in sortings. |
463 | | /// limit - if it isn't 0, puts only first limit elements in the result. |
464 | | using Permutation = PaddedPODArray<size_t>; |
465 | | virtual Ptr permute(const Permutation& perm, size_t limit) const = 0; |
466 | | |
467 | | /// Creates new column with values column[indexes[:limit]]. If limit is 0, all indexes are used. |
468 | | /// Indexes must be one of the ColumnUInt. For default implementation, see select_index_impl from ColumnsCommon.h |
469 | 0 | virtual Ptr index(const IColumn& indexes, size_t limit) const { |
470 | 0 | LOG(FATAL) << "column not support index"; |
471 | 0 | __builtin_unreachable(); |
472 | 0 | } |
473 | | |
474 | | /** Compares (*this)[n] and rhs[m]. Column rhs should have the same type. |
475 | | * Returns negative number, 0, or positive number (*this)[n] is less, equal, greater than rhs[m] respectively. |
476 | | * Is used in sortings. |
477 | | * |
478 | | * If one of element's value is NaN or NULLs, then: |
479 | | * - if nan_direction_hint == -1, NaN and NULLs are considered as least than everything other; |
480 | | * - if nan_direction_hint == 1, NaN and NULLs are considered as greatest than everything other. |
481 | | * For example, if nan_direction_hint == -1 is used by descending sorting, NaNs will be at the end. |
482 | | * |
483 | | * For non Nullable and non floating point types, nan_direction_hint is ignored. |
484 | | * For array/map/struct types, we compare with nested column element and offsets size |
485 | | */ |
486 | | virtual int compare_at(size_t n, size_t m, const IColumn& rhs, |
487 | | int nan_direction_hint) const = 0; |
488 | | |
489 | | /** |
490 | | * To compare all rows in this column with another row (with row_id = rhs_row_id in column rhs) |
491 | | * @param nan_direction_hint and direction indicates the ordering. |
492 | | * @param cmp_res if we already has a comparison result for row i, e.g. cmp_res[i] = 1, we can skip row i |
493 | | * @param filter this stores comparison results for all rows. filter[i] = 1 means row i is less than row rhs_row_id in rhs |
494 | | */ |
495 | | virtual void compare_internal(size_t rhs_row_id, const IColumn& rhs, int nan_direction_hint, |
496 | | int direction, std::vector<uint8>& cmp_res, |
497 | | uint8* __restrict filter) const; |
498 | | |
499 | | /** Returns a permutation that sorts elements of this column, |
500 | | * i.e. perm[i]-th element of source column should be i-th element of sorted column. |
501 | | * reverse - reverse ordering (ascending). |
502 | | * limit - if isn't 0, then only first limit elements of the result column could be sorted. |
503 | | * nan_direction_hint - see above. |
504 | | */ |
505 | | virtual void get_permutation(bool reverse, size_t limit, int nan_direction_hint, |
506 | | Permutation& res) const = 0; |
507 | | |
508 | | /** Copies each element according offsets parameter. |
509 | | * (i-th element should be copied offsets[i] - offsets[i - 1] times.) |
510 | | * It is necessary in ARRAY JOIN operation. |
511 | | */ |
512 | | virtual Ptr replicate(const Offsets& offsets) const = 0; |
513 | | |
514 | | /// Appends one field multiple times. Can be optimized in inherited classes. |
515 | 0 | virtual void insert_many(const Field& field, size_t length) { |
516 | 0 | for (size_t i = 0; i < length; ++i) { |
517 | 0 | insert(field); |
518 | 0 | } |
519 | 0 | } |
520 | | /// Returns indices of values in column, that not equal to default value of column. |
521 | | virtual void get_indices_of_non_default_rows(Offsets64& indices, size_t from, |
522 | 0 | size_t limit) const { |
523 | 0 | LOG(FATAL) << "column not support get_indices_of_non_default_rows"; |
524 | 0 | __builtin_unreachable(); |
525 | 0 | } |
526 | | |
527 | | template <typename Derived> |
528 | | void get_indices_of_non_default_rows_impl(IColumn::Offsets64& indices, size_t from, |
529 | | size_t limit) const; |
530 | | |
531 | | /** Split column to smaller columns. Each value goes to column index, selected by corresponding element of 'selector'. |
532 | | * Selector must contain values from 0 to num_columns - 1. |
533 | | * For default implementation, see scatter_impl. |
534 | | */ |
535 | | using ColumnIndex = UInt64; |
536 | | using Selector = PaddedPODArray<ColumnIndex>; |
537 | | |
538 | | virtual void append_data_by_selector(MutablePtr& res, const Selector& selector) const = 0; |
539 | | |
540 | | virtual void append_data_by_selector(MutablePtr& res, const Selector& selector, size_t begin, |
541 | | size_t end) const = 0; |
542 | | |
543 | | /// Insert data from several other columns according to source mask (used in vertical merge). |
544 | | /// For now it is a helper to de-virtualize calls to insert*() functions inside gather loop |
545 | | /// (descendants should call gatherer_stream.gather(*this) to implement this function.) |
546 | | /// TODO: interface decoupled from ColumnGathererStream that allows non-generic specializations. |
547 | | // virtual void gather(ColumnGathererStream & gatherer_stream) = 0; |
548 | | |
549 | | /// Reserves memory for specified amount of elements. If reservation isn't possible, does nothing. |
550 | | /// It affects performance only (not correctness). |
551 | 0 | virtual void reserve(size_t /*n*/) {} |
552 | | |
553 | | /// Resize memory for specified amount of elements. If reservation isn't possible, does nothing. |
554 | | /// It affects performance only (not correctness). |
555 | 0 | virtual void resize(size_t /*n*/) {} |
556 | | |
557 | | /// Size of column data in memory (may be approximate) - for profiling. Zero, if could not be determined. |
558 | | virtual size_t byte_size() const = 0; |
559 | | |
560 | | /// Size of memory, allocated for column. |
561 | | /// This is greater or equals to byte_size due to memory reservation in containers. |
562 | | /// Zero, if could not be determined. |
563 | | virtual size_t allocated_bytes() const = 0; |
564 | | |
565 | | /// If the column contains subcolumns (such as Array, Nullable, etc), do callback on them. |
566 | | /// Shallow: doesn't do recursive calls; don't do call for itself. |
567 | | using ColumnCallback = std::function<void(WrappedPtr&)>; |
568 | | using ImutableColumnCallback = std::function<void(const IColumn&)>; |
569 | 43.5k | virtual void for_each_subcolumn(ColumnCallback) {} |
570 | | |
571 | | /// Columns have equal structure. |
572 | | /// If true - you can use "compare_at", "insert_from", etc. methods. |
573 | 0 | virtual bool structure_equals(const IColumn&) const { |
574 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
575 | 0 | "Method structure_equals is not supported for " + get_name()); |
576 | 0 | return false; |
577 | 0 | } |
578 | | |
579 | 45.1k | MutablePtr mutate() const&& { |
580 | 45.1k | MutablePtr res = shallow_mutate(); |
581 | 45.1k | res->for_each_subcolumn( |
582 | 45.1k | [](WrappedPtr& subcolumn) { subcolumn = std::move(*subcolumn).mutate(); }); |
583 | 45.1k | return res; |
584 | 45.1k | } |
585 | | |
586 | 0 | static MutablePtr mutate(Ptr ptr) { |
587 | 0 | MutablePtr res = ptr->shallow_mutate(); /// Now use_count is 2. |
588 | 0 | ptr.reset(); /// Reset use_count to 1. |
589 | 0 | res->for_each_subcolumn( |
590 | 0 | [](WrappedPtr& subcolumn) { subcolumn = std::move(*subcolumn).mutate(); }); |
591 | 0 | return res; |
592 | 0 | } |
593 | | |
594 | | /** Some columns can contain another columns inside. |
595 | | * So, we have a tree of columns. But not all combinations are possible. |
596 | | * There are the following rules: |
597 | | * |
598 | | * ColumnConst may be only at top. It cannot be inside any column. |
599 | | * ColumnNullable can contain only simple columns. |
600 | | */ |
601 | | |
602 | | /// Various properties on behaviour of column type. |
603 | | |
604 | | /// True if column contains something nullable inside. It's true for ColumnNullable, can be true or false for ColumnConst, etc. |
605 | 30.8k | virtual bool is_nullable() const { return false; } |
606 | | |
607 | 0 | virtual bool is_bitmap() const { return false; } |
608 | | |
609 | 0 | virtual bool is_hll() const { return false; } |
610 | | |
611 | | // true if column has null element |
612 | 0 | virtual bool has_null() const { return false; } |
613 | | |
614 | | // true if column has null element [0,size) |
615 | 1.65k | virtual bool has_null(size_t size) const { return false; } |
616 | | |
617 | 6 | virtual bool is_exclusive() const { return use_count() == 1; } |
618 | | |
619 | | /// Clear data of column, just like vector clear |
620 | | virtual void clear() = 0; |
621 | | |
622 | | /** Memory layout properties. |
623 | | * |
624 | | * Each value of a column can be placed in memory contiguously or not. |
625 | | * |
626 | | * Example: simple columns like UInt64 or FixedString store their values contiguously in single memory buffer. |
627 | | * |
628 | | * Example: Tuple store values of each component in separate subcolumn, so the values of Tuples with at least two components are not contiguous. |
629 | | * Another example is Nullable. Each value have null flag, that is stored separately, so the value is not contiguous in memory. |
630 | | * |
631 | | * There are some important cases, when values are not stored contiguously, but for each value, you can get contiguous memory segment, |
632 | | * that will unambiguously identify the value. In this case, methods get_data_at and insert_data are implemented. |
633 | | * Example: String column: bytes of strings are stored concatenated in one memory buffer |
634 | | * and offsets to that buffer are stored in another buffer. The same is for Array of fixed-size contiguous elements. |
635 | | * |
636 | | * To avoid confusion between these cases, we don't have isContiguous method. |
637 | | */ |
638 | | |
639 | | /// Values in column have fixed size (including the case when values span many memory segments). |
640 | 0 | virtual bool values_have_fixed_size() const { return is_fixed_and_contiguous(); } |
641 | | |
642 | | /// Values in column are represented as continuous memory segment of fixed size. Implies values_have_fixed_size. |
643 | 0 | virtual bool is_fixed_and_contiguous() const { return false; } |
644 | | |
645 | | /// If is_fixed_and_contiguous, returns the underlying data array, otherwise throws an exception. |
646 | 0 | virtual StringRef get_raw_data() const { |
647 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
648 | 0 | "Column {} is not a contiguous block of memory", get_name()); |
649 | 0 | return StringRef {}; |
650 | 0 | } |
651 | | |
652 | | /// If values_have_fixed_size, returns size of value, otherwise throw an exception. |
653 | 0 | virtual size_t size_of_value_if_fixed() const { |
654 | 0 | throw doris::Exception(ErrorCode::NOT_IMPLEMENTED_ERROR, |
655 | 0 | "Values of column {} are not fixed size.", get_name()); |
656 | 0 | return 0; |
657 | 0 | } |
658 | | |
659 | | /// Returns ratio of values in column, that are equal to default value of column. |
660 | | /// Checks only @sample_ratio ratio of rows. |
661 | 0 | virtual double get_ratio_of_default_rows(double sample_ratio = 1.0) const { |
662 | 0 | LOG(FATAL) << fmt::format("get_ratio_of_default_rows of column {} are not implemented.", |
663 | 0 | get_name()); |
664 | 0 | return 0.0; |
665 | 0 | } |
666 | | |
667 | | /// Template is to devirtualize calls to 'isDefaultAt' method. |
668 | | template <typename Derived> |
669 | | double get_ratio_of_default_rows_impl(double sample_ratio) const; |
670 | | |
671 | | /// Column is ColumnVector of numbers or ColumnConst of it. Note that Nullable columns are not numeric. |
672 | | /// Implies is_fixed_and_contiguous. |
673 | 0 | virtual bool is_numeric() const { return false; } |
674 | | |
675 | | // Column is ColumnString/ColumnArray/ColumnMap or other variable length column at every row |
676 | 3 | virtual bool is_variable_length() const { return false; } |
677 | | |
678 | 3 | virtual bool is_column_string() const { return false; } |
679 | | |
680 | 0 | virtual bool is_column_string64() const { return false; } |
681 | | |
682 | 0 | virtual bool is_column_decimal() const { return false; } |
683 | | |
684 | 4.16k | virtual bool is_column_dictionary() const { return false; } |
685 | | |
686 | 0 | virtual bool is_column_array() const { return false; } |
687 | | |
688 | 8 | virtual bool is_column_map() const { return false; } |
689 | | |
690 | 0 | virtual bool is_column_struct() const { return false; } |
691 | | |
692 | | /// If the only value column can contain is NULL. |
693 | 532 | virtual bool only_null() const { return false; } |
694 | | |
695 | | virtual void sort_column(const ColumnSorter* sorter, EqualFlags& flags, |
696 | | IColumn::Permutation& perms, EqualRange& range, |
697 | | bool last_column) const; |
698 | | |
699 | 39.1k | virtual ~IColumn() = default; |
700 | 39.1k | IColumn() = default; |
701 | 4 | IColumn(const IColumn&) = default; |
702 | | |
703 | | /** Print column name, size, and recursively print all subcolumns. |
704 | | */ |
705 | | String dump_structure() const; |
706 | | |
707 | | // only used in agg value replace |
708 | | // ColumnString should replace according to 0,1,2... ,size,0,1,2... |
709 | | virtual void replace_column_data(const IColumn&, size_t row, size_t self_row = 0) = 0; |
710 | | |
711 | | // only used in ColumnNullable replace_column_data |
712 | | virtual void replace_column_data_default(size_t self_row = 0) = 0; |
713 | | |
714 | 0 | virtual void replace_column_null_data(const uint8_t* __restrict null_map) {} |
715 | | |
716 | 500k | virtual bool is_date_type() const { return is_date; } |
717 | 500k | virtual bool is_datetime_type() const { return is_date_time; } |
718 | | |
719 | 138 | virtual void set_date_type() { is_date = true; } |
720 | 280 | virtual void set_datetime_type() { is_date_time = true; } |
721 | | |
722 | 51 | void copy_date_types(const IColumn& col) { |
723 | 51 | if (col.is_date_type()) { |
724 | 1 | set_date_type(); |
725 | 1 | } |
726 | 51 | if (col.is_datetime_type()) { |
727 | 4 | set_datetime_type(); |
728 | 4 | } |
729 | 51 | } |
730 | | |
731 | | // todo(wb): a temporary implemention, need re-abstract here |
732 | | bool is_date = false; |
733 | | bool is_date_time = false; |
734 | | |
735 | | protected: |
736 | | template <typename Derived> |
737 | | void append_data_by_selector_impl(MutablePtr& res, const Selector& selector) const; |
738 | | template <typename Derived> |
739 | | void append_data_by_selector_impl(MutablePtr& res, const Selector& selector, size_t begin, |
740 | | size_t end) const; |
741 | | }; |
742 | | |
743 | | using ColumnPtr = IColumn::Ptr; |
744 | | using MutableColumnPtr = IColumn::MutablePtr; |
745 | | using Columns = std::vector<ColumnPtr>; |
746 | | using MutableColumns = std::vector<MutableColumnPtr>; |
747 | | using ColumnPtrs = std::vector<ColumnPtr>; |
748 | | using ColumnRawPtrs = std::vector<const IColumn*>; |
749 | | |
750 | | template <typename... Args> |
751 | | struct IsMutableColumns; |
752 | | |
753 | | template <typename Arg, typename... Args> |
754 | | struct IsMutableColumns<Arg, Args...> { |
755 | | static const bool value = |
756 | | std::is_assignable<MutableColumnPtr&&, Arg>::value && IsMutableColumns<Args...>::value; |
757 | | }; |
758 | | |
759 | | template <> |
760 | | struct IsMutableColumns<> { |
761 | | static const bool value = true; |
762 | | }; |
763 | | |
764 | | template <typename Type> |
765 | 3.86k | const Type* check_and_get_column(const IColumn& column) { |
766 | 3.86k | return typeid_cast<const Type*>(&column); |
767 | 3.86k | } _ZN5doris10vectorized20check_and_get_columnINS0_11ColumnArrayEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 18 | const Type* check_and_get_column(const IColumn& column) { | 766 | 18 | return typeid_cast<const Type*>(&column); | 767 | 18 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIhEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 71 | const Type* check_and_get_column(const IColumn& column) { | 766 | 71 | return typeid_cast<const Type*>(&column); | 767 | 71 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIdEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 7 | const Type* check_and_get_column(const IColumn& column) { | 766 | 7 | return typeid_cast<const Type*>(&column); | 767 | 7 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_14ColumnNullableEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 2.24k | const Type* check_and_get_column(const IColumn& column) { | 766 | 2.24k | return typeid_cast<const Type*>(&column); | 767 | 2.24k | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE5EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE5EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE11EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE11EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE12EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE12EEEEEPKT_RKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIiEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 93 | const Type* check_and_get_column(const IColumn& column) { | 766 | 93 | return typeid_cast<const Type*>(&column); | 767 | 93 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIaEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 35 | const Type* check_and_get_column(const IColumn& column) { | 766 | 35 | return typeid_cast<const Type*>(&column); | 767 | 35 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIsEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 30 | const Type* check_and_get_column(const IColumn& column) { | 766 | 30 | return typeid_cast<const Type*>(&column); | 767 | 30 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIlEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 37 | const Type* check_and_get_column(const IColumn& column) { | 766 | 37 | return typeid_cast<const Type*>(&column); | 767 | 37 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorInEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 19 | const Type* check_and_get_column(const IColumn& column) { | 766 | 19 | return typeid_cast<const Type*>(&column); | 767 | 19 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalInEEEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 10 | const Type* check_and_get_column(const IColumn& column) { | 766 | 10 | return typeid_cast<const Type*>(&column); | 767 | 10 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIfEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 10 | const Type* check_and_get_column(const IColumn& column) { | 766 | 10 | return typeid_cast<const Type*>(&column); | 767 | 10 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIjEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 17 | const Type* check_and_get_column(const IColumn& column) { | 766 | 17 | return typeid_cast<const Type*>(&column); | 767 | 17 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorImEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 17 | const Type* check_and_get_column(const IColumn& column) { | 766 | 17 | return typeid_cast<const Type*>(&column); | 767 | 17 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_14ColumnNullableEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 27 | const Type* check_and_get_column(const IColumn& column) { | 766 | 27 | return typeid_cast<const Type*>(&column); | 767 | 27 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_11ColumnConstEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 1.06k | const Type* check_and_get_column(const IColumn& column) { | 766 | 1.06k | return typeid_cast<const Type*>(&column); | 767 | 1.06k | } |
_ZN5doris10vectorized20check_and_get_columnINS0_9ColumnStrIjEEEEPKT_RKNS0_7IColumnE Line | Count | Source | 765 | 166 | const Type* check_and_get_column(const IColumn& column) { | 766 | 166 | return typeid_cast<const Type*>(&column); | 767 | 166 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIiEEEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIlEEEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_12Decimal128V3EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_11ColumnConstEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIN4wide7integerILm256EiEEEEEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIoEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE3EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE3EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE4EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE4EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE6EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE6EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE7EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE7EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE8EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE8EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE9EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE9EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE20EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE20EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE28EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE28EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE29EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE29EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE30EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE30EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE35EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE35EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_16ColumnDictionaryIiEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE15EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE15EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE23EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE23EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE25EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE25EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE26EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE26EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE2EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE2EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE36EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE36EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_19PredicateColumnTypeILNS_13PrimitiveTypeE37EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE37EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_9ColumnMapEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnStructEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnObjectEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorItEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorINS0_7UInt128EEEEEPKT_RKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIhEEEEPKT_RKNS0_7IColumnE |
768 | | |
769 | | template <typename Type> |
770 | 28.0k | const Type* check_and_get_column(const IColumn* column) { |
771 | 28.0k | return typeid_cast<const Type*>(column); |
772 | 28.0k | } _ZN5doris10vectorized20check_and_get_columnINS0_14ColumnNullableEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 553 | const Type* check_and_get_column(const IColumn* column) { | 771 | 553 | return typeid_cast<const Type*>(column); | 772 | 553 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE5EEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 4.07k | const Type* check_and_get_column(const IColumn* column) { | 771 | 4.07k | return typeid_cast<const Type*>(column); | 772 | 4.07k | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE11EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE12EEEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnINS0_9ColumnStrIjEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 227 | const Type* check_and_get_column(const IColumn* column) { | 771 | 227 | return typeid_cast<const Type*>(column); | 772 | 227 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_11ColumnArrayEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 35 | const Type* check_and_get_column(const IColumn* column) { | 771 | 35 | return typeid_cast<const Type*>(column); | 772 | 35 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIhEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 56 | const Type* check_and_get_column(const IColumn* column) { | 771 | 56 | return typeid_cast<const Type*>(column); | 772 | 56 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorItEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 21 | const Type* check_and_get_column(const IColumn* column) { | 771 | 21 | return typeid_cast<const Type*>(column); | 772 | 21 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIjEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 60 | const Type* check_and_get_column(const IColumn* column) { | 771 | 60 | return typeid_cast<const Type*>(column); | 772 | 60 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorImEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 61 | const Type* check_and_get_column(const IColumn* column) { | 771 | 61 | return typeid_cast<const Type*>(column); | 772 | 61 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIaEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 58 | const Type* check_and_get_column(const IColumn* column) { | 771 | 58 | return typeid_cast<const Type*>(column); | 772 | 58 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIsEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 51 | const Type* check_and_get_column(const IColumn* column) { | 771 | 51 | return typeid_cast<const Type*>(column); | 772 | 51 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIiEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 68 | const Type* check_and_get_column(const IColumn* column) { | 771 | 68 | return typeid_cast<const Type*>(column); | 772 | 68 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIlEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 96 | const Type* check_and_get_column(const IColumn* column) { | 771 | 96 | return typeid_cast<const Type*>(column); | 772 | 96 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorInEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 18 | const Type* check_and_get_column(const IColumn* column) { | 771 | 18 | return typeid_cast<const Type*>(column); | 772 | 18 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIfEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 13 | const Type* check_and_get_column(const IColumn* column) { | 771 | 13 | return typeid_cast<const Type*>(column); | 772 | 13 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIdEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 26 | const Type* check_and_get_column(const IColumn* column) { | 771 | 26 | return typeid_cast<const Type*>(column); | 772 | 26 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIiEEEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 1 | const Type* check_and_get_column(const IColumn* column) { | 771 | 1 | return typeid_cast<const Type*>(column); | 772 | 1 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIlEEEEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalInEEEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_12Decimal128V3EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_13ColumnDecimalINS0_7DecimalIN4wide7integerILm256EiEEEEEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE3EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE4EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE6EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE7EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE8EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE9EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE20EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE28EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE29EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE30EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE35EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_16ColumnDictionaryIiEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE15EEEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE23EEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 20 | const Type* check_and_get_column(const IColumn* column) { | 771 | 20 | return typeid_cast<const Type*>(column); | 772 | 20 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE25EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE26EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE2EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE36EEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_19PredicateColumnTypeILNS_13PrimitiveTypeE37EEEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnINS0_11ColumnConstEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 22.4k | const Type* check_and_get_column(const IColumn* column) { | 771 | 22.4k | return typeid_cast<const Type*>(column); | 772 | 22.4k | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_9ColumnMapEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnIKNS0_11ColumnArrayEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 70 | const Type* check_and_get_column(const IColumn* column) { | 771 | 70 | return typeid_cast<const Type*>(column); | 772 | 70 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_14ColumnNullableEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 12 | const Type* check_and_get_column(const IColumn* column) { | 771 | 12 | return typeid_cast<const Type*>(column); | 772 | 12 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_12ColumnVectorIoEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
_ZN5doris10vectorized20check_and_get_columnINS0_17ColumnComplexTypeINS_11BitmapValueEEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 8 | const Type* check_and_get_column(const IColumn* column) { | 771 | 8 | return typeid_cast<const Type*>(column); | 772 | 8 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnStructEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIhEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 4 | const Type* check_and_get_column(const IColumn* column) { | 771 | 4 | return typeid_cast<const Type*>(column); | 772 | 4 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIaEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIsEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIiEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
_ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIlEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorInEEEEPKT_PKNS0_7IColumnE _ZN5doris10vectorized20check_and_get_columnIKNS0_12ColumnVectorIdEEEEPKT_PKNS0_7IColumnE Line | Count | Source | 770 | 2 | const Type* check_and_get_column(const IColumn* column) { | 771 | 2 | return typeid_cast<const Type*>(column); | 772 | 2 | } |
Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_17ColumnComplexTypeINS_11HyperLogLogEEEEEPKT_PKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized20check_and_get_columnINS0_12ColumnObjectEEEPKT_PKNS0_7IColumnE |
773 | | |
774 | | template <typename Type> |
775 | 22.8k | bool check_column(const IColumn& column) { |
776 | 22.8k | return check_and_get_column<Type>(&column); |
777 | 22.8k | } _ZN5doris10vectorized12check_columnINS0_14ColumnNullableEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 355 | bool check_column(const IColumn& column) { | 776 | 355 | return check_and_get_column<Type>(&column); | 777 | 355 | } |
_ZN5doris10vectorized12check_columnINS0_11ColumnConstEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 22.4k | bool check_column(const IColumn& column) { | 776 | 22.4k | return check_and_get_column<Type>(&column); | 777 | 22.4k | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIhEEEEbRKNS0_7IColumnE _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIaEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 2 | bool check_column(const IColumn& column) { | 776 | 2 | return check_and_get_column<Type>(&column); | 777 | 2 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIsEEEEbRKNS0_7IColumnE _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIiEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 3 | bool check_column(const IColumn& column) { | 776 | 3 | return check_and_get_column<Type>(&column); | 777 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIlEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 5 | bool check_column(const IColumn& column) { | 776 | 5 | return check_and_get_column<Type>(&column); | 777 | 5 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorInEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 1 | bool check_column(const IColumn& column) { | 776 | 1 | return check_and_get_column<Type>(&column); | 777 | 1 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIfEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 1 | bool check_column(const IColumn& column) { | 776 | 1 | return check_and_get_column<Type>(&column); | 777 | 1 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIdEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 1 | bool check_column(const IColumn& column) { | 776 | 1 | return check_and_get_column<Type>(&column); | 777 | 1 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIiEEEEEEbRKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIlEEEEEEbRKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_12Decimal128V3EEEEEbRKNS0_7IColumnE _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalInEEEEEEbRKNS0_7IColumnE Line | Count | Source | 775 | 2 | bool check_column(const IColumn& column) { | 776 | 2 | return check_and_get_column<Type>(&column); | 777 | 2 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIN4wide7integerILm256EiEEEEEEEEbRKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIjEEEEbRKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorImEEEEbRKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_9ColumnStrIjEEEEbRKNS0_7IColumnE |
778 | | |
779 | | template <typename Type> |
780 | 36 | bool check_column(const IColumn* column) { |
781 | 36 | return check_and_get_column<Type>(column); |
782 | 36 | } _ZN5doris10vectorized12check_columnINS0_11ColumnArrayEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 15 | bool check_column(const IColumn* column) { | 781 | 15 | return check_and_get_column<Type>(column); | 782 | 15 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_9ColumnMapEEEbPKNS0_7IColumnE _ZN5doris10vectorized12check_columnINS0_12ColumnVectorItEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIjEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorImEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIaEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIsEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
_ZN5doris10vectorized12check_columnINS0_12ColumnVectorIiEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIlEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorInEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIoEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIfEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIdEEEEbPKNS0_7IColumnE _ZN5doris10vectorized12check_columnINS0_12ColumnVectorIhEEEEbPKNS0_7IColumnE Line | Count | Source | 780 | 3 | bool check_column(const IColumn* column) { | 781 | 3 | return check_and_get_column<Type>(column); | 782 | 3 | } |
Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIiEEEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIlEEEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalInEEEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_12Decimal128V3EEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_13ColumnDecimalINS0_7DecimalIN4wide7integerILm256EiEEEEEEEEbPKNS0_7IColumnE Unexecuted instantiation: _ZN5doris10vectorized12check_columnINS0_9ColumnStrIjEEEEbPKNS0_7IColumnE |
783 | | |
784 | | /// True if column's an ColumnConst instance. It's just a syntax sugar for type check. |
785 | | bool is_column_const(const IColumn& column); |
786 | | |
787 | | /// True if column's an ColumnNullable instance. It's just a syntax sugar for type check. |
788 | | bool is_column_nullable(const IColumn& column); |
789 | | } // namespace doris::vectorized |
790 | | |
791 | | // Wrap `ColumnPtr` because `ColumnPtr` can't be used in forward declaration. |
792 | | namespace doris { |
793 | | struct ColumnPtrWrapper { |
794 | | vectorized::ColumnPtr column_ptr; |
795 | | |
796 | 196 | ColumnPtrWrapper(vectorized::ColumnPtr col) : column_ptr(col) {} |
797 | | }; |
798 | | } // namespace doris |