/root/doris/be/src/olap/tablet_schema.h
Line | Count | Source |
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 | | |
18 | | #pragma once |
19 | | |
20 | | #include <gen_cpp/Types_types.h> |
21 | | #include <gen_cpp/olap_common.pb.h> |
22 | | #include <gen_cpp/olap_file.pb.h> |
23 | | #include <gen_cpp/segment_v2.pb.h> |
24 | | #include <parallel_hashmap/phmap.h> |
25 | | |
26 | | #include <algorithm> |
27 | | #include <cstdint> |
28 | | #include <map> |
29 | | #include <memory> |
30 | | #include <string> |
31 | | #include <unordered_map> |
32 | | #include <unordered_set> |
33 | | #include <utility> |
34 | | #include <vector> |
35 | | |
36 | | #include "common/consts.h" |
37 | | #include "common/status.h" |
38 | | #include "olap/inverted_index_parser.h" |
39 | | #include "olap/metadata_adder.h" |
40 | | #include "olap/olap_common.h" |
41 | | #include "olap/rowset/segment_v2/options.h" |
42 | | #include "runtime/define_primitive_type.h" |
43 | | #include "runtime/descriptors.h" |
44 | | #include "runtime/memory/lru_cache_policy.h" |
45 | | #include "util/debug_points.h" |
46 | | #include "util/string_parser.hpp" |
47 | | #include "util/string_util.h" |
48 | | #include "vec/aggregate_functions/aggregate_function.h" |
49 | | #include "vec/common/string_ref.h" |
50 | | #include "vec/common/string_utils/string_utils.h" |
51 | | #include "vec/core/types.h" |
52 | | #include "vec/json/path_in_data.h" |
53 | | |
54 | | namespace doris { |
55 | | namespace vectorized { |
56 | | class Block; |
57 | | class PathInData; |
58 | | class IDataType; |
59 | | } // namespace vectorized |
60 | | |
61 | | #include "common/compile_check_begin.h" |
62 | | |
63 | | struct OlapTableIndexSchema; |
64 | | class TColumn; |
65 | | class TOlapTableIndex; |
66 | | class TabletColumn; |
67 | | |
68 | | using TabletColumnPtr = std::shared_ptr<TabletColumn>; |
69 | | |
70 | | class TabletColumn : public MetadataAdder<TabletColumn> { |
71 | | public: |
72 | | struct VariantParams { |
73 | | int32_t max_subcolumns_count = 0; |
74 | | bool enable_typed_paths_to_sparse = false; |
75 | | int32_t max_sparse_column_statistics_size = |
76 | | BeConsts::DEFAULT_VARIANT_MAX_SPARSE_COLUMN_STATS_SIZE; |
77 | | // default to 0, no shard |
78 | | int32_t sparse_hash_shard_count = 0; |
79 | | |
80 | | bool enable_doc_mode = false; |
81 | | int64_t doc_materialization_min_rows = 0; |
82 | | int32_t doc_hash_shard_count = 64; |
83 | | }; |
84 | | |
85 | | TabletColumn(); |
86 | | TabletColumn(const ColumnPB& column); |
87 | | TabletColumn(const TColumn& column); |
88 | | TabletColumn(FieldAggregationMethod agg, FieldType type); |
89 | | TabletColumn(FieldAggregationMethod agg, FieldType filed_type, bool is_nullable); |
90 | | TabletColumn(FieldAggregationMethod agg, FieldType filed_type, bool is_nullable, |
91 | | int32_t unique_id, size_t length); |
92 | | |
93 | | #ifdef BE_TEST |
94 | 146k | virtual ~TabletColumn() = default; |
95 | | #endif |
96 | | |
97 | | void init_from_pb(const ColumnPB& column); |
98 | | void init_from_thrift(const TColumn& column); |
99 | | void to_schema_pb(ColumnPB* column) const; |
100 | | |
101 | 311k | int32_t unique_id() const { return _unique_id; } |
102 | 1.52k | void set_unique_id(int32_t id) { _unique_id = id; } |
103 | 271k | const std::string& name() const { return _col_name; } |
104 | 22.4k | const std::string& name_lower_case() const { return _col_name_lower_case; } |
105 | 4.54k | void set_name(std::string col_name) { |
106 | 4.54k | _col_name = col_name; |
107 | 4.54k | _col_name_lower_case = to_lower(_col_name); |
108 | 4.54k | } |
109 | 1.21M | MOCK_FUNCTION FieldType type() const { return _type; } |
110 | 4.85k | void set_type(FieldType type) { _type = type; } |
111 | 141k | bool is_key() const { return _is_key; } |
112 | 214k | bool is_nullable() const { return _is_nullable; } |
113 | 0 | bool is_auto_increment() const { return _is_auto_increment; } |
114 | 0 | bool is_seqeunce_col() const { return _col_name == SEQUENCE_COL; } |
115 | 0 | bool is_on_update_current_timestamp() const { return _is_on_update_current_timestamp; } |
116 | 84.3k | bool is_variant_type() const { return _type == FieldType::OLAP_FIELD_TYPE_VARIANT; } |
117 | 18.6k | bool is_bf_column() const { return _is_bf_column; } |
118 | 55.8k | bool is_array_type() const { return _type == FieldType::OLAP_FIELD_TYPE_ARRAY; } |
119 | 12.5k | bool is_agg_state_type() const { return _type == FieldType::OLAP_FIELD_TYPE_AGG_STATE; } |
120 | 0 | bool is_jsonb_type() const { return _type == FieldType::OLAP_FIELD_TYPE_JSONB; } |
121 | 0 | bool is_length_variable_type() const { |
122 | 0 | return _type == FieldType::OLAP_FIELD_TYPE_CHAR || |
123 | 0 | _type == FieldType::OLAP_FIELD_TYPE_VARCHAR || |
124 | 0 | _type == FieldType::OLAP_FIELD_TYPE_STRING || |
125 | 0 | _type == FieldType::OLAP_FIELD_TYPE_HLL || |
126 | 0 | _type == FieldType::OLAP_FIELD_TYPE_BITMAP || |
127 | 0 | _type == FieldType::OLAP_FIELD_TYPE_QUANTILE_STATE || |
128 | 0 | _type == FieldType::OLAP_FIELD_TYPE_AGG_STATE; |
129 | 0 | } |
130 | | // Such columns are not exist in frontend schema info, so we need to |
131 | | // add them into tablet_schema for later column indexing. |
132 | | static TabletColumn create_materialized_variant_column(const std::string& root, |
133 | | const std::vector<std::string>& paths, |
134 | | int32_t parent_unique_id, |
135 | | int32_t max_subcolumns_count); |
136 | 193 | bool has_default_value() const { return _has_default_value; } |
137 | 17.9k | std::string default_value() const { return _default_value; } |
138 | 211k | int32_t length() const { return _length; } |
139 | 2.28k | void set_length(int32_t length) { _length = length; } |
140 | 656 | void set_default_value(const std::string& default_value) { |
141 | 656 | _default_value = default_value; |
142 | 656 | _has_default_value = true; |
143 | 656 | } |
144 | 75.9k | int32_t index_length() const { return _index_length; } |
145 | 1.59k | void set_index_length(int32_t index_length) { _index_length = index_length; } |
146 | 1.30k | void set_is_key(bool is_key) { _is_key = is_key; } |
147 | 2.33k | void set_is_nullable(bool is_nullable) { _is_nullable = is_nullable; } |
148 | 0 | void set_is_auto_increment(bool is_auto_increment) { _is_auto_increment = is_auto_increment; } |
149 | 0 | void set_is_on_update_current_timestamp(bool is_on_update_current_timestamp) { |
150 | 0 | _is_on_update_current_timestamp = is_on_update_current_timestamp; |
151 | 0 | } |
152 | | void set_path_info(const vectorized::PathInData& path); |
153 | 67.0k | FieldAggregationMethod aggregation() const { return _aggregation; } |
154 | | vectorized::AggregateFunctionPtr get_aggregate_function_union( |
155 | | vectorized::DataTypePtr type, int current_be_exec_version) const; |
156 | | vectorized::AggregateFunctionPtr get_aggregate_function(std::string suffix, |
157 | | int current_be_exec_version) const; |
158 | 139k | int precision() const { return _precision; } |
159 | 139k | int frac() const { return _frac; } |
160 | 2 | inline bool visible() const { return _visible; } |
161 | | bool has_char_type() const; |
162 | | |
163 | 1.72k | void set_aggregation_method(FieldAggregationMethod agg) { |
164 | 1.72k | _aggregation = agg; |
165 | 1.72k | _aggregation_name = get_string_by_aggregation_type(agg); |
166 | 1.72k | } |
167 | | |
168 | | /** |
169 | | * Add a sub column. |
170 | | */ |
171 | | void add_sub_column(TabletColumn& sub_column); |
172 | | |
173 | 20.6k | uint32_t get_subtype_count() const { return _sub_column_count; } |
174 | 3.40k | MOCK_FUNCTION const TabletColumn& get_sub_column(uint64_t i) const { return *_sub_columns[i]; } |
175 | 1.04k | const std::vector<TabletColumnPtr>& get_sub_columns() const { return _sub_columns; } |
176 | | |
177 | | friend bool operator==(const TabletColumn& a, const TabletColumn& b); |
178 | | friend bool operator!=(const TabletColumn& a, const TabletColumn& b); |
179 | | |
180 | | static std::string get_string_by_field_type(FieldType type); |
181 | | static std::string get_string_by_aggregation_type(FieldAggregationMethod aggregation_type); |
182 | | static FieldType get_field_type_by_string(const std::string& str); |
183 | | static FieldType get_field_type_by_type(PrimitiveType type); |
184 | | static PrimitiveType get_primitive_type_by_field_type(FieldType type); |
185 | | static FieldAggregationMethod get_aggregation_type_by_string(const std::string& str); |
186 | | static uint32_t get_field_length_by_type(TPrimitiveType::type type, uint32_t string_length); |
187 | | bool is_row_store_column() const; |
188 | 15.9k | std::string get_aggregation_name() const { return _aggregation_name; } |
189 | 15.9k | bool get_result_is_nullable() const { return _result_is_nullable; } |
190 | 16.0k | int get_be_exec_version() const { return _be_exec_version; } |
191 | 76.9k | bool has_path_info() const { return _column_path != nullptr && !_column_path->empty(); } |
192 | 91.9k | const vectorized::PathInDataPtr& path_info_ptr() const { return _column_path; } |
193 | | // If it is an extracted column from variant column |
194 | 237k | bool is_extracted_column() const { |
195 | 237k | return _column_path != nullptr && !_column_path->empty() && _parent_col_unique_id > 0; |
196 | 237k | }; |
197 | 28.6k | std::string suffix_path() const { |
198 | 28.6k | return is_extracted_column() ? _column_path->get_path() : ""; |
199 | 28.6k | } |
200 | 5 | bool is_nested_subcolumn() const { |
201 | 5 | return _column_path != nullptr && _column_path->has_nested_part(); |
202 | 5 | } |
203 | 75.1k | int32_t parent_unique_id() const { return _parent_col_unique_id; } |
204 | 1.79k | void set_parent_unique_id(int32_t col_unique_id) { _parent_col_unique_id = col_unique_id; } |
205 | 1.02k | void set_is_bf_column(bool is_bf_column) { _is_bf_column = is_bf_column; } |
206 | | std::shared_ptr<const vectorized::IDataType> get_vec_type() const; |
207 | | |
208 | 653 | Status check_valid() const { |
209 | 653 | if (type() != FieldType::OLAP_FIELD_TYPE_ARRAY && |
210 | 653 | type() != FieldType::OLAP_FIELD_TYPE_STRUCT && |
211 | 653 | type() != FieldType::OLAP_FIELD_TYPE_MAP) { |
212 | 653 | return Status::OK(); |
213 | 653 | } |
214 | 0 | if (is_bf_column()) { |
215 | 0 | return Status::NotSupported("Do not support bloom filter index, type={}", |
216 | 0 | get_string_by_field_type(type())); |
217 | 0 | } |
218 | 0 | return Status::OK(); |
219 | 0 | } |
220 | | |
221 | 2 | void set_precision(int precision) { |
222 | 2 | _precision = precision; |
223 | 2 | _is_decimal = true; |
224 | 2 | } |
225 | | |
226 | 33 | void set_frac(int frac) { _frac = frac; } |
227 | | |
228 | 0 | const VariantParams& variant_params() const { return _variant; } |
229 | 0 | VariantParams* mutable_variant_params() { return &_variant; } |
230 | | |
231 | 2.12k | int32_t variant_max_subcolumns_count() const { return _variant.max_subcolumns_count; } |
232 | | |
233 | 69 | void set_variant_max_subcolumns_count(int32_t variant_max_subcolumns_count) { |
234 | 69 | _variant.max_subcolumns_count = variant_max_subcolumns_count; |
235 | 69 | } |
236 | | |
237 | 94 | PatternTypePB pattern_type() const { return _pattern_type; } |
238 | | |
239 | 402 | bool variant_enable_typed_paths_to_sparse() const { |
240 | 402 | return _variant.enable_typed_paths_to_sparse; |
241 | 402 | } |
242 | | |
243 | 20.7k | int32_t variant_max_sparse_column_statistics_size() const { |
244 | 20.7k | return _variant.max_sparse_column_statistics_size; |
245 | 20.7k | } |
246 | | |
247 | 315 | int32_t variant_sparse_hash_shard_count() const { return _variant.sparse_hash_shard_count; } |
248 | | |
249 | 593 | bool variant_enable_doc_mode() const { return _variant.enable_doc_mode; } |
250 | | |
251 | 1 | int64_t variant_doc_materialization_min_rows() const { |
252 | 1 | return _variant.doc_materialization_min_rows; |
253 | 1 | } |
254 | | |
255 | 2 | int32_t variant_doc_hash_shard_count() const { return _variant.doc_hash_shard_count; } |
256 | | |
257 | 0 | void set_variant_doc_materialization_min_rows(int64_t variant_doc_materialization_min_rows) { |
258 | 0 | _variant.doc_materialization_min_rows = variant_doc_materialization_min_rows; |
259 | 0 | } |
260 | | |
261 | 0 | void set_variant_doc_hash_shard_count(int32_t variant_doc_hash_shard_count) { |
262 | 0 | _variant.doc_hash_shard_count = variant_doc_hash_shard_count; |
263 | 0 | } |
264 | | |
265 | | void set_variant_max_sparse_column_statistics_size( |
266 | 2 | int32_t variant_max_sparse_column_statistics_size) { |
267 | 2 | _variant.max_sparse_column_statistics_size = variant_max_sparse_column_statistics_size; |
268 | 2 | } |
269 | | |
270 | 0 | void set_variant_sparse_hash_shard_count(int32_t variant_sparse_hash_shard_count) { |
271 | 0 | _variant.sparse_hash_shard_count = variant_sparse_hash_shard_count; |
272 | 0 | } |
273 | | |
274 | 0 | void set_variant_enable_doc_mode(bool variant_enable_doc_mode) { |
275 | 0 | _variant.enable_doc_mode = variant_enable_doc_mode; |
276 | 0 | } |
277 | | |
278 | 1 | void set_variant_enable_typed_paths_to_sparse(bool variant_enable_typed_paths_to_sparse) { |
279 | 1 | _variant.enable_typed_paths_to_sparse = variant_enable_typed_paths_to_sparse; |
280 | 1 | } |
281 | | |
282 | 31 | bool is_decimal() const { return _is_decimal; } |
283 | | |
284 | | private: |
285 | | int32_t _unique_id = -1; |
286 | | std::string _col_name; |
287 | | std::string _col_name_lower_case; |
288 | | // the field _type will change from TPrimitiveType |
289 | | // to string by 'EnumToString(TPrimitiveType, tcolumn.column_type.type, data_type);' (reference: TabletMeta::init_column_from_tcolumn) |
290 | | // to FieldType by 'TabletColumn::get_field_type_by_string' (reference: TabletColumn::init_from_pb). |
291 | | // And the _type in columnPB is string and it changed from FieldType by 'get_string_by_field_type' (reference: TabletColumn::to_schema_pb). |
292 | | FieldType _type; |
293 | | bool _is_key = false; |
294 | | FieldAggregationMethod _aggregation; |
295 | | std::string _aggregation_name; |
296 | | bool _is_nullable = false; |
297 | | bool _is_auto_increment = false; |
298 | | bool _is_on_update_current_timestamp {false}; |
299 | | |
300 | | bool _has_default_value = false; |
301 | | std::string _default_value; |
302 | | |
303 | | bool _is_decimal = false; |
304 | | int32_t _precision = -1; |
305 | | int32_t _frac = -1; |
306 | | |
307 | | int32_t _length = -1; |
308 | | int32_t _index_length = -1; |
309 | | |
310 | | bool _is_bf_column = false; |
311 | | |
312 | | bool _visible = true; |
313 | | |
314 | | std::vector<TabletColumnPtr> _sub_columns; |
315 | | uint32_t _sub_column_count = 0; |
316 | | |
317 | | bool _result_is_nullable = false; |
318 | | int _be_exec_version = -1; |
319 | | |
320 | | // The extracted sub-columns from "variant" contain the following information: |
321 | | int32_t _parent_col_unique_id = -1; // "variant" -> col_unique_id |
322 | | vectorized::PathInDataPtr _column_path; // the path of the sub-columns themselves |
323 | | PatternTypePB _pattern_type = PatternTypePB::MATCH_NAME_GLOB; |
324 | | |
325 | | VariantParams _variant; |
326 | | }; |
327 | | |
328 | | bool operator==(const TabletColumn& a, const TabletColumn& b); |
329 | | bool operator!=(const TabletColumn& a, const TabletColumn& b); |
330 | | |
331 | | class TabletIndex : public MetadataAdder<TabletIndex> { |
332 | | public: |
333 | 7.61k | TabletIndex() = default; |
334 | | void init_from_thrift(const TOlapTableIndex& index, const TabletSchema& tablet_schema); |
335 | | void init_from_thrift(const TOlapTableIndex& index, const std::vector<int32_t>& column_uids); |
336 | | void init_from_pb(const TabletIndexPB& index); |
337 | | void to_schema_pb(TabletIndexPB* index) const; |
338 | | |
339 | 19.1k | int64_t index_id() const { return _index_id; } |
340 | 25 | const std::string& index_name() const { return _index_name; } |
341 | 12.2k | MOCK_FUNCTION IndexType index_type() const { return _index_type; } |
342 | 9.59k | const std::vector<int32_t>& col_unique_ids() const { return _col_unique_ids; } |
343 | 23.9k | MOCK_FUNCTION const std::map<std::string, std::string>& properties() const { |
344 | 23.9k | return _properties; |
345 | 23.9k | } |
346 | 1 | int32_t get_gram_size() const { |
347 | 1 | if (_properties.contains("gram_size")) { |
348 | 1 | return std::stoi(_properties.at("gram_size")); |
349 | 1 | } |
350 | | |
351 | 0 | return 0; |
352 | 1 | } |
353 | 1 | int32_t get_gram_bf_size() const { |
354 | 1 | if (_properties.contains("bf_size")) { |
355 | 1 | return std::stoi(_properties.at("bf_size")); |
356 | 1 | } |
357 | | |
358 | 0 | return 0; |
359 | 1 | } |
360 | | |
361 | 15.9k | const std::string& get_index_suffix() const { return _escaped_index_suffix_path; } |
362 | | |
363 | | void set_escaped_escaped_index_suffix_path(const std::string& name); |
364 | | |
365 | 2.28k | bool is_inverted_index() const { return _index_type == IndexType::INVERTED; } |
366 | | |
367 | 2 | bool is_ann_index() const { return _index_type == IndexType::ANN; } |
368 | | |
369 | 8 | void remove_parser_and_analyzer() { |
370 | 8 | _properties.erase(INVERTED_INDEX_PARSER_KEY); |
371 | 8 | _properties.erase(INVERTED_INDEX_PARSER_KEY_ALIAS); |
372 | 8 | _properties.erase(INVERTED_INDEX_ANALYZER_NAME_KEY); |
373 | 8 | _properties.erase(INVERTED_INDEX_NORMALIZER_NAME_KEY); |
374 | 8 | } |
375 | | |
376 | 7.49k | std::string field_pattern() const { |
377 | 7.49k | if (_properties.contains("field_pattern")) { |
378 | 8 | return _properties.at("field_pattern"); |
379 | 8 | } |
380 | 7.48k | return ""; |
381 | 7.49k | } |
382 | | |
383 | 8 | bool is_same_except_id(const TabletIndex* other) const { |
384 | 8 | return _escaped_index_suffix_path == other->_escaped_index_suffix_path && |
385 | 8 | _index_name == other->_index_name && _index_type == other->_index_type && |
386 | 8 | _col_unique_ids == other->_col_unique_ids && _properties == other->_properties; |
387 | 8 | } |
388 | | |
389 | | private: |
390 | | int64_t _index_id = -1; |
391 | | // Identify the different index with the same _index_id |
392 | | std::string _escaped_index_suffix_path; |
393 | | std::string _index_name; |
394 | | IndexType _index_type; |
395 | | std::vector<int32_t> _col_unique_ids; |
396 | | std::map<std::string, std::string> _properties; |
397 | | }; |
398 | | |
399 | | using TabletIndexPtr = std::shared_ptr<TabletIndex>; |
400 | | using TabletIndexes = std::vector<std::shared_ptr<TabletIndex>>; |
401 | | using PathSet = phmap::flat_hash_set<std::string>; |
402 | | |
403 | | class TabletSchema : public MetadataAdder<TabletSchema> { |
404 | | public: |
405 | | enum class ColumnType { NORMAL = 0, DROPPED = 1, VARIANT = 2 }; |
406 | | // TODO(yingchun): better to make constructor as private to avoid |
407 | | // manually init members incorrectly, and define a new function like |
408 | | // void create_from_pb(const TabletSchemaPB& schema, TabletSchema* tablet_schema). |
409 | | TabletSchema(); |
410 | | ~TabletSchema() override; |
411 | | |
412 | | // Init from pb |
413 | | // ignore_extracted_columns: ignore the extracted columns from variant column |
414 | | // reuse_cached_column: reuse the cached column in the schema if they are the same, to reduce memory usage |
415 | | void init_from_pb(const TabletSchemaPB& schema, bool ignore_extracted_columns = false, |
416 | | bool reuse_cached_column = false); |
417 | | // Notice: Use deterministic way to serialize protobuf, |
418 | | // since serialize Map in protobuf may could lead to un-deterministic by default |
419 | | template <class PbType> |
420 | 7.43k | static std::string deterministic_string_serialize(const PbType& pb) { |
421 | 7.43k | std::string output; |
422 | 7.43k | google::protobuf::io::StringOutputStream string_output_stream(&output); |
423 | 7.43k | google::protobuf::io::CodedOutputStream output_stream(&string_output_stream); |
424 | 7.43k | output_stream.SetSerializationDeterministic(true); |
425 | 7.43k | pb.SerializeToCodedStream(&output_stream); |
426 | 7.43k | return output; |
427 | 7.43k | } _ZN5doris12TabletSchema30deterministic_string_serializeINS_14TabletSchemaPBEEENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_ Line | Count | Source | 420 | 6.93k | static std::string deterministic_string_serialize(const PbType& pb) { | 421 | 6.93k | std::string output; | 422 | 6.93k | google::protobuf::io::StringOutputStream string_output_stream(&output); | 423 | 6.93k | google::protobuf::io::CodedOutputStream output_stream(&string_output_stream); | 424 | 6.93k | output_stream.SetSerializationDeterministic(true); | 425 | 6.93k | pb.SerializeToCodedStream(&output_stream); | 426 | 6.93k | return output; | 427 | 6.93k | } |
_ZN5doris12TabletSchema30deterministic_string_serializeINS_8ColumnPBEEENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_ Line | Count | Source | 420 | 345 | static std::string deterministic_string_serialize(const PbType& pb) { | 421 | 345 | std::string output; | 422 | 345 | google::protobuf::io::StringOutputStream string_output_stream(&output); | 423 | 345 | google::protobuf::io::CodedOutputStream output_stream(&string_output_stream); | 424 | 345 | output_stream.SetSerializationDeterministic(true); | 425 | 345 | pb.SerializeToCodedStream(&output_stream); | 426 | 345 | return output; | 427 | 345 | } |
_ZN5doris12TabletSchema30deterministic_string_serializeINS_13TabletIndexPBEEENSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_ Line | Count | Source | 420 | 163 | static std::string deterministic_string_serialize(const PbType& pb) { | 421 | 163 | std::string output; | 422 | 163 | google::protobuf::io::StringOutputStream string_output_stream(&output); | 423 | 163 | google::protobuf::io::CodedOutputStream output_stream(&string_output_stream); | 424 | 163 | output_stream.SetSerializationDeterministic(true); | 425 | 163 | pb.SerializeToCodedStream(&output_stream); | 426 | 163 | return output; | 427 | 163 | } |
|
428 | | void to_schema_pb(TabletSchemaPB* tablet_meta_pb) const; |
429 | | void append_column(TabletColumn column, ColumnType col_type = ColumnType::NORMAL); |
430 | | void append_index(TabletIndex&& index); |
431 | | void remove_index(int64_t index_id); |
432 | | void clear_index(); |
433 | | // Must make sure the row column is always the last column |
434 | | void add_row_column(); |
435 | | void copy_from(const TabletSchema& tablet_schema); |
436 | | // lightweight copy, take care of lifecycle of TabletColumn |
437 | | void shawdow_copy_without_columns(const TabletSchema& tablet_schema); |
438 | | void update_index_info_from(const TabletSchema& tablet_schema); |
439 | | std::string to_key() const; |
440 | | // get_metadata_size is only the memory of the TabletSchema itself, not include child objects. |
441 | 70 | int64_t mem_size() const { return get_metadata_size(); } |
442 | | size_t row_size() const; |
443 | | int32_t field_index(const std::string& field_name) const; |
444 | | int32_t field_index(const vectorized::PathInData& path) const; |
445 | | int32_t field_index(int32_t col_unique_id) const; |
446 | | const TabletColumn& column(size_t ordinal) const; |
447 | | Result<const TabletColumn*> column(const std::string& field_name) const; |
448 | | Status have_column(const std::string& field_name) const; |
449 | | bool exist_column(const std::string& field_name) const; |
450 | | bool has_column_unique_id(int32_t col_unique_id) const; |
451 | | const TabletColumn& column_by_uid(int32_t col_unique_id) const; |
452 | | TabletColumn& mutable_column_by_uid(int32_t col_unique_id); |
453 | | TabletColumn& mutable_column(size_t ordinal); |
454 | | void replace_column(size_t pos, TabletColumn new_col); |
455 | | const std::vector<TabletColumnPtr>& columns() const; |
456 | 794k | size_t num_columns() const { return _num_columns; } |
457 | 1.08M | size_t num_key_columns() const { return _num_key_columns; } |
458 | 136k | const std::vector<uint32_t>& cluster_key_uids() const { return _cluster_key_uids; } |
459 | 0 | size_t num_null_columns() const { return _num_null_columns; } |
460 | 5.37k | size_t num_short_key_columns() const { return _num_short_key_columns; } |
461 | 0 | size_t num_rows_per_row_block() const { return _num_rows_per_row_block; } |
462 | 10.4k | size_t num_variant_columns() const { return _num_variant_columns; }; |
463 | 0 | size_t num_virtual_columns() const { return _num_virtual_columns; } |
464 | 7.12M | KeysType keys_type() const { return _keys_type; } |
465 | 5.62k | SortType sort_type() const { return _sort_type; } |
466 | 0 | size_t sort_col_num() const { return _sort_col_num; } |
467 | 0 | CompressKind compress_kind() const { return _compress_kind; } |
468 | 0 | size_t next_column_unique_id() const { return _next_column_unique_id; } |
469 | 4 | bool has_bf_fpp() const { return _has_bf_fpp; } |
470 | 4 | double bloom_filter_fpp() const { return _bf_fpp; } |
471 | 15.7k | bool is_in_memory() const { return _is_in_memory; } |
472 | 0 | void set_is_in_memory(bool is_in_memory) { _is_in_memory = is_in_memory; } |
473 | 2 | void set_disable_auto_compaction(bool disable_auto_compaction) { |
474 | 2 | _disable_auto_compaction = disable_auto_compaction; |
475 | 2 | } |
476 | 288 | bool disable_auto_compaction() const { return _disable_auto_compaction; } |
477 | 0 | void set_enable_variant_flatten_nested(bool flatten_nested) { |
478 | 0 | _enable_variant_flatten_nested = flatten_nested; |
479 | 0 | } |
480 | 271 | bool variant_flatten_nested() const { return _enable_variant_flatten_nested; } |
481 | 0 | void set_enable_single_replica_compaction(bool enable_single_replica_compaction) { |
482 | 0 | _enable_single_replica_compaction = enable_single_replica_compaction; |
483 | 0 | } |
484 | 356 | bool enable_single_replica_compaction() const { return _enable_single_replica_compaction; } |
485 | | // indicate if full row store column(all the columns encodes as row) exists |
486 | 0 | bool has_row_store_for_all_columns() const { |
487 | 0 | return _store_row_column && row_columns_uids().empty(); |
488 | 0 | } |
489 | 0 | void set_skip_write_index_on_load(bool skip) { _skip_write_index_on_load = skip; } |
490 | 73 | bool skip_write_index_on_load() const { return _skip_write_index_on_load; } |
491 | 8.20k | int32_t delete_sign_idx() const { return _delete_sign_idx; } |
492 | 143k | bool has_sequence_col() const { return _sequence_col_idx != -1; } |
493 | 64.7k | int32_t sequence_col_idx() const { return _sequence_col_idx; } |
494 | 0 | void set_version_col_idx(int32_t version_col_idx) { _version_col_idx = version_col_idx; } |
495 | 0 | int32_t version_col_idx() const { return _version_col_idx; } |
496 | 0 | bool has_skip_bitmap_col() const { return _skip_bitmap_col_idx != -1; } |
497 | 0 | int32_t skip_bitmap_col_idx() const { return _skip_bitmap_col_idx; } |
498 | 5.25k | segment_v2::CompressionTypePB compression_type() const { return _compression_type; } |
499 | 0 | void set_row_store_page_size(long page_size) { _row_store_page_size = page_size; } |
500 | 0 | long row_store_page_size() const { return _row_store_page_size; } |
501 | 0 | void set_storage_page_size(long storage_page_size) { _storage_page_size = storage_page_size; } |
502 | 15.9k | long storage_page_size() const { return _storage_page_size; } |
503 | 0 | void set_storage_dict_page_size(long storage_dict_page_size) { |
504 | 0 | _storage_dict_page_size = storage_dict_page_size; |
505 | 0 | } |
506 | 15.9k | long storage_dict_page_size() const { return _storage_dict_page_size; } |
507 | 0 | bool has_global_row_id() const { |
508 | 0 | for (auto [col_name, _] : _field_name_to_index) { |
509 | 0 | if (col_name.start_with(StringRef(BeConsts::GLOBAL_ROWID_COL.data(), |
510 | 0 | BeConsts::GLOBAL_ROWID_COL.size()))) { |
511 | 0 | return true; |
512 | 0 | } |
513 | 0 | } |
514 | 0 | return false; |
515 | 0 | } |
516 | | |
517 | 121 | const std::vector<const TabletIndex*> inverted_indexes() const { |
518 | 121 | std::vector<const TabletIndex*> inverted_indexes; |
519 | 1.26k | for (const auto& index : _indexes) { |
520 | 1.26k | if (index->index_type() == IndexType::INVERTED) { |
521 | 1.25k | inverted_indexes.emplace_back(index.get()); |
522 | 1.25k | } |
523 | 1.26k | } |
524 | 121 | return inverted_indexes; |
525 | 121 | } |
526 | 12.1k | bool has_inverted_index() const { |
527 | 12.1k | for (const auto& index : _indexes) { |
528 | 837 | DBUG_EXECUTE_IF("tablet_schema::has_inverted_index", { |
529 | 837 | if (index->col_unique_ids().empty()) { |
530 | 837 | throw Exception(Status::InternalError("col unique ids cannot be empty")); |
531 | 837 | } |
532 | 837 | }); |
533 | | |
534 | 837 | if (index->index_type() == IndexType::INVERTED) { |
535 | | //if index_id == -1, ignore it. |
536 | 829 | if (!index->col_unique_ids().empty() && index->col_unique_ids()[0] >= 0) { |
537 | 829 | return true; |
538 | 829 | } |
539 | 829 | } |
540 | 837 | } |
541 | 11.2k | return false; |
542 | 12.1k | } |
543 | | |
544 | 10.7k | bool has_ann_index() const { |
545 | 10.7k | for (const auto& index : _indexes) { |
546 | 7 | if (index->index_type() == IndexType::ANN) { |
547 | 5 | if (!index->col_unique_ids().empty() && index->col_unique_ids()[0] >= 0) { |
548 | 5 | return true; |
549 | 5 | } |
550 | 5 | } |
551 | 7 | } |
552 | 10.7k | return false; |
553 | 10.7k | } |
554 | | |
555 | | bool has_inverted_index_with_index_id(int64_t index_id) const; |
556 | | |
557 | | std::vector<const TabletIndex*> inverted_indexs(const TabletColumn& col) const; |
558 | | |
559 | | std::vector<const TabletIndex*> inverted_indexs(int32_t col_unique_id, |
560 | | const std::string& suffix_path = "") const; |
561 | | const TabletIndex* ann_index(const TabletColumn& col) const; |
562 | | |
563 | | // Regardless of whether this column supports inverted index |
564 | | // TabletIndex information will be returned as long as it exists. |
565 | | const TabletIndex* ann_index(int32_t col_unique_id, const std::string& suffix_path = "") const; |
566 | | |
567 | | std::vector<TabletIndexPtr> inverted_index_by_field_pattern( |
568 | | int32_t col_unique_id, const std::string& field_pattern) const; |
569 | | |
570 | | bool has_ngram_bf_index(int32_t col_unique_id) const; |
571 | | const TabletIndex* get_ngram_bf_index(int32_t col_unique_id) const; |
572 | | const TabletIndex* get_index(int32_t col_unique_id, IndexType index_type, |
573 | | const std::string& suffix_path) const; |
574 | | void update_indexes_from_thrift(const std::vector<doris::TOlapTableIndex>& indexes); |
575 | | // If schema version is not set, it should be -1 |
576 | 7.45k | int32_t schema_version() const { return _schema_version; } |
577 | | void clear_columns(); |
578 | | vectorized::Block create_block( |
579 | | const std::vector<uint32_t>& return_columns, |
580 | | const std::unordered_set<uint32_t>* tablet_columns_need_convert_null = nullptr) const; |
581 | | vectorized::Block create_block(bool ignore_dropped_col = true) const; |
582 | 2 | void set_schema_version(int32_t version) { _schema_version = version; } |
583 | 0 | void set_auto_increment_column(const std::string& auto_increment_column) { |
584 | 0 | _auto_increment_column = auto_increment_column; |
585 | 0 | } |
586 | 0 | std::string auto_increment_column() const { return _auto_increment_column; } |
587 | | |
588 | 28 | void set_table_id(int64_t table_id) { _table_id = table_id; } |
589 | 495 | int64_t table_id() const { return _table_id; } |
590 | 28 | void set_db_id(int64_t db_id) { _db_id = db_id; } |
591 | 0 | int64_t db_id() const { return _db_id; } |
592 | | void build_current_tablet_schema(int64_t index_id, int32_t version, |
593 | | const OlapTableIndexSchema* index, |
594 | | const TabletSchema& out_tablet_schema); |
595 | | |
596 | | // Merge columns that not exit in current schema, these column is dropped in current schema |
597 | | // but they are useful in some cases. For example, |
598 | | // 1. origin schema is ColA, ColB |
599 | | // 2. insert values 1, 2 |
600 | | // 3. delete where ColB = 2 |
601 | | // 4. drop ColB |
602 | | // 5. insert values 3 |
603 | | // 6. add column ColB, although it is name ColB, but it is different with previous ColB, the new ColB we name could call ColB' |
604 | | // 7. insert value 4, 5 |
605 | | // Then the read schema should be ColA, ColB, ColB' because the delete predicate need ColB to remove related data. |
606 | | // Because they have same name, so that the dropped column should not be added to the map, only with unique id. |
607 | | void merge_dropped_columns(const TabletSchema& src_schema); |
608 | | |
609 | | bool is_dropped_column(const TabletColumn& col) const; |
610 | | |
611 | | // copy extracted columns from src_schema |
612 | | void copy_extracted_columns(const TabletSchema& src_schema); |
613 | | |
614 | | // only reserve extracted columns |
615 | | void reserve_extracted_columns(); |
616 | | |
617 | 4.04k | std::string get_all_field_names() const { |
618 | 4.04k | std::string str = "["; |
619 | 4.04k | for (auto p : _field_name_to_index) { |
620 | 4.04k | if (str.size() > 1) { |
621 | 0 | str += ", "; |
622 | 0 | } |
623 | 4.04k | str += p.first.to_string() + "(" + std::to_string(_cols[p.second]->unique_id()) + ")"; |
624 | 4.04k | } |
625 | 4.04k | str += "]"; |
626 | 4.04k | return str; |
627 | 4.04k | } |
628 | | |
629 | | // Dump [(name, type, is_nullable), ...] |
630 | 1 | std::string dump_structure() const { |
631 | 1 | std::string str = "["; |
632 | 15 | for (auto p : _cols) { |
633 | 15 | if (str.size() > 1) { |
634 | 14 | str += ", "; |
635 | 14 | } |
636 | 15 | str += "("; |
637 | 15 | str += p->name(); |
638 | 15 | str += ", "; |
639 | 15 | str += TabletColumn::get_string_by_field_type(p->type()); |
640 | 15 | str += ", "; |
641 | 15 | str += "is_nullable:"; |
642 | 15 | str += (p->is_nullable() ? "true" : "false"); |
643 | 15 | str += ")"; |
644 | 15 | } |
645 | 1 | str += "]"; |
646 | 1 | return str; |
647 | 1 | } |
648 | | |
649 | 1 | std::string dump_full_schema() const { |
650 | 1 | std::string str = "["; |
651 | 4 | for (auto p : _cols) { |
652 | 4 | if (str.size() > 1) { |
653 | 3 | str += ", "; |
654 | 3 | } |
655 | 4 | ColumnPB col_pb; |
656 | 4 | p->to_schema_pb(&col_pb); |
657 | 4 | str += "("; |
658 | 4 | str += col_pb.ShortDebugString(); |
659 | 4 | str += ")"; |
660 | 4 | } |
661 | 1 | str += "]"; |
662 | 1 | return str; |
663 | 1 | } |
664 | | |
665 | | vectorized::Block create_block_by_cids(const std::vector<uint32_t>& cids) const; |
666 | | |
667 | | std::shared_ptr<TabletSchema> copy_without_variant_extracted_columns(); |
668 | 9.49k | InvertedIndexStorageFormatPB get_inverted_index_storage_format() const { |
669 | 9.49k | return _inverted_index_storage_format; |
670 | 9.49k | } |
671 | | |
672 | | void update_tablet_columns(const TabletSchema& tablet_schema, |
673 | | const std::vector<TColumn>& t_columns); |
674 | | |
675 | 0 | const std::vector<int32_t>& row_columns_uids() const { return _row_store_column_unique_ids; } |
676 | | |
677 | | int64_t get_metadata_size() const override; |
678 | | |
679 | | struct SubColumnInfo { |
680 | | TabletColumn column; |
681 | | TabletIndexes indexes; |
682 | | }; |
683 | | |
684 | | // all path in path_set_info are relative to the parent column |
685 | | struct PathsSetInfo { |
686 | | std::unordered_map<std::string, SubColumnInfo> typed_path_set; // typed columns |
687 | | std::unordered_map<std::string, TabletIndexes> subcolumn_indexes; // subcolumns indexes |
688 | | PathSet sub_path_set; // extracted columns |
689 | | PathSet sparse_path_set; // sparse columns |
690 | | }; |
691 | | |
692 | 41 | void set_path_set_info(std::unordered_map<int32_t, PathsSetInfo>&& path_set_info_map) { |
693 | 41 | _path_set_info_map = std::move(path_set_info_map); |
694 | 41 | } |
695 | | |
696 | 2 | const PathsSetInfo& path_set_info(int32_t unique_id) const { |
697 | 2 | return _path_set_info_map.at(unique_id); |
698 | 2 | } |
699 | | |
700 | 6 | bool need_record_variant_extended_schema() const { return variant_max_subcolumns_count() == 0; } |
701 | | |
702 | 11 | int32_t variant_max_subcolumns_count() const { |
703 | 12 | for (const auto& col : _cols) { |
704 | 12 | if (col->is_variant_type()) { |
705 | 7 | return col->variant_max_subcolumns_count(); |
706 | 7 | } |
707 | 12 | } |
708 | 4 | return 0; |
709 | 11 | } |
710 | | const std::unordered_map<uint32_t, std::vector<uint32_t>>& seq_col_idx_to_value_cols_idx() |
711 | 0 | const { |
712 | 0 | return _seq_col_idx_to_value_cols_idx; |
713 | 0 | } |
714 | | |
715 | 4.76k | bool has_seq_map() const { return !_seq_col_idx_to_value_cols_idx.empty(); } |
716 | | |
717 | 0 | const std::unordered_map<uint32_t, uint32_t>& value_col_idx_to_seq_col_idx() const { |
718 | 0 | return _value_col_idx_to_seq_col_idx; |
719 | 0 | } |
720 | | |
721 | 0 | void add_pruned_columns_data_type(int32_t col_unique_id, vectorized::DataTypePtr data_type) { |
722 | 0 | _pruned_columns_data_type[col_unique_id] = std::move(data_type); |
723 | 0 | } |
724 | | |
725 | 0 | void clear_pruned_columns_data_type() { _pruned_columns_data_type.clear(); } |
726 | | |
727 | 0 | bool has_pruned_columns() const { return !_pruned_columns_data_type.empty(); } |
728 | | |
729 | | // Whether new segments use externalized ColumnMetaPB layout (CMO) by default |
730 | 5.26k | bool is_external_segment_column_meta_used() const { |
731 | 5.26k | return _is_external_segment_column_meta_used; |
732 | 5.26k | } |
733 | | |
734 | 28 | void set_external_segment_meta_used_default(bool v) { |
735 | 28 | _is_external_segment_column_meta_used = v; |
736 | 28 | } |
737 | | |
738 | 15.9k | bool integer_type_default_use_plain_encoding() const { |
739 | 15.9k | return _integer_type_default_use_plain_encoding; |
740 | 15.9k | } |
741 | | |
742 | 0 | void set_integer_type_default_use_plain_encoding(bool v) { |
743 | 0 | _integer_type_default_use_plain_encoding = v; |
744 | 0 | } |
745 | | |
746 | 15.9k | BinaryPlainEncodingTypePB binary_plain_encoding_default_impl() const { |
747 | 15.9k | return _binary_plain_encoding_default_impl; |
748 | 15.9k | } |
749 | | |
750 | 0 | void set_binary_plain_encoding_default_impl(BinaryPlainEncodingTypePB impl) { |
751 | 0 | _binary_plain_encoding_default_impl = impl; |
752 | 0 | } |
753 | | |
754 | | private: |
755 | | friend bool operator==(const TabletSchema& a, const TabletSchema& b); |
756 | | friend bool operator!=(const TabletSchema& a, const TabletSchema& b); |
757 | 0 | TabletSchema(const TabletSchema&) = default; |
758 | | |
759 | | KeysType _keys_type = DUP_KEYS; |
760 | | SortType _sort_type = SortType::LEXICAL; |
761 | | size_t _sort_col_num = 0; |
762 | | std::vector<TabletColumnPtr> _cols; |
763 | | |
764 | | std::vector<TabletIndexPtr> _indexes; |
765 | | std::unordered_map<StringRef, int32_t, StringRefHash> _field_name_to_index; |
766 | | std::unordered_map<int32_t, int32_t> _field_uniqueid_to_index; |
767 | | std::unordered_map<vectorized::PathInDataRef, int32_t, vectorized::PathInDataRef::Hash> |
768 | | _field_path_to_index; |
769 | | |
770 | | // index_type/col_unique_id/suffix -> idxs in _indexes |
771 | | using IndexKey = std::tuple<IndexType, int32_t, std::string>; |
772 | | struct IndexKeyHash { |
773 | 56.2k | size_t operator()(const IndexKey& t) const { |
774 | 56.2k | uint32_t seed = 0; |
775 | 56.2k | seed = doris::HashUtil::hash((const char*)&std::get<0>(t), sizeof(std::get<0>(t)), |
776 | 56.2k | seed); |
777 | 56.2k | seed = doris::HashUtil::hash((const char*)&std::get<1>(t), sizeof(std::get<1>(t)), |
778 | 56.2k | seed); |
779 | 56.2k | seed = doris::HashUtil::hash((const char*)std::get<2>(t).c_str(), |
780 | 56.2k | static_cast<uint32_t>(std::get<2>(t).size()), seed); |
781 | 56.2k | return seed; |
782 | 56.2k | } |
783 | | }; |
784 | | std::unordered_map<IndexKey, std::vector<size_t>, IndexKeyHash> _col_id_suffix_to_index; |
785 | | |
786 | | int32_t _num_columns = 0; |
787 | | size_t _num_variant_columns = 0; |
788 | | size_t _num_virtual_columns = 0; |
789 | | size_t _num_key_columns = 0; |
790 | | std::vector<uint32_t> _cluster_key_uids; |
791 | | size_t _num_null_columns = 0; |
792 | | size_t _num_short_key_columns = 0; |
793 | | size_t _num_rows_per_row_block = 0; |
794 | | CompressKind _compress_kind = COMPRESS_NONE; |
795 | | segment_v2::CompressionTypePB _compression_type = segment_v2::CompressionTypePB::LZ4F; |
796 | | long _row_store_page_size = segment_v2::ROW_STORE_PAGE_SIZE_DEFAULT_VALUE; |
797 | | long _storage_page_size = segment_v2::STORAGE_PAGE_SIZE_DEFAULT_VALUE; |
798 | | long _storage_dict_page_size = segment_v2::STORAGE_DICT_PAGE_SIZE_DEFAULT_VALUE; |
799 | | size_t _next_column_unique_id = 0; |
800 | | std::string _auto_increment_column; |
801 | | |
802 | | bool _has_bf_fpp = false; |
803 | | double _bf_fpp = 0; |
804 | | bool _is_in_memory = false; |
805 | | int32_t _delete_sign_idx = -1; |
806 | | int32_t _sequence_col_idx = -1; |
807 | | int32_t _version_col_idx = -1; |
808 | | int32_t _skip_bitmap_col_idx = -1; |
809 | | int32_t _schema_version = -1; |
810 | | int64_t _table_id = -1; |
811 | | int64_t _db_id = -1; |
812 | | bool _disable_auto_compaction = false; |
813 | | bool _enable_single_replica_compaction = false; |
814 | | bool _store_row_column = false; |
815 | | bool _skip_write_index_on_load = false; |
816 | | InvertedIndexStorageFormatPB _inverted_index_storage_format = InvertedIndexStorageFormatPB::V1; |
817 | | |
818 | | // Contains column ids of which columns should be encoded into row store. |
819 | | // ATTN: For compability reason empty cids means all columns of tablet schema are encoded to row column |
820 | | std::vector<int32_t> _row_store_column_unique_ids; |
821 | | bool _enable_variant_flatten_nested = false; |
822 | | |
823 | | std::map<size_t, int32_t> _vir_col_idx_to_unique_id; |
824 | | std::map<int32_t, vectorized::DataTypePtr> _pruned_columns_data_type; |
825 | | |
826 | | // value: extracted path set and sparse path set |
827 | | std::unordered_map<int32_t, PathsSetInfo> _path_set_info_map; |
828 | | |
829 | | // key: field_pattern |
830 | | // value: indexes |
831 | | using PatternToIndex = std::unordered_map<std::string, std::vector<TabletIndexPtr>>; |
832 | | std::unordered_map<int32_t, PatternToIndex> _index_by_unique_id_with_pattern; |
833 | | |
834 | | // Default behavior for new segments: use external ColumnMeta region + CMO table if true |
835 | | bool _is_external_segment_column_meta_used = false; |
836 | | |
837 | | bool _integer_type_default_use_plain_encoding {false}; |
838 | | BinaryPlainEncodingTypePB _binary_plain_encoding_default_impl { |
839 | | BinaryPlainEncodingTypePB::BINARY_PLAIN_ENCODING_V1}; |
840 | | // Sequence column unique id mapping to value columns unique id |
841 | | std::unordered_map<uint32_t, std::vector<uint32_t>> _seq_col_uid_to_value_cols_uid; |
842 | | // Value column unique id mapping to sequence column unique id(also map sequence column it self) |
843 | | std::unordered_map<uint32_t, uint32_t> _value_col_uid_to_seq_col_uid; |
844 | | // Sequence column index mapping to value column index |
845 | | std::unordered_map<uint32_t, std::vector<uint32_t>> _seq_col_idx_to_value_cols_idx; |
846 | | // Value column index mapping to sequence column index(also map sequence column it self) |
847 | | std::unordered_map<uint32_t, uint32_t> _value_col_idx_to_seq_col_idx; |
848 | | }; |
849 | | |
850 | | bool operator==(const TabletSchema& a, const TabletSchema& b); |
851 | | bool operator!=(const TabletSchema& a, const TabletSchema& b); |
852 | | |
853 | | using TabletSchemaSPtr = std::shared_ptr<TabletSchema>; |
854 | | |
855 | | #include "common/compile_check_end.h" |
856 | | } // namespace doris |