be/src/format_v2/table_reader.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 | | |
18 | | #pragma once |
19 | | |
20 | | #include <bvar/status.h> |
21 | | |
22 | | #include <algorithm> |
23 | | #include <exception> |
24 | | #include <map> |
25 | | #include <memory> |
26 | | #include <optional> |
27 | | #include <string> |
28 | | #include <string_view> |
29 | | #include <utility> |
30 | | #include <vector> |
31 | | |
32 | | #include "common/cast_set.h" |
33 | | #include "common/exception.h" |
34 | | #include "common/logging.h" |
35 | | #include "common/status.h" |
36 | | #include "core/assert_cast.h" |
37 | | #include "core/block/block.h" |
38 | | #include "core/column/column_array.h" |
39 | | #include "core/column/column_const.h" |
40 | | #include "core/column/column_map.h" |
41 | | #include "core/column/column_nullable.h" |
42 | | #include "core/column/column_struct.h" |
43 | | #include "core/column/column_vector.h" |
44 | | #include "core/data_type/data_type.h" |
45 | | #include "core/data_type/data_type_array.h" |
46 | | #include "core/data_type/data_type_map.h" |
47 | | #include "core/data_type/data_type_nullable.h" |
48 | | #include "core/data_type/data_type_number.h" |
49 | | #include "core/data_type/data_type_string.h" |
50 | | #include "core/data_type/data_type_struct.h" |
51 | | #include "core/field.h" |
52 | | #include "exec/common/stringop_substring.h" |
53 | | #include "exprs/vexpr.h" |
54 | | #include "exprs/vexpr_context.h" |
55 | | #include "exprs/vexpr_fwd.h" |
56 | | #include "exprs/vslot_ref.h" |
57 | | #include "format/table/deletion_vector.h" |
58 | | #include "format_v2/column_data.h" |
59 | | #include "format_v2/column_mapper.h" |
60 | | #include "format_v2/expr/cast.h" |
61 | | #include "format_v2/expr/delete_predicate.h" |
62 | | #include "format_v2/file_reader.h" |
63 | | #include "format_v2/parquet/reader/column_reader.h" |
64 | | #include "format_v2/schema_projection.h" |
65 | | #include "gen_cpp/PlanNodes_types.h" |
66 | | #include "io/io_common.h" |
67 | | #include "runtime/descriptors.h" |
68 | | #include "storage/segment/condition_cache.h" |
69 | | |
70 | | namespace doris { |
71 | | class Block; |
72 | | struct DeleteFileDesc; |
73 | | class RuntimeState; |
74 | | } // namespace doris |
75 | | |
76 | | namespace doris::format { |
77 | | |
78 | | using DeleteRows = std::vector<int64_t>; |
79 | | |
80 | | // Row-level predicates on table/global schema. They are rewritten to file-local expressions when |
81 | | // possible, and remain the source of row-level filtering after localization. |
82 | | struct TableFilter { |
83 | | VExprContextSPtr conjunct; |
84 | | std::vector<GlobalIndex> global_indices; |
85 | | }; |
86 | | |
87 | | struct ScanTask { |
88 | 61.7k | virtual ~ScanTask() = default; |
89 | | |
90 | | std::unique_ptr<io::FileDescription> data_file; |
91 | | }; |
92 | | |
93 | | struct ProjectedColumnBuildContext { |
94 | | const TFileScanRangeParams* scan_params = nullptr; |
95 | | const TFileRangeDesc* range = nullptr; |
96 | | RuntimeState* runtime_state = nullptr; |
97 | | std::optional<ColumnDefinition> schema_column = std::nullopt; |
98 | | size_t next_file_column_idx = 0; |
99 | | }; |
100 | | |
101 | | struct ReadProfile { |
102 | | RuntimeProfile::Counter* total_timer = nullptr; |
103 | | RuntimeProfile::Counter* init_timer = nullptr; |
104 | | RuntimeProfile::Counter* num_delete_files = nullptr; |
105 | | RuntimeProfile::Counter* num_delete_rows = nullptr; |
106 | | RuntimeProfile::Counter* parse_delete_file_time = nullptr; |
107 | | RuntimeProfile::Counter* decoded_dv_cache_hit_count = nullptr; |
108 | | RuntimeProfile::Counter* decoded_dv_cache_miss_count = nullptr; |
109 | | RuntimeProfile::Counter* dv_file_cache_hit_count = nullptr; |
110 | | RuntimeProfile::Counter* dv_file_cache_miss_count = nullptr; |
111 | | RuntimeProfile::Counter* dv_file_cache_peer_read_count = nullptr; |
112 | | RuntimeProfile::Counter* exec_timer = nullptr; |
113 | | RuntimeProfile::Counter* prepare_split_timer = nullptr; |
114 | | RuntimeProfile::Counter* finalize_timer = nullptr; |
115 | | RuntimeProfile::Counter* create_reader_timer = nullptr; |
116 | | RuntimeProfile::Counter* pushdown_agg_timer = nullptr; |
117 | | RuntimeProfile::Counter* open_reader_timer = nullptr; |
118 | | RuntimeProfile::Counter* runtime_filter_partition_prune_timer = nullptr; |
119 | | RuntimeProfile::Counter* runtime_filter_partition_pruned_range_counter = nullptr; |
120 | | RuntimeProfile::Counter* close_timer = nullptr; |
121 | | RuntimeProfile::Counter* file_reader_total_timer = nullptr; |
122 | | RuntimeProfile::Counter* file_reader_init_timer = nullptr; |
123 | | RuntimeProfile::Counter* file_reader_schema_timer = nullptr; |
124 | | RuntimeProfile::Counter* file_reader_mapper_timer = nullptr; |
125 | | RuntimeProfile::Counter* file_reader_open_timer = nullptr; |
126 | | RuntimeProfile::Counter* file_reader_get_block_timer = nullptr; |
127 | | RuntimeProfile::Counter* file_reader_aggregate_timer = nullptr; |
128 | | RuntimeProfile::Counter* file_reader_close_timer = nullptr; |
129 | | }; |
130 | | |
131 | | struct TableReadOptions { |
132 | | // Columns need to be read from file and output by table reader. They are all in table/global |
133 | | // schema semantics. |
134 | | const std::vector<ColumnDefinition> projected_columns; |
135 | | // All complex conjuncts from scan operator |
136 | | const VExprContextSPtrs conjuncts; |
137 | | // File format of the underlying data files, needed for reader initialization and reader-level |
138 | | // filter pushdown. |
139 | | const FileFormat format; |
140 | | TFileScanRangeParams* scan_params; |
141 | | std::shared_ptr<io::IOContext> io_ctx; |
142 | | RuntimeState* runtime_state; |
143 | | RuntimeProfile* scanner_profile; |
144 | | // File formats without complete self-describing metadata, such as CSV, Text, and JSON, need |
145 | | // the FE-planned physical file slots to build their file-local schema and deserialize values. |
146 | | const std::vector<SlotDescriptor*>* file_slot_descs = nullptr; |
147 | | // Push-down aggregate type. |
148 | | const TPushAggOp::type push_down_agg_type = TPushAggOp::type::NONE; |
149 | | // Table/global indices of explicit COUNT arguments. nullopt means an old FE did not send the |
150 | | // semantic argument field, while an explicit empty vector means COUNT(*)/COUNT(1). Keeping |
151 | | // those states separate prevents a rolling-upgrade plan from being reinterpreted by a new BE. |
152 | | const std::optional<std::vector<GlobalIndex>> push_down_count_columns = std::nullopt; |
153 | | // Initial digest of predicates available during scanner open. Scanner-driven splits override it |
154 | | // with SplitReadOptions::condition_cache_digest after collecting late-arrival runtime filters. |
155 | | // A zero digest disables condition cache. |
156 | | uint64_t condition_cache_digest = 0; |
157 | | }; |
158 | | |
159 | | struct SplitReadOptions { |
160 | | // Split-level information for reader initialization, which may include file path, partition values, delete file info, etc. The content is table format specific and opaque to table reader base class; it's the responsibility of the concrete table reader implementation to parse necessary information for reader initialization and filter pushdown. |
161 | | std::map<std::string, Field> partition_values; |
162 | | // Latest scanner conjuncts rewritten to table/global column indices. Runtime filters may |
163 | | // arrive after TableReader::init(), so scanner-driven splits replace the initial snapshot. |
164 | | // nullopt preserves the initial snapshot for standalone TableReader callers. |
165 | | std::optional<VExprContextSPtrs> conjuncts = std::nullopt; |
166 | | // Independent clones used for partition pruning because evaluation prepares and opens them |
167 | | // against a synthetic partition block before the file reader opens its row-level conjuncts. |
168 | | VExprContextSPtrs partition_prune_conjuncts; |
169 | | // Table-level COUNT may emit one metadata-derived batch and resume on a later scheduler turn. |
170 | | // It is safe only after every runtime filter assigned to the scanner has arrived; otherwise a |
171 | | // filter could arrive after synthetic rows have already been returned and those rows cannot be |
172 | | // retracted. Standalone TableReader callers have no scanner runtime-filter lifecycle. |
173 | | bool all_runtime_filters_applied = true; |
174 | | // Digest for the exact scanner conjunct snapshot attached to this split. FileScannerV2 rebuilds |
175 | | // it after collecting late-arrival RFs, so different RF payloads cannot share a cache entry. A |
176 | | // zero value explicitly disables condition cache for this split. |
177 | | std::optional<uint64_t> condition_cache_digest; |
178 | | ShardedKVCache* cache = nullptr; |
179 | | TFileRangeDesc current_range; |
180 | | FileFormat current_split_format = FileFormat::PARQUET; |
181 | | std::optional<GlobalRowIdContext> global_rowid_context; |
182 | | }; |
183 | | |
184 | | // Base class for table-level readers. |
185 | | // This layer owns common table-level orchestration, such as split iteration, dynamic partition |
186 | | // pruning, delete handling and conversion from file-local blocks to table-schema blocks. Concrete |
187 | | // table-format readers only need to provide format-specific hooks for opening readers and parsing |
188 | | // split metadata. |
189 | | class TableReader { |
190 | | public: |
191 | 40.6k | virtual ~TableReader() = default; |
192 | | |
193 | | // Initialize common runtime options for the table reader. Subclasses may call this from their |
194 | | // own init(options); table-format schema and split metadata are provided later per split. |
195 | | virtual Status init(TableReadOptions&& options); |
196 | | |
197 | | // FileScannerV2 adjusts this before each get_block() using an adaptive bytes-per-row estimate. |
198 | | // Store it here as well as forwarding to the current reader so newly opened split readers start |
199 | | // with the latest predicted batch size. |
200 | 246k | virtual void set_batch_size(size_t batch_size) { |
201 | 246k | _batch_size = std::max<size_t>(1, batch_size); |
202 | 246k | if (_data_reader.reader != nullptr) { |
203 | 123k | _data_reader.reader->set_batch_size(_batch_size); |
204 | 123k | } |
205 | 246k | } |
206 | | |
207 | | #ifdef BE_TEST |
208 | | size_t TEST_batch_size() const { return _batch_size; } |
209 | | bool TEST_current_data_file_is_immutable() const { |
210 | | DORIS_CHECK(_current_task != nullptr); |
211 | | DORIS_CHECK(_current_task->data_file != nullptr); |
212 | | DORIS_CHECK(_current_file_description.has_value()); |
213 | | DORIS_CHECK(_current_task->data_file->is_immutable == |
214 | | _current_file_description->is_immutable); |
215 | | return _current_task->data_file->is_immutable; |
216 | | } |
217 | | #endif |
218 | | |
219 | | // Prepare for reading a new split/task. |
220 | | // 1. Pass a new split/task to reader, which will be used in subsequent open_reader() to initialize the underlying file reader. |
221 | | // 2. Parse delete predicates from split/task information, which will be used for later dynamic filtering and delete handling. |
222 | | virtual Status prepare_split(const SplitReadOptions& options); |
223 | | |
224 | 90.2k | virtual bool current_split_pruned() const { return _current_split_pruned; } |
225 | 312k | virtual bool current_split_uses_metadata_count() const { |
226 | 312k | return _current_split_uses_metadata_count; |
227 | 312k | } |
228 | | |
229 | | // Discard the active split after the caller decides an error is ignorable, for example a |
230 | | // stale external-table file listing that returns NOT_FOUND. The next prepare_split() must start |
231 | | // with no concrete reader or split-local state left from the failed split. |
232 | 1 | virtual Status abort_split() { |
233 | | // Ignored open failures still spend time closing partially initialized readers. Include |
234 | | // that recovery path in the common lifecycle profile so NOT_FOUND cannot become invisible. |
235 | 1 | SCOPED_TIMER(_profile.total_timer); |
236 | 1 | SCOPED_TIMER(_profile.close_timer); |
237 | 1 | if (_data_reader.reader != nullptr) { |
238 | 1 | RETURN_IF_ERROR(close_current_reader()); |
239 | 1 | } else { |
240 | 0 | _current_task.reset(); |
241 | 0 | _current_file_description.reset(); |
242 | 0 | } |
243 | 1 | _delete_rows = nullptr; |
244 | 1 | _remaining_table_level_count = -1; |
245 | 1 | _current_split_uses_metadata_count = false; |
246 | 1 | _current_split_pruned = false; |
247 | 1 | return Status::OK(); |
248 | 1 | } |
249 | | |
250 | | // Public entry point for reading a table-schema block. The base class opens the current reader, |
251 | | // advances across EOF, and closes exhausted readers. Subclasses provide protected hooks for |
252 | | // table-format-specific behavior. |
253 | 186k | virtual Status get_block(Block* block, bool* eos) { |
254 | 186k | SCOPED_TIMER(_profile.total_timer); |
255 | 186k | SCOPED_TIMER(_profile.exec_timer); |
256 | 186k | DORIS_CHECK(block->columns() == _projected_columns.size()); |
257 | 186k | block->clear_column_data(_projected_columns.size()); |
258 | | |
259 | 256k | while (true) { |
260 | 256k | if (*eos) { |
261 | 0 | return Status::OK(); |
262 | 0 | } |
263 | 256k | if (_io_ctx != nullptr && _io_ctx->should_stop) { |
264 | 12 | *eos = true; |
265 | 12 | return Status::OK(); |
266 | 12 | } |
267 | 256k | if (!_data_reader.reader) { |
268 | 121k | if (_is_table_level_count_active()) { |
269 | 302 | RETURN_IF_ERROR(_read_table_level_count(block, eos)); |
270 | 302 | return Status::OK(); |
271 | 302 | } |
272 | 121k | RETURN_IF_ERROR(create_next_reader(eos)); |
273 | 121k | if (!_data_reader.reader) { |
274 | 60.8k | DCHECK(*eos); |
275 | 60.8k | return Status::OK(); |
276 | 60.8k | } |
277 | 121k | } |
278 | | |
279 | | // Materialize a reduced row set for upper aggregate operators when aggregate |
280 | | // pushdown can be applied. This is not the final aggregate result: COUNT emits |
281 | | // `count` default rows for the upper COUNT(*), and MIN/MAX emits two rows containing |
282 | | // file-level min/max values for the upper MIN/MAX. |
283 | 195k | if (!_aggregate_pushdown_tried) { |
284 | 60.2k | SCOPED_TIMER(_profile.pushdown_agg_timer); |
285 | 60.2k | bool pushed_down = false; |
286 | 60.2k | const auto status = _try_materialize_aggregate_pushdown_rows(block, &pushed_down); |
287 | 60.2k | if (!status.ok()) { |
288 | 1 | if (_io_ctx != nullptr && _io_ctx->should_stop && |
289 | 1 | status.is<ErrorCode::END_OF_FILE>()) { |
290 | 1 | *eos = true; |
291 | 1 | return Status::OK(); |
292 | 1 | } |
293 | 0 | return status; |
294 | 1 | } |
295 | 60.2k | if (pushed_down) { |
296 | 1.26k | return Status::OK(); |
297 | 1.26k | } |
298 | 60.2k | } |
299 | | |
300 | 194k | bool current_eof = false; |
301 | 194k | _data_reader.block_template.clear_column_data( |
302 | 194k | cast_set<int64_t>(_data_reader.file_block_layout.size())); |
303 | 194k | size_t current_rows = 0; |
304 | 194k | { |
305 | 194k | SCOPED_TIMER(_profile.file_reader_total_timer); |
306 | 194k | SCOPED_TIMER(_profile.file_reader_get_block_timer); |
307 | 194k | RETURN_IF_ERROR(_data_reader.reader->get_block(&_data_reader.block_template, |
308 | 194k | ¤t_rows, ¤t_eof)); |
309 | 194k | } |
310 | 194k | const bool stopped_during_read = _io_ctx != nullptr && _io_ctx->should_stop; |
311 | 194k | if (current_rows == 0) { |
312 | 69.8k | if (current_eof) { |
313 | 58.4k | _current_reader_reached_eof = !stopped_during_read; |
314 | 58.4k | RETURN_IF_ERROR(close_current_reader()); |
315 | 58.4k | } |
316 | 69.8k | continue; |
317 | 69.8k | } |
318 | 194k | DCHECK_EQ(_data_reader.block_template.columns(), _data_reader.file_block_layout.size()) |
319 | 0 | << _data_reader.block_template.dump_structure(); |
320 | 124k | #ifndef NDEBUG |
321 | 124k | RETURN_IF_ERROR(_check_file_block_columns("after file reader get_block", current_rows)); |
322 | 124k | #endif |
323 | 124k | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
324 | 124k | RETURN_IF_ERROR(finalize_chunk(block, current_rows)); |
325 | 124k | #ifndef NDEBUG |
326 | 124k | RETURN_IF_ERROR( |
327 | 124k | _check_table_block_columns("after finalize_chunk", block, current_rows)); |
328 | 124k | #endif |
329 | 124k | if (current_eof) { |
330 | 18 | _current_reader_reached_eof = !stopped_during_read; |
331 | 18 | RETURN_IF_ERROR(close_current_reader()); |
332 | 18 | } |
333 | 124k | return Status::OK(); |
334 | 124k | } |
335 | 186k | } |
336 | | |
337 | | // Close the table reader and the currently active file reader. Subclasses that hold additional |
338 | | // table-format resources should override this and call TableReader::close() first. |
339 | 40.6k | virtual Status close() { |
340 | 40.6k | SCOPED_TIMER(_profile.total_timer); |
341 | 40.6k | SCOPED_TIMER(_profile.close_timer); |
342 | 40.6k | if (_data_reader.reader) { |
343 | 628 | RETURN_IF_ERROR(close_current_reader()); |
344 | 628 | } |
345 | 40.6k | _current_task.reset(); |
346 | 40.6k | _current_file_description.reset(); |
347 | 40.6k | _remaining_table_level_count = -1; |
348 | 40.6k | _current_split_uses_metadata_count = false; |
349 | 40.6k | return Status::OK(); |
350 | 40.6k | } |
351 | | |
352 | 80.9k | int64_t condition_cache_hit_count() const { return _condition_cache_hit_count; } |
353 | | |
354 | | virtual std::string debug_string() const; |
355 | | |
356 | | virtual Status annotate_projected_column(const TFileScanSlotInfo& slot_info, |
357 | | ProjectedColumnBuildContext* context, |
358 | | ColumnDefinition* column) const; |
359 | | |
360 | 21.8k | virtual Status validate_projected_columns(const ProjectedColumnBuildContext& context) const { |
361 | 21.8k | (void)context; |
362 | 21.8k | return Status::OK(); |
363 | 21.8k | } |
364 | | |
365 | | protected: |
366 | | // TableReader keeps the active file description both in the scan task and separately for |
367 | | // creating the physical reader. Table-format readers must update both copies when their |
368 | | // snapshot protocol guarantees that a file path is never overwritten with different bytes. |
369 | | // This guarantee lets readers safely build cache keys without mtime; it must not be used for |
370 | | // ordinary Hive/TVF files whose paths may be overwritten in place. |
371 | 28.6k | void mark_current_data_file_immutable() { |
372 | 28.6k | DORIS_CHECK(_current_task != nullptr); |
373 | 28.6k | DORIS_CHECK(_current_task->data_file != nullptr); |
374 | 28.6k | DORIS_CHECK(_current_file_description.has_value()); |
375 | 28.6k | _current_task->data_file->is_immutable = true; |
376 | 28.6k | _current_file_description->is_immutable = true; |
377 | 28.6k | } |
378 | | |
379 | | std::optional<ColumnDefinition> _find_current_table_column_by_field_id(int32_t field_id, |
380 | | DataTypePtr type) const; |
381 | | |
382 | | // Parse deletion vector information from table format specific file description. |
383 | | virtual Status _parse_deletion_vector_file(const TTableFormatFileDesc& t_desc, |
384 | 32.7k | DeleteFileDesc* desc, bool* has_delete_file) { |
385 | 32.7k | *has_delete_file = false; |
386 | 32.7k | return Status::OK(); |
387 | 32.7k | } |
388 | | |
389 | | // Advance to the next reader. This closes the current reader first and then opens the next |
390 | | // concrete reader. Subclasses should not duplicate this loop. |
391 | | Status create_next_reader(bool* eos); |
392 | | virtual Status create_file_reader(std::unique_ptr<FileReader>* reader); |
393 | 6.36k | virtual TableColumnMappingMode mapping_mode() const { return TableColumnMappingMode::BY_NAME; } |
394 | 34.9k | virtual Status annotate_file_schema(std::vector<ColumnDefinition>* file_schema) { |
395 | 34.9k | DORIS_CHECK(file_schema != nullptr); |
396 | 34.9k | return Status::OK(); |
397 | 34.9k | } |
398 | | |
399 | | // Open the concrete reader for the current split/task and build the file-local scan request. |
400 | 61.5k | virtual Status open_reader() { |
401 | 61.5k | SCOPED_TIMER(_profile.open_reader_timer); |
402 | | // 1. Get file schema and create column mapping. |
403 | 61.5k | std::vector<ColumnDefinition> file_schema; |
404 | 61.5k | { |
405 | 61.5k | SCOPED_TIMER(_profile.file_reader_total_timer); |
406 | 61.5k | SCOPED_TIMER(_profile.file_reader_schema_timer); |
407 | 61.5k | RETURN_IF_ERROR(_data_reader.reader->get_schema(&file_schema)); |
408 | 61.5k | } |
409 | | // For Paimon/Hudi, FE can provide field ids through `history_schema_info`. Annotate the |
410 | | // file schema before column mapping when the table format maps columns by field id. |
411 | 61.5k | RETURN_IF_ERROR(annotate_file_schema(&file_schema)); |
412 | 61.5k | _data_reader.file_schema = file_schema; |
413 | 61.5k | _mapper_options.mode = mapping_mode(); |
414 | | |
415 | 61.5k | { |
416 | 61.5k | SCOPED_TIMER(_profile.file_reader_total_timer); |
417 | 61.5k | SCOPED_TIMER(_profile.file_reader_mapper_timer); |
418 | 61.5k | _data_reader.column_mapper = _data_reader.reader->create_column_mapper(_mapper_options); |
419 | 61.5k | } |
420 | 61.5k | DORIS_CHECK(_data_reader.column_mapper != nullptr); |
421 | 61.5k | RETURN_IF_ERROR(_data_reader.column_mapper->create_mapping(_projected_columns, |
422 | 61.5k | _partition_values, file_schema)); |
423 | 61.5k | DORIS_CHECK(_data_reader.column_mapper->mappings().size() == _projected_columns.size()); |
424 | | |
425 | | // 2. Build table filters based on conjuncts and column predicates. |
426 | 61.5k | RETURN_IF_ERROR(_build_table_filters_from_conjuncts()); |
427 | | |
428 | | // 3. Create file scan request based on column mapping and table filters, then open file |
429 | | // reader with the request. File scan request carries row-level expression filters and |
430 | | // file-level pruning hints. Only expression filters decide returned rows. |
431 | 61.5k | auto file_request = std::make_shared<FileScanRequest>(); |
432 | 61.5k | RETURN_IF_ERROR(_data_reader.column_mapper->create_scan_request( |
433 | 61.5k | _table_filters, _projected_columns, file_request.get(), _runtime_state)); |
434 | 61.5k | bool constant_filter_pruned_split = false; |
435 | 61.5k | RETURN_IF_ERROR(_evaluate_constant_filters(&constant_filter_pruned_split)); |
436 | 61.5k | if (constant_filter_pruned_split) { |
437 | 1.24k | RETURN_IF_ERROR(close_current_reader()); |
438 | 1.24k | return Status::OK(); |
439 | 1.24k | } |
440 | | // COUNT(*) has no semantic column argument, but Nereids retains a minimum-width scan slot |
441 | | // so the scan node still has an output tuple. Record only the current non-predicate file |
442 | | // columns before table-format hooks add row-position or equality-delete dependencies. This |
443 | | // marker is independent of aggregate eligibility: with position deletes, for example, |
444 | | // metadata COUNT must fall back to reading rows, but an arbitrary unsupported TIME_MILLIS |
445 | | // placeholder still must not be validated or decoded merely to carry the surviving count. |
446 | 60.2k | if (_push_down_agg_type == TPushAggOp::type::COUNT && |
447 | 60.2k | _push_down_count_columns.has_value() && _push_down_count_columns->empty()) { |
448 | 1.96k | file_request->count_star_placeholder_columns.reserve( |
449 | 1.96k | file_request->non_predicate_columns.size()); |
450 | 1.96k | for (const auto& column : file_request->non_predicate_columns) { |
451 | 1.93k | file_request->count_star_placeholder_columns.push_back(column.column_id()); |
452 | 1.93k | } |
453 | 1.96k | } |
454 | 60.2k | RETURN_IF_ERROR(customize_file_scan_request(file_request.get())); |
455 | 60.2k | RETURN_IF_ERROR(_open_local_filter_exprs(*file_request)); |
456 | 60.2k | _data_reader.file_block_layout.clear(); |
457 | 60.2k | _data_reader.block_template.clear(); |
458 | 60.2k | _data_reader.file_block_layout.resize(file_request->local_positions.size()); |
459 | | |
460 | | // 4. Build file block layout from file schema and column mapping. The layout describes |
461 | | // the block returned by file reader before table-column materialization. |
462 | 384k | for (const auto& [file_column_id, block_position] : file_request->local_positions) { |
463 | 384k | DORIS_CHECK(block_position.value() < _data_reader.file_block_layout.size()); |
464 | 384k | const auto* field = _find_column_definition(_data_reader.file_schema, file_column_id); |
465 | 384k | DORIS_CHECK(field != nullptr); |
466 | | |
467 | 384k | ColumnDefinition projected_field; |
468 | 384k | { |
469 | 384k | auto it = std::find_if( |
470 | 384k | file_request->non_predicate_columns.begin(), |
471 | 384k | file_request->non_predicate_columns.end(), |
472 | 7.88M | [&](const LocalColumnIndex& p) { return p.column_id() == file_column_id; }); |
473 | 384k | if (it != file_request->non_predicate_columns.end()) { |
474 | 350k | RETURN_IF_ERROR(project_column_definition(*field, *it, &projected_field)); |
475 | 350k | } |
476 | 384k | } |
477 | 384k | { |
478 | 384k | auto it = std::find_if( |
479 | 384k | file_request->predicate_columns.begin(), |
480 | 384k | file_request->predicate_columns.end(), |
481 | 384k | [&](const LocalColumnIndex& p) { return p.column_id() == file_column_id; }); |
482 | 384k | if (it != file_request->predicate_columns.end()) { |
483 | 33.9k | RETURN_IF_ERROR(project_column_definition(*field, *it, &projected_field)); |
484 | 33.9k | } |
485 | 384k | } |
486 | 384k | _data_reader.file_block_layout[block_position.value()] = { |
487 | 384k | .file_column_id = file_column_id, |
488 | 384k | .name = projected_field.name, |
489 | 384k | .type = projected_field.type, |
490 | 384k | }; |
491 | 384k | DORIS_CHECK(_data_reader.file_block_layout[block_position.value()].type != nullptr); |
492 | 384k | } |
493 | | |
494 | | // 5. Prepare block template from file block layout. The block template stores the block |
495 | | // returned by file reader before table-column materialization. |
496 | 60.2k | _data_reader.block_template.reserve(_data_reader.file_block_layout.size()); |
497 | 384k | for (const auto& column : _data_reader.file_block_layout) { |
498 | 384k | _data_reader.block_template.insert( |
499 | 384k | {column.type->create_column(), column.type, column.name}); |
500 | 384k | } |
501 | 60.2k | if (VLOG_DEBUG_IS_ON) { |
502 | 0 | VLOG_DEBUG << "TableReader debug: " << debug_string(); |
503 | 0 | } |
504 | 60.2k | RETURN_IF_ERROR(_open_mapping_exprs()); |
505 | 60.2k | { |
506 | 60.2k | SCOPED_TIMER(_profile.file_reader_total_timer); |
507 | 60.2k | SCOPED_TIMER(_profile.file_reader_open_timer); |
508 | 60.2k | RETURN_IF_ERROR(_data_reader.reader->open(file_request)); |
509 | 60.2k | } |
510 | 60.2k | RETURN_IF_ERROR(_init_reader_condition_cache(*file_request)); |
511 | 60.2k | return Status::OK(); |
512 | 60.2k | } |
513 | | |
514 | | Status _build_table_filters_from_conjuncts(); |
515 | | Status _evaluate_partition_prune_conjuncts(const VExprContextSPtrs& conjuncts, |
516 | | bool* can_filter_all); |
517 | | static bool _is_safe_to_pre_execute(const VExprContextSPtr& conjunct); |
518 | | Status _build_partition_prune_block(Block* block) const; |
519 | | Status _open_local_filter_exprs(const FileScanRequest& file_request); |
520 | | Status _init_reader_condition_cache(const FileScanRequest& file_request); |
521 | | void _finalize_reader_condition_cache(); |
522 | | bool _should_enable_condition_cache(const FileScanRequest& file_request) const; |
523 | | |
524 | 61.3k | Status _evaluate_constant_filters(bool* can_filter_all) { |
525 | 61.3k | DORIS_CHECK(can_filter_all != nullptr); |
526 | 61.3k | DORIS_CHECK_LE(_constant_pruning_safe_filter_count, _table_filters.size()); |
527 | 61.3k | *can_filter_all = false; |
528 | | // The bound was derived from the original `_conjuncts` order, which includes slotless |
529 | | // expressions omitted from `_table_filters`. Iterating only this prefix therefore cannot |
530 | | // skip an unsafe row-level predicate and pre-execute a later constant predicate. |
531 | 100k | for (size_t i = 0; i < _constant_pruning_safe_filter_count; ++i) { |
532 | 40.5k | const auto& table_filter = _table_filters[i]; |
533 | 40.5k | if (table_filter.conjunct == nullptr) { |
534 | 0 | continue; |
535 | 0 | } |
536 | 40.5k | DORIS_CHECK(_is_safe_to_pre_execute(table_filter.conjunct)); |
537 | | // RuntimeFilterExpr does not implement execute_column_impl(); it is evaluated by the |
538 | | // row-level filter path through execute_filter(). Constant split pruning uses |
539 | | // VExprContext::execute() on a one-row synthetic block, so runtime filters must not be |
540 | | // pre-executed here even when their referenced slot maps to a constant value. |
541 | 40.5k | if (table_filter.conjunct->root()->is_rf_wrapper() || |
542 | 40.5k | !_table_filter_has_only_constant_entries(table_filter)) { |
543 | 37.1k | continue; |
544 | 37.1k | } |
545 | 3.37k | Block eval_block; |
546 | 3.37k | RETURN_IF_ERROR(_build_constant_filter_block(table_filter, &eval_block)); |
547 | 3.37k | RowDescriptor row_desc; |
548 | 3.37k | RETURN_IF_ERROR(table_filter.conjunct->prepare(_runtime_state, row_desc)); |
549 | 3.37k | RETURN_IF_ERROR(table_filter.conjunct->open(_runtime_state)); |
550 | 3.37k | int result_column_id = -1; |
551 | 3.37k | RETURN_IF_ERROR(table_filter.conjunct->execute(&eval_block, &result_column_id)); |
552 | 3.37k | DORIS_CHECK(result_column_id >= 0); |
553 | 3.37k | if (_filter_result_filters_all(eval_block.get_by_position(result_column_id).column)) { |
554 | 1.24k | *can_filter_all = true; |
555 | 1.24k | return Status::OK(); |
556 | 1.24k | } |
557 | 3.37k | } |
558 | 60.0k | return Status::OK(); |
559 | 61.3k | } |
560 | | |
561 | 35.0k | bool _table_filter_has_only_constant_entries(const TableFilter& table_filter) const { |
562 | 35.0k | const auto& filter_entries = _data_reader.column_mapper->filter_entries(); |
563 | 35.3k | for (const auto global_index : table_filter.global_indices) { |
564 | 35.3k | const auto entry_it = filter_entries.find(global_index); |
565 | 35.5k | if (entry_it == filter_entries.end() || !entry_it->second.is_constant()) { |
566 | 31.8k | return false; |
567 | 31.8k | } |
568 | 35.3k | } |
569 | 3.25k | return !table_filter.global_indices.empty(); |
570 | 35.0k | } |
571 | | |
572 | 3.41k | Status _build_constant_filter_block(const TableFilter& table_filter, Block* eval_block) { |
573 | 3.41k | DORIS_CHECK(eval_block != nullptr); |
574 | 3.41k | eval_block->clear(); |
575 | 3.41k | const auto& mappings = _data_reader.column_mapper->mappings(); |
576 | 3.41k | const auto& filter_entries = _data_reader.column_mapper->filter_entries(); |
577 | 3.41k | DORIS_CHECK(mappings.size() == _projected_columns.size()); |
578 | 14.6k | for (size_t column_idx = 0; column_idx < mappings.size(); ++column_idx) { |
579 | 11.2k | const auto global_index = GlobalIndex(column_idx); |
580 | 11.2k | const auto& mapping = mappings[column_idx]; |
581 | 11.2k | const auto entry_it = filter_entries.find(global_index); |
582 | 11.2k | const bool referenced_by_filter = |
583 | 11.2k | std::find(table_filter.global_indices.begin(), |
584 | 11.2k | table_filter.global_indices.end(), |
585 | 11.2k | global_index) != table_filter.global_indices.end(); |
586 | 11.2k | if (referenced_by_filter && entry_it != filter_entries.end() && |
587 | 11.2k | entry_it->second.is_constant()) { |
588 | 3.66k | ColumnPtr constant_column; |
589 | 3.66k | RETURN_IF_ERROR(_materialize_constant_filter_column( |
590 | 3.66k | entry_it->second.constant_index(), &constant_column)); |
591 | 3.66k | eval_block->insert({std::move(constant_column), mapping.table_type, |
592 | 3.66k | mapping.table_column_name}); |
593 | 7.58k | } else { |
594 | 7.58k | eval_block->insert({mapping.table_type->create_column_const_with_default_value(1), |
595 | 7.58k | mapping.table_type, mapping.table_column_name}); |
596 | 7.58k | } |
597 | 11.2k | } |
598 | 3.41k | return Status::OK(); |
599 | 3.41k | } |
600 | | |
601 | 3.66k | Status _materialize_constant_filter_column(ConstantIndex constant_index, ColumnPtr* column) { |
602 | 3.66k | DORIS_CHECK(column != nullptr); |
603 | 3.66k | const auto& constant_entry = _data_reader.column_mapper->constant_map().get(constant_index); |
604 | 3.66k | DORIS_CHECK(constant_entry.expr != nullptr); |
605 | 3.66k | DORIS_CHECK(constant_entry.type != nullptr); |
606 | 3.66k | RowDescriptor row_desc; |
607 | 3.66k | RETURN_IF_ERROR(constant_entry.expr->prepare(_runtime_state, row_desc)); |
608 | 3.66k | RETURN_IF_ERROR(constant_entry.expr->open(_runtime_state)); |
609 | 3.66k | Block eval_block; |
610 | 3.66k | eval_block.insert({constant_entry.type->create_column_const_with_default_value(1), |
611 | 3.66k | constant_entry.type, "__table_reader_constant_filter"}); |
612 | 3.66k | int result_column_id = -1; |
613 | 3.66k | RETURN_IF_ERROR(constant_entry.expr->execute(&eval_block, &result_column_id)); |
614 | 3.66k | DORIS_CHECK(result_column_id >= 0); |
615 | 3.66k | *column = eval_block.get_by_position(result_column_id).column; |
616 | 3.66k | DORIS_CHECK((*column)->size() == 1); |
617 | 3.66k | return Status::OK(); |
618 | 3.66k | } |
619 | | |
620 | 3.41k | static bool _filter_result_filters_all(const ColumnPtr& filter_column) { |
621 | 3.41k | DORIS_CHECK(filter_column.get() != nullptr); |
622 | 3.41k | DORIS_CHECK(filter_column->size() == 1); |
623 | 3.41k | return !filter_column->get_bool(0); |
624 | 3.41k | } |
625 | | |
626 | 59.9k | virtual Status customize_file_scan_request(FileScanRequest* file_request) { |
627 | 59.9k | return _append_delete_predicate(file_request); |
628 | 59.9k | } |
629 | | |
630 | 213k | bool _is_table_level_count_active() const { return _remaining_table_level_count >= 0; } |
631 | | |
632 | 1.39k | Status _materialize_count_rows(size_t rows, Block* block) const { |
633 | 1.39k | DORIS_CHECK(block != nullptr); |
634 | 1.39k | DORIS_CHECK(block->columns() > 0 || rows == 0); |
635 | 2.79k | for (size_t column_idx = 0; column_idx < block->columns(); ++column_idx) { |
636 | 1.39k | auto column = block->get_by_position(column_idx).type->create_column(); |
637 | 1.39k | column->resize(rows); |
638 | 1.39k | block->replace_by_position(column_idx, std::move(column)); |
639 | 1.39k | } |
640 | 1.39k | return Status::OK(); |
641 | 1.39k | } |
642 | | |
643 | 302 | Status _read_table_level_count(Block* block, bool* eos) { |
644 | 302 | DORIS_CHECK(block != nullptr); |
645 | 302 | DORIS_CHECK(eos != nullptr); |
646 | 302 | DORIS_CHECK(_push_down_agg_type == TPushAggOp::type::COUNT); |
647 | 302 | DORIS_CHECK(_remaining_table_level_count >= 0); |
648 | 302 | if (_remaining_table_level_count == 0) { |
649 | 150 | _remaining_table_level_count = -1; |
650 | 150 | _current_task.reset(); |
651 | 150 | *eos = true; |
652 | 150 | return Status::OK(); |
653 | 150 | } |
654 | | |
655 | 152 | const int64_t batch_size = _runtime_state == nullptr |
656 | 152 | ? _remaining_table_level_count |
657 | 152 | : static_cast<int64_t>(_runtime_state->batch_size()); |
658 | 152 | const auto rows = std::min(_remaining_table_level_count, batch_size); |
659 | 152 | RETURN_IF_ERROR(_materialize_count_rows(cast_set<size_t>(rows), block)); |
660 | 152 | _remaining_table_level_count -= rows; |
661 | 152 | *eos = false; |
662 | 152 | return Status::OK(); |
663 | 152 | } |
664 | | |
665 | | void _append_file_scan_column(FileScanRequest* request, LocalColumnId column_id, |
666 | 12.8k | std::vector<LocalColumnIndex>* scan_columns) { |
667 | 12.8k | DORIS_CHECK(request != nullptr); |
668 | 12.8k | DORIS_CHECK(scan_columns != nullptr); |
669 | 12.8k | FileScanRequestBuilder builder(request); |
670 | 12.8k | Status status; |
671 | 12.8k | if (scan_columns == &request->predicate_columns) { |
672 | 10.7k | status = builder.add_predicate_column(column_id); |
673 | 10.7k | } else { |
674 | 2.10k | DORIS_CHECK(scan_columns == &request->non_predicate_columns); |
675 | 2.10k | status = builder.add_non_predicate_column(column_id); |
676 | 2.10k | } |
677 | 12.8k | DORIS_CHECK(status.ok()) << status.to_string(); |
678 | 12.8k | if (column_id == LocalColumnId(ROW_POSITION_COLUMN_ID) && |
679 | 12.8k | _find_column_definition(_data_reader.file_schema, column_id) == nullptr) { |
680 | 7.47k | _data_reader.file_schema.push_back(row_position_column_definition()); |
681 | 7.47k | } |
682 | 12.8k | } |
683 | | |
684 | | // Append DeletePredicate to file scan request if there are deletes. The predicate will be evaluated in file reader level and filter out deleted rows before returning data to table reader. |
685 | 59.8k | Status _append_delete_predicate(FileScanRequest* request) { |
686 | 59.8k | DORIS_CHECK(request != nullptr); |
687 | 59.8k | if ((_delete_rows == nullptr || _delete_rows->empty()) && |
688 | 59.8k | (_deletion_vector == nullptr || _deletion_vector->isEmpty())) { |
689 | 54.1k | return Status::OK(); |
690 | 54.1k | } |
691 | 5.70k | const auto row_position_column_id = LocalColumnId(ROW_POSITION_COLUMN_ID); |
692 | 5.70k | _append_file_scan_column(request, row_position_column_id, &request->predicate_columns); |
693 | | |
694 | 5.70k | const auto block_position = request->local_positions.at(row_position_column_id); |
695 | 5.82k | auto append_predicate = [&](auto& deleted_rows) { |
696 | 5.82k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); |
697 | 5.82k | delete_predicate->add_child(VSlotRef::create_shared( |
698 | 5.82k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), |
699 | 5.82k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); |
700 | 5.82k | request->delete_conjuncts.push_back( |
701 | 5.82k | VExprContext::create_shared(std::move(delete_predicate))); |
702 | 5.82k | }; _ZZN5doris6format11TableReader24_append_delete_predicateEPNS0_15FileScanRequestEENKUlRT_E_clISt6vectorIlSaIlEEEEDaS5_ Line | Count | Source | 695 | 1.65k | auto append_predicate = [&](auto& deleted_rows) { | 696 | 1.65k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); | 697 | 1.65k | delete_predicate->add_child(VSlotRef::create_shared( | 698 | 1.65k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), | 699 | 1.65k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); | 700 | 1.65k | request->delete_conjuncts.push_back( | 701 | 1.65k | VExprContext::create_shared(std::move(delete_predicate))); | 702 | 1.65k | }; |
_ZZN5doris6format11TableReader24_append_delete_predicateEPNS0_15FileScanRequestEENKUlRT_E_clIN7roaring12Roaring64MapEEEDaS5_ Line | Count | Source | 695 | 4.17k | auto append_predicate = [&](auto& deleted_rows) { | 696 | 4.17k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); | 697 | 4.17k | delete_predicate->add_child(VSlotRef::create_shared( | 698 | 4.17k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), | 699 | 4.17k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); | 700 | 4.17k | request->delete_conjuncts.push_back( | 701 | 4.17k | VExprContext::create_shared(std::move(delete_predicate))); | 702 | 4.17k | }; |
|
703 | 5.70k | if (_delete_rows != nullptr && !_delete_rows->empty()) { |
704 | 1.65k | append_predicate(*_delete_rows); |
705 | 1.65k | } |
706 | 5.70k | if (_deletion_vector != nullptr && !_deletion_vector->isEmpty()) { |
707 | 4.18k | append_predicate(*_deletion_vector); |
708 | 4.18k | } |
709 | 5.70k | return Status::OK(); |
710 | 59.8k | } |
711 | | |
712 | | // Close the current concrete reader. This hook is called by both create_next_reader() and |
713 | | // close(), so it should remain idempotent. |
714 | 61.5k | virtual Status close_current_reader() { |
715 | 61.5k | _finalize_reader_condition_cache(); |
716 | 61.5k | { |
717 | 61.5k | SCOPED_TIMER(_profile.file_reader_total_timer); |
718 | 61.5k | SCOPED_TIMER(_profile.file_reader_close_timer); |
719 | 61.5k | RETURN_IF_ERROR(_data_reader.reader->close()); |
720 | 61.5k | } |
721 | 61.5k | _data_reader.reader.reset(); |
722 | 61.5k | if (_data_reader.column_mapper != nullptr) { |
723 | 61.3k | _data_reader.column_mapper->clear(); |
724 | 61.3k | _data_reader.column_mapper.reset(); |
725 | 61.3k | } |
726 | 61.5k | _table_filters.clear(); |
727 | 61.5k | _constant_pruning_safe_filter_count = 0; |
728 | 61.5k | _data_reader.file_schema.clear(); |
729 | 61.5k | _data_reader.file_block_layout.clear(); |
730 | 61.5k | _data_reader.block_template.clear(); |
731 | 61.5k | _current_task.reset(); |
732 | 61.5k | _current_file_description.reset(); |
733 | 61.5k | _current_reader_reached_eof = false; |
734 | 61.5k | return Status::OK(); |
735 | 61.5k | } |
736 | | |
737 | 2 | void _record_scan_rows(size_t rows) { |
738 | 2 | if (_io_ctx != nullptr && _io_ctx->file_reader_stats != nullptr) { |
739 | 2 | _io_ctx->file_reader_stats->read_rows += rows; |
740 | 2 | } |
741 | 2 | } |
742 | | |
743 | | // Finalize file-local block to table/global schema block. |
744 | 124k | Status finalize_chunk(Block* block, const size_t rows) { |
745 | 124k | SCOPED_TIMER(_profile.finalize_timer); |
746 | 124k | size_t idx = 0; |
747 | 124k | const auto& mappings = _data_reader.column_mapper->mappings(); |
748 | 684k | for (const auto& mapping : mappings) { |
749 | 684k | ColumnPtr column; |
750 | 684k | RETURN_IF_ERROR(_materialize_mapping_column(mapping, &_data_reader.block_template, rows, |
751 | 684k | &column, idx + 1 == mappings.size())); |
752 | 684k | block->replace_by_position(idx, IColumn::mutate(std::move(column))); |
753 | 684k | idx++; |
754 | 684k | } |
755 | 124k | RETURN_IF_ERROR(materialize_virtual_columns(block)); |
756 | | // Enforce CHAR/VARCHAR length declared by the table schema after all file-to-table |
757 | | // materialization has finished. |
758 | 124k | RETURN_IF_ERROR(_truncate_char_or_varchar_columns(block)); |
759 | 124k | return Status::OK(); |
760 | 124k | } |
761 | | |
762 | | // Materialize virtual columns in the table block, such as Iceberg _row_id and |
763 | | // _last_updated_sequence_number. This runs after normal column materialization so finalize |
764 | | // expressions can reference those virtual columns. |
765 | 97.5k | virtual Status materialize_virtual_columns(Block* table_block) { return Status::OK(); } |
766 | | |
767 | | #ifndef NDEBUG |
768 | 124k | Status _check_file_block_columns(std::string_view stage, size_t rows) { |
769 | 124k | DORIS_CHECK(_data_reader.block_template.columns() == _data_reader.file_block_layout.size()); |
770 | 797k | for (size_t idx = 0; idx < _data_reader.block_template.columns(); ++idx) { |
771 | 673k | const auto& file_block_column = _data_reader.file_block_layout[idx]; |
772 | 673k | const auto& column_with_type = _data_reader.block_template.get_by_position(idx); |
773 | 673k | const auto* column = column_with_type.column.get(); |
774 | 673k | try { |
775 | 673k | if (column == nullptr) { |
776 | 0 | auto st = Status::InternalError( |
777 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
778 | 0 | "type={}, column=null, expected_rows={}, reader={}", |
779 | 0 | idx, stage, file_block_column.file_column_id.value(), |
780 | 0 | file_block_column.name, |
781 | 0 | file_block_column.type == nullptr ? "null" |
782 | 0 | : file_block_column.type->get_name(), |
783 | 0 | rows, debug_string()); |
784 | 0 | LOG(WARNING) << st; |
785 | 0 | return st; |
786 | 0 | } |
787 | 673k | column->sanity_check(); |
788 | 673k | auto st = column_with_type.check_type_and_column_match(); |
789 | 673k | if (!st.ok()) { |
790 | 0 | auto contextual_status = Status::InternalError( |
791 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
792 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
793 | 0 | "reader={}", |
794 | 0 | idx, stage, file_block_column.file_column_id.value(), |
795 | 0 | file_block_column.name, |
796 | 0 | file_block_column.type == nullptr ? "null" |
797 | 0 | : file_block_column.type->get_name(), |
798 | 0 | column->get_name(), column->size(), rows, st.to_string(), |
799 | 0 | debug_string()); |
800 | 0 | LOG(WARNING) << contextual_status; |
801 | 0 | return contextual_status; |
802 | 0 | } |
803 | 673k | } catch (const Exception& e) { |
804 | 0 | auto st = Status::InternalError( |
805 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
806 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
807 | 0 | "reader={}", |
808 | 0 | idx, stage, file_block_column.file_column_id.value(), |
809 | 0 | file_block_column.name, |
810 | 0 | file_block_column.type == nullptr ? "null" |
811 | 0 | : file_block_column.type->get_name(), |
812 | 0 | column == nullptr ? "null" : column->get_name(), |
813 | 0 | column == nullptr ? 0 : column->size(), rows, e.to_string(), |
814 | 0 | debug_string()); |
815 | 0 | LOG(WARNING) << st; |
816 | 0 | return st; |
817 | 0 | } catch (const std::exception& e) { |
818 | 0 | auto st = Status::InternalError( |
819 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
820 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
821 | 0 | "reader={}", |
822 | 0 | idx, stage, file_block_column.file_column_id.value(), |
823 | 0 | file_block_column.name, |
824 | 0 | file_block_column.type == nullptr ? "null" |
825 | 0 | : file_block_column.type->get_name(), |
826 | 0 | column == nullptr ? "null" : column->get_name(), |
827 | 0 | column == nullptr ? 0 : column->size(), rows, e.what(), debug_string()); |
828 | 0 | LOG(WARNING) << st; |
829 | 0 | return st; |
830 | 0 | } |
831 | 673k | } |
832 | 124k | return Status::OK(); |
833 | 124k | } |
834 | | |
835 | 124k | Status _check_table_block_columns(std::string_view stage, const Block* block, size_t rows) { |
836 | 124k | DORIS_CHECK(block != nullptr); |
837 | 124k | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
838 | 809k | for (size_t idx = 0; idx < block->columns(); ++idx) { |
839 | 684k | const auto& mapping = _data_reader.column_mapper->mappings()[idx]; |
840 | 684k | const auto& column_with_type = block->get_by_position(idx); |
841 | 684k | const auto* column = column_with_type.column.get(); |
842 | 684k | try { |
843 | 684k | if (column == nullptr) { |
844 | 0 | auto st = Status::InternalError( |
845 | 0 | "Invalid table block column {} at {}: table_column='{}', " |
846 | 0 | "global_index={}, type={}, column=null, expected_rows={}, mapping={}", |
847 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
848 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
849 | 0 | rows, mapping.debug_string()); |
850 | 0 | LOG(WARNING) << st; |
851 | 0 | return st; |
852 | 0 | } |
853 | 684k | column->sanity_check(); |
854 | 684k | auto st = column_with_type.check_type_and_column_match(); |
855 | 684k | if (!st.ok()) { |
856 | 0 | auto contextual_status = Status::InternalError( |
857 | 0 | "Invalid table block column {} at {}: table_column='{}', " |
858 | 0 | "global_index={}, type={}, column={}, column_size={}, " |
859 | 0 | "expected_rows={}, error={}, mapping={}", |
860 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
861 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
862 | 0 | column->get_name(), column->size(), rows, st.to_string(), |
863 | 0 | mapping.debug_string()); |
864 | 0 | LOG(WARNING) << contextual_status; |
865 | 0 | return contextual_status; |
866 | 0 | } |
867 | 684k | } catch (const Exception& e) { |
868 | 0 | auto st = Status::InternalError( |
869 | 0 | "Invalid table block column {} at {}: table_column='{}', global_index={}, " |
870 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
871 | 0 | "mapping={}", |
872 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
873 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
874 | 0 | column == nullptr ? "null" : column->get_name(), |
875 | 0 | column == nullptr ? 0 : column->size(), rows, e.to_string(), |
876 | 0 | mapping.debug_string()); |
877 | 0 | LOG(WARNING) << st; |
878 | 0 | return st; |
879 | 0 | } catch (const std::exception& e) { |
880 | 0 | auto st = Status::InternalError( |
881 | 0 | "Invalid table block column {} at {}: table_column='{}', global_index={}, " |
882 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
883 | 0 | "mapping={}", |
884 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
885 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
886 | 0 | column == nullptr ? "null" : column->get_name(), |
887 | 0 | column == nullptr ? 0 : column->size(), rows, e.what(), |
888 | 0 | mapping.debug_string()); |
889 | 0 | LOG(WARNING) << st; |
890 | 0 | return st; |
891 | 0 | } |
892 | 684k | } |
893 | 124k | return Status::OK(); |
894 | 124k | } |
895 | | #endif |
896 | | |
897 | 124k | Status _truncate_char_or_varchar_columns(Block* block) { |
898 | 124k | DORIS_CHECK(block != nullptr); |
899 | 124k | if (_runtime_state == nullptr || |
900 | 124k | !_runtime_state->query_options().truncate_char_or_varchar_columns) { |
901 | 124k | return Status::OK(); |
902 | 124k | } |
903 | 0 | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
904 | 36 | for (size_t idx = 0; idx < _data_reader.column_mapper->mappings().size(); ++idx) { |
905 | 36 | const auto& mapping = _data_reader.column_mapper->mappings()[idx]; |
906 | 36 | if (!_should_truncate_char_or_varchar_column(mapping)) { |
907 | 12 | continue; |
908 | 12 | } |
909 | 24 | const auto target_len = |
910 | 24 | assert_cast<const DataTypeString*>(remove_nullable(mapping.table_type).get()) |
911 | 24 | ->len(); |
912 | 24 | _truncate_char_or_varchar_column(block, idx, target_len); |
913 | 24 | } |
914 | 0 | return Status::OK(); |
915 | 124k | } |
916 | | |
917 | | // Return true when the table schema has a bounded CHAR/VARCHAR length that is stricter than |
918 | | // the file-side type. Examples: |
919 | | // - table VARCHAR(10), file VARCHAR(20): truncate to 10; |
920 | | // - table VARCHAR(10), file STRING: truncate to 10 because STRING has no declared bound; |
921 | | // - table STRING, any file type: no truncation because the target has no bound. |
922 | 41 | static bool _should_truncate_char_or_varchar_column(const ColumnMapping& mapping) { |
923 | 41 | if (mapping.table_type == nullptr) { |
924 | 0 | return false; |
925 | 0 | } |
926 | 41 | const auto table_type = remove_nullable(mapping.table_type); |
927 | 41 | const auto primitive_type = table_type->get_primitive_type(); |
928 | 41 | if (primitive_type != TYPE_VARCHAR && primitive_type != TYPE_CHAR) { |
929 | 13 | return false; |
930 | 13 | } |
931 | 28 | const auto target_len = assert_cast<const DataTypeString*>(table_type.get())->len(); |
932 | 28 | if (target_len <= 0) { |
933 | 0 | return false; |
934 | 0 | } |
935 | 28 | if (mapping.file_type == nullptr) { |
936 | 0 | return true; |
937 | 0 | } |
938 | 28 | const auto file_type = remove_nullable(mapping.file_type); |
939 | 28 | DORIS_CHECK(file_type != nullptr); |
940 | 28 | int file_len = -1; |
941 | 28 | if (file_type->get_primitive_type() == TYPE_VARCHAR || |
942 | 28 | file_type->get_primitive_type() == TYPE_CHAR || |
943 | 28 | file_type->get_primitive_type() == TYPE_STRING) { |
944 | 27 | file_len = assert_cast<const DataTypeString*>(file_type.get())->len(); |
945 | 27 | } |
946 | | |
947 | 28 | return file_len < 0 || target_len < file_len; |
948 | 28 | } |
949 | | |
950 | | // Truncate a materialized CHAR/VARCHAR column in place by reusing the vectorized substring |
951 | | // implementation: substring(column, 1, len). Nullable columns are unwrapped before substring |
952 | | // execution and wrapped back with the original null map afterward, because substring operates |
953 | | // on the nested string payload only. |
954 | 25 | static void _truncate_char_or_varchar_column(Block* block, size_t idx, int len) { |
955 | 25 | DORIS_CHECK(block != nullptr); |
956 | 25 | auto int_type = std::make_shared<DataTypeInt32>(); |
957 | 25 | const auto num_columns_without_result = cast_set<uint32_t>(block->columns()); |
958 | 25 | auto& target = block->get_by_position(idx); |
959 | 25 | const bool is_nullable = target.type->is_nullable(); |
960 | 25 | ColumnPtr input_column = target.column; |
961 | 25 | ColumnPtr null_map_column; |
962 | 25 | if (is_nullable) { |
963 | 25 | const auto* nullable_column = assert_cast<const ColumnNullable*>(target.column.get()); |
964 | 25 | input_column = nullable_column->get_nested_column_ptr(); |
965 | 25 | null_map_column = nullable_column->get_null_map_column_ptr(); |
966 | 25 | } |
967 | 25 | block->replace_by_position(idx, std::move(input_column)); |
968 | 25 | block->insert({int_type->create_column_const(block->rows(), to_field<TYPE_INT>(1)), |
969 | 25 | int_type, "const 1"}); |
970 | 25 | block->insert({int_type->create_column_const(block->rows(), to_field<TYPE_INT>(len)), |
971 | 25 | int_type, "const len"}); |
972 | 25 | block->insert({nullptr, std::make_shared<DataTypeString>(), "result"}); |
973 | | |
974 | 25 | ColumnNumbers temp_arguments(3); |
975 | 25 | temp_arguments[0] = cast_set<uint32_t>(idx); |
976 | 25 | temp_arguments[1] = num_columns_without_result; |
977 | 25 | temp_arguments[2] = num_columns_without_result + 1; |
978 | 25 | const uint32_t result_column_id = num_columns_without_result + 2; |
979 | 25 | SubstringUtil::substring_execute(*block, temp_arguments, result_column_id, block->rows()); |
980 | | |
981 | 25 | ColumnPtr result_column = block->get_by_position(result_column_id).column; |
982 | 25 | if (is_nullable) { |
983 | 25 | result_column = ColumnNullable::create(std::move(result_column), null_map_column); |
984 | 25 | } |
985 | 25 | block->replace_by_position(idx, std::move(result_column)); |
986 | 25 | block->erase_tail(num_columns_without_result); |
987 | 25 | } |
988 | | |
989 | 60.1k | Status _try_materialize_aggregate_pushdown_rows(Block* block, bool* pushed_down) { |
990 | 60.1k | DORIS_CHECK(block != nullptr); |
991 | 60.1k | DORIS_CHECK(pushed_down != nullptr); |
992 | 60.1k | *pushed_down = false; |
993 | 60.1k | block->clear_column_data(_projected_columns.size()); |
994 | 60.1k | _aggregate_pushdown_tried = true; |
995 | 60.1k | if (!_supports_aggregate_pushdown(_push_down_agg_type)) { |
996 | 58.8k | return Status::OK(); |
997 | 58.8k | } |
998 | | |
999 | 1.28k | FileAggregateRequest file_request; |
1000 | 1.28k | RETURN_IF_ERROR(_build_file_aggregate_request(_push_down_agg_type, &file_request)); |
1001 | 1.28k | FileAggregateResult file_result; |
1002 | 1.28k | Status status; |
1003 | 1.28k | { |
1004 | 1.28k | SCOPED_TIMER(_profile.file_reader_total_timer); |
1005 | 1.28k | SCOPED_TIMER(_profile.file_reader_aggregate_timer); |
1006 | 1.28k | status = _data_reader.reader->get_aggregate_result(file_request, &file_result); |
1007 | 1.28k | } |
1008 | 1.28k | if (status.is<ErrorCode::NOT_IMPLEMENTED_ERROR>()) { |
1009 | 5 | return Status::OK(); |
1010 | 5 | } |
1011 | 1.27k | RETURN_IF_ERROR(status); |
1012 | 1.27k | RETURN_IF_ERROR( |
1013 | 1.27k | _materialize_aggregate_pushdown_rows(_push_down_agg_type, file_result, block)); |
1014 | 1.27k | if (_push_down_agg_type == TPushAggOp::type::COUNT) { |
1015 | 1.24k | _current_split_uses_metadata_count = true; |
1016 | 1.24k | } |
1017 | 1.27k | *pushed_down = true; |
1018 | 1.27k | RETURN_IF_ERROR(close_current_reader()); |
1019 | 1.27k | return Status::OK(); |
1020 | 1.27k | } |
1021 | | |
1022 | 61.4k | virtual bool _supports_aggregate_pushdown(TPushAggOp::type agg_type) const { |
1023 | | // Only COUNT and MIN/MAX can be push down. |
1024 | 61.4k | if (agg_type != TPushAggOp::type::COUNT && agg_type != TPushAggOp::type::MINMAX) { |
1025 | 57.9k | return false; |
1026 | 57.9k | } |
1027 | | // Aggregate pushdown returns reduced synthetic rows and may close the physical reader |
1028 | | // before the next scheduler turn. If a runtime filter is still pending, those rows could |
1029 | | // escape before the filter arrives and cannot later be reconstructed from real file rows. |
1030 | | // This is the same irreversibility constraint as table-level metadata COUNT, and applies |
1031 | | // to COUNT and MIN/MAX for Parquet/ORC as well as COUNT for text readers. |
1032 | 3.46k | if (!_all_runtime_filters_applied_for_split) { |
1033 | 2 | return false; |
1034 | 2 | } |
1035 | | // Scanner owns the original conjunct list and evaluates it after TableReader finalizes |
1036 | | // rows. Even a slotless conjunct that cannot become a TableFilter must see every source |
1037 | | // row before an aggregate reduces the stream to synthetic COUNT/MINMAX rows. |
1038 | 3.46k | if (!_conjuncts.empty()) { |
1039 | 5 | return false; |
1040 | 5 | } |
1041 | | // Only support aggregate pushdown when there is no delete or filter, so |
1042 | | // the reduced rows consumed by the upper aggregate remain semantically equivalent to a |
1043 | | // normal scan. |
1044 | 3.45k | if ((_delete_rows != nullptr && !_delete_rows->empty()) || |
1045 | 3.45k | (_deletion_vector != nullptr && !_deletion_vector->isEmpty())) { |
1046 | 597 | return false; |
1047 | 597 | } |
1048 | 2.85k | if (!_table_filters.empty()) { |
1049 | 0 | return false; |
1050 | 0 | } |
1051 | 2.85k | if (agg_type == TPushAggOp::type::COUNT) { |
1052 | | // Old FEs do not serialize push_down_count_slot_ids. During the supported BE-first |
1053 | | // rolling upgrade, nullopt therefore means "COUNT semantics are unknown", not |
1054 | | // COUNT(*). Fall back to reading rows until the FE explicitly sends either an empty |
1055 | | // list for COUNT(*) or one slot for COUNT(col). |
1056 | 2.63k | if (!_push_down_count_columns.has_value()) { |
1057 | 3 | return false; |
1058 | 3 | } |
1059 | | // COUNT(*) needs no column metadata. COUNT(col) currently supports one direct file |
1060 | | // column; multiple COUNT arguments fall back to the normal scan so every upper |
1061 | | // aggregate receives the original rows. |
1062 | 2.62k | if (_push_down_count_columns->empty()) { |
1063 | 2.62k | return true; |
1064 | 2.62k | } |
1065 | 9 | if (_push_down_count_columns->size() != 1) { |
1066 | 1 | return false; |
1067 | 1 | } |
1068 | 8 | const auto& mapping = _push_down_count_mapping(); |
1069 | | // Metadata COUNT skips TableReader's normal materialization path. Only a trivial |
1070 | | // mapping is safe: for example, a nullable Parquet INT mapped to a NOT NULL table |
1071 | | // BIGINT normally needs both an INT->BIGINT cast and nullability validation. Counting |
1072 | | // footer values directly would bypass both operations and could hide invalid data. |
1073 | 8 | return mapping.file_local_id.has_value() && mapping.file_type != nullptr && |
1074 | 8 | mapping.table_type != nullptr && mapping.is_trivial && |
1075 | 8 | mapping.virtual_column_type == TableVirtualColumnType::INVALID && |
1076 | 8 | mapping.default_expr == nullptr; |
1077 | 9 | } |
1078 | | // For MIN/MAX, only support direct file-to-table column mappings. The two emitted rows |
1079 | | // must be enough for the upper MIN/MAX aggregate without evaluating default expressions or |
1080 | | // virtual columns. |
1081 | 325 | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1082 | 325 | if (!mapping.file_local_id.has_value() || |
1083 | 325 | mapping.virtual_column_type != TableVirtualColumnType::INVALID || |
1084 | 325 | mapping.default_expr != nullptr || mapping.file_type == nullptr || |
1085 | 325 | mapping.table_type == nullptr) { |
1086 | 9 | return false; |
1087 | 9 | } |
1088 | 316 | if (!_can_push_down_minmax_for_mapping(mapping)) { |
1089 | 222 | return false; |
1090 | 222 | } |
1091 | 316 | } |
1092 | 18.4E | return true; |
1093 | 227 | } |
1094 | | |
1095 | 676k | static ColumnPtr _detach_column(ColumnPtr column) { |
1096 | 676k | DORIS_CHECK(column.get() != nullptr); |
1097 | 676k | return IColumn::mutate(std::move(column)); |
1098 | 676k | } |
1099 | | |
1100 | 112k | static ColumnPtr _take_and_detach_block_column(Block* block, int position) { |
1101 | 112k | DORIS_CHECK(block != nullptr); |
1102 | 112k | DORIS_CHECK(position >= 0 && position < static_cast<int>(block->columns())); |
1103 | 112k | auto& source = block->get_by_position(position); |
1104 | 112k | ColumnPtr column = source.column; |
1105 | | // The final mapping no longer needs the file block. Release its COW owner before mutate(), |
1106 | | // otherwise nested MAP/STRING columns are deep-copied and a multi-GB payload can OOM. |
1107 | 112k | block->replace_by_position(position, source.type->create_column()); |
1108 | 112k | return _detach_column(std::move(column)); |
1109 | 112k | } |
1110 | | |
1111 | 94.4k | static Status _align_column_nullability(ColumnPtr* column, const DataTypePtr& table_type) { |
1112 | 94.4k | DORIS_CHECK(column != nullptr); |
1113 | 94.4k | DORIS_CHECK(column->get() != nullptr); |
1114 | 94.4k | DORIS_CHECK(table_type != nullptr); |
1115 | | // Must return non-const column |
1116 | 94.4k | *column = (*column)->convert_to_full_column_if_const(); |
1117 | 94.4k | if (table_type->is_nullable()) { |
1118 | 47.1k | const auto& nested_type = |
1119 | 47.1k | assert_cast<const DataTypeNullable&>(*table_type).get_nested_type(); |
1120 | 47.1k | if (!(*column)->is_nullable()) { |
1121 | 2 | RETURN_IF_ERROR(_align_column_nullability(column, nested_type)); |
1122 | 2 | *column = make_nullable(*column); |
1123 | 2 | return Status::OK(); |
1124 | 2 | } |
1125 | 47.1k | const auto& nullable_column = assert_cast<const ColumnNullable&>(**column); |
1126 | 47.1k | ColumnPtr nested_column = nullable_column.get_nested_column_ptr(); |
1127 | 47.1k | RETURN_IF_ERROR(_align_column_nullability(&nested_column, nested_type)); |
1128 | 47.1k | *column = ColumnNullable::create(nested_column, |
1129 | 47.1k | nullable_column.get_null_map_column_ptr()); |
1130 | 47.1k | return Status::OK(); |
1131 | 47.1k | } |
1132 | 47.2k | if ((*column)->is_nullable()) { |
1133 | 0 | const auto& nullable_column = assert_cast<const ColumnNullable&>(**column); |
1134 | 0 | if (nullable_column.has_null()) { |
1135 | 0 | return Status::InternalError( |
1136 | 0 | "Default expression produced NULL for non-nullable table column"); |
1137 | 0 | } |
1138 | 0 | ColumnPtr nested_column = nullable_column.get_nested_column_ptr(); |
1139 | 0 | RETURN_IF_ERROR(_align_column_nullability(&nested_column, table_type)); |
1140 | 0 | *column = nested_column; |
1141 | 0 | return Status::OK(); |
1142 | 0 | } |
1143 | 47.2k | if (const auto* array_type = typeid_cast<const DataTypeArray*>(table_type.get())) { |
1144 | 129 | const auto& array_column = assert_cast<const ColumnArray&>(**column); |
1145 | 129 | ColumnPtr nested_column = array_column.get_data_ptr(); |
1146 | 129 | RETURN_IF_ERROR( |
1147 | 129 | _align_column_nullability(&nested_column, array_type->get_nested_type())); |
1148 | 129 | *column = ColumnArray::create(nested_column, array_column.get_offsets_ptr()); |
1149 | 129 | return Status::OK(); |
1150 | 129 | } |
1151 | 47.1k | if (const auto* map_type = typeid_cast<const DataTypeMap*>(table_type.get())) { |
1152 | 8 | const auto& map_column = assert_cast<const ColumnMap&>(**column); |
1153 | 8 | ColumnPtr key_column = map_column.get_keys_ptr(); |
1154 | 8 | ColumnPtr value_column = map_column.get_values_ptr(); |
1155 | 8 | RETURN_IF_ERROR(_align_column_nullability(&key_column, map_type->get_key_type())); |
1156 | 8 | RETURN_IF_ERROR(_align_column_nullability(&value_column, map_type->get_value_type())); |
1157 | 8 | *column = ColumnMap::create(key_column, value_column, map_column.get_offsets_ptr()); |
1158 | 8 | return Status::OK(); |
1159 | 8 | } |
1160 | 47.1k | if (const auto* struct_type = typeid_cast<const DataTypeStruct*>(table_type.get())) { |
1161 | 5.62k | const auto& struct_column = assert_cast<const ColumnStruct&>(**column); |
1162 | 5.62k | Columns columns = struct_column.get_columns_copy(); |
1163 | 5.62k | DORIS_CHECK(columns.size() == struct_type->get_elements().size()); |
1164 | 19.0k | for (size_t i = 0; i < columns.size(); ++i) { |
1165 | 13.3k | RETURN_IF_ERROR( |
1166 | 13.3k | _align_column_nullability(&columns[i], struct_type->get_element(i))); |
1167 | 13.3k | } |
1168 | 5.62k | *column = ColumnStruct::create(columns); |
1169 | 5.62k | return Status::OK(); |
1170 | 5.62k | } |
1171 | 41.4k | return Status::OK(); |
1172 | 47.1k | } |
1173 | | |
1174 | | static Status _execute_default_expr_without_root_type_check( |
1175 | | const VExprContextSPtr& default_expr, const Block* block, |
1176 | 16.6k | ColumnWithTypeAndName* result_data) { |
1177 | 16.6k | DORIS_CHECK(default_expr != nullptr); |
1178 | 16.6k | DORIS_CHECK(block != nullptr); |
1179 | 16.6k | DORIS_CHECK(result_data != nullptr); |
1180 | 16.6k | ColumnPtr result_column; |
1181 | 16.6k | Status st; |
1182 | 16.6k | RETURN_IF_CATCH_EXCEPTION({ |
1183 | 16.6k | st = default_expr->root()->execute_column_impl(default_expr.get(), block, nullptr, |
1184 | 16.6k | block->rows(), result_column); |
1185 | 16.6k | }); |
1186 | 16.6k | RETURN_IF_ERROR(st); |
1187 | 16.6k | DORIS_CHECK(result_column.get() != nullptr); |
1188 | 16.6k | if (result_column->size() != block->rows()) { |
1189 | 0 | return Status::InternalError( |
1190 | 0 | "Default expr {} return column size {} not equal to expected size {}", |
1191 | 0 | default_expr->expr_name(), result_column->size(), block->rows()); |
1192 | 0 | } |
1193 | 16.6k | result_data->column = result_column; |
1194 | 16.6k | result_data->type = default_expr->execute_type(block); |
1195 | 16.6k | result_data->name = default_expr->expr_name(); |
1196 | 16.6k | return Status::OK(); |
1197 | 16.6k | } |
1198 | | |
1199 | | Status _cast_column_to_type(ColumnPtr* column, const DataTypePtr& file_type, |
1200 | | const DataTypePtr& table_type, |
1201 | 8.74k | const std::string& column_name) const { |
1202 | 8.74k | DORIS_CHECK(column != nullptr); |
1203 | 8.74k | DORIS_CHECK(column->get() != nullptr); |
1204 | 8.74k | DORIS_CHECK(file_type != nullptr); |
1205 | 8.74k | DORIS_CHECK(table_type != nullptr); |
1206 | 8.74k | if (file_type->equals(*table_type)) { |
1207 | 0 | return Status::OK(); |
1208 | 0 | } |
1209 | | |
1210 | 8.74k | DataTypePtr input_type = file_type; |
1211 | | // Cast wrappers unwrap nullable inputs according to the declared input type, so keep the |
1212 | | // root nullability of the declared type aligned with the actual column shape. |
1213 | 8.74k | if ((*column)->is_nullable() && !input_type->is_nullable()) { |
1214 | 0 | input_type = make_nullable(input_type); |
1215 | 8.74k | } else if (!(*column)->is_nullable() && input_type->is_nullable()) { |
1216 | 1 | input_type = remove_nullable(input_type); |
1217 | 1 | } |
1218 | 8.74k | Block cast_block; |
1219 | 8.74k | cast_block.insert({*column, input_type, column_name}); |
1220 | 8.74k | auto slot_ref = VSlotRef::create_shared(0, 0, -1, input_type, column_name); |
1221 | 8.74k | auto cast_expr = Cast::create_shared(table_type); |
1222 | 8.74k | cast_expr->add_child(std::move(slot_ref)); |
1223 | 8.74k | auto cast_ctx = VExprContext::create_shared(std::move(cast_expr)); |
1224 | 8.74k | RowDescriptor row_desc; |
1225 | 8.74k | RETURN_IF_ERROR(cast_ctx->prepare(_runtime_state, row_desc)); |
1226 | 8.74k | RETURN_IF_ERROR(cast_ctx->open(_runtime_state)); |
1227 | 8.74k | ColumnPtr cast_column; |
1228 | 8.74k | RETURN_IF_ERROR(cast_ctx->execute(&cast_block, cast_column)); |
1229 | 8.74k | *column = std::move(cast_column); |
1230 | 8.74k | return Status::OK(); |
1231 | 8.74k | } |
1232 | | |
1233 | | Status _materialize_present_child_mapping_column(const ColumnMapping& mapping, |
1234 | | const ColumnPtr& file_column, |
1235 | 17.0k | const size_t rows, ColumnPtr* column) { |
1236 | 17.0k | DORIS_CHECK(column != nullptr); |
1237 | 17.0k | DORIS_CHECK(mapping.file_type != nullptr); |
1238 | 17.0k | DORIS_CHECK(mapping.table_type != nullptr); |
1239 | 17.0k | *column = file_column; |
1240 | 17.0k | if (!mapping.is_trivial) { |
1241 | 10.7k | if (!mapping.child_mappings.empty()) { |
1242 | 1.99k | RETURN_IF_ERROR( |
1243 | 1.99k | _materialize_complex_mapping_column(mapping, *column, rows, column)); |
1244 | 8.74k | } else { |
1245 | 8.74k | RETURN_IF_ERROR(_cast_column_to_type(column, mapping.file_type, mapping.table_type, |
1246 | 8.74k | mapping.file_column_name)); |
1247 | 8.74k | } |
1248 | 10.7k | } |
1249 | 17.0k | RETURN_IF_ERROR(_align_column_nullability(column, mapping.table_type)); |
1250 | 17.0k | return Status::OK(); |
1251 | 17.0k | } |
1252 | | |
1253 | | Status _materialize_mapping_column(const ColumnMapping& mapping, Block* current_block, |
1254 | | const size_t rows, ColumnPtr* column, |
1255 | 684k | bool take_projection_result = false) { |
1256 | 684k | if (!mapping.is_trivial && mapping.file_local_id.has_value() && |
1257 | 684k | !mapping.child_mappings.empty()) { |
1258 | 9.60k | DCHECK(mapping.projection != nullptr); |
1259 | 9.60k | int res_id; |
1260 | 9.60k | auto st = mapping.projection->execute(current_block, &res_id); |
1261 | 9.60k | if (!st.ok()) { |
1262 | 0 | return Status::InternalError( |
1263 | 0 | "Failed to execute complex mapping projection for table column '{}' " |
1264 | 0 | "(global_index={}, file_local_id={}, rows={}): {}, mapping={}", |
1265 | 0 | mapping.table_column_name, mapping.global_index.value(), |
1266 | 0 | *mapping.file_local_id, rows, st.to_string(), mapping.debug_string()); |
1267 | 0 | } |
1268 | 9.60k | ColumnPtr result_column = take_projection_result |
1269 | 9.60k | ? _take_and_detach_block_column(current_block, res_id) |
1270 | 9.60k | : current_block->get_by_position(res_id).column; |
1271 | 9.60k | RETURN_IF_ERROR( |
1272 | 9.60k | _materialize_complex_mapping_column(mapping, result_column, rows, column)); |
1273 | 9.60k | return Status::OK(); |
1274 | 9.60k | } |
1275 | 675k | if (mapping.projection != nullptr) { |
1276 | 655k | int res_id; |
1277 | 655k | auto st = mapping.projection->execute(current_block, &res_id); |
1278 | 655k | if (!st.ok()) { |
1279 | 1 | std::string file_local_id = "null"; |
1280 | 1 | if (mapping.file_local_id.has_value()) { |
1281 | 1 | file_local_id = std::to_string(*mapping.file_local_id); |
1282 | 1 | } |
1283 | 1 | return Status::InternalError( |
1284 | 1 | "Failed to execute mapping projection for table column '{}' " |
1285 | 1 | "(global_index={}, file_local_id={}, rows={}): {}, mapping={}", |
1286 | 1 | mapping.table_column_name, mapping.global_index.value(), file_local_id, |
1287 | 1 | rows, st.to_string(), mapping.debug_string()); |
1288 | 1 | } |
1289 | 655k | if (take_projection_result) { |
1290 | 111k | *column = _take_and_detach_block_column(current_block, res_id); |
1291 | 544k | } else { |
1292 | 544k | ColumnPtr result_column = current_block->get_by_position(res_id).column; |
1293 | 544k | *column = _detach_column(std::move(result_column)); |
1294 | 544k | } |
1295 | 655k | return Status::OK(); |
1296 | 655k | } |
1297 | 19.5k | if (mapping.default_expr != nullptr) { |
1298 | 16.6k | if (current_block->rows() == rows) { |
1299 | 14.6k | ColumnWithTypeAndName result; |
1300 | 14.6k | RETURN_IF_ERROR(_execute_default_expr_without_root_type_check( |
1301 | 14.6k | mapping.default_expr, current_block, &result)); |
1302 | 14.6k | ColumnPtr result_column = result.column; |
1303 | 14.6k | RETURN_IF_ERROR(_align_column_nullability(&result_column, mapping.table_type)); |
1304 | 14.6k | *column = _detach_column(std::move(result_column)); |
1305 | 14.6k | } else { |
1306 | 1.98k | DORIS_CHECK(mapping.constant_index.has_value()); |
1307 | 1.98k | Block eval_block; |
1308 | 1.98k | eval_block.insert({mapping.table_type->create_column_const_with_default_value(rows), |
1309 | 1.98k | mapping.table_type, "__table_reader_const_rows"}); |
1310 | 1.98k | ColumnWithTypeAndName result; |
1311 | 1.98k | RETURN_IF_ERROR(_execute_default_expr_without_root_type_check( |
1312 | 1.98k | mapping.default_expr, &eval_block, &result)); |
1313 | 1.98k | ColumnPtr result_column = result.column; |
1314 | 1.98k | RETURN_IF_ERROR(_align_column_nullability(&result_column, mapping.table_type)); |
1315 | 1.98k | *column = _detach_column(std::move(result_column)); |
1316 | 1.98k | } |
1317 | 16.6k | return Status::OK(); |
1318 | 16.6k | } |
1319 | 2.86k | ColumnPtr result_column = mapping.table_type->create_column_const_with_default_value(rows); |
1320 | 2.86k | *column = _detach_column(std::move(result_column)); |
1321 | 2.86k | return Status::OK(); |
1322 | 19.5k | } |
1323 | | |
1324 | | Status _materialize_complex_mapping_column(const ColumnMapping& mapping, |
1325 | | const ColumnPtr& file_column, const size_t rows, |
1326 | 11.5k | ColumnPtr* column) { |
1327 | 11.5k | DORIS_CHECK(mapping.table_type != nullptr); |
1328 | 11.5k | DORIS_CHECK(file_column.get() != nullptr); |
1329 | 11.5k | const auto table_type = remove_nullable(mapping.table_type); |
1330 | 11.5k | switch (table_type->get_primitive_type()) { |
1331 | 3.61k | case TYPE_STRUCT: |
1332 | 3.61k | RETURN_IF_ERROR(_materialize_struct_mapping_column(mapping, file_column, rows, column)); |
1333 | 3.61k | break; |
1334 | 4.43k | case TYPE_ARRAY: |
1335 | 4.43k | RETURN_IF_ERROR(_materialize_array_mapping_column(mapping, file_column, rows, column)); |
1336 | 4.43k | break; |
1337 | 4.43k | case TYPE_MAP: |
1338 | 3.54k | RETURN_IF_ERROR(_materialize_map_mapping_column(mapping, file_column, rows, column)); |
1339 | 3.54k | break; |
1340 | 3.54k | default: |
1341 | 0 | *column = _detach_column(file_column); |
1342 | 0 | break; |
1343 | 11.5k | } |
1344 | 11.5k | return Status::OK(); |
1345 | 11.5k | } |
1346 | | |
1347 | | static std::vector<const ColumnMapping*> _present_child_mappings_in_file_order( |
1348 | 3.61k | const std::vector<ColumnMapping>& child_mappings) { |
1349 | 3.61k | std::vector<const ColumnMapping*> result; |
1350 | 3.61k | result.reserve(child_mappings.size()); |
1351 | 9.10k | for (const auto& child_mapping : child_mappings) { |
1352 | 9.10k | if (child_mapping.file_local_id.has_value()) { |
1353 | 5.48k | result.push_back(&child_mapping); |
1354 | 5.48k | } |
1355 | 9.10k | } |
1356 | 3.88k | std::ranges::sort(result, [](const ColumnMapping* lhs, const ColumnMapping* rhs) { |
1357 | 3.88k | DORIS_CHECK(lhs->file_local_id.has_value()); |
1358 | 3.88k | DORIS_CHECK(rhs->file_local_id.has_value()); |
1359 | 3.88k | return *lhs->file_local_id < *rhs->file_local_id; |
1360 | 3.88k | }); |
1361 | 3.61k | return result; |
1362 | 3.61k | } |
1363 | | |
1364 | | static size_t _file_child_ordinal_for_mapping( |
1365 | | const ColumnMapping& mapping, const ColumnMapping& child_mapping, |
1366 | 5.48k | const std::vector<const ColumnMapping*>& file_ordered_children) { |
1367 | 5.48k | DORIS_CHECK(child_mapping.file_local_id.has_value()); |
1368 | 5.48k | if (!mapping.projected_file_children.empty()) { |
1369 | 5.48k | const auto child_it = std::ranges::find_if( |
1370 | 8.04k | mapping.projected_file_children, [&](const ColumnDefinition& file_child) { |
1371 | 8.04k | return file_child.file_local_id() == *child_mapping.file_local_id; |
1372 | 8.04k | }); |
1373 | 5.48k | DORIS_CHECK(child_it != mapping.projected_file_children.end()); |
1374 | 5.48k | return static_cast<size_t>( |
1375 | 5.48k | std::distance(mapping.projected_file_children.begin(), child_it)); |
1376 | 5.48k | } |
1377 | 4 | const auto child_it = std::ranges::find(file_ordered_children, &child_mapping); |
1378 | 4 | DORIS_CHECK(child_it != file_ordered_children.end()); |
1379 | 4 | return static_cast<size_t>(std::distance(file_ordered_children.begin(), child_it)); |
1380 | 5.48k | } |
1381 | | |
1382 | | static std::vector<const ColumnMapping*> _child_mappings_in_table_type_order( |
1383 | 3.61k | const ColumnMapping& mapping, const DataTypeStruct& table_type) { |
1384 | 3.61k | std::vector<const ColumnMapping*> result; |
1385 | 3.61k | result.reserve(mapping.child_mappings.size()); |
1386 | 12.7k | for (size_t child_idx = 0; child_idx < table_type.get_elements().size(); ++child_idx) { |
1387 | 9.10k | const auto& child_name = table_type.get_element_name(child_idx); |
1388 | 9.10k | const auto child_it = std::ranges::find_if( |
1389 | 17.0k | mapping.child_mappings, [&](const ColumnMapping& child_mapping) { |
1390 | 17.0k | return child_mapping.table_column_name == child_name; |
1391 | 17.0k | }); |
1392 | 9.10k | DORIS_CHECK(child_it != mapping.child_mappings.end()) |
1393 | 0 | << mapping.debug_string() << ", table_child_name=" << child_name; |
1394 | 9.10k | result.push_back(&*child_it); |
1395 | 9.10k | } |
1396 | 3.61k | return result; |
1397 | 3.61k | } |
1398 | | |
1399 | | static const IColumn* _nested_column_if_nullable(const ColumnPtr& column, |
1400 | 11.5k | const NullMap** null_map) { |
1401 | 11.5k | DORIS_CHECK(column.get() != nullptr); |
1402 | 11.5k | if (const auto* nullable_column = check_and_get_column<ColumnNullable>(*column)) { |
1403 | 11.5k | if (null_map != nullptr) { |
1404 | 11.5k | *null_map = &nullable_column->get_null_map_data(); |
1405 | 11.5k | } |
1406 | 11.5k | return &nullable_column->get_nested_column(); |
1407 | 11.5k | } |
1408 | 2 | return column.get(); |
1409 | 11.5k | } |
1410 | | |
1411 | | Status _materialize_struct_mapping_column(const ColumnMapping& mapping, |
1412 | | const ColumnPtr& file_column, const size_t rows, |
1413 | 3.61k | ColumnPtr* column) { |
1414 | 3.61k | DORIS_CHECK(mapping.table_type != nullptr); |
1415 | 3.61k | const auto* table_type = |
1416 | 3.61k | assert_cast<const DataTypeStruct*>(remove_nullable(mapping.table_type).get()); |
1417 | 3.61k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1418 | 3.61k | const NullMap* parent_null_map = nullptr; |
1419 | 3.61k | const auto* nested_file_column = |
1420 | 3.61k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1421 | 3.61k | const auto* file_struct = assert_cast<const ColumnStruct*>(nested_file_column); |
1422 | 3.61k | DORIS_CHECK(table_type->get_elements().size() == mapping.child_mappings.size()); |
1423 | | |
1424 | 3.61k | Columns child_columns; |
1425 | 3.61k | child_columns.reserve(mapping.child_mappings.size()); |
1426 | 3.61k | const auto file_ordered_children = |
1427 | 3.61k | _present_child_mappings_in_file_order(mapping.child_mappings); |
1428 | 3.61k | const auto table_ordered_children = |
1429 | 3.61k | _child_mappings_in_table_type_order(mapping, *table_type); |
1430 | 9.10k | for (const auto* child_mapping : table_ordered_children) { |
1431 | 9.10k | DORIS_CHECK(child_mapping != nullptr); |
1432 | 9.10k | if (!child_mapping->file_local_id.has_value()) { |
1433 | 3.61k | child_columns.push_back( |
1434 | 3.61k | child_mapping->table_type->create_column_const_with_default_value(rows) |
1435 | 3.61k | ->convert_to_full_column_if_const()); |
1436 | 3.61k | continue; |
1437 | 3.61k | } |
1438 | 5.48k | const auto file_child_idx = |
1439 | 5.48k | _file_child_ordinal_for_mapping(mapping, *child_mapping, file_ordered_children); |
1440 | 5.48k | DORIS_CHECK(file_child_idx < file_struct->get_columns().size()); |
1441 | 5.48k | ColumnPtr child_column = file_struct->get_column_ptr(file_child_idx); |
1442 | 5.48k | RETURN_IF_ERROR(_materialize_present_child_mapping_column(*child_mapping, child_column, |
1443 | 5.48k | rows, &child_column)); |
1444 | 5.48k | child_columns.push_back(std::move(child_column)); |
1445 | 5.48k | } |
1446 | 3.61k | MutableColumns mutable_child_columns; |
1447 | 3.61k | mutable_child_columns.reserve(child_columns.size()); |
1448 | 9.10k | for (auto& child_column : child_columns) { |
1449 | 9.10k | mutable_child_columns.push_back(IColumn::mutate(std::move(child_column))); |
1450 | 9.10k | } |
1451 | 3.61k | auto result = ColumnStruct::create(std::move(mutable_child_columns)); |
1452 | 3.61k | if (mapping.table_type->is_nullable()) { |
1453 | 3.61k | auto null_map = ColumnUInt8::create(); |
1454 | 3.61k | auto& null_map_data = null_map->get_data(); |
1455 | 3.61k | null_map_data.resize(rows); |
1456 | 3.61k | if (parent_null_map != nullptr) { |
1457 | 3.61k | DORIS_CHECK(parent_null_map->size() == rows); |
1458 | 3.61k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1459 | 3.61k | } else { |
1460 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1461 | 0 | } |
1462 | 3.61k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1463 | 3.61k | } else { |
1464 | 2 | *column = std::move(result); |
1465 | 2 | } |
1466 | 3.61k | return Status::OK(); |
1467 | 3.61k | } |
1468 | | |
1469 | | Status _materialize_array_mapping_column(const ColumnMapping& mapping, |
1470 | | const ColumnPtr& file_column, const size_t rows, |
1471 | 4.43k | ColumnPtr* column) { |
1472 | 4.43k | DORIS_CHECK(mapping.child_mappings.size() == 1); |
1473 | 4.43k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1474 | 4.43k | const NullMap* parent_null_map = nullptr; |
1475 | 4.43k | const auto* nested_file_column = |
1476 | 4.43k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1477 | 4.43k | const auto* file_array = assert_cast<const ColumnArray*>(nested_file_column); |
1478 | 4.43k | ColumnPtr nested_column = file_array->get_data_ptr(); |
1479 | 4.43k | const auto& element_mapping = mapping.child_mappings[0]; |
1480 | 4.43k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1481 | 4.43k | element_mapping, nested_column, nested_column->size(), &nested_column)); |
1482 | 4.43k | auto offsets_column = file_array->get_offsets_ptr()->convert_to_full_column_if_const(); |
1483 | 4.43k | auto result = ColumnArray::create(IColumn::mutate(std::move(nested_column)), |
1484 | 4.43k | IColumn::mutate(std::move(offsets_column))); |
1485 | 4.43k | if (mapping.table_type->is_nullable()) { |
1486 | 4.43k | auto null_map = ColumnUInt8::create(); |
1487 | 4.43k | auto& null_map_data = null_map->get_data(); |
1488 | 4.43k | null_map_data.resize(rows); |
1489 | 4.43k | if (parent_null_map != nullptr) { |
1490 | 4.43k | DORIS_CHECK(parent_null_map->size() == rows); |
1491 | 4.43k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1492 | 4.43k | } else { |
1493 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1494 | 0 | } |
1495 | 4.43k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1496 | 4.43k | } else { |
1497 | 0 | *column = std::move(result); |
1498 | 0 | } |
1499 | 4.43k | return Status::OK(); |
1500 | 4.43k | } |
1501 | | |
1502 | | Status _materialize_map_mapping_column(const ColumnMapping& mapping, |
1503 | | const ColumnPtr& file_column, const size_t rows, |
1504 | 3.54k | ColumnPtr* column) { |
1505 | 3.54k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1506 | 3.54k | const NullMap* parent_null_map = nullptr; |
1507 | 3.54k | const auto* nested_file_column = |
1508 | 3.54k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1509 | 3.54k | const auto* file_map = assert_cast<const ColumnMap*>(nested_file_column); |
1510 | 3.54k | ColumnPtr key_column = file_map->get_keys_ptr(); |
1511 | 3.54k | ColumnPtr value_column = file_map->get_values_ptr(); |
1512 | | |
1513 | 3.54k | const ColumnMapping* key_mapping = nullptr; |
1514 | 3.54k | const ColumnMapping* value_mapping = nullptr; |
1515 | 7.09k | for (const auto& child_mapping : mapping.child_mappings) { |
1516 | 7.09k | if (!child_mapping.file_local_id.has_value()) { |
1517 | 0 | continue; |
1518 | 0 | } |
1519 | 7.09k | if (*child_mapping.file_local_id == 0) { |
1520 | 3.54k | key_mapping = &child_mapping; |
1521 | 3.54k | } else if (*child_mapping.file_local_id == 1) { |
1522 | 3.54k | value_mapping = &child_mapping; |
1523 | 3.54k | } |
1524 | 7.09k | } |
1525 | | |
1526 | 3.54k | if (key_mapping != nullptr) { |
1527 | 3.54k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1528 | 3.54k | *key_mapping, key_column, key_column->size(), &key_column)); |
1529 | 3.54k | } |
1530 | 3.54k | if (value_mapping != nullptr) { |
1531 | 3.54k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1532 | 3.54k | *value_mapping, value_column, value_column->size(), &value_column)); |
1533 | 3.54k | } |
1534 | 3.54k | auto offsets_column = file_map->get_offsets_ptr()->convert_to_full_column_if_const(); |
1535 | 3.54k | auto result = ColumnMap::create(IColumn::mutate(std::move(key_column)), |
1536 | 3.54k | IColumn::mutate(std::move(value_column)), |
1537 | 3.54k | IColumn::mutate(std::move(offsets_column))); |
1538 | 3.54k | if (mapping.table_type->is_nullable()) { |
1539 | 3.54k | auto null_map = ColumnUInt8::create(); |
1540 | 3.54k | auto& null_map_data = null_map->get_data(); |
1541 | 3.54k | null_map_data.resize(rows); |
1542 | 3.54k | if (parent_null_map != nullptr) { |
1543 | 3.54k | DORIS_CHECK(parent_null_map->size() == rows); |
1544 | 3.54k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1545 | 3.54k | } else { |
1546 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1547 | 0 | } |
1548 | 3.54k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1549 | 3.54k | } else { |
1550 | 0 | *column = std::move(result); |
1551 | 0 | } |
1552 | 3.54k | return Status::OK(); |
1553 | 3.54k | } |
1554 | | |
1555 | 59.9k | Status _open_mapping_exprs() { |
1556 | 59.9k | RowDescriptor row_desc; |
1557 | 396k | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1558 | 396k | if (mapping.projection != nullptr) { |
1559 | 376k | RETURN_IF_ERROR(mapping.projection->prepare(_runtime_state, row_desc)); |
1560 | 376k | RETURN_IF_ERROR(mapping.projection->open(_runtime_state)); |
1561 | 376k | } |
1562 | 396k | if (mapping.default_expr != nullptr) { |
1563 | 17.2k | RETURN_IF_ERROR(mapping.default_expr->prepare(_runtime_state, row_desc)); |
1564 | 17.2k | RETURN_IF_ERROR(mapping.default_expr->open(_runtime_state)); |
1565 | 17.2k | } |
1566 | 396k | } |
1567 | 59.9k | return Status::OK(); |
1568 | 59.9k | } |
1569 | | |
1570 | | Status _build_file_aggregate_request(TPushAggOp::type agg_type, |
1571 | 1.26k | FileAggregateRequest* request) const { |
1572 | 1.26k | DORIS_CHECK(request != nullptr); |
1573 | 1.26k | DORIS_CHECK(_supports_aggregate_pushdown(agg_type)); |
1574 | 1.26k | request->agg_type = agg_type; |
1575 | 1.26k | request->columns.clear(); |
1576 | 1.26k | if (agg_type == TPushAggOp::type::COUNT) { |
1577 | 1.24k | DORIS_CHECK(_push_down_count_columns.has_value()); |
1578 | | // An empty explicit list is the semantic signal for COUNT(*). Do not inspect the |
1579 | | // mapping count: `SELECT COUNT(*) FROM t` may still project one nullable column because |
1580 | | // the planner keeps a placeholder slot. In a 10,000-row file where that arbitrary slot |
1581 | | // has 9,015 non-null values, passing the slot would ask Parquet/ORC metadata for |
1582 | | // COUNT(slot)=9,015 instead of the required row count 10,000. |
1583 | 1.24k | if (!_push_down_count_columns->empty()) { |
1584 | 3 | const auto& mapping = _push_down_count_mapping(); |
1585 | 3 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1586 | 3 | FileAggregateRequest::Column column; |
1587 | 3 | column.projection = |
1588 | 3 | LocalColumnIndex::top_level(LocalColumnId(*mapping.file_local_id)); |
1589 | 3 | request->columns.push_back(std::move(column)); |
1590 | 3 | } |
1591 | 1.24k | return Status::OK(); |
1592 | 1.24k | } |
1593 | 24 | request->columns.reserve(_data_reader.column_mapper->mappings().size()); |
1594 | 47 | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1595 | 47 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1596 | 47 | FileAggregateRequest::Column column; |
1597 | 47 | column.projection = LocalColumnIndex::top_level(LocalColumnId(*mapping.file_local_id)); |
1598 | 47 | if (!mapping.child_mappings.empty()) { |
1599 | 1 | RETURN_IF_ERROR(build_aggregate_projection(mapping, &column.projection)); |
1600 | 1 | } |
1601 | 47 | request->columns.push_back(std::move(column)); |
1602 | 47 | } |
1603 | 24 | return Status::OK(); |
1604 | 24 | } |
1605 | | |
1606 | 11 | const ColumnMapping& _push_down_count_mapping() const { |
1607 | 11 | DORIS_CHECK(_push_down_count_columns.has_value()); |
1608 | 11 | DORIS_CHECK(_push_down_count_columns->size() == 1); |
1609 | 11 | const auto mapping_it = |
1610 | 11 | std::ranges::find(_data_reader.column_mapper->mappings(), |
1611 | 11 | _push_down_count_columns->front(), &ColumnMapping::global_index); |
1612 | | // FileScannerV2 translates FE SlotIds through the same projected-column list used to build |
1613 | | // the mapper, so a missing mapping is an FE/BE contract violation rather than a fallback. |
1614 | 11 | DORIS_CHECK(mapping_it != _data_reader.column_mapper->mappings().end()); |
1615 | 11 | return *mapping_it; |
1616 | 11 | } |
1617 | | |
1618 | | Status _materialize_aggregate_pushdown_rows(TPushAggOp::type agg_type, |
1619 | | const FileAggregateResult& file_result, |
1620 | 1.26k | Block* block) { |
1621 | 1.26k | if (agg_type == TPushAggOp::type::COUNT) { |
1622 | | // COUNT pushdown is not a final count value. It emits `count` default rows so the |
1623 | | // upper COUNT(*) aggregate can count them and produce the final result, including |
1624 | | // zero rows when count is 0. |
1625 | 1.24k | DORIS_CHECK(file_result.count >= 0); |
1626 | 1.24k | return _materialize_count_rows(cast_set<size_t>(file_result.count), block); |
1627 | 1.24k | } |
1628 | | // MIN/MAX pushdown emits two rows, min first and max second, for each projected column. |
1629 | | // The upper MIN/MAX aggregate consumes those two rows to produce the final aggregate value. |
1630 | 21 | DORIS_CHECK(file_result.columns.size() == _data_reader.column_mapper->mappings().size()); |
1631 | 21 | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
1632 | 21 | Block file_block; |
1633 | 21 | file_block.reserve(_data_reader.file_block_layout.size()); |
1634 | 26 | for (const auto& column : _data_reader.file_block_layout) { |
1635 | 26 | file_block.insert({column.type->create_column(), column.type, column.name}); |
1636 | 26 | } |
1637 | 47 | for (size_t column_idx = 0; column_idx < file_result.columns.size(); ++column_idx) { |
1638 | 26 | const auto& result_column = file_result.columns[column_idx]; |
1639 | 26 | if (!result_column.has_min || !result_column.has_max) { |
1640 | 0 | return Status::NotSupported("Missing min/max aggregate result for column {}", |
1641 | 0 | _projected_columns[column_idx].name); |
1642 | 0 | } |
1643 | 26 | bool found_file_column = false; |
1644 | 33 | for (size_t block_position = 0; block_position < _data_reader.file_block_layout.size(); |
1645 | 33 | ++block_position) { |
1646 | 33 | if (_data_reader.file_block_layout[block_position].file_column_id == |
1647 | 33 | file_result.columns[column_idx].projection.column_id()) { |
1648 | 26 | found_file_column = true; |
1649 | 26 | auto column = file_block.get_by_position(block_position) |
1650 | 26 | .type->create_column() |
1651 | 26 | ->assert_mutable(); |
1652 | 26 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1653 | 26 | file_result.columns[column_idx].projection, result_column.min_value, |
1654 | 26 | column.get())); |
1655 | 26 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1656 | 26 | file_result.columns[column_idx].projection, result_column.max_value, |
1657 | 26 | column.get())); |
1658 | 26 | file_block.replace_by_position(block_position, std::move(column)); |
1659 | 26 | break; |
1660 | 26 | } |
1661 | 33 | } |
1662 | 26 | DORIS_CHECK(found_file_column); |
1663 | 26 | } |
1664 | 47 | for (size_t column_idx = 0; column_idx < _data_reader.column_mapper->mappings().size(); |
1665 | 26 | ++column_idx) { |
1666 | 26 | ColumnPtr table_column; |
1667 | 26 | RETURN_IF_ERROR(_materialize_mapping_column( |
1668 | 26 | _data_reader.column_mapper->mappings()[column_idx], &file_block, 2, |
1669 | 26 | &table_column, |
1670 | 26 | column_idx + 1 == _data_reader.column_mapper->mappings().size())); |
1671 | 26 | block->replace_by_position(column_idx, std::move(table_column)); |
1672 | 26 | } |
1673 | 21 | return Status::OK(); |
1674 | 21 | } |
1675 | | |
1676 | | struct FileBlockColumn { |
1677 | | LocalColumnId file_column_id = LocalColumnId::invalid(); |
1678 | | std::string name; |
1679 | | DataTypePtr type; |
1680 | | }; |
1681 | | |
1682 | | struct DataReader { |
1683 | | std::unique_ptr<FileReader> reader; |
1684 | | std::unique_ptr<TableColumnMapper> column_mapper; |
1685 | | // Schema of the data file, also including virtual column (row position). |
1686 | | std::vector<ColumnDefinition> file_schema; |
1687 | | // Layout of the block returned by file reader, determined by column mapping and file |
1688 | | // schema. It is used for file reader to materialize columns into correct type and position. |
1689 | | std::vector<FileBlockColumn> file_block_layout; |
1690 | | Block block_template; |
1691 | | }; |
1692 | | DataReader _data_reader; |
1693 | | std::vector<ColumnDefinition> _projected_columns; |
1694 | | std::unique_ptr<ScanTask> _current_task; |
1695 | | std::optional<io::FileDescription> _current_file_description; |
1696 | | // Range-level compression has higher priority than scan-param compression. TVF/load can keep |
1697 | | // the logical format as CSV/TEXT while carrying the concrete compression such as GZ or LZO on |
1698 | | // each TFileRangeDesc, matching the old FileScanner reader contract. |
1699 | | TFileCompressType::type _current_range_compress_type = TFileCompressType::UNKNOWN; |
1700 | | std::optional<TUniqueId> _current_range_load_id; |
1701 | | TFileRangeDesc _current_file_range_desc; |
1702 | | std::shared_ptr<io::FileSystemProperties> _system_properties; |
1703 | | // partition key -> value |
1704 | | std::map<std::string, Field> _partition_values; |
1705 | | // Predicates built from scan conjuncts before file-level localization. |
1706 | | std::vector<TableFilter> _table_filters; |
1707 | | // Number of localized filters before the first unsafe conjunct in the original row-level |
1708 | | // order. This differs from scanning `_table_filters` for safety because slotless predicates are |
1709 | | // intentionally absent from that vector but must still act as ordering barriers. |
1710 | | size_t _constant_pruning_safe_filter_count = 0; |
1711 | | VExprContextSPtrs _conjuncts; |
1712 | | ReadProfile _profile; |
1713 | | // Parsed from row-position based delete files, including position delete and deletion vector. |
1714 | | DeleteRows* _delete_rows = nullptr; |
1715 | | DeletionVector* _deletion_vector = nullptr; |
1716 | | TFileScanRangeParams* _scan_params; |
1717 | | std::shared_ptr<io::IOContext> _io_ctx; |
1718 | | RuntimeState* _runtime_state; |
1719 | | RuntimeProfile* _scanner_profile; |
1720 | | const std::vector<SlotDescriptor*>* _file_slot_descs = nullptr; |
1721 | | FileFormat _format; |
1722 | | TPushAggOp::type _push_down_agg_type = TPushAggOp::type::NONE; |
1723 | | std::optional<std::vector<GlobalIndex>> _push_down_count_columns; |
1724 | | size_t _batch_size = 0; |
1725 | | uint64_t _initial_condition_cache_digest = 0; |
1726 | | uint64_t _condition_cache_digest = 0; |
1727 | | // True only when prepare_split() received a digest for the exact conjunct snapshot used by |
1728 | | // this split. Standalone callers that only supplied TableReadOptions::condition_cache_digest |
1729 | | // keep the conservative runtime-filter guard. |
1730 | | bool _condition_cache_digest_covers_current_split = false; |
1731 | | segment_v2::ConditionCache::ExternalCacheKey _condition_cache_key; |
1732 | | std::shared_ptr<std::vector<bool>> _condition_cache; |
1733 | | std::shared_ptr<ConditionCacheContext> _condition_cache_ctx; |
1734 | | int64_t _condition_cache_hit_count = 0; |
1735 | | bool _current_reader_reached_eof = false; |
1736 | | int64_t _remaining_table_level_count = -1; |
1737 | | // True only after the active split selects a table-level row-count shortcut or successfully |
1738 | | // materializes COUNT rows from file metadata. FileScannerV2 uses this result, rather than the |
1739 | | // raw aggregate opcode, to keep adaptive batching enabled for normal row-scan fallbacks. |
1740 | | bool _current_split_uses_metadata_count = false; |
1741 | | // Snapshot supplied by FileScannerV2 for the active split. It gates every shortcut that emits |
1742 | | // irreversible aggregate rows, not only the table-level row-count shortcut in prepare_split(). |
1743 | | bool _all_runtime_filters_applied_for_split = true; |
1744 | | std::optional<GlobalRowIdContext> _global_rowid_context; |
1745 | | bool _aggregate_pushdown_tried = false; |
1746 | | bool _current_split_pruned = false; |
1747 | | TableColumnMapperOptions _mapper_options; |
1748 | | |
1749 | | private: |
1750 | | static const ColumnDefinition* _find_column_definition( |
1751 | 392k | const std::vector<ColumnDefinition>& schema, LocalColumnId column_id) { |
1752 | 9.42M | for (const auto& field : schema) { |
1753 | 9.42M | if (field.file_local_id() == column_id.value()) { |
1754 | 385k | return &field; |
1755 | 385k | } |
1756 | 9.42M | } |
1757 | 7.35k | return nullptr; |
1758 | 392k | } |
1759 | | |
1760 | 318 | static bool _can_push_down_minmax_for_mapping(const ColumnMapping& mapping) { |
1761 | 318 | if (mapping.child_mappings.empty()) { |
1762 | | // Direct mappings use a slot-ref projection to materialize the file column. The |
1763 | | // projection does not transform ordering; casts and other conversions are already |
1764 | | // represented by a non-trivial mapping and must fall back to row scanning. |
1765 | 315 | return mapping.is_trivial; |
1766 | 315 | } |
1767 | 3 | const auto primitive_type = remove_nullable(mapping.file_type)->get_primitive_type(); |
1768 | 3 | if (primitive_type != TYPE_STRUCT) { |
1769 | 1 | return false; |
1770 | 1 | } |
1771 | 2 | size_t mapped_children = 0; |
1772 | 2 | const ColumnMapping* mapped_child = nullptr; |
1773 | 2 | for (const auto& child_mapping : mapping.child_mappings) { |
1774 | 2 | if (!child_mapping.file_local_id.has_value()) { |
1775 | 0 | continue; |
1776 | 0 | } |
1777 | 2 | ++mapped_children; |
1778 | 2 | mapped_child = &child_mapping; |
1779 | 2 | } |
1780 | 2 | return mapped_children == 1 && mapped_child != nullptr && |
1781 | 2 | _can_push_down_minmax_for_mapping(*mapped_child); |
1782 | 3 | } |
1783 | | |
1784 | | static Status build_aggregate_projection(const ColumnMapping& mapping, |
1785 | 2 | LocalColumnIndex* projection) { |
1786 | 2 | DORIS_CHECK(projection != nullptr); |
1787 | 2 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1788 | 2 | *projection = LocalColumnIndex::local(*mapping.file_local_id); |
1789 | 2 | projection->children.clear(); |
1790 | 2 | projection->project_all_children = true; |
1791 | 2 | if (mapping.child_mappings.empty()) { |
1792 | 1 | return Status::OK(); |
1793 | 1 | } |
1794 | 1 | projection->project_all_children = false; |
1795 | 1 | for (const auto& child_mapping : mapping.child_mappings) { |
1796 | 1 | if (!child_mapping.file_local_id.has_value()) { |
1797 | 0 | continue; |
1798 | 0 | } |
1799 | 1 | LocalColumnIndex child_projection; |
1800 | 1 | RETURN_IF_ERROR(build_aggregate_projection(child_mapping, &child_projection)); |
1801 | 1 | projection->children.push_back(std::move(child_projection)); |
1802 | 1 | } |
1803 | 1 | DORIS_CHECK(projection->children.size() == 1); |
1804 | 1 | return Status::OK(); |
1805 | 1 | } |
1806 | | |
1807 | | static Status _insert_aggregate_projection_value(const LocalColumnIndex& projection, |
1808 | 108 | const Field& value, IColumn* column) { |
1809 | 108 | DORIS_CHECK(column != nullptr); |
1810 | 108 | if (auto* nullable_column = check_and_get_column<ColumnNullable>(*column)) { |
1811 | 54 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1812 | 54 | projection, value, &nullable_column->get_nested_column())); |
1813 | 54 | nullable_column->get_null_map_data().push_back(0); |
1814 | 54 | return Status::OK(); |
1815 | 54 | } |
1816 | 54 | if (projection.project_all_children || projection.children.empty()) { |
1817 | 52 | column->insert(value); |
1818 | 52 | return Status::OK(); |
1819 | 52 | } |
1820 | 2 | auto* struct_column = assert_cast<ColumnStruct*>(column); |
1821 | 2 | DORIS_CHECK(projection.children.size() == 1); |
1822 | 2 | const auto& child_projection = projection.children[0]; |
1823 | 2 | DORIS_CHECK(struct_column->get_columns().size() == 1); |
1824 | 2 | RETURN_IF_ERROR(_insert_aggregate_projection_value(child_projection, value, |
1825 | 2 | &struct_column->get_column(0))); |
1826 | 2 | return Status::OK(); |
1827 | 2 | } |
1828 | | |
1829 | | // Parse a DV into its compressed bitmap. Position delete files continue to use _delete_rows. |
1830 | | Status _parse_delete_predicates(const SplitReadOptions& options); |
1831 | | }; |
1832 | | |
1833 | | } // namespace doris::format |