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; otherwise TableReader evaluates them after final table-schema materialization. |
82 | | struct TableFilter { |
83 | | VExprContextSPtr conjunct; |
84 | | std::vector<GlobalIndex> global_indices; |
85 | | size_t source_conjunct_index = 0; |
86 | | // False after the first unsafe source conjunct so file-local execution cannot reorder a later |
87 | | // predicate ahead of stateful or error-preserving table semantics. |
88 | | bool can_localize = true; |
89 | | }; |
90 | | |
91 | | struct ScanTask { |
92 | 62.0k | virtual ~ScanTask() = default; |
93 | | |
94 | | std::unique_ptr<io::FileDescription> data_file; |
95 | | }; |
96 | | |
97 | | struct ProjectedColumnBuildContext { |
98 | | const TFileScanRangeParams* scan_params = nullptr; |
99 | | const TFileRangeDesc* range = nullptr; |
100 | | RuntimeState* runtime_state = nullptr; |
101 | | std::optional<ColumnDefinition> schema_column = std::nullopt; |
102 | | size_t next_file_column_idx = 0; |
103 | | }; |
104 | | |
105 | | struct ReadProfile { |
106 | | RuntimeProfile::Counter* total_timer = nullptr; |
107 | | RuntimeProfile::Counter* init_timer = nullptr; |
108 | | RuntimeProfile::Counter* num_delete_files = nullptr; |
109 | | RuntimeProfile::Counter* num_delete_rows = nullptr; |
110 | | RuntimeProfile::Counter* parse_delete_file_time = nullptr; |
111 | | RuntimeProfile::Counter* decoded_dv_cache_hit_count = nullptr; |
112 | | RuntimeProfile::Counter* decoded_dv_cache_miss_count = nullptr; |
113 | | RuntimeProfile::Counter* dv_file_cache_hit_count = nullptr; |
114 | | RuntimeProfile::Counter* dv_file_cache_miss_count = nullptr; |
115 | | RuntimeProfile::Counter* dv_file_cache_peer_read_count = nullptr; |
116 | | RuntimeProfile::Counter* exec_timer = nullptr; |
117 | | RuntimeProfile::Counter* prepare_split_timer = nullptr; |
118 | | RuntimeProfile::Counter* finalize_timer = nullptr; |
119 | | RuntimeProfile::Counter* residual_filter_timer = nullptr; |
120 | | RuntimeProfile::Counter* create_reader_timer = nullptr; |
121 | | RuntimeProfile::Counter* pushdown_agg_timer = nullptr; |
122 | | RuntimeProfile::Counter* open_reader_timer = nullptr; |
123 | | RuntimeProfile::Counter* runtime_filter_partition_prune_timer = nullptr; |
124 | | RuntimeProfile::Counter* runtime_filter_partition_pruned_range_counter = nullptr; |
125 | | RuntimeProfile::Counter* close_timer = nullptr; |
126 | | RuntimeProfile::Counter* file_reader_total_timer = nullptr; |
127 | | RuntimeProfile::Counter* file_reader_init_timer = nullptr; |
128 | | RuntimeProfile::Counter* file_reader_schema_timer = nullptr; |
129 | | RuntimeProfile::Counter* file_reader_mapper_timer = nullptr; |
130 | | RuntimeProfile::Counter* file_reader_open_timer = nullptr; |
131 | | RuntimeProfile::Counter* file_reader_get_block_timer = nullptr; |
132 | | RuntimeProfile::Counter* file_reader_aggregate_timer = nullptr; |
133 | | RuntimeProfile::Counter* file_reader_close_timer = nullptr; |
134 | | }; |
135 | | |
136 | | struct MaterializedBlockStats { |
137 | | bool has_materialized_input = false; |
138 | | size_t rows = 0; |
139 | | size_t bytes = 0; |
140 | | size_t allocated_bytes = 0; |
141 | | }; |
142 | | |
143 | | struct TableReadOptions { |
144 | | // Columns need to be read from file and output by table reader. They are all in table/global |
145 | | // schema semantics. |
146 | | const std::vector<ColumnDefinition> projected_columns; |
147 | | // All complex conjuncts from scan operator |
148 | | const VExprContextSPtrs conjuncts; |
149 | | // Number of leading conjuncts whose row-level execution is owned by TableReader/FileReader. |
150 | | // FileScannerV2 still passes the complete ordered list so mapping, pruning guards, aggregate |
151 | | // eligibility, and condition-cache analysis see the exact query semantics. nullopt means all. |
152 | | const std::optional<size_t> table_reader_owned_conjunct_count = std::nullopt; |
153 | | // File format of the underlying data files, needed for reader initialization and reader-level |
154 | | // filter pushdown. |
155 | | const FileFormat format; |
156 | | TFileScanRangeParams* scan_params; |
157 | | std::shared_ptr<io::IOContext> io_ctx; |
158 | | RuntimeState* runtime_state; |
159 | | RuntimeProfile* scanner_profile; |
160 | | // File formats without complete self-describing metadata, such as CSV, Text, and JSON, need |
161 | | // the FE-planned physical file slots to build their file-local schema and deserialize values. |
162 | | const std::vector<SlotDescriptor*>* file_slot_descs = nullptr; |
163 | | // Push-down aggregate type. |
164 | | const TPushAggOp::type push_down_agg_type = TPushAggOp::type::NONE; |
165 | | // Table/global indices of explicit COUNT arguments. nullopt means an old FE did not send the |
166 | | // semantic argument field, while an explicit empty vector means COUNT(*)/COUNT(1). Keeping |
167 | | // those states separate prevents a rolling-upgrade plan from being reinterpreted by a new BE. |
168 | | const std::optional<std::vector<GlobalIndex>> push_down_count_columns = std::nullopt; |
169 | | // Initial digest of predicates available during scanner open. Scanner-driven splits override it |
170 | | // with SplitReadOptions::condition_cache_digest after collecting late-arrival runtime filters. |
171 | | // A zero digest disables condition cache. |
172 | | uint64_t condition_cache_digest = 0; |
173 | | }; |
174 | | |
175 | | struct SplitReadOptions { |
176 | | // 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. |
177 | | std::map<std::string, Field> partition_values; |
178 | | // Latest scanner conjuncts rewritten to table/global column indices. Runtime filters may |
179 | | // arrive after TableReader::init(), so scanner-driven splits replace the initial snapshot. |
180 | | // nullopt preserves the initial snapshot for standalone TableReader callers. |
181 | | std::optional<VExprContextSPtrs> conjuncts = std::nullopt; |
182 | | // Independent clones used for partition pruning because evaluation prepares and opens them |
183 | | // against a synthetic partition block before the file reader opens its row-level conjuncts. |
184 | | VExprContextSPtrs partition_prune_conjuncts; |
185 | | // Table-level COUNT may emit one metadata-derived batch and resume on a later scheduler turn. |
186 | | // It is safe only after every runtime filter assigned to the scanner has arrived; otherwise a |
187 | | // filter could arrive after synthetic rows have already been returned and those rows cannot be |
188 | | // retracted. Standalone TableReader callers have no scanner runtime-filter lifecycle. |
189 | | bool all_runtime_filters_applied = true; |
190 | | // Digest for the exact scanner conjunct snapshot attached to this split. FileScannerV2 rebuilds |
191 | | // it after collecting late-arrival RFs, so different RF payloads cannot share a cache entry. A |
192 | | // zero value explicitly disables condition cache for this split. |
193 | | std::optional<uint64_t> condition_cache_digest; |
194 | | ShardedKVCache* cache = nullptr; |
195 | | TFileRangeDesc current_range; |
196 | | FileFormat current_split_format = FileFormat::PARQUET; |
197 | | std::optional<GlobalRowIdContext> global_rowid_context; |
198 | | }; |
199 | | |
200 | | // Base class for table-level readers. |
201 | | // This layer owns common table-level orchestration, such as split iteration, dynamic partition |
202 | | // pruning, delete handling and conversion from file-local blocks to table-schema blocks. Concrete |
203 | | // table-format readers only need to provide format-specific hooks for opening readers and parsing |
204 | | // split metadata. |
205 | | class TableReader { |
206 | | public: |
207 | 41.0k | virtual ~TableReader() = default; |
208 | | |
209 | | // Initialize common runtime options for the table reader. Subclasses may call this from their |
210 | | // own init(options); table-format schema and split metadata are provided later per split. |
211 | | virtual Status init(TableReadOptions&& options); |
212 | | |
213 | | // FileScannerV2 adjusts this before each get_block() using an adaptive bytes-per-row estimate. |
214 | | // Store it here as well as forwarding to the current reader so newly opened split readers start |
215 | | // with the latest predicted batch size. |
216 | 262k | virtual void set_batch_size(size_t batch_size) { |
217 | 262k | _batch_size = std::max<size_t>(1, batch_size); |
218 | 262k | if (_data_reader.reader != nullptr) { |
219 | 139k | _data_reader.reader->set_batch_size(_batch_size); |
220 | 139k | } |
221 | 262k | } |
222 | | |
223 | | #ifdef BE_TEST |
224 | | size_t TEST_batch_size() const { return _batch_size; } |
225 | | size_t TEST_conjunct_count() const { return _conjuncts.size(); } |
226 | | size_t TEST_table_reader_owned_conjunct_count() const { |
227 | | return _table_reader_owned_conjunct_count; |
228 | | } |
229 | | void TEST_set_condition_cache_hit_count(int64_t hits) { _condition_cache_hit_count = hits; } |
230 | | bool TEST_current_data_file_is_immutable() const { |
231 | | DORIS_CHECK(_current_task != nullptr); |
232 | | DORIS_CHECK(_current_task->data_file != nullptr); |
233 | | DORIS_CHECK(_current_file_description.has_value()); |
234 | | DORIS_CHECK(_current_task->data_file->is_immutable == |
235 | | _current_file_description->is_immutable); |
236 | | return _current_task->data_file->is_immutable; |
237 | | } |
238 | | #endif |
239 | | |
240 | | // Prepare for reading a new split/task. |
241 | | // 1. Pass a new split/task to reader, which will be used in subsequent open_reader() to initialize the underlying file reader. |
242 | | // 2. Parse delete predicates from split/task information, which will be used for later dynamic filtering and delete handling. |
243 | | virtual Status prepare_split(const SplitReadOptions& options); |
244 | | |
245 | 90.8k | virtual bool current_split_pruned() const { return _current_split_pruned; } |
246 | 346k | virtual bool current_split_uses_metadata_count() const { |
247 | 346k | return _current_split_uses_metadata_count; |
248 | 346k | } |
249 | | |
250 | | // Runtime filters that arrive after a split has opened cannot be pushed into that file reader. |
251 | | // Keep their expression contexts in TableReader and evaluate them as residual predicates for |
252 | | // the active reader; later splits can localize them normally. |
253 | | virtual Status append_conjuncts(const VExprContextSPtrs& conjuncts); |
254 | | |
255 | | // Append a full ordered snapshot delta while marking only its leading prefix as owned by |
256 | | // TableReader/FileReader. This non-virtual wrapper preserves the long-standing virtual API and |
257 | | // carries the ownership boundary through hybrid readers to their children. |
258 | | Status append_conjuncts_with_ownership(const VExprContextSPtrs& conjuncts, |
259 | | size_t table_reader_owned_conjunct_count); |
260 | | |
261 | | // Shared safety classification for deciding which ordered conjunct prefix may execute below |
262 | | // Scanner without changing stateful or error-preserving semantics. |
263 | | static bool is_safe_to_pre_execute(const VExprContextSPtr& conjunct); |
264 | | |
265 | 425k | virtual const MaterializedBlockStats& last_materialized_block_stats() const { |
266 | 425k | return _last_materialized_block_stats; |
267 | 425k | } |
268 | | |
269 | | // Discard the active split after the caller decides an error is ignorable, for example a |
270 | | // stale external-table file listing that returns NOT_FOUND. The next prepare_split() must start |
271 | | // with no concrete reader or split-local state left from the failed split. |
272 | 1 | virtual Status abort_split() { |
273 | | // Ignored open failures still spend time closing partially initialized readers. Include |
274 | | // that recovery path in the common lifecycle profile so NOT_FOUND cannot become invisible. |
275 | 1 | SCOPED_TIMER(_profile.total_timer); |
276 | 1 | SCOPED_TIMER(_profile.close_timer); |
277 | 1 | if (_data_reader.reader != nullptr) { |
278 | 1 | RETURN_IF_ERROR(close_current_reader()); |
279 | 1 | } else { |
280 | 0 | _current_task.reset(); |
281 | 0 | _current_file_description.reset(); |
282 | 0 | } |
283 | 1 | _delete_rows = nullptr; |
284 | 1 | _remaining_table_level_count = -1; |
285 | 1 | _remaining_file_level_count = -1; |
286 | 1 | _current_split_uses_metadata_count = false; |
287 | 1 | _current_split_pruned = false; |
288 | 1 | _remaining_conjuncts.clear(); |
289 | 1 | return Status::OK(); |
290 | 1 | } |
291 | | |
292 | | // Public entry point for reading a table-schema block. The base class opens the current reader, |
293 | | // advances across EOF, and closes exhausted readers. Subclasses provide protected hooks for |
294 | | // table-format-specific behavior. |
295 | 204k | virtual Status get_block(Block* block, bool* eos) { |
296 | 204k | SCOPED_TIMER(_profile.total_timer); |
297 | 204k | SCOPED_TIMER(_profile.exec_timer); |
298 | 204k | _last_materialized_block_stats = {}; |
299 | 204k | DORIS_CHECK(block->columns() == _projected_columns.size()); |
300 | 204k | block->clear_column_data(_projected_columns.size()); |
301 | | |
302 | 269k | while (true) { |
303 | 269k | if (*eos) { |
304 | 0 | return Status::OK(); |
305 | 0 | } |
306 | 269k | if (_io_ctx != nullptr && _io_ctx->should_stop) { |
307 | 10 | *eos = true; |
308 | 10 | return Status::OK(); |
309 | 10 | } |
310 | 269k | if (!_data_reader.reader) { |
311 | 123k | if (_is_table_level_count_active()) { |
312 | 302 | RETURN_IF_ERROR(_read_table_level_count(block, eos)); |
313 | 302 | return Status::OK(); |
314 | 302 | } |
315 | 123k | if (_is_file_level_count_active()) { |
316 | 2.93k | RETURN_IF_ERROR(_read_file_level_count(block, eos)); |
317 | 2.93k | return Status::OK(); |
318 | 2.93k | } |
319 | 120k | RETURN_IF_ERROR(create_next_reader(eos)); |
320 | 120k | if (!_data_reader.reader) { |
321 | 59.6k | DCHECK(*eos); |
322 | 59.6k | return Status::OK(); |
323 | 59.6k | } |
324 | 120k | } |
325 | | |
326 | | // Materialize a reduced row set for upper aggregate operators when aggregate |
327 | | // pushdown can be applied. This is not the final aggregate result: COUNT emits |
328 | | // `count` default rows for the upper COUNT(*), and MIN/MAX emits two rows containing |
329 | | // file-level min/max values for the upper MIN/MAX. |
330 | 206k | if (!_aggregate_pushdown_tried) { |
331 | 61.1k | SCOPED_TIMER(_profile.pushdown_agg_timer); |
332 | 61.1k | bool pushed_down = false; |
333 | 61.1k | const auto status = _try_materialize_aggregate_pushdown_rows(block, &pushed_down); |
334 | 61.1k | if (!status.ok()) { |
335 | 1 | if (_io_ctx != nullptr && _io_ctx->should_stop && |
336 | 1 | status.is<ErrorCode::END_OF_FILE>()) { |
337 | 1 | *eos = true; |
338 | 1 | return Status::OK(); |
339 | 1 | } |
340 | 0 | return status; |
341 | 1 | } |
342 | 61.1k | if (pushed_down) { |
343 | 1.48k | return Status::OK(); |
344 | 1.48k | } |
345 | 61.1k | } |
346 | | |
347 | 205k | bool current_eof = false; |
348 | 205k | _data_reader.block_template.clear_column_data( |
349 | 205k | cast_set<int64_t>(_data_reader.file_block_layout.size())); |
350 | 205k | size_t current_rows = 0; |
351 | 205k | { |
352 | 205k | SCOPED_TIMER(_profile.file_reader_total_timer); |
353 | 205k | SCOPED_TIMER(_profile.file_reader_get_block_timer); |
354 | 205k | RETURN_IF_ERROR(_data_reader.reader->get_block(&_data_reader.block_template, |
355 | 205k | ¤t_rows, ¤t_eof)); |
356 | 205k | } |
357 | 205k | const bool stopped_during_read = _io_ctx != nullptr && _io_ctx->should_stop; |
358 | 204k | if (current_rows == 0) { |
359 | 65.2k | if (current_eof) { |
360 | 59.0k | _current_reader_reached_eof = !stopped_during_read; |
361 | 59.0k | RETURN_IF_ERROR(close_current_reader()); |
362 | 59.0k | } |
363 | 65.2k | continue; |
364 | 65.2k | } |
365 | 204k | DCHECK_EQ(_data_reader.block_template.columns(), _data_reader.file_block_layout.size()) |
366 | 0 | << _data_reader.block_template.dump_structure(); |
367 | 139k | #ifndef NDEBUG |
368 | 139k | RETURN_IF_ERROR(_check_file_block_columns("after file reader get_block", current_rows)); |
369 | 139k | #endif |
370 | 139k | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
371 | 139k | RETURN_IF_ERROR(finalize_chunk(block, ¤t_rows)); |
372 | 139k | #ifndef NDEBUG |
373 | 139k | RETURN_IF_ERROR( |
374 | 139k | _check_table_block_columns("after finalize_chunk", block, current_rows)); |
375 | 139k | #endif |
376 | 139k | if (current_eof) { |
377 | 24 | _current_reader_reached_eof = !stopped_during_read; |
378 | 24 | RETURN_IF_ERROR(close_current_reader()); |
379 | 24 | } |
380 | 139k | if (current_rows == 0) { |
381 | | // One materialized batch is one Scanner progress unit even when residual |
382 | | // predicates reject every row. Returning here preserves row-budget and |
383 | | // cancellation checks in Scanner::get_block(). |
384 | 254 | block->clear_column_data(_projected_columns.size()); |
385 | 254 | return Status::OK(); |
386 | 254 | } |
387 | 139k | return Status::OK(); |
388 | 139k | } |
389 | 204k | } |
390 | | |
391 | | // Close the table reader and the currently active file reader. Subclasses that hold additional |
392 | | // table-format resources should override this and call TableReader::close() first. |
393 | 40.9k | virtual Status close() { |
394 | 40.9k | SCOPED_TIMER(_profile.total_timer); |
395 | 40.9k | SCOPED_TIMER(_profile.close_timer); |
396 | 40.9k | if (_data_reader.reader) { |
397 | 654 | RETURN_IF_ERROR(close_current_reader()); |
398 | 654 | } |
399 | 40.9k | _current_task.reset(); |
400 | 40.9k | _current_file_description.reset(); |
401 | 40.9k | _remaining_table_level_count = -1; |
402 | 40.9k | _remaining_file_level_count = -1; |
403 | 40.9k | _current_split_uses_metadata_count = false; |
404 | 40.9k | _remaining_conjuncts.clear(); |
405 | 40.9k | return Status::OK(); |
406 | 40.9k | } |
407 | | |
408 | 81.6k | virtual int64_t condition_cache_hit_count() const { return _condition_cache_hit_count; } |
409 | | |
410 | | virtual std::string debug_string() const; |
411 | | |
412 | | virtual Status annotate_projected_column(const TFileScanSlotInfo& slot_info, |
413 | | ProjectedColumnBuildContext* context, |
414 | | ColumnDefinition* column) const; |
415 | | |
416 | 22.2k | virtual Status validate_projected_columns(const ProjectedColumnBuildContext& context) const { |
417 | 22.2k | (void)context; |
418 | 22.2k | return Status::OK(); |
419 | 22.2k | } |
420 | | |
421 | | protected: |
422 | | // TableReader keeps the active file description both in the scan task and separately for |
423 | | // creating the physical reader. Table-format readers must update both copies when their |
424 | | // snapshot protocol guarantees that a file path is never overwritten with different bytes. |
425 | | // This guarantee lets readers safely build cache keys without mtime; it must not be used for |
426 | | // ordinary Hive/TVF files whose paths may be overwritten in place. |
427 | 28.9k | void mark_current_data_file_immutable() { |
428 | 28.9k | DORIS_CHECK(_current_task != nullptr); |
429 | 28.9k | DORIS_CHECK(_current_task->data_file != nullptr); |
430 | 28.9k | DORIS_CHECK(_current_file_description.has_value()); |
431 | 28.9k | _current_task->data_file->is_immutable = true; |
432 | 28.9k | _current_file_description->is_immutable = true; |
433 | 28.9k | } |
434 | | |
435 | | std::optional<ColumnDefinition> _find_current_table_column_by_field_id(int32_t field_id, |
436 | | DataTypePtr type) const; |
437 | | |
438 | | // Parse deletion vector information from table format specific file description. |
439 | | virtual Status _parse_deletion_vector_file(const TTableFormatFileDesc& t_desc, |
440 | 32.7k | DeleteFileDesc* desc, bool* has_delete_file) { |
441 | 32.7k | *has_delete_file = false; |
442 | 32.7k | return Status::OK(); |
443 | 32.7k | } |
444 | | |
445 | | // Advance to the next reader. This closes the current reader first and then opens the next |
446 | | // concrete reader. Subclasses should not duplicate this loop. |
447 | | Status create_next_reader(bool* eos); |
448 | | virtual Status create_file_reader(std::unique_ptr<FileReader>* reader); |
449 | 6.46k | virtual TableColumnMappingMode mapping_mode() const { return TableColumnMappingMode::BY_NAME; } |
450 | 32.8k | virtual void configure_mapper_options(TableColumnMapperOptions*) const {} |
451 | 35.3k | virtual Status annotate_file_schema(std::vector<ColumnDefinition>* file_schema) { |
452 | 35.3k | DORIS_CHECK(file_schema != nullptr); |
453 | 35.3k | return Status::OK(); |
454 | 35.3k | } |
455 | | |
456 | | // Open the concrete reader for the current split/task and build the file-local scan request. |
457 | 61.8k | virtual Status open_reader() { |
458 | 61.8k | SCOPED_TIMER(_profile.open_reader_timer); |
459 | | // 1. Get file schema and create column mapping. |
460 | 61.8k | std::vector<ColumnDefinition> file_schema; |
461 | 61.8k | { |
462 | 61.8k | SCOPED_TIMER(_profile.file_reader_total_timer); |
463 | 61.8k | SCOPED_TIMER(_profile.file_reader_schema_timer); |
464 | 61.8k | RETURN_IF_ERROR(_data_reader.reader->get_schema(&file_schema)); |
465 | 61.8k | } |
466 | | // For Paimon/Hudi, FE can provide field ids through `history_schema_info`. Annotate the |
467 | | // file schema before column mapping when the table format maps columns by field id. |
468 | 61.8k | RETURN_IF_ERROR(annotate_file_schema(&file_schema)); |
469 | 61.8k | _data_reader.file_schema = file_schema; |
470 | 61.8k | _mapper_options.mode = mapping_mode(); |
471 | 61.8k | configure_mapper_options(&_mapper_options); |
472 | | |
473 | 61.8k | { |
474 | 61.8k | SCOPED_TIMER(_profile.file_reader_total_timer); |
475 | 61.8k | SCOPED_TIMER(_profile.file_reader_mapper_timer); |
476 | 61.8k | _data_reader.column_mapper = _data_reader.reader->create_column_mapper(_mapper_options); |
477 | 61.8k | } |
478 | 61.8k | DORIS_CHECK(_data_reader.column_mapper != nullptr); |
479 | 61.8k | RETURN_IF_ERROR(_data_reader.column_mapper->create_mapping(_projected_columns, |
480 | 61.8k | _partition_values, file_schema)); |
481 | 61.8k | DORIS_CHECK(_data_reader.column_mapper->mappings().size() == _projected_columns.size()); |
482 | | |
483 | | // 2. Build table filters based on conjuncts and column predicates. |
484 | 61.8k | RETURN_IF_ERROR(_build_table_filters_from_conjuncts()); |
485 | | |
486 | | // 3. Create file scan request based on column mapping and table filters, then open file |
487 | | // reader with the request. File scan request carries row-level expression filters and |
488 | | // file-level pruning hints. Only expression filters decide returned rows. |
489 | 61.8k | auto file_request = std::make_shared<FileScanRequest>(); |
490 | 61.8k | FilterLocalizationResult localization_result; |
491 | 61.8k | RETURN_IF_ERROR(_data_reader.column_mapper->create_scan_request( |
492 | 61.8k | _table_filters, _projected_columns, file_request.get(), _runtime_state, |
493 | 61.8k | &localization_result)); |
494 | 61.8k | bool constant_filter_pruned_split = false; |
495 | 61.8k | RETURN_IF_ERROR(_evaluate_constant_filters(&constant_filter_pruned_split)); |
496 | 61.8k | if (constant_filter_pruned_split) { |
497 | 645 | RETURN_IF_ERROR(close_current_reader()); |
498 | 645 | return Status::OK(); |
499 | 645 | } |
500 | 61.2k | RETURN_IF_ERROR(_prepare_remaining_conjuncts(localization_result)); |
501 | | // COUNT(*) has no semantic column argument, but Nereids retains a minimum-width scan slot |
502 | | // so the scan node still has an output tuple. Record only the current non-predicate file |
503 | | // columns before table-format hooks add row-position or equality-delete dependencies. This |
504 | | // marker is independent of aggregate eligibility: with position deletes, for example, |
505 | | // metadata COUNT must fall back to reading rows, but an arbitrary unsupported TIME_MILLIS |
506 | | // placeholder still must not be validated or decoded merely to carry the surviving count. |
507 | 61.2k | if (_push_down_agg_type == TPushAggOp::type::COUNT && |
508 | 61.2k | _push_down_count_columns.has_value() && _push_down_count_columns->empty()) { |
509 | 1.93k | file_request->count_star_placeholder_columns.reserve( |
510 | 1.93k | file_request->non_predicate_columns.size()); |
511 | 1.93k | for (const auto& column : file_request->non_predicate_columns) { |
512 | 1.90k | file_request->count_star_placeholder_columns.push_back(column.column_id()); |
513 | 1.90k | } |
514 | 1.93k | } |
515 | 61.2k | RETURN_IF_ERROR(customize_file_scan_request(file_request.get())); |
516 | 61.2k | RETURN_IF_ERROR(_open_local_filter_exprs(*file_request)); |
517 | 61.2k | _data_reader.file_block_layout.clear(); |
518 | 61.2k | _data_reader.block_template.clear(); |
519 | 61.2k | _data_reader.file_block_layout.resize(file_request->local_positions.size()); |
520 | | |
521 | | // 4. Build file block layout from file schema and column mapping. The layout describes |
522 | | // the block returned by file reader before table-column materialization. |
523 | 380k | for (const auto& [file_column_id, block_position] : file_request->local_positions) { |
524 | 380k | DORIS_CHECK(block_position.value() < _data_reader.file_block_layout.size()); |
525 | 380k | const auto* field = _find_column_definition(_data_reader.file_schema, file_column_id); |
526 | 380k | DORIS_CHECK(field != nullptr); |
527 | | |
528 | 380k | ColumnDefinition projected_field; |
529 | 380k | { |
530 | 380k | auto it = std::find_if( |
531 | 380k | file_request->non_predicate_columns.begin(), |
532 | 380k | file_request->non_predicate_columns.end(), |
533 | 7.68M | [&](const LocalColumnIndex& p) { return p.column_id() == file_column_id; }); |
534 | 380k | if (it != file_request->non_predicate_columns.end()) { |
535 | 352k | RETURN_IF_ERROR(project_column_definition(*field, *it, &projected_field)); |
536 | 352k | } |
537 | 380k | } |
538 | 380k | { |
539 | 380k | auto it = std::find_if( |
540 | 380k | file_request->predicate_columns.begin(), |
541 | 380k | file_request->predicate_columns.end(), |
542 | 380k | [&](const LocalColumnIndex& p) { return p.column_id() == file_column_id; }); |
543 | 380k | if (it != file_request->predicate_columns.end()) { |
544 | 27.9k | RETURN_IF_ERROR(project_column_definition(*field, *it, &projected_field)); |
545 | 27.9k | } |
546 | 380k | } |
547 | 380k | _data_reader.file_block_layout[block_position.value()] = { |
548 | 380k | .file_column_id = file_column_id, |
549 | 380k | .name = projected_field.name, |
550 | 380k | .type = projected_field.type, |
551 | 380k | }; |
552 | 380k | DORIS_CHECK(_data_reader.file_block_layout[block_position.value()].type != nullptr); |
553 | 380k | } |
554 | | |
555 | | // 5. Prepare block template from file block layout. The block template stores the block |
556 | | // returned by file reader before table-column materialization. |
557 | 61.2k | _data_reader.block_template.reserve(_data_reader.file_block_layout.size()); |
558 | 380k | for (const auto& column : _data_reader.file_block_layout) { |
559 | 380k | _data_reader.block_template.insert( |
560 | 380k | {column.type->create_column(), column.type, column.name}); |
561 | 380k | } |
562 | 61.2k | if (VLOG_DEBUG_IS_ON) { |
563 | 0 | VLOG_DEBUG << "TableReader debug: " << debug_string(); |
564 | 0 | } |
565 | 61.2k | RETURN_IF_ERROR(_open_mapping_exprs()); |
566 | 61.2k | { |
567 | 61.2k | SCOPED_TIMER(_profile.file_reader_total_timer); |
568 | 61.2k | SCOPED_TIMER(_profile.file_reader_open_timer); |
569 | 61.2k | RETURN_IF_ERROR(_data_reader.reader->open(file_request)); |
570 | 61.2k | } |
571 | 61.1k | RETURN_IF_ERROR(_init_reader_condition_cache(*file_request)); |
572 | 61.1k | return Status::OK(); |
573 | 61.1k | } |
574 | | |
575 | | Status _build_table_filters_from_conjuncts(); |
576 | | Status _replace_conjuncts(const VExprContextSPtrs& conjuncts); |
577 | | Status _prepare_conjunct(const VExprContextSPtr& source, VExprContextSPtr* prepared); |
578 | | Status _prepare_remaining_conjuncts(const FilterLocalizationResult& localization_result); |
579 | | Status _prepare_all_conjuncts_as_remaining(); |
580 | | Status _filter_remaining_conjuncts(Block* block, size_t* rows); |
581 | | Status _evaluate_partition_prune_conjuncts(const VExprContextSPtrs& conjuncts, |
582 | | bool* can_filter_all); |
583 | | Status _build_partition_prune_block(Block* block) const; |
584 | | Status _open_local_filter_exprs(const FileScanRequest& file_request); |
585 | | Status _init_reader_condition_cache(const FileScanRequest& file_request); |
586 | | void _finalize_reader_condition_cache(); |
587 | | bool _should_enable_condition_cache(const FileScanRequest& file_request) const; |
588 | | |
589 | 61.5k | Status _evaluate_constant_filters(bool* can_filter_all) { |
590 | 61.5k | DORIS_CHECK(can_filter_all != nullptr); |
591 | 61.5k | DORIS_CHECK_LE(_constant_pruning_safe_filter_count, _table_filters.size()); |
592 | 61.5k | *can_filter_all = false; |
593 | | // The bound was derived from the original `_conjuncts` order, which includes slotless |
594 | | // expressions omitted from `_table_filters`. Iterating only this prefix therefore cannot |
595 | | // skip an unsafe row-level predicate and pre-execute a later constant predicate. |
596 | 91.0k | for (size_t i = 0; i < _constant_pruning_safe_filter_count; ++i) { |
597 | 30.1k | const auto& table_filter = _table_filters[i]; |
598 | 30.1k | if (table_filter.conjunct == nullptr) { |
599 | 0 | continue; |
600 | 0 | } |
601 | 30.1k | DORIS_CHECK(is_safe_to_pre_execute(table_filter.conjunct)); |
602 | | // RuntimeFilterExpr does not implement execute_column_impl(); it is evaluated by the |
603 | | // row-level filter path through execute_filter(). Constant split pruning uses |
604 | | // VExprContext::execute() on a one-row synthetic block, so runtime filters must not be |
605 | | // pre-executed here even when their referenced slot maps to a constant value. |
606 | 30.1k | if (table_filter.conjunct->root()->is_rf_wrapper() || |
607 | 30.1k | !_table_filter_has_only_constant_entries(table_filter)) { |
608 | 27.4k | continue; |
609 | 27.4k | } |
610 | 2.68k | Block eval_block; |
611 | 2.68k | RETURN_IF_ERROR(_build_constant_filter_block(table_filter, &eval_block)); |
612 | 2.68k | RowDescriptor row_desc; |
613 | 2.68k | RETURN_IF_ERROR(table_filter.conjunct->prepare(_runtime_state, row_desc)); |
614 | 2.68k | RETURN_IF_ERROR(table_filter.conjunct->open(_runtime_state)); |
615 | 2.68k | int result_column_id = -1; |
616 | 2.68k | RETURN_IF_ERROR(table_filter.conjunct->execute(&eval_block, &result_column_id)); |
617 | 2.68k | DORIS_CHECK(result_column_id >= 0); |
618 | 2.68k | if (_filter_result_filters_all(eval_block.get_by_position(result_column_id).column)) { |
619 | 645 | *can_filter_all = true; |
620 | 645 | return Status::OK(); |
621 | 645 | } |
622 | 2.68k | } |
623 | 60.9k | return Status::OK(); |
624 | 61.5k | } |
625 | | |
626 | 25.1k | bool _table_filter_has_only_constant_entries(const TableFilter& table_filter) const { |
627 | 25.1k | const auto& filter_entries = _data_reader.column_mapper->filter_entries(); |
628 | 25.1k | for (const auto global_index : table_filter.global_indices) { |
629 | 25.1k | const auto entry_it = filter_entries.find(global_index); |
630 | 25.3k | if (entry_it == filter_entries.end() || !entry_it->second.is_constant()) { |
631 | 22.4k | return false; |
632 | 22.4k | } |
633 | 25.1k | } |
634 | 2.68k | return !table_filter.global_indices.empty(); |
635 | 25.1k | } |
636 | | |
637 | 2.81k | Status _build_constant_filter_block(const TableFilter& table_filter, Block* eval_block) { |
638 | 2.81k | DORIS_CHECK(eval_block != nullptr); |
639 | 2.81k | eval_block->clear(); |
640 | 2.81k | const auto& mappings = _data_reader.column_mapper->mappings(); |
641 | 2.81k | const auto& filter_entries = _data_reader.column_mapper->filter_entries(); |
642 | 2.81k | DORIS_CHECK(mappings.size() == _projected_columns.size()); |
643 | 12.0k | for (size_t column_idx = 0; column_idx < mappings.size(); ++column_idx) { |
644 | 9.21k | const auto global_index = GlobalIndex(column_idx); |
645 | 9.21k | const auto& mapping = mappings[column_idx]; |
646 | 9.21k | const auto entry_it = filter_entries.find(global_index); |
647 | 9.21k | const bool referenced_by_filter = |
648 | 9.21k | std::find(table_filter.global_indices.begin(), |
649 | 9.21k | table_filter.global_indices.end(), |
650 | 9.21k | global_index) != table_filter.global_indices.end(); |
651 | 9.21k | if (referenced_by_filter && entry_it != filter_entries.end() && |
652 | 9.21k | entry_it->second.is_constant()) { |
653 | 2.88k | ColumnPtr constant_column; |
654 | 2.88k | RETURN_IF_ERROR(_materialize_constant_filter_column( |
655 | 2.88k | entry_it->second.constant_index(), &constant_column)); |
656 | 2.88k | eval_block->insert({std::move(constant_column), mapping.table_type, |
657 | 2.88k | mapping.table_column_name}); |
658 | 6.33k | } else { |
659 | 6.33k | eval_block->insert({mapping.table_type->create_column_const_with_default_value(1), |
660 | 6.33k | mapping.table_type, mapping.table_column_name}); |
661 | 6.33k | } |
662 | 9.21k | } |
663 | 2.81k | return Status::OK(); |
664 | 2.81k | } |
665 | | |
666 | 2.88k | Status _materialize_constant_filter_column(ConstantIndex constant_index, ColumnPtr* column) { |
667 | 2.88k | DORIS_CHECK(column != nullptr); |
668 | 2.88k | const auto& constant_entry = _data_reader.column_mapper->constant_map().get(constant_index); |
669 | 2.88k | DORIS_CHECK(constant_entry.expr != nullptr); |
670 | 2.88k | DORIS_CHECK(constant_entry.type != nullptr); |
671 | 2.88k | RowDescriptor row_desc; |
672 | 2.88k | RETURN_IF_ERROR(constant_entry.expr->prepare(_runtime_state, row_desc)); |
673 | 2.88k | RETURN_IF_ERROR(constant_entry.expr->open(_runtime_state)); |
674 | 2.88k | Block eval_block; |
675 | 2.88k | eval_block.insert({constant_entry.type->create_column_const_with_default_value(1), |
676 | 2.88k | constant_entry.type, "__table_reader_constant_filter"}); |
677 | 2.88k | int result_column_id = -1; |
678 | 2.88k | RETURN_IF_ERROR(constant_entry.expr->execute(&eval_block, &result_column_id)); |
679 | 2.88k | DORIS_CHECK(result_column_id >= 0); |
680 | 2.88k | *column = eval_block.get_by_position(result_column_id).column; |
681 | 2.88k | DORIS_CHECK((*column)->size() == 1); |
682 | 2.88k | return Status::OK(); |
683 | 2.88k | } |
684 | | |
685 | 2.82k | static bool _filter_result_filters_all(const ColumnPtr& filter_column) { |
686 | 2.82k | DORIS_CHECK(filter_column.get() != nullptr); |
687 | 2.82k | DORIS_CHECK(filter_column->size() == 1); |
688 | 2.82k | return !filter_column->get_bool(0); |
689 | 2.82k | } |
690 | | |
691 | 60.7k | virtual Status customize_file_scan_request(FileScanRequest* file_request) { |
692 | 60.7k | return _append_delete_predicate(file_request); |
693 | 60.7k | } |
694 | | |
695 | 216k | bool _is_table_level_count_active() const { return _remaining_table_level_count >= 0; } |
696 | | |
697 | 123k | bool _is_file_level_count_active() const { return _remaining_file_level_count >= 0; } |
698 | | |
699 | 3.07k | Status _materialize_count_rows(size_t rows, Block* block) const { |
700 | 3.07k | DORIS_CHECK(block != nullptr); |
701 | 3.07k | DORIS_CHECK(block->columns() > 0 || rows == 0); |
702 | 6.16k | for (size_t column_idx = 0; column_idx < block->columns(); ++column_idx) { |
703 | 3.08k | auto column = block->get_by_position(column_idx).type->create_column(); |
704 | 3.08k | if (auto* nullable = check_and_get_column<ColumnNullable>(*column)) { |
705 | | // Metadata COUNT emits synthetic input rows for the unchanged upper aggregate. |
706 | | // They must be non-NULL for COUNT(nullable_col), and constructing them explicitly |
707 | | // also keeps every nullable null map boolean-valid in debug/ASAN block checks. |
708 | 3.08k | nullable->get_nested_column().insert_many_defaults(rows); |
709 | 3.08k | nullable->get_null_map_data().resize_fill(rows, 0); |
710 | 18.4E | } else { |
711 | 18.4E | column->insert_many_defaults(rows); |
712 | 18.4E | } |
713 | 3.08k | block->replace_by_position(column_idx, std::move(column)); |
714 | 3.08k | } |
715 | 3.07k | return Status::OK(); |
716 | 3.07k | } |
717 | | |
718 | 3.08k | Status _materialize_next_count_batch(int64_t* remaining_rows, Block* block) const { |
719 | 3.08k | DORIS_CHECK(remaining_rows != nullptr); |
720 | 3.08k | DORIS_CHECK(*remaining_rows > 0); |
721 | 3.08k | const int64_t batch_size = _runtime_state == nullptr |
722 | 3.08k | ? *remaining_rows |
723 | 3.08k | : static_cast<int64_t>(_runtime_state->batch_size()); |
724 | 3.08k | const auto rows = std::min(*remaining_rows, batch_size); |
725 | 3.08k | RETURN_IF_ERROR(_materialize_count_rows(cast_set<size_t>(rows), block)); |
726 | 3.08k | *remaining_rows -= rows; |
727 | 3.08k | return Status::OK(); |
728 | 3.08k | } |
729 | | |
730 | 3.23k | Status _read_count_batch(int64_t* remaining_rows, Block* block, bool* eos) { |
731 | 3.23k | DORIS_CHECK(block != nullptr); |
732 | 3.23k | DORIS_CHECK(eos != nullptr); |
733 | 3.23k | DORIS_CHECK(_push_down_agg_type == TPushAggOp::type::COUNT); |
734 | 3.23k | DORIS_CHECK(remaining_rows != nullptr); |
735 | 3.23k | DORIS_CHECK(*remaining_rows >= 0); |
736 | 3.23k | if (*remaining_rows == 0) { |
737 | 1.60k | *remaining_rows = -1; |
738 | 1.60k | _current_task.reset(); |
739 | 1.60k | *eos = true; |
740 | 1.60k | return Status::OK(); |
741 | 1.60k | } |
742 | 1.62k | RETURN_IF_ERROR(_materialize_next_count_batch(remaining_rows, block)); |
743 | 1.62k | *eos = false; |
744 | 1.62k | return Status::OK(); |
745 | 1.62k | } |
746 | | |
747 | 302 | Status _read_table_level_count(Block* block, bool* eos) { |
748 | 302 | return _read_count_batch(&_remaining_table_level_count, block, eos); |
749 | 302 | } |
750 | | |
751 | 2.93k | Status _read_file_level_count(Block* block, bool* eos) { |
752 | 2.93k | return _read_count_batch(&_remaining_file_level_count, block, eos); |
753 | 2.93k | } |
754 | | |
755 | | void _append_file_scan_column(FileScanRequest* request, LocalColumnId column_id, |
756 | 12.8k | std::vector<LocalColumnIndex>* scan_columns) { |
757 | 12.8k | DORIS_CHECK(request != nullptr); |
758 | 12.8k | DORIS_CHECK(scan_columns != nullptr); |
759 | 12.8k | FileScanRequestBuilder builder(request); |
760 | 12.8k | Status status; |
761 | 12.8k | if (scan_columns == &request->predicate_columns) { |
762 | 10.7k | status = builder.add_predicate_column(column_id); |
763 | 10.7k | } else { |
764 | 2.11k | DORIS_CHECK(scan_columns == &request->non_predicate_columns); |
765 | 2.11k | status = builder.add_non_predicate_column(column_id); |
766 | 2.11k | } |
767 | 12.8k | DORIS_CHECK(status.ok()) << status.to_string(); |
768 | 12.8k | if (column_id == LocalColumnId(ROW_POSITION_COLUMN_ID) && |
769 | 12.8k | _find_column_definition(_data_reader.file_schema, column_id) == nullptr) { |
770 | 7.48k | _data_reader.file_schema.push_back(row_position_column_definition()); |
771 | 7.48k | } |
772 | 12.8k | } |
773 | | |
774 | | // 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. |
775 | 60.7k | Status _append_delete_predicate(FileScanRequest* request) { |
776 | 60.7k | DORIS_CHECK(request != nullptr); |
777 | 60.7k | if ((_delete_rows == nullptr || _delete_rows->empty()) && |
778 | 60.7k | (_deletion_vector == nullptr || _deletion_vector->isEmpty())) { |
779 | 54.8k | return Status::OK(); |
780 | 54.8k | } |
781 | 5.87k | const auto row_position_column_id = LocalColumnId(ROW_POSITION_COLUMN_ID); |
782 | 5.87k | _append_file_scan_column(request, row_position_column_id, &request->predicate_columns); |
783 | | |
784 | 5.87k | const auto block_position = request->local_positions.at(row_position_column_id); |
785 | 5.87k | auto append_predicate = [&](auto& deleted_rows) { |
786 | 5.85k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); |
787 | 5.85k | delete_predicate->add_child(VSlotRef::create_shared( |
788 | 5.85k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), |
789 | 5.85k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); |
790 | 5.85k | request->delete_conjuncts.push_back( |
791 | 5.85k | VExprContext::create_shared(std::move(delete_predicate))); |
792 | 5.85k | }; _ZZN5doris6format11TableReader24_append_delete_predicateEPNS0_15FileScanRequestEENKUlRT_E_clISt6vectorIlSaIlEEEEDaS5_ Line | Count | Source | 785 | 1.67k | auto append_predicate = [&](auto& deleted_rows) { | 786 | 1.67k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); | 787 | 1.67k | delete_predicate->add_child(VSlotRef::create_shared( | 788 | 1.67k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), | 789 | 1.67k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); | 790 | 1.67k | request->delete_conjuncts.push_back( | 791 | 1.67k | VExprContext::create_shared(std::move(delete_predicate))); | 792 | 1.67k | }; |
_ZZN5doris6format11TableReader24_append_delete_predicateEPNS0_15FileScanRequestEENKUlRT_E_clIN7roaring12Roaring64MapEEEDaS5_ Line | Count | Source | 785 | 4.18k | auto append_predicate = [&](auto& deleted_rows) { | 786 | 4.18k | auto delete_predicate = std::make_shared<DeletePredicate>(deleted_rows); | 787 | 4.18k | delete_predicate->add_child(VSlotRef::create_shared( | 788 | 4.18k | cast_set<int>(block_position.value()), cast_set<int>(block_position.value()), | 789 | 4.18k | -1, std::make_shared<DataTypeInt64>(), ROW_POSITION_COLUMN_NAME)); | 790 | 4.18k | request->delete_conjuncts.push_back( | 791 | 4.18k | VExprContext::create_shared(std::move(delete_predicate))); | 792 | 4.18k | }; |
|
793 | 5.87k | if (_delete_rows != nullptr && !_delete_rows->empty()) { |
794 | 1.67k | append_predicate(*_delete_rows); |
795 | 1.67k | } |
796 | 5.87k | if (_deletion_vector != nullptr && !_deletion_vector->isEmpty()) { |
797 | 4.18k | append_predicate(*_deletion_vector); |
798 | 4.18k | } |
799 | 5.87k | return Status::OK(); |
800 | 60.7k | } |
801 | | |
802 | | // Close the current concrete reader. This hook is called by both create_next_reader() and |
803 | | // close(), so it should remain idempotent. |
804 | 61.8k | virtual Status close_current_reader() { |
805 | 61.8k | _finalize_reader_condition_cache(); |
806 | 61.8k | { |
807 | 61.8k | SCOPED_TIMER(_profile.file_reader_total_timer); |
808 | 61.8k | SCOPED_TIMER(_profile.file_reader_close_timer); |
809 | 61.8k | RETURN_IF_ERROR(_data_reader.reader->close()); |
810 | 61.8k | } |
811 | 61.8k | _data_reader.reader.reset(); |
812 | 61.8k | if (_data_reader.column_mapper != nullptr) { |
813 | 61.7k | _data_reader.column_mapper->clear(); |
814 | 61.7k | _data_reader.column_mapper.reset(); |
815 | 61.7k | } |
816 | 61.8k | _table_filters.clear(); |
817 | 61.8k | _constant_pruning_safe_filter_count = 0; |
818 | 61.8k | _remaining_conjuncts.clear(); |
819 | 61.8k | _data_reader.file_schema.clear(); |
820 | 61.8k | _data_reader.file_block_layout.clear(); |
821 | 61.8k | _data_reader.block_template.clear(); |
822 | 61.8k | _current_task.reset(); |
823 | 61.8k | _current_file_description.reset(); |
824 | 61.8k | _current_reader_reached_eof = false; |
825 | 61.8k | return Status::OK(); |
826 | 61.8k | } |
827 | | |
828 | 3 | void _record_scan_rows(size_t rows) { |
829 | 3 | if (_io_ctx != nullptr && _io_ctx->file_reader_stats != nullptr) { |
830 | 2 | _io_ctx->file_reader_stats->read_rows += rows; |
831 | 2 | } |
832 | 3 | } |
833 | | |
834 | 6 | void _reset_materialized_block_stats() { _last_materialized_block_stats = {}; } |
835 | | |
836 | 140k | void _record_materialized_block_stats(const Block& block, size_t rows) { |
837 | 140k | _last_materialized_block_stats = { |
838 | 140k | .has_materialized_input = true, |
839 | 140k | .rows = rows, |
840 | 140k | .bytes = block.bytes(), |
841 | 140k | .allocated_bytes = block.allocated_bytes(), |
842 | 140k | }; |
843 | 140k | } |
844 | | |
845 | | // Finalize file-local block to table/global schema block. |
846 | 139k | Status finalize_chunk(Block* block, size_t* rows) { |
847 | 139k | DORIS_CHECK(rows != nullptr); |
848 | 139k | SCOPED_TIMER(_profile.finalize_timer); |
849 | 139k | size_t idx = 0; |
850 | 139k | const auto& mappings = _data_reader.column_mapper->mappings(); |
851 | 718k | for (const auto& mapping : mappings) { |
852 | 718k | ColumnPtr column; |
853 | 718k | RETURN_IF_ERROR(_materialize_mapping_column(mapping, &_data_reader.block_template, |
854 | 718k | *rows, &column, |
855 | 718k | idx + 1 == mappings.size())); |
856 | 718k | block->replace_by_position(idx, IColumn::mutate(std::move(column))); |
857 | 718k | idx++; |
858 | 718k | } |
859 | 139k | RETURN_IF_ERROR(materialize_virtual_columns(block)); |
860 | | // Enforce CHAR/VARCHAR length declared by the table schema after all file-to-table |
861 | | // materialization has finished. |
862 | 139k | RETURN_IF_ERROR(_truncate_char_or_varchar_columns(block)); |
863 | | // Preserve the cost of materialization before residual predicates shrink the block. The |
864 | | // scanner uses this snapshot for bounded progress and adaptive batch sizing. |
865 | 139k | _record_materialized_block_stats(*block, *rows); |
866 | | // Predicate ownership is split-local: only predicates not acknowledged as exact by this |
867 | | // split's FileScanRequest run here, after virtual/default/schema-evolution values exist. |
868 | 139k | return _filter_remaining_conjuncts(block, rows); |
869 | 139k | } |
870 | | |
871 | | // Materialize virtual columns in the table block, such as Iceberg _row_id and |
872 | | // _last_updated_sequence_number. This runs after normal column materialization so finalize |
873 | | // expressions can reference those virtual columns. |
874 | 109k | virtual Status materialize_virtual_columns(Block* table_block) { return Status::OK(); } |
875 | | |
876 | | #ifndef NDEBUG |
877 | 140k | Status _check_file_block_columns(std::string_view stage, size_t rows) { |
878 | 140k | DORIS_CHECK(_data_reader.block_template.columns() == _data_reader.file_block_layout.size()); |
879 | 847k | for (size_t idx = 0; idx < _data_reader.block_template.columns(); ++idx) { |
880 | 707k | const auto& file_block_column = _data_reader.file_block_layout[idx]; |
881 | 707k | const auto& column_with_type = _data_reader.block_template.get_by_position(idx); |
882 | 707k | const auto* column = column_with_type.column.get(); |
883 | 707k | try { |
884 | 707k | if (column == nullptr) { |
885 | 0 | auto st = Status::InternalError( |
886 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
887 | 0 | "type={}, column=null, expected_rows={}, reader={}", |
888 | 0 | idx, stage, file_block_column.file_column_id.value(), |
889 | 0 | file_block_column.name, |
890 | 0 | file_block_column.type == nullptr ? "null" |
891 | 0 | : file_block_column.type->get_name(), |
892 | 0 | rows, debug_string()); |
893 | 0 | LOG(WARNING) << st; |
894 | 0 | return st; |
895 | 0 | } |
896 | 707k | column->sanity_check(); |
897 | 707k | auto st = column_with_type.check_type_and_column_match(); |
898 | 707k | if (!st.ok()) { |
899 | 0 | auto contextual_status = Status::InternalError( |
900 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
901 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
902 | 0 | "reader={}", |
903 | 0 | idx, stage, file_block_column.file_column_id.value(), |
904 | 0 | file_block_column.name, |
905 | 0 | file_block_column.type == nullptr ? "null" |
906 | 0 | : file_block_column.type->get_name(), |
907 | 0 | column->get_name(), column->size(), rows, st.to_string(), |
908 | 0 | debug_string()); |
909 | 0 | LOG(WARNING) << contextual_status; |
910 | 0 | return contextual_status; |
911 | 0 | } |
912 | 707k | } catch (const Exception& e) { |
913 | 0 | auto st = Status::InternalError( |
914 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
915 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
916 | 0 | "reader={}", |
917 | 0 | idx, stage, file_block_column.file_column_id.value(), |
918 | 0 | file_block_column.name, |
919 | 0 | file_block_column.type == nullptr ? "null" |
920 | 0 | : file_block_column.type->get_name(), |
921 | 0 | column == nullptr ? "null" : column->get_name(), |
922 | 0 | column == nullptr ? 0 : column->size(), rows, e.to_string(), |
923 | 0 | debug_string()); |
924 | 0 | LOG(WARNING) << st; |
925 | 0 | return st; |
926 | 0 | } catch (const std::exception& e) { |
927 | 0 | auto st = Status::InternalError( |
928 | 0 | "Invalid file block column {} at {}: file_column_id={}, name='{}', " |
929 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
930 | 0 | "reader={}", |
931 | 0 | idx, stage, file_block_column.file_column_id.value(), |
932 | 0 | file_block_column.name, |
933 | 0 | file_block_column.type == nullptr ? "null" |
934 | 0 | : file_block_column.type->get_name(), |
935 | 0 | column == nullptr ? "null" : column->get_name(), |
936 | 0 | column == nullptr ? 0 : column->size(), rows, e.what(), debug_string()); |
937 | 0 | LOG(WARNING) << st; |
938 | 0 | return st; |
939 | 0 | } |
940 | 707k | } |
941 | 139k | return Status::OK(); |
942 | 140k | } |
943 | | |
944 | 140k | Status _check_table_block_columns(std::string_view stage, const Block* block, size_t rows) { |
945 | 140k | DORIS_CHECK(block != nullptr); |
946 | 140k | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
947 | 858k | for (size_t idx = 0; idx < block->columns(); ++idx) { |
948 | 718k | const auto& mapping = _data_reader.column_mapper->mappings()[idx]; |
949 | 718k | const auto& column_with_type = block->get_by_position(idx); |
950 | 718k | const auto* column = column_with_type.column.get(); |
951 | 718k | try { |
952 | 718k | if (column == nullptr) { |
953 | 0 | auto st = Status::InternalError( |
954 | 0 | "Invalid table block column {} at {}: table_column='{}', " |
955 | 0 | "global_index={}, type={}, column=null, expected_rows={}, mapping={}", |
956 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
957 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
958 | 0 | rows, mapping.debug_string()); |
959 | 0 | LOG(WARNING) << st; |
960 | 0 | return st; |
961 | 0 | } |
962 | 718k | column->sanity_check(); |
963 | 718k | auto st = column_with_type.check_type_and_column_match(); |
964 | 718k | if (!st.ok()) { |
965 | 0 | auto contextual_status = Status::InternalError( |
966 | 0 | "Invalid table block column {} at {}: table_column='{}', " |
967 | 0 | "global_index={}, type={}, column={}, column_size={}, " |
968 | 0 | "expected_rows={}, error={}, mapping={}", |
969 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
970 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
971 | 0 | column->get_name(), column->size(), rows, st.to_string(), |
972 | 0 | mapping.debug_string()); |
973 | 0 | LOG(WARNING) << contextual_status; |
974 | 0 | return contextual_status; |
975 | 0 | } |
976 | 718k | } catch (const Exception& e) { |
977 | 0 | auto st = Status::InternalError( |
978 | 0 | "Invalid table block column {} at {}: table_column='{}', global_index={}, " |
979 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
980 | 0 | "mapping={}", |
981 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
982 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
983 | 0 | column == nullptr ? "null" : column->get_name(), |
984 | 0 | column == nullptr ? 0 : column->size(), rows, e.to_string(), |
985 | 0 | mapping.debug_string()); |
986 | 0 | LOG(WARNING) << st; |
987 | 0 | return st; |
988 | 0 | } catch (const std::exception& e) { |
989 | 0 | auto st = Status::InternalError( |
990 | 0 | "Invalid table block column {} at {}: table_column='{}', global_index={}, " |
991 | 0 | "type={}, column={}, column_size={}, expected_rows={}, error={}, " |
992 | 0 | "mapping={}", |
993 | 0 | idx, stage, mapping.table_column_name, mapping.global_index.value(), |
994 | 0 | mapping.table_type == nullptr ? "null" : mapping.table_type->get_name(), |
995 | 0 | column == nullptr ? "null" : column->get_name(), |
996 | 0 | column == nullptr ? 0 : column->size(), rows, e.what(), |
997 | 0 | mapping.debug_string()); |
998 | 0 | LOG(WARNING) << st; |
999 | 0 | return st; |
1000 | 0 | } |
1001 | 718k | } |
1002 | 139k | return Status::OK(); |
1003 | 140k | } |
1004 | | #endif |
1005 | | |
1006 | 139k | Status _truncate_char_or_varchar_columns(Block* block) { |
1007 | 139k | DORIS_CHECK(block != nullptr); |
1008 | 139k | if (_runtime_state == nullptr || |
1009 | 140k | !_runtime_state->query_options().truncate_char_or_varchar_columns) { |
1010 | 139k | return Status::OK(); |
1011 | 139k | } |
1012 | 4 | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
1013 | 40 | for (size_t idx = 0; idx < _data_reader.column_mapper->mappings().size(); ++idx) { |
1014 | 36 | const auto& mapping = _data_reader.column_mapper->mappings()[idx]; |
1015 | 36 | if (!_should_truncate_char_or_varchar_column(mapping)) { |
1016 | 12 | continue; |
1017 | 12 | } |
1018 | 24 | const auto target_len = |
1019 | 24 | assert_cast<const DataTypeString*>(remove_nullable(mapping.table_type).get()) |
1020 | 24 | ->len(); |
1021 | 24 | _truncate_char_or_varchar_column(block, idx, target_len); |
1022 | 24 | } |
1023 | 4 | return Status::OK(); |
1024 | 139k | } |
1025 | | |
1026 | | // Return true when the table schema has a bounded CHAR/VARCHAR length that is stricter than |
1027 | | // the file-side type. Examples: |
1028 | | // - table VARCHAR(10), file VARCHAR(20): truncate to 10; |
1029 | | // - table VARCHAR(10), file STRING: truncate to 10 because STRING has no declared bound; |
1030 | | // - table STRING, any file type: no truncation because the target has no bound. |
1031 | 41 | static bool _should_truncate_char_or_varchar_column(const ColumnMapping& mapping) { |
1032 | 41 | return requires_char_or_varchar_truncation(mapping); |
1033 | 41 | } |
1034 | | |
1035 | | // Truncate a materialized CHAR/VARCHAR column in place by reusing the vectorized substring |
1036 | | // implementation: substring(column, 1, len). Nullable columns are unwrapped before substring |
1037 | | // execution and wrapped back with the original null map afterward, because substring operates |
1038 | | // on the nested string payload only. |
1039 | 25 | static void _truncate_char_or_varchar_column(Block* block, size_t idx, int len) { |
1040 | 25 | DORIS_CHECK(block != nullptr); |
1041 | 25 | auto int_type = std::make_shared<DataTypeInt32>(); |
1042 | 25 | const auto num_columns_without_result = cast_set<uint32_t>(block->columns()); |
1043 | 25 | auto& target = block->get_by_position(idx); |
1044 | 25 | const bool is_nullable = target.type->is_nullable(); |
1045 | 25 | ColumnPtr input_column = target.column; |
1046 | 25 | ColumnPtr null_map_column; |
1047 | 25 | if (is_nullable) { |
1048 | 25 | const auto* nullable_column = assert_cast<const ColumnNullable*>(target.column.get()); |
1049 | 25 | input_column = nullable_column->get_nested_column_ptr(); |
1050 | 25 | null_map_column = nullable_column->get_null_map_column_ptr(); |
1051 | 25 | } |
1052 | 25 | block->replace_by_position(idx, std::move(input_column)); |
1053 | 25 | block->insert({int_type->create_column_const(block->rows(), to_field<TYPE_INT>(1)), |
1054 | 25 | int_type, "const 1"}); |
1055 | 25 | block->insert({int_type->create_column_const(block->rows(), to_field<TYPE_INT>(len)), |
1056 | 25 | int_type, "const len"}); |
1057 | 25 | block->insert({nullptr, std::make_shared<DataTypeString>(), "result"}); |
1058 | | |
1059 | 25 | ColumnNumbers temp_arguments(3); |
1060 | 25 | temp_arguments[0] = cast_set<uint32_t>(idx); |
1061 | 25 | temp_arguments[1] = num_columns_without_result; |
1062 | 25 | temp_arguments[2] = num_columns_without_result + 1; |
1063 | 25 | const uint32_t result_column_id = num_columns_without_result + 2; |
1064 | 25 | SubstringUtil::substring_execute(*block, temp_arguments, result_column_id, block->rows()); |
1065 | | |
1066 | 25 | ColumnPtr result_column = block->get_by_position(result_column_id).column; |
1067 | 25 | if (is_nullable) { |
1068 | 25 | result_column = ColumnNullable::create(std::move(result_column), null_map_column); |
1069 | 25 | } |
1070 | 25 | block->replace_by_position(idx, std::move(result_column)); |
1071 | 25 | block->erase_tail(num_columns_without_result); |
1072 | 25 | } |
1073 | | |
1074 | 61.0k | Status _try_materialize_aggregate_pushdown_rows(Block* block, bool* pushed_down) { |
1075 | 61.0k | DORIS_CHECK(block != nullptr); |
1076 | 61.0k | DORIS_CHECK(pushed_down != nullptr); |
1077 | 61.0k | *pushed_down = false; |
1078 | 61.0k | block->clear_column_data(_projected_columns.size()); |
1079 | 61.0k | _aggregate_pushdown_tried = true; |
1080 | 61.0k | if (!_supports_aggregate_pushdown(_push_down_agg_type)) { |
1081 | 59.5k | return Status::OK(); |
1082 | 59.5k | } |
1083 | | |
1084 | 1.53k | FileAggregateRequest file_request; |
1085 | 1.53k | RETURN_IF_ERROR(_build_file_aggregate_request(_push_down_agg_type, &file_request)); |
1086 | 1.53k | FileAggregateResult file_result; |
1087 | 1.53k | Status status; |
1088 | 1.53k | { |
1089 | 1.53k | SCOPED_TIMER(_profile.file_reader_total_timer); |
1090 | 1.53k | SCOPED_TIMER(_profile.file_reader_aggregate_timer); |
1091 | 1.53k | status = _data_reader.reader->get_aggregate_result(file_request, &file_result); |
1092 | 1.53k | } |
1093 | 1.53k | if (status.is<ErrorCode::NOT_IMPLEMENTED_ERROR>()) { |
1094 | 13 | return Status::OK(); |
1095 | 13 | } |
1096 | 1.52k | RETURN_IF_ERROR(status); |
1097 | 1.51k | if (_push_down_agg_type == TPushAggOp::type::COUNT) { |
1098 | 1.46k | DORIS_CHECK(file_result.count >= 0); |
1099 | | // The upper aggregate consumes synthetic input rows, but emitting the whole metadata |
1100 | | // count in one block bypasses the runtime batch contract and can allocate by file size. |
1101 | | // Keep the remaining cardinality as split state and expose at most one batch per call. |
1102 | 1.46k | _remaining_file_level_count = file_result.count; |
1103 | 1.46k | _current_split_uses_metadata_count = true; |
1104 | 1.46k | if (_remaining_file_level_count > 0) { |
1105 | 1.46k | RETURN_IF_ERROR(_materialize_next_count_batch(&_remaining_file_level_count, block)); |
1106 | 1.46k | } |
1107 | 1.46k | } else { |
1108 | 57 | RETURN_IF_ERROR( |
1109 | 57 | _materialize_aggregate_pushdown_rows(_push_down_agg_type, file_result, block)); |
1110 | 57 | } |
1111 | 1.51k | *pushed_down = true; |
1112 | 1.51k | RETURN_IF_ERROR(close_current_reader()); |
1113 | 1.51k | return Status::OK(); |
1114 | 1.51k | } |
1115 | | |
1116 | 62.5k | virtual bool _supports_aggregate_pushdown(TPushAggOp::type agg_type) const { |
1117 | | // Only COUNT and MIN/MAX can be push down. |
1118 | 62.5k | if (agg_type != TPushAggOp::type::COUNT && agg_type != TPushAggOp::type::MINMAX) { |
1119 | 57.8k | return false; |
1120 | 57.8k | } |
1121 | | // Aggregate pushdown returns reduced synthetic rows and may close the physical reader |
1122 | | // before the next scheduler turn. If a runtime filter is still pending, those rows could |
1123 | | // escape before the filter arrives and cannot later be reconstructed from real file rows. |
1124 | | // This is the same irreversibility constraint as table-level metadata COUNT, and applies |
1125 | | // to COUNT and MIN/MAX for Parquet/ORC as well as COUNT for text readers. |
1126 | 4.73k | if (!_all_runtime_filters_applied_for_split) { |
1127 | 2 | return false; |
1128 | 2 | } |
1129 | | // Even a slotless conjunct that cannot become a TableFilter must see every source row |
1130 | | // before an aggregate reduces the stream to synthetic COUNT/MINMAX rows. |
1131 | 4.73k | if (!_conjuncts.empty()) { |
1132 | 5 | return false; |
1133 | 5 | } |
1134 | | // Only support aggregate pushdown when there is no delete or filter, so |
1135 | | // the reduced rows consumed by the upper aggregate remain semantically equivalent to a |
1136 | | // normal scan. |
1137 | 4.72k | if ((_delete_rows != nullptr && !_delete_rows->empty()) || |
1138 | 4.72k | (_deletion_vector != nullptr && !_deletion_vector->isEmpty())) { |
1139 | 1.08k | return false; |
1140 | 1.08k | } |
1141 | 3.64k | if (!_table_filters.empty()) { |
1142 | 0 | return false; |
1143 | 0 | } |
1144 | 3.64k | if (agg_type == TPushAggOp::type::COUNT) { |
1145 | | // Old FEs do not serialize push_down_count_slot_ids. During the supported BE-first |
1146 | | // rolling upgrade, nullopt therefore means "COUNT semantics are unknown", not |
1147 | | // COUNT(*). Fall back to reading rows until the FE explicitly sends either an empty |
1148 | | // list for COUNT(*) or one slot for COUNT(col). |
1149 | 3.39k | if (!_push_down_count_columns.has_value()) { |
1150 | 3 | return false; |
1151 | 3 | } |
1152 | | // COUNT(*) needs no column metadata. COUNT(col) currently supports one direct file |
1153 | | // column; multiple COUNT arguments fall back to the normal scan so every upper |
1154 | | // aggregate receives the original rows. |
1155 | 3.39k | if (_push_down_count_columns->empty()) { |
1156 | 2.57k | return true; |
1157 | 2.57k | } |
1158 | 821 | if (_push_down_count_columns->size() != 1) { |
1159 | 37 | return false; |
1160 | 37 | } |
1161 | 784 | const auto& mapping = _push_down_count_mapping(); |
1162 | | // Metadata COUNT skips TableReader's normal materialization path. Only a trivial |
1163 | | // mapping is safe: for example, a nullable Parquet INT mapped to a NOT NULL table |
1164 | | // BIGINT normally needs both an INT->BIGINT cast and nullability validation. Counting |
1165 | | // footer values directly would bypass both operations and could hide invalid data. |
1166 | 784 | return mapping.file_local_id.has_value() && mapping.file_type != nullptr && |
1167 | 784 | mapping.table_type != nullptr && mapping.is_trivial && |
1168 | 784 | mapping.virtual_column_type == TableVirtualColumnType::INVALID && |
1169 | 784 | mapping.default_expr == nullptr; |
1170 | 821 | } |
1171 | | // For MIN/MAX, only support direct file-to-table column mappings. The two emitted rows |
1172 | | // must be enough for the upper MIN/MAX aggregate without evaluating default expressions or |
1173 | | // virtual columns. |
1174 | 325 | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1175 | 325 | if (!mapping.file_local_id.has_value() || |
1176 | 325 | mapping.virtual_column_type != TableVirtualColumnType::INVALID || |
1177 | 325 | mapping.default_expr != nullptr || mapping.file_type == nullptr || |
1178 | 325 | mapping.table_type == nullptr) { |
1179 | 9 | return false; |
1180 | 9 | } |
1181 | 316 | if (!_can_push_down_minmax_for_mapping(mapping)) { |
1182 | 222 | return false; |
1183 | 222 | } |
1184 | 316 | } |
1185 | 14 | return true; |
1186 | 245 | } |
1187 | | |
1188 | 709k | static ColumnPtr _detach_column(ColumnPtr column) { |
1189 | 709k | DORIS_CHECK(column.get() != nullptr); |
1190 | 709k | return IColumn::mutate(std::move(column)); |
1191 | 709k | } |
1192 | | |
1193 | 127k | static ColumnPtr _take_and_detach_block_column(Block* block, int position) { |
1194 | 127k | DORIS_CHECK(block != nullptr); |
1195 | 127k | DORIS_CHECK(position >= 0 && position < static_cast<int>(block->columns())); |
1196 | 127k | auto& source = block->get_by_position(position); |
1197 | 127k | ColumnPtr column = source.column; |
1198 | | // The final mapping no longer needs the file block. Release its COW owner before mutate(), |
1199 | | // otherwise nested MAP/STRING columns are deep-copied and a multi-GB payload can OOM. |
1200 | 127k | block->replace_by_position(position, source.type->create_column()); |
1201 | 127k | return _detach_column(std::move(column)); |
1202 | 127k | } |
1203 | | |
1204 | 110k | static Status _align_column_nullability(ColumnPtr* column, const DataTypePtr& table_type) { |
1205 | 110k | DORIS_CHECK(column != nullptr); |
1206 | 110k | DORIS_CHECK(column->get() != nullptr); |
1207 | 110k | DORIS_CHECK(table_type != nullptr); |
1208 | | // Must return non-const column |
1209 | 110k | *column = (*column)->convert_to_full_column_if_const(); |
1210 | 110k | if (table_type->is_nullable()) { |
1211 | 55.1k | const auto& nested_type = |
1212 | 55.1k | assert_cast<const DataTypeNullable&>(*table_type).get_nested_type(); |
1213 | 55.1k | if (!(*column)->is_nullable()) { |
1214 | 2 | RETURN_IF_ERROR(_align_column_nullability(column, nested_type)); |
1215 | 2 | *column = make_nullable(*column); |
1216 | 2 | return Status::OK(); |
1217 | 2 | } |
1218 | 55.1k | const auto& nullable_column = assert_cast<const ColumnNullable&>(**column); |
1219 | 55.1k | ColumnPtr nested_column = nullable_column.get_nested_column_ptr(); |
1220 | 55.1k | RETURN_IF_ERROR(_align_column_nullability(&nested_column, nested_type)); |
1221 | 55.1k | *column = ColumnNullable::create(nested_column, |
1222 | 55.1k | nullable_column.get_null_map_column_ptr()); |
1223 | 55.1k | return Status::OK(); |
1224 | 55.1k | } |
1225 | 55.1k | if ((*column)->is_nullable()) { |
1226 | 0 | const auto& nullable_column = assert_cast<const ColumnNullable&>(**column); |
1227 | 0 | if (nullable_column.has_null()) { |
1228 | 0 | return Status::InternalError( |
1229 | 0 | "Default expression produced NULL for non-nullable table column"); |
1230 | 0 | } |
1231 | 0 | ColumnPtr nested_column = nullable_column.get_nested_column_ptr(); |
1232 | 0 | RETURN_IF_ERROR(_align_column_nullability(&nested_column, table_type)); |
1233 | 0 | *column = nested_column; |
1234 | 0 | return Status::OK(); |
1235 | 0 | } |
1236 | 55.1k | if (const auto* array_type = typeid_cast<const DataTypeArray*>(table_type.get())) { |
1237 | 173 | const auto& array_column = assert_cast<const ColumnArray&>(**column); |
1238 | 173 | ColumnPtr nested_column = array_column.get_data_ptr(); |
1239 | 173 | RETURN_IF_ERROR( |
1240 | 173 | _align_column_nullability(&nested_column, array_type->get_nested_type())); |
1241 | 173 | *column = ColumnArray::create(nested_column, array_column.get_offsets_ptr()); |
1242 | 173 | return Status::OK(); |
1243 | 173 | } |
1244 | 55.0k | if (const auto* map_type = typeid_cast<const DataTypeMap*>(table_type.get())) { |
1245 | 24 | const auto& map_column = assert_cast<const ColumnMap&>(**column); |
1246 | 24 | ColumnPtr key_column = map_column.get_keys_ptr(); |
1247 | 24 | ColumnPtr value_column = map_column.get_values_ptr(); |
1248 | 24 | RETURN_IF_ERROR(_align_column_nullability(&key_column, map_type->get_key_type())); |
1249 | 24 | RETURN_IF_ERROR(_align_column_nullability(&value_column, map_type->get_value_type())); |
1250 | 24 | *column = ColumnMap::create(key_column, value_column, map_column.get_offsets_ptr()); |
1251 | 24 | return Status::OK(); |
1252 | 24 | } |
1253 | 54.9k | if (const auto* struct_type = typeid_cast<const DataTypeStruct*>(table_type.get())) { |
1254 | 7.51k | const auto& struct_column = assert_cast<const ColumnStruct&>(**column); |
1255 | 7.51k | Columns columns = struct_column.get_columns_copy(); |
1256 | 7.51k | DORIS_CHECK(columns.size() == struct_type->get_elements().size()); |
1257 | 25.2k | for (size_t i = 0; i < columns.size(); ++i) { |
1258 | 17.7k | RETURN_IF_ERROR( |
1259 | 17.7k | _align_column_nullability(&columns[i], struct_type->get_element(i))); |
1260 | 17.7k | } |
1261 | 7.51k | *column = ColumnStruct::create(columns); |
1262 | 7.51k | return Status::OK(); |
1263 | 7.51k | } |
1264 | 47.4k | return Status::OK(); |
1265 | 54.9k | } |
1266 | | |
1267 | | static Status _execute_default_expr_without_root_type_check( |
1268 | | const VExprContextSPtr& default_expr, const Block* block, |
1269 | 17.8k | ColumnWithTypeAndName* result_data) { |
1270 | 17.8k | DORIS_CHECK(default_expr != nullptr); |
1271 | 17.8k | DORIS_CHECK(block != nullptr); |
1272 | 17.8k | DORIS_CHECK(result_data != nullptr); |
1273 | 17.8k | ColumnPtr result_column; |
1274 | 17.8k | Status st; |
1275 | 17.8k | RETURN_IF_CATCH_EXCEPTION({ |
1276 | 17.8k | st = default_expr->root()->execute_column_impl(default_expr.get(), block, nullptr, |
1277 | 17.8k | block->rows(), result_column); |
1278 | 17.8k | }); |
1279 | 17.8k | RETURN_IF_ERROR(st); |
1280 | 17.8k | DORIS_CHECK(result_column.get() != nullptr); |
1281 | 17.8k | if (result_column->size() != block->rows()) { |
1282 | 0 | return Status::InternalError( |
1283 | 0 | "Default expr {} return column size {} not equal to expected size {}", |
1284 | 0 | default_expr->expr_name(), result_column->size(), block->rows()); |
1285 | 0 | } |
1286 | 17.8k | result_data->column = result_column; |
1287 | 17.8k | result_data->type = default_expr->execute_type(block); |
1288 | 17.8k | result_data->name = default_expr->expr_name(); |
1289 | 17.8k | return Status::OK(); |
1290 | 17.8k | } |
1291 | | |
1292 | | Status _cast_column_to_type(ColumnPtr* column, const DataTypePtr& file_type, |
1293 | | const DataTypePtr& table_type, |
1294 | 9.06k | const std::string& column_name) const { |
1295 | 9.06k | DORIS_CHECK(column != nullptr); |
1296 | 9.06k | DORIS_CHECK(column->get() != nullptr); |
1297 | 9.06k | DORIS_CHECK(file_type != nullptr); |
1298 | 9.06k | DORIS_CHECK(table_type != nullptr); |
1299 | 9.06k | if (file_type->equals(*table_type)) { |
1300 | 0 | return Status::OK(); |
1301 | 0 | } |
1302 | | |
1303 | 9.06k | DataTypePtr input_type = file_type; |
1304 | | // Cast wrappers unwrap nullable inputs according to the declared input type, so keep the |
1305 | | // root nullability of the declared type aligned with the actual column shape. |
1306 | 9.06k | if ((*column)->is_nullable() && !input_type->is_nullable()) { |
1307 | 0 | input_type = make_nullable(input_type); |
1308 | 9.06k | } else if (!(*column)->is_nullable() && input_type->is_nullable()) { |
1309 | 1 | input_type = remove_nullable(input_type); |
1310 | 1 | } |
1311 | 9.06k | Block cast_block; |
1312 | 9.06k | cast_block.insert({*column, input_type, column_name}); |
1313 | 9.06k | auto slot_ref = VSlotRef::create_shared(0, 0, -1, input_type, column_name); |
1314 | 9.06k | auto cast_expr = Cast::create_shared(table_type); |
1315 | 9.06k | cast_expr->add_child(std::move(slot_ref)); |
1316 | 9.06k | auto cast_ctx = VExprContext::create_shared(std::move(cast_expr)); |
1317 | 9.06k | RowDescriptor row_desc; |
1318 | 9.06k | RETURN_IF_ERROR(cast_ctx->prepare(_runtime_state, row_desc)); |
1319 | 9.06k | RETURN_IF_ERROR(cast_ctx->open(_runtime_state)); |
1320 | 9.06k | ColumnPtr cast_column; |
1321 | 9.06k | RETURN_IF_ERROR(cast_ctx->execute(&cast_block, cast_column)); |
1322 | 9.06k | *column = std::move(cast_column); |
1323 | 9.06k | return Status::OK(); |
1324 | 9.06k | } |
1325 | | |
1326 | | Status _materialize_present_child_mapping_column(const ColumnMapping& mapping, |
1327 | | const ColumnPtr& file_column, |
1328 | 19.4k | const size_t rows, ColumnPtr* column) { |
1329 | 19.4k | DORIS_CHECK(column != nullptr); |
1330 | 19.4k | DORIS_CHECK(mapping.file_type != nullptr); |
1331 | 19.4k | DORIS_CHECK(mapping.table_type != nullptr); |
1332 | 19.4k | *column = file_column; |
1333 | 19.4k | if (!mapping.is_trivial) { |
1334 | 11.5k | if (!mapping.child_mappings.empty()) { |
1335 | 2.44k | RETURN_IF_ERROR( |
1336 | 2.44k | _materialize_complex_mapping_column(mapping, *column, rows, column)); |
1337 | 9.06k | } else { |
1338 | 9.06k | RETURN_IF_ERROR(_cast_column_to_type(column, mapping.file_type, mapping.table_type, |
1339 | 9.06k | mapping.file_column_name)); |
1340 | 9.06k | } |
1341 | 11.5k | } |
1342 | 19.4k | RETURN_IF_ERROR(_align_column_nullability(column, mapping.table_type)); |
1343 | 19.4k | return Status::OK(); |
1344 | 19.4k | } |
1345 | | |
1346 | | Status _materialize_mapping_column(const ColumnMapping& mapping, Block* current_block, |
1347 | | const size_t rows, ColumnPtr* column, |
1348 | 718k | bool take_projection_result = false) { |
1349 | 718k | if (!mapping.is_trivial && mapping.file_local_id.has_value() && |
1350 | 718k | !mapping.child_mappings.empty()) { |
1351 | 10.6k | DCHECK(mapping.projection != nullptr); |
1352 | 10.6k | int res_id; |
1353 | 10.6k | auto st = mapping.projection->execute(current_block, &res_id); |
1354 | 10.6k | if (!st.ok()) { |
1355 | 0 | return Status::InternalError( |
1356 | 0 | "Failed to execute complex mapping projection for table column '{}' " |
1357 | 0 | "(global_index={}, file_local_id={}, rows={}): {}, mapping={}", |
1358 | 0 | mapping.table_column_name, mapping.global_index.value(), |
1359 | 0 | *mapping.file_local_id, rows, st.to_string(), mapping.debug_string()); |
1360 | 0 | } |
1361 | 10.6k | ColumnPtr result_column = take_projection_result |
1362 | 10.6k | ? _take_and_detach_block_column(current_block, res_id) |
1363 | 10.6k | : current_block->get_by_position(res_id).column; |
1364 | 10.6k | RETURN_IF_ERROR( |
1365 | 10.6k | _materialize_complex_mapping_column(mapping, result_column, rows, column)); |
1366 | 10.6k | return Status::OK(); |
1367 | 10.6k | } |
1368 | 707k | if (mapping.projection != nullptr) { |
1369 | 687k | int res_id; |
1370 | 687k | auto st = mapping.projection->execute(current_block, &res_id); |
1371 | 687k | if (!st.ok()) { |
1372 | 1 | std::string file_local_id = "null"; |
1373 | 1 | if (mapping.file_local_id.has_value()) { |
1374 | 1 | file_local_id = std::to_string(*mapping.file_local_id); |
1375 | 1 | } |
1376 | 1 | return Status::InternalError( |
1377 | 1 | "Failed to execute mapping projection for table column '{}' " |
1378 | 1 | "(global_index={}, file_local_id={}, rows={}): {}, mapping={}", |
1379 | 1 | mapping.table_column_name, mapping.global_index.value(), file_local_id, |
1380 | 1 | rows, st.to_string(), mapping.debug_string()); |
1381 | 1 | } |
1382 | 687k | if (take_projection_result) { |
1383 | 125k | *column = _take_and_detach_block_column(current_block, res_id); |
1384 | 561k | } else { |
1385 | 561k | ColumnPtr result_column = current_block->get_by_position(res_id).column; |
1386 | 561k | *column = _detach_column(std::move(result_column)); |
1387 | 561k | } |
1388 | 687k | return Status::OK(); |
1389 | 687k | } |
1390 | 20.6k | if (mapping.default_expr != nullptr) { |
1391 | 17.8k | if (current_block->rows() == rows) { |
1392 | 15.8k | ColumnWithTypeAndName result; |
1393 | 15.8k | RETURN_IF_ERROR(_execute_default_expr_without_root_type_check( |
1394 | 15.8k | mapping.default_expr, current_block, &result)); |
1395 | 15.8k | ColumnPtr result_column = result.column; |
1396 | 15.8k | RETURN_IF_ERROR(_align_column_nullability(&result_column, mapping.table_type)); |
1397 | 15.8k | *column = _detach_column(std::move(result_column)); |
1398 | 15.8k | } else { |
1399 | 2.01k | DORIS_CHECK(mapping.constant_index.has_value()); |
1400 | 2.01k | Block eval_block; |
1401 | 2.01k | eval_block.insert({mapping.table_type->create_column_const_with_default_value(rows), |
1402 | 2.01k | mapping.table_type, "__table_reader_const_rows"}); |
1403 | 2.01k | ColumnWithTypeAndName result; |
1404 | 2.01k | RETURN_IF_ERROR(_execute_default_expr_without_root_type_check( |
1405 | 2.01k | mapping.default_expr, &eval_block, &result)); |
1406 | 2.01k | ColumnPtr result_column = result.column; |
1407 | 2.01k | RETURN_IF_ERROR(_align_column_nullability(&result_column, mapping.table_type)); |
1408 | 2.01k | *column = _detach_column(std::move(result_column)); |
1409 | 2.01k | } |
1410 | 17.8k | return Status::OK(); |
1411 | 17.8k | } |
1412 | 2.85k | ColumnPtr result_column = mapping.table_type->create_column_const_with_default_value(rows); |
1413 | 2.85k | *column = _detach_column(std::move(result_column)); |
1414 | 2.85k | return Status::OK(); |
1415 | 20.6k | } |
1416 | | |
1417 | | Status _materialize_complex_mapping_column(const ColumnMapping& mapping, |
1418 | | const ColumnPtr& file_column, const size_t rows, |
1419 | 13.0k | ColumnPtr* column) { |
1420 | 13.0k | DORIS_CHECK(mapping.table_type != nullptr); |
1421 | 13.0k | DORIS_CHECK(file_column.get() != nullptr); |
1422 | 13.0k | const auto table_type = remove_nullable(mapping.table_type); |
1423 | 13.0k | switch (table_type->get_primitive_type()) { |
1424 | 4.42k | case TYPE_STRUCT: |
1425 | 4.42k | RETURN_IF_ERROR(_materialize_struct_mapping_column(mapping, file_column, rows, column)); |
1426 | 4.42k | break; |
1427 | 4.79k | case TYPE_ARRAY: |
1428 | 4.79k | RETURN_IF_ERROR(_materialize_array_mapping_column(mapping, file_column, rows, column)); |
1429 | 4.79k | break; |
1430 | 4.79k | case TYPE_MAP: |
1431 | 3.86k | RETURN_IF_ERROR(_materialize_map_mapping_column(mapping, file_column, rows, column)); |
1432 | 3.86k | break; |
1433 | 3.86k | default: |
1434 | 0 | *column = _detach_column(file_column); |
1435 | 0 | break; |
1436 | 13.0k | } |
1437 | 13.0k | return Status::OK(); |
1438 | 13.0k | } |
1439 | | |
1440 | | static std::vector<const ColumnMapping*> _present_child_mappings_in_file_order( |
1441 | 4.42k | const std::vector<ColumnMapping>& child_mappings) { |
1442 | 4.42k | std::vector<const ColumnMapping*> result; |
1443 | 4.42k | result.reserve(child_mappings.size()); |
1444 | 11.3k | for (const auto& child_mapping : child_mappings) { |
1445 | 11.3k | if (child_mapping.file_local_id.has_value()) { |
1446 | 6.89k | result.push_back(&child_mapping); |
1447 | 6.89k | } |
1448 | 11.3k | } |
1449 | 5.01k | std::ranges::sort(result, [](const ColumnMapping* lhs, const ColumnMapping* rhs) { |
1450 | 5.01k | DORIS_CHECK(lhs->file_local_id.has_value()); |
1451 | 5.01k | DORIS_CHECK(rhs->file_local_id.has_value()); |
1452 | 5.01k | return *lhs->file_local_id < *rhs->file_local_id; |
1453 | 5.01k | }); |
1454 | 4.42k | return result; |
1455 | 4.42k | } |
1456 | | |
1457 | | static size_t _file_child_ordinal_for_mapping( |
1458 | | const ColumnMapping& mapping, const ColumnMapping& child_mapping, |
1459 | 6.89k | const std::vector<const ColumnMapping*>& file_ordered_children) { |
1460 | 6.89k | DORIS_CHECK(child_mapping.file_local_id.has_value()); |
1461 | 6.89k | if (!mapping.projected_file_children.empty()) { |
1462 | 6.89k | const auto child_it = std::ranges::find_if( |
1463 | 10.2k | mapping.projected_file_children, [&](const ColumnDefinition& file_child) { |
1464 | 10.2k | return file_child.file_local_id() == *child_mapping.file_local_id; |
1465 | 10.2k | }); |
1466 | 6.89k | DORIS_CHECK(child_it != mapping.projected_file_children.end()); |
1467 | 6.89k | return static_cast<size_t>( |
1468 | 6.89k | std::distance(mapping.projected_file_children.begin(), child_it)); |
1469 | 6.89k | } |
1470 | 2 | const auto child_it = std::ranges::find(file_ordered_children, &child_mapping); |
1471 | 2 | DORIS_CHECK(child_it != file_ordered_children.end()); |
1472 | 2 | return static_cast<size_t>(std::distance(file_ordered_children.begin(), child_it)); |
1473 | 6.89k | } |
1474 | | |
1475 | | static std::vector<const ColumnMapping*> _child_mappings_in_table_type_order( |
1476 | 4.42k | const ColumnMapping& mapping, const DataTypeStruct& table_type) { |
1477 | 4.42k | std::vector<const ColumnMapping*> result; |
1478 | 4.42k | result.reserve(mapping.child_mappings.size()); |
1479 | 15.7k | for (size_t child_idx = 0; child_idx < table_type.get_elements().size(); ++child_idx) { |
1480 | 11.3k | const auto& child_name = table_type.get_element_name(child_idx); |
1481 | 11.3k | const auto child_it = std::ranges::find_if( |
1482 | 21.5k | mapping.child_mappings, [&](const ColumnMapping& child_mapping) { |
1483 | 21.5k | return child_mapping.table_column_name == child_name; |
1484 | 21.5k | }); |
1485 | 11.3k | DORIS_CHECK(child_it != mapping.child_mappings.end()) |
1486 | 2 | << mapping.debug_string() << ", table_child_name=" << child_name; |
1487 | 11.3k | result.push_back(&*child_it); |
1488 | 11.3k | } |
1489 | 4.42k | return result; |
1490 | 4.42k | } |
1491 | | |
1492 | | static const IColumn* _nested_column_if_nullable(const ColumnPtr& column, |
1493 | 13.0k | const NullMap** null_map) { |
1494 | 13.0k | DORIS_CHECK(column.get() != nullptr); |
1495 | 13.0k | if (const auto* nullable_column = check_and_get_column<ColumnNullable>(*column)) { |
1496 | 13.0k | if (null_map != nullptr) { |
1497 | 13.0k | *null_map = &nullable_column->get_null_map_data(); |
1498 | 13.0k | } |
1499 | 13.0k | return &nullable_column->get_nested_column(); |
1500 | 13.0k | } |
1501 | 4 | return column.get(); |
1502 | 13.0k | } |
1503 | | |
1504 | | Status _materialize_struct_mapping_column(const ColumnMapping& mapping, |
1505 | | const ColumnPtr& file_column, const size_t rows, |
1506 | 4.42k | ColumnPtr* column) { |
1507 | 4.42k | DORIS_CHECK(mapping.table_type != nullptr); |
1508 | 4.42k | const auto* table_type = |
1509 | 4.42k | assert_cast<const DataTypeStruct*>(remove_nullable(mapping.table_type).get()); |
1510 | 4.42k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1511 | 4.42k | const NullMap* parent_null_map = nullptr; |
1512 | 4.42k | const auto* nested_file_column = |
1513 | 4.42k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1514 | 4.42k | const auto* file_struct = assert_cast<const ColumnStruct*>(nested_file_column); |
1515 | 4.42k | DORIS_CHECK(table_type->get_elements().size() == mapping.child_mappings.size()); |
1516 | | |
1517 | 4.42k | Columns child_columns; |
1518 | 4.42k | child_columns.reserve(mapping.child_mappings.size()); |
1519 | 4.42k | const auto file_ordered_children = |
1520 | 4.42k | _present_child_mappings_in_file_order(mapping.child_mappings); |
1521 | 4.42k | const auto table_ordered_children = |
1522 | 4.42k | _child_mappings_in_table_type_order(mapping, *table_type); |
1523 | 11.3k | for (const auto* child_mapping : table_ordered_children) { |
1524 | 11.3k | DORIS_CHECK(child_mapping != nullptr); |
1525 | 11.3k | if (!child_mapping->file_local_id.has_value()) { |
1526 | 4.42k | child_columns.push_back( |
1527 | 4.42k | (child_mapping->initial_default_column |
1528 | 4.42k | ? child_mapping->initial_default_column->clone_resized(rows) |
1529 | 4.42k | : child_mapping->table_type |
1530 | 4.42k | ->create_column_const_with_default_value(rows)) |
1531 | 4.42k | ->convert_to_full_column_if_const()); |
1532 | 4.42k | continue; |
1533 | 4.42k | } |
1534 | 6.89k | const auto file_child_idx = |
1535 | 6.89k | _file_child_ordinal_for_mapping(mapping, *child_mapping, file_ordered_children); |
1536 | 6.89k | DORIS_CHECK(file_child_idx < file_struct->get_columns().size()); |
1537 | 6.89k | ColumnPtr child_column = file_struct->get_column_ptr(file_child_idx); |
1538 | 6.89k | RETURN_IF_ERROR(_materialize_present_child_mapping_column(*child_mapping, child_column, |
1539 | 6.89k | rows, &child_column)); |
1540 | 6.89k | child_columns.push_back(std::move(child_column)); |
1541 | 6.89k | } |
1542 | 4.42k | MutableColumns mutable_child_columns; |
1543 | 4.42k | mutable_child_columns.reserve(child_columns.size()); |
1544 | 11.3k | for (auto& child_column : child_columns) { |
1545 | 11.3k | mutable_child_columns.push_back(IColumn::mutate(std::move(child_column))); |
1546 | 11.3k | } |
1547 | 4.42k | auto result = ColumnStruct::create(std::move(mutable_child_columns)); |
1548 | 4.42k | if (mapping.table_type->is_nullable()) { |
1549 | 4.42k | auto null_map = ColumnUInt8::create(); |
1550 | 4.42k | auto& null_map_data = null_map->get_data(); |
1551 | 4.42k | null_map_data.resize(rows); |
1552 | 4.42k | if (parent_null_map != nullptr) { |
1553 | 4.42k | DORIS_CHECK(parent_null_map->size() == rows); |
1554 | 4.42k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1555 | 4.42k | } else { |
1556 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1557 | 0 | } |
1558 | 4.42k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1559 | 4.42k | } else { |
1560 | 2 | *column = std::move(result); |
1561 | 2 | } |
1562 | 4.42k | return Status::OK(); |
1563 | 4.42k | } |
1564 | | |
1565 | | Status _materialize_array_mapping_column(const ColumnMapping& mapping, |
1566 | | const ColumnPtr& file_column, const size_t rows, |
1567 | 4.79k | ColumnPtr* column) { |
1568 | 4.79k | DORIS_CHECK(mapping.child_mappings.size() == 1); |
1569 | 4.79k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1570 | 4.79k | const NullMap* parent_null_map = nullptr; |
1571 | 4.79k | const auto* nested_file_column = |
1572 | 4.79k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1573 | 4.79k | const auto* file_array = assert_cast<const ColumnArray*>(nested_file_column); |
1574 | 4.79k | ColumnPtr nested_column = file_array->get_data_ptr(); |
1575 | 4.79k | const auto& element_mapping = mapping.child_mappings[0]; |
1576 | 4.79k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1577 | 4.79k | element_mapping, nested_column, nested_column->size(), &nested_column)); |
1578 | 4.79k | auto offsets_column = file_array->get_offsets_ptr()->convert_to_full_column_if_const(); |
1579 | 4.79k | auto result = ColumnArray::create(IColumn::mutate(std::move(nested_column)), |
1580 | 4.79k | IColumn::mutate(std::move(offsets_column))); |
1581 | 4.79k | if (mapping.table_type->is_nullable()) { |
1582 | 4.79k | auto null_map = ColumnUInt8::create(); |
1583 | 4.79k | auto& null_map_data = null_map->get_data(); |
1584 | 4.79k | null_map_data.resize(rows); |
1585 | 4.79k | if (parent_null_map != nullptr) { |
1586 | 4.79k | DORIS_CHECK(parent_null_map->size() == rows); |
1587 | 4.79k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1588 | 4.79k | } else { |
1589 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1590 | 0 | } |
1591 | 4.79k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1592 | 4.79k | } else { |
1593 | 0 | *column = std::move(result); |
1594 | 0 | } |
1595 | 4.79k | return Status::OK(); |
1596 | 4.79k | } |
1597 | | |
1598 | | Status _materialize_map_mapping_column(const ColumnMapping& mapping, |
1599 | | const ColumnPtr& file_column, const size_t rows, |
1600 | 3.86k | ColumnPtr* column) { |
1601 | 3.86k | const auto full_file_column = file_column->convert_to_full_column_if_const(); |
1602 | 3.86k | const NullMap* parent_null_map = nullptr; |
1603 | 3.86k | const auto* nested_file_column = |
1604 | 3.86k | _nested_column_if_nullable(full_file_column, &parent_null_map); |
1605 | 3.86k | const auto* file_map = assert_cast<const ColumnMap*>(nested_file_column); |
1606 | 3.86k | ColumnPtr key_column = file_map->get_keys_ptr(); |
1607 | 3.86k | ColumnPtr value_column = file_map->get_values_ptr(); |
1608 | | |
1609 | 3.86k | const ColumnMapping* key_mapping = nullptr; |
1610 | 3.86k | const ColumnMapping* value_mapping = nullptr; |
1611 | 7.73k | for (const auto& child_mapping : mapping.child_mappings) { |
1612 | 7.73k | if (!child_mapping.file_local_id.has_value()) { |
1613 | 0 | continue; |
1614 | 0 | } |
1615 | 7.73k | if (*child_mapping.file_local_id == 0) { |
1616 | 3.86k | key_mapping = &child_mapping; |
1617 | 3.86k | } else if (*child_mapping.file_local_id == 1) { |
1618 | 3.86k | value_mapping = &child_mapping; |
1619 | 3.86k | } |
1620 | 7.73k | } |
1621 | | |
1622 | 3.86k | if (key_mapping != nullptr) { |
1623 | 3.86k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1624 | 3.86k | *key_mapping, key_column, key_column->size(), &key_column)); |
1625 | 3.86k | } |
1626 | 3.86k | if (value_mapping != nullptr) { |
1627 | 3.86k | RETURN_IF_ERROR(_materialize_present_child_mapping_column( |
1628 | 3.86k | *value_mapping, value_column, value_column->size(), &value_column)); |
1629 | 3.86k | } |
1630 | 3.86k | auto offsets_column = file_map->get_offsets_ptr()->convert_to_full_column_if_const(); |
1631 | 3.86k | auto result = ColumnMap::create(IColumn::mutate(std::move(key_column)), |
1632 | 3.86k | IColumn::mutate(std::move(value_column)), |
1633 | 3.86k | IColumn::mutate(std::move(offsets_column))); |
1634 | 3.86k | if (mapping.table_type->is_nullable()) { |
1635 | 3.86k | auto null_map = ColumnUInt8::create(); |
1636 | 3.86k | auto& null_map_data = null_map->get_data(); |
1637 | 3.86k | null_map_data.resize(rows); |
1638 | 3.86k | if (parent_null_map != nullptr) { |
1639 | 3.86k | DORIS_CHECK(parent_null_map->size() == rows); |
1640 | 3.86k | null_map_data.assign(parent_null_map->begin(), parent_null_map->end()); |
1641 | 3.86k | } else { |
1642 | 0 | std::fill(null_map_data.begin(), null_map_data.end(), 0); |
1643 | 0 | } |
1644 | 3.86k | *column = ColumnNullable::create(std::move(result), std::move(null_map)); |
1645 | 3.86k | } else { |
1646 | 0 | *column = std::move(result); |
1647 | 0 | } |
1648 | 3.86k | return Status::OK(); |
1649 | 3.86k | } |
1650 | | |
1651 | 60.8k | Status _open_mapping_exprs() { |
1652 | 60.8k | RowDescriptor row_desc; |
1653 | 394k | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1654 | 394k | if (mapping.projection != nullptr) { |
1655 | 372k | RETURN_IF_ERROR(mapping.projection->prepare(_runtime_state, row_desc)); |
1656 | 372k | RETURN_IF_ERROR(mapping.projection->open(_runtime_state)); |
1657 | 372k | } |
1658 | 394k | if (mapping.default_expr != nullptr) { |
1659 | 18.1k | RETURN_IF_ERROR(mapping.default_expr->prepare(_runtime_state, row_desc)); |
1660 | 18.1k | RETURN_IF_ERROR(mapping.default_expr->open(_runtime_state)); |
1661 | 18.1k | } |
1662 | 394k | } |
1663 | 60.8k | return Status::OK(); |
1664 | 60.8k | } |
1665 | | |
1666 | | Status _build_file_aggregate_request(TPushAggOp::type agg_type, |
1667 | 1.49k | FileAggregateRequest* request) const { |
1668 | 1.49k | DORIS_CHECK(request != nullptr); |
1669 | 1.49k | DORIS_CHECK(_supports_aggregate_pushdown(agg_type)); |
1670 | 1.49k | request->agg_type = agg_type; |
1671 | 1.49k | request->columns.clear(); |
1672 | 1.49k | if (agg_type == TPushAggOp::type::COUNT) { |
1673 | 1.47k | DORIS_CHECK(_push_down_count_columns.has_value()); |
1674 | | // An empty explicit list is the semantic signal for COUNT(*). Do not inspect the |
1675 | | // mapping count: `SELECT COUNT(*) FROM t` may still project one nullable column because |
1676 | | // the planner keeps a placeholder slot. In a 10,000-row file where that arbitrary slot |
1677 | | // has 9,015 non-null values, passing the slot would ask Parquet/ORC metadata for |
1678 | | // COUNT(slot)=9,015 instead of the required row count 10,000. |
1679 | 1.47k | if (!_push_down_count_columns->empty()) { |
1680 | 254 | const auto& mapping = _push_down_count_mapping(); |
1681 | 254 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1682 | 254 | FileAggregateRequest::Column column; |
1683 | 254 | column.projection = |
1684 | 254 | LocalColumnIndex::top_level(LocalColumnId(*mapping.file_local_id)); |
1685 | 254 | request->columns.push_back(std::move(column)); |
1686 | 254 | } |
1687 | 1.47k | return Status::OK(); |
1688 | 1.47k | } |
1689 | 18 | request->columns.reserve(_data_reader.column_mapper->mappings().size()); |
1690 | 47 | for (const auto& mapping : _data_reader.column_mapper->mappings()) { |
1691 | 47 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1692 | 47 | FileAggregateRequest::Column column; |
1693 | 47 | column.projection = LocalColumnIndex::top_level(LocalColumnId(*mapping.file_local_id)); |
1694 | 47 | if (!mapping.child_mappings.empty()) { |
1695 | 1 | RETURN_IF_ERROR(build_aggregate_projection(mapping, &column.projection)); |
1696 | 1 | } |
1697 | 47 | request->columns.push_back(std::move(column)); |
1698 | 47 | } |
1699 | 18 | return Status::OK(); |
1700 | 18 | } |
1701 | | |
1702 | 1.03k | const ColumnMapping& _push_down_count_mapping() const { |
1703 | 1.03k | DORIS_CHECK(_push_down_count_columns.has_value()); |
1704 | 1.03k | DORIS_CHECK(_push_down_count_columns->size() == 1); |
1705 | 1.03k | const auto mapping_it = |
1706 | 1.03k | std::ranges::find(_data_reader.column_mapper->mappings(), |
1707 | 1.03k | _push_down_count_columns->front(), &ColumnMapping::global_index); |
1708 | | // FileScannerV2 translates FE SlotIds through the same projected-column list used to build |
1709 | | // the mapper, so a missing mapping is an FE/BE contract violation rather than a fallback. |
1710 | 1.03k | DORIS_CHECK(mapping_it != _data_reader.column_mapper->mappings().end()); |
1711 | 1.03k | return *mapping_it; |
1712 | 1.03k | } |
1713 | | |
1714 | | Status _materialize_aggregate_pushdown_rows(TPushAggOp::type agg_type, |
1715 | | const FileAggregateResult& file_result, |
1716 | 21 | Block* block) { |
1717 | 21 | DORIS_CHECK(agg_type == TPushAggOp::type::MINMAX); |
1718 | | // MIN/MAX pushdown emits two rows, min first and max second, for each projected column. |
1719 | | // The upper MIN/MAX aggregate consumes those two rows to produce the final aggregate value. |
1720 | 21 | DORIS_CHECK(file_result.columns.size() == _data_reader.column_mapper->mappings().size()); |
1721 | 21 | DORIS_CHECK(block->columns() == _data_reader.column_mapper->mappings().size()); |
1722 | 21 | Block file_block; |
1723 | 21 | file_block.reserve(_data_reader.file_block_layout.size()); |
1724 | 26 | for (const auto& column : _data_reader.file_block_layout) { |
1725 | 26 | file_block.insert({column.type->create_column(), column.type, column.name}); |
1726 | 26 | } |
1727 | 47 | for (size_t column_idx = 0; column_idx < file_result.columns.size(); ++column_idx) { |
1728 | 26 | const auto& result_column = file_result.columns[column_idx]; |
1729 | 26 | if (!result_column.has_min || !result_column.has_max) { |
1730 | 0 | return Status::NotSupported("Missing min/max aggregate result for column {}", |
1731 | 0 | _projected_columns[column_idx].name); |
1732 | 0 | } |
1733 | 26 | bool found_file_column = false; |
1734 | 33 | for (size_t block_position = 0; block_position < _data_reader.file_block_layout.size(); |
1735 | 33 | ++block_position) { |
1736 | 33 | if (_data_reader.file_block_layout[block_position].file_column_id == |
1737 | 33 | file_result.columns[column_idx].projection.column_id()) { |
1738 | 26 | found_file_column = true; |
1739 | 26 | auto column = file_block.get_by_position(block_position) |
1740 | 26 | .type->create_column() |
1741 | 26 | ->assert_mutable(); |
1742 | 26 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1743 | 26 | file_result.columns[column_idx].projection, result_column.min_value, |
1744 | 26 | column.get())); |
1745 | 26 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1746 | 26 | file_result.columns[column_idx].projection, result_column.max_value, |
1747 | 26 | column.get())); |
1748 | 26 | file_block.replace_by_position(block_position, std::move(column)); |
1749 | 26 | break; |
1750 | 26 | } |
1751 | 33 | } |
1752 | 26 | DORIS_CHECK(found_file_column); |
1753 | 26 | } |
1754 | 47 | for (size_t column_idx = 0; column_idx < _data_reader.column_mapper->mappings().size(); |
1755 | 26 | ++column_idx) { |
1756 | 26 | ColumnPtr table_column; |
1757 | 26 | RETURN_IF_ERROR(_materialize_mapping_column( |
1758 | 26 | _data_reader.column_mapper->mappings()[column_idx], &file_block, 2, |
1759 | 26 | &table_column, |
1760 | 26 | column_idx + 1 == _data_reader.column_mapper->mappings().size())); |
1761 | 26 | block->replace_by_position(column_idx, std::move(table_column)); |
1762 | 26 | } |
1763 | 21 | return Status::OK(); |
1764 | 21 | } |
1765 | | |
1766 | | struct FileBlockColumn { |
1767 | | LocalColumnId file_column_id = LocalColumnId::invalid(); |
1768 | | std::string name; |
1769 | | DataTypePtr type; |
1770 | | }; |
1771 | | |
1772 | | struct DataReader { |
1773 | | std::unique_ptr<FileReader> reader; |
1774 | | std::unique_ptr<TableColumnMapper> column_mapper; |
1775 | | // Schema of the data file, also including virtual column (row position). |
1776 | | std::vector<ColumnDefinition> file_schema; |
1777 | | // Layout of the block returned by file reader, determined by column mapping and file |
1778 | | // schema. It is used for file reader to materialize columns into correct type and position. |
1779 | | std::vector<FileBlockColumn> file_block_layout; |
1780 | | Block block_template; |
1781 | | }; |
1782 | | DataReader _data_reader; |
1783 | | std::vector<ColumnDefinition> _projected_columns; |
1784 | | std::unique_ptr<ScanTask> _current_task; |
1785 | | std::optional<io::FileDescription> _current_file_description; |
1786 | | // Range-level compression has higher priority than scan-param compression. TVF/load can keep |
1787 | | // the logical format as CSV/TEXT while carrying the concrete compression such as GZ or LZO on |
1788 | | // each TFileRangeDesc, matching the old FileScanner reader contract. |
1789 | | TFileCompressType::type _current_range_compress_type = TFileCompressType::UNKNOWN; |
1790 | | std::optional<TUniqueId> _current_range_load_id; |
1791 | | TFileRangeDesc _current_file_range_desc; |
1792 | | std::shared_ptr<io::FileSystemProperties> _system_properties; |
1793 | | // partition key -> value |
1794 | | std::map<std::string, Field> _partition_values; |
1795 | | // Predicates built from scan conjuncts before file-level localization. |
1796 | | std::vector<TableFilter> _table_filters; |
1797 | | // Number of localized filters before the first unsafe conjunct in the original row-level |
1798 | | // order. This differs from scanning `_table_filters` for safety because slotless predicates are |
1799 | | // intentionally absent from that vector but must still act as ordering barriers. |
1800 | | size_t _constant_pruning_safe_filter_count = 0; |
1801 | | VExprContextSPtrs _conjuncts; |
1802 | | size_t _table_reader_owned_conjunct_count = 0; |
1803 | | std::optional<size_t> _appended_table_reader_owned_conjunct_count; |
1804 | | VExprContextSPtrs _remaining_conjuncts; |
1805 | | MaterializedBlockStats _last_materialized_block_stats; |
1806 | | ReadProfile _profile; |
1807 | | // Parsed from row-position based delete files, including position delete and deletion vector. |
1808 | | DeleteRows* _delete_rows = nullptr; |
1809 | | DeletionVector* _deletion_vector = nullptr; |
1810 | | TFileScanRangeParams* _scan_params; |
1811 | | std::shared_ptr<io::IOContext> _io_ctx; |
1812 | | RuntimeState* _runtime_state; |
1813 | | RuntimeProfile* _scanner_profile; |
1814 | | const std::vector<SlotDescriptor*>* _file_slot_descs = nullptr; |
1815 | | FileFormat _format; |
1816 | | TPushAggOp::type _push_down_agg_type = TPushAggOp::type::NONE; |
1817 | | std::optional<std::vector<GlobalIndex>> _push_down_count_columns; |
1818 | | size_t _batch_size = 0; |
1819 | | uint64_t _initial_condition_cache_digest = 0; |
1820 | | uint64_t _condition_cache_digest = 0; |
1821 | | // True only when prepare_split() received a digest for the exact conjunct snapshot used by |
1822 | | // this split. Standalone callers that only supplied TableReadOptions::condition_cache_digest |
1823 | | // keep the conservative runtime-filter guard. |
1824 | | bool _condition_cache_digest_covers_current_split = false; |
1825 | | segment_v2::ConditionCache::ExternalCacheKey _condition_cache_key; |
1826 | | std::shared_ptr<std::vector<bool>> _condition_cache; |
1827 | | std::shared_ptr<ConditionCacheContext> _condition_cache_ctx; |
1828 | | int64_t _condition_cache_hit_count = 0; |
1829 | | bool _current_reader_reached_eof = false; |
1830 | | int64_t _remaining_table_level_count = -1; |
1831 | | int64_t _remaining_file_level_count = -1; |
1832 | | // True only after the active split selects a table-level row-count shortcut or successfully |
1833 | | // materializes COUNT rows from file metadata. FileScannerV2 uses this result, rather than the |
1834 | | // raw aggregate opcode, to keep adaptive batching enabled for normal row-scan fallbacks. |
1835 | | bool _current_split_uses_metadata_count = false; |
1836 | | // Snapshot supplied by FileScannerV2 for the active split. It gates every shortcut that emits |
1837 | | // irreversible aggregate rows, not only the table-level row-count shortcut in prepare_split(). |
1838 | | bool _all_runtime_filters_applied_for_split = true; |
1839 | | std::optional<GlobalRowIdContext> _global_rowid_context; |
1840 | | bool _aggregate_pushdown_tried = false; |
1841 | | bool _current_split_pruned = false; |
1842 | | TableColumnMapperOptions _mapper_options; |
1843 | | |
1844 | | private: |
1845 | | static const ColumnDefinition* _find_column_definition( |
1846 | 388k | const std::vector<ColumnDefinition>& schema, LocalColumnId column_id) { |
1847 | 9.22M | for (const auto& field : schema) { |
1848 | 9.22M | if (field.file_local_id() == column_id.value()) { |
1849 | 381k | return &field; |
1850 | 381k | } |
1851 | 9.22M | } |
1852 | 7.48k | return nullptr; |
1853 | 388k | } |
1854 | | |
1855 | 318 | static bool _can_push_down_minmax_for_mapping(const ColumnMapping& mapping) { |
1856 | 318 | if (mapping.child_mappings.empty()) { |
1857 | | // Direct mappings use a slot-ref projection to materialize the file column. The |
1858 | | // projection does not transform ordering; casts and other conversions are already |
1859 | | // represented by a non-trivial mapping and must fall back to row scanning. |
1860 | 315 | return mapping.is_trivial; |
1861 | 315 | } |
1862 | 3 | const auto primitive_type = remove_nullable(mapping.file_type)->get_primitive_type(); |
1863 | 3 | if (primitive_type != TYPE_STRUCT) { |
1864 | 1 | return false; |
1865 | 1 | } |
1866 | 2 | size_t mapped_children = 0; |
1867 | 2 | const ColumnMapping* mapped_child = nullptr; |
1868 | 2 | for (const auto& child_mapping : mapping.child_mappings) { |
1869 | 2 | if (!child_mapping.file_local_id.has_value()) { |
1870 | 0 | continue; |
1871 | 0 | } |
1872 | 2 | ++mapped_children; |
1873 | 2 | mapped_child = &child_mapping; |
1874 | 2 | } |
1875 | 2 | return mapped_children == 1 && mapped_child != nullptr && |
1876 | 2 | _can_push_down_minmax_for_mapping(*mapped_child); |
1877 | 3 | } |
1878 | | |
1879 | | static Status build_aggregate_projection(const ColumnMapping& mapping, |
1880 | 2 | LocalColumnIndex* projection) { |
1881 | 2 | DORIS_CHECK(projection != nullptr); |
1882 | 2 | DORIS_CHECK(mapping.file_local_id.has_value()); |
1883 | 2 | *projection = LocalColumnIndex::local(*mapping.file_local_id); |
1884 | 2 | projection->children.clear(); |
1885 | 2 | projection->project_all_children = true; |
1886 | 2 | if (mapping.child_mappings.empty()) { |
1887 | 1 | return Status::OK(); |
1888 | 1 | } |
1889 | 1 | projection->project_all_children = false; |
1890 | 1 | for (const auto& child_mapping : mapping.child_mappings) { |
1891 | 1 | if (!child_mapping.file_local_id.has_value()) { |
1892 | 0 | continue; |
1893 | 0 | } |
1894 | 1 | LocalColumnIndex child_projection; |
1895 | 1 | RETURN_IF_ERROR(build_aggregate_projection(child_mapping, &child_projection)); |
1896 | 1 | projection->children.push_back(std::move(child_projection)); |
1897 | 1 | } |
1898 | 1 | DORIS_CHECK(projection->children.size() == 1); |
1899 | 1 | return Status::OK(); |
1900 | 1 | } |
1901 | | |
1902 | | static Status _insert_aggregate_projection_value(const LocalColumnIndex& projection, |
1903 | 108 | const Field& value, IColumn* column) { |
1904 | 108 | DORIS_CHECK(column != nullptr); |
1905 | 108 | if (auto* nullable_column = check_and_get_column<ColumnNullable>(*column)) { |
1906 | 54 | RETURN_IF_ERROR(_insert_aggregate_projection_value( |
1907 | 54 | projection, value, &nullable_column->get_nested_column())); |
1908 | 54 | nullable_column->get_null_map_data().push_back(0); |
1909 | 54 | return Status::OK(); |
1910 | 54 | } |
1911 | 54 | if (projection.project_all_children || projection.children.empty()) { |
1912 | 52 | column->insert(value); |
1913 | 52 | return Status::OK(); |
1914 | 52 | } |
1915 | 2 | auto* struct_column = assert_cast<ColumnStruct*>(column); |
1916 | 2 | DORIS_CHECK(projection.children.size() == 1); |
1917 | 2 | const auto& child_projection = projection.children[0]; |
1918 | 2 | DORIS_CHECK(struct_column->get_columns().size() == 1); |
1919 | 2 | RETURN_IF_ERROR(_insert_aggregate_projection_value(child_projection, value, |
1920 | 2 | &struct_column->get_column(0))); |
1921 | 2 | return Status::OK(); |
1922 | 2 | } |
1923 | | |
1924 | | // Parse a DV into its compressed bitmap. Position delete files continue to use _delete_rows. |
1925 | | Status _parse_delete_predicates(const SplitReadOptions& options); |
1926 | | }; |
1927 | | |
1928 | | } // namespace doris::format |