be/src/format/parquet/vparquet_reader.cpp
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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 | | #include "format/parquet/vparquet_reader.h" |
19 | | |
20 | | #include <gen_cpp/Metrics_types.h> |
21 | | #include <gen_cpp/PlanNodes_types.h> |
22 | | #include <gen_cpp/parquet_types.h> |
23 | | #include <glog/logging.h> |
24 | | |
25 | | #include <algorithm> |
26 | | #include <functional> |
27 | | #include <sstream> |
28 | | #include <utility> |
29 | | |
30 | | #include "common/config.h" |
31 | | #include "common/status.h" |
32 | | #include "core/block/block.h" |
33 | | #include "core/block/column_with_type_and_name.h" |
34 | | #include "core/column/column.h" |
35 | | #include "core/data_type/define_primitive_type.h" |
36 | | #include "core/typeid_cast.h" |
37 | | #include "core/types.h" |
38 | | #include "exec/scan/file_scanner.h" |
39 | | #include "exprs/vbloom_predicate.h" |
40 | | #include "exprs/vdirect_in_predicate.h" |
41 | | #include "exprs/vexpr.h" |
42 | | #include "exprs/vexpr_context.h" |
43 | | #include "exprs/vin_predicate.h" |
44 | | #include "exprs/vruntimefilter_wrapper.h" |
45 | | #include "exprs/vslot_ref.h" |
46 | | #include "exprs/vtopn_pred.h" |
47 | | #include "format/column_type_convert.h" |
48 | | #include "format/parquet/parquet_block_split_bloom_filter.h" |
49 | | #include "format/parquet/parquet_common.h" |
50 | | #include "format/parquet/parquet_predicate.h" |
51 | | #include "format/parquet/parquet_thrift_util.h" |
52 | | #include "format/parquet/schema_desc.h" |
53 | | #include "format/parquet/vparquet_file_metadata.h" |
54 | | #include "format/parquet/vparquet_group_reader.h" |
55 | | #include "format/parquet/vparquet_page_index.h" |
56 | | #include "format/table/hive/hive_parquet_nested_column_utils.h" |
57 | | #include "format/table/nested_column_access_helper.h" |
58 | | #include "information_schema/schema_scanner.h" |
59 | | #include "io/file_factory.h" |
60 | | #include "io/fs/buffered_reader.h" |
61 | | #include "io/fs/file_reader.h" |
62 | | #include "io/fs/file_reader_writer_fwd.h" |
63 | | #include "io/fs/tracing_file_reader.h" |
64 | | #include "runtime/descriptors.h" |
65 | | #include "util/slice.h" |
66 | | #include "util/string_util.h" |
67 | | #include "util/timezone_utils.h" |
68 | | |
69 | | namespace cctz { |
70 | | class time_zone; |
71 | | } // namespace cctz |
72 | | namespace doris { |
73 | | class RowDescriptor; |
74 | | class RuntimeState; |
75 | | class SlotDescriptor; |
76 | | class TupleDescriptor; |
77 | | namespace io { |
78 | | struct IOContext; |
79 | | enum class FileCachePolicy : uint8_t; |
80 | | } // namespace io |
81 | | class Block; |
82 | | } // namespace doris |
83 | | |
84 | | namespace doris { |
85 | | |
86 | | ParquetReader::ParquetReader(RuntimeProfile* profile, const TFileScanRangeParams& params, |
87 | | const TFileRangeDesc& range, size_t batch_size, |
88 | | const cctz::time_zone* ctz, io::IOContext* io_ctx, RuntimeState* state, |
89 | | FileMetaCache* meta_cache, bool enable_lazy_mat) |
90 | 98 | : _profile(profile), |
91 | 98 | _scan_params(params), |
92 | 98 | _scan_range(range), |
93 | 98 | _batch_size(std::max(batch_size, 1UL)), |
94 | 98 | _range_start_offset(range.start_offset), |
95 | 98 | _range_size(range.size), |
96 | 98 | _ctz(ctz), |
97 | 98 | _io_ctx(io_ctx), |
98 | 98 | _state(state), |
99 | 98 | _enable_lazy_mat(enable_lazy_mat), |
100 | | _enable_filter_by_min_max( |
101 | 98 | state == nullptr ? true |
102 | 98 | : state->query_options().enable_parquet_filter_by_min_max), |
103 | | _enable_filter_by_bloom_filter( |
104 | 98 | state == nullptr ? true |
105 | 98 | : state->query_options().enable_parquet_filter_by_bloom_filter) { |
106 | 98 | _meta_cache = meta_cache; |
107 | 98 | _init_profile(); |
108 | 98 | _init_system_properties(); |
109 | 98 | _init_file_description(); |
110 | 98 | } |
111 | | |
112 | 0 | void ParquetReader::set_batch_size(size_t batch_size) { |
113 | 0 | if (_batch_size == batch_size) { |
114 | 0 | return; |
115 | 0 | } |
116 | 0 | _batch_size = batch_size; |
117 | 0 | } |
118 | | |
119 | | ParquetReader::ParquetReader(RuntimeProfile* profile, const TFileScanRangeParams& params, |
120 | | const TFileRangeDesc& range, size_t batch_size, |
121 | | const cctz::time_zone* ctz, |
122 | | std::shared_ptr<io::IOContext> io_ctx_holder, RuntimeState* state, |
123 | | FileMetaCache* meta_cache, bool enable_lazy_mat) |
124 | 0 | : _profile(profile), |
125 | 0 | _scan_params(params), |
126 | 0 | _scan_range(range), |
127 | 0 | _batch_size(std::max(batch_size, 1UL)), |
128 | 0 | _range_start_offset(range.start_offset), |
129 | 0 | _range_size(range.size), |
130 | 0 | _ctz(ctz), |
131 | 0 | _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr), |
132 | 0 | _io_ctx_holder(std::move(io_ctx_holder)), |
133 | 0 | _state(state), |
134 | 0 | _enable_lazy_mat(enable_lazy_mat), |
135 | | _enable_filter_by_min_max( |
136 | 0 | state == nullptr ? true |
137 | 0 | : state->query_options().enable_parquet_filter_by_min_max), |
138 | | _enable_filter_by_bloom_filter( |
139 | 0 | state == nullptr ? true |
140 | 0 | : state->query_options().enable_parquet_filter_by_bloom_filter) { |
141 | 0 | _meta_cache = meta_cache; |
142 | 0 | _init_profile(); |
143 | 0 | _init_system_properties(); |
144 | 0 | _init_file_description(); |
145 | 0 | } |
146 | | |
147 | | ParquetReader::ParquetReader(const TFileScanRangeParams& params, const TFileRangeDesc& range, |
148 | | io::IOContext* io_ctx, RuntimeState* state, FileMetaCache* meta_cache, |
149 | | bool enable_lazy_mat) |
150 | 5 | : _profile(nullptr), |
151 | 5 | _scan_params(params), |
152 | 5 | _scan_range(range), |
153 | 5 | _io_ctx(io_ctx), |
154 | 5 | _state(state), |
155 | 5 | _enable_lazy_mat(enable_lazy_mat), |
156 | | _enable_filter_by_min_max( |
157 | 5 | state == nullptr ? true |
158 | 5 | : state->query_options().enable_parquet_filter_by_min_max), |
159 | | _enable_filter_by_bloom_filter( |
160 | 5 | state == nullptr ? true |
161 | 5 | : state->query_options().enable_parquet_filter_by_bloom_filter) { |
162 | 5 | _meta_cache = meta_cache; |
163 | 5 | _init_system_properties(); |
164 | 5 | _init_file_description(); |
165 | 5 | } |
166 | | |
167 | | ParquetReader::ParquetReader(const TFileScanRangeParams& params, const TFileRangeDesc& range, |
168 | | std::shared_ptr<io::IOContext> io_ctx_holder, RuntimeState* state, |
169 | | FileMetaCache* meta_cache, bool enable_lazy_mat) |
170 | 0 | : _profile(nullptr), |
171 | 0 | _scan_params(params), |
172 | 0 | _scan_range(range), |
173 | 0 | _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr), |
174 | 0 | _io_ctx_holder(std::move(io_ctx_holder)), |
175 | 0 | _state(state), |
176 | 0 | _enable_lazy_mat(enable_lazy_mat), |
177 | | _enable_filter_by_min_max( |
178 | 0 | state == nullptr ? true |
179 | 0 | : state->query_options().enable_parquet_filter_by_min_max), |
180 | | _enable_filter_by_bloom_filter( |
181 | 0 | state == nullptr ? true |
182 | 0 | : state->query_options().enable_parquet_filter_by_bloom_filter) { |
183 | 0 | _meta_cache = meta_cache; |
184 | 0 | _init_system_properties(); |
185 | 0 | _init_file_description(); |
186 | 0 | } |
187 | | |
188 | 103 | ParquetReader::~ParquetReader() { |
189 | 103 | _close_internal(); |
190 | 103 | } |
191 | | |
192 | | #ifdef BE_TEST |
193 | | // for unit test |
194 | 69 | void ParquetReader::set_file_reader(io::FileReaderSPtr file_reader) { |
195 | 69 | _file_reader = file_reader; |
196 | 69 | _tracing_file_reader = file_reader; |
197 | 69 | } |
198 | | #endif |
199 | | |
200 | 98 | void ParquetReader::_init_profile() { |
201 | 98 | if (_profile != nullptr) { |
202 | 50 | static const char* parquet_profile = "ParquetReader"; |
203 | 50 | ADD_TIMER_WITH_LEVEL(_profile, parquet_profile, 1); |
204 | | |
205 | 50 | _parquet_profile.filtered_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL( |
206 | 50 | _profile, "RowGroupsFiltered", TUnit::UNIT, parquet_profile, 1); |
207 | 50 | _parquet_profile.filtered_row_groups_by_min_max = ADD_CHILD_COUNTER_WITH_LEVEL( |
208 | 50 | _profile, "RowGroupsFilteredByMinMax", TUnit::UNIT, parquet_profile, 1); |
209 | 50 | _parquet_profile.filtered_row_groups_by_bloom_filter = ADD_CHILD_COUNTER_WITH_LEVEL( |
210 | 50 | _profile, "RowGroupsFilteredByBloomFilter", TUnit::UNIT, parquet_profile, 1); |
211 | 50 | _parquet_profile.to_read_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL( |
212 | 50 | _profile, "RowGroupsReadNum", TUnit::UNIT, parquet_profile, 1); |
213 | 50 | _parquet_profile.total_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL( |
214 | 50 | _profile, "RowGroupsTotalNum", TUnit::UNIT, parquet_profile, 1); |
215 | 50 | _parquet_profile.filtered_group_rows = ADD_CHILD_COUNTER_WITH_LEVEL( |
216 | 50 | _profile, "FilteredRowsByGroup", TUnit::UNIT, parquet_profile, 1); |
217 | 50 | _parquet_profile.filtered_page_rows = ADD_CHILD_COUNTER_WITH_LEVEL( |
218 | 50 | _profile, "FilteredRowsByPage", TUnit::UNIT, parquet_profile, 1); |
219 | 50 | _parquet_profile.lazy_read_filtered_rows = ADD_CHILD_COUNTER_WITH_LEVEL( |
220 | 50 | _profile, "FilteredRowsByLazyRead", TUnit::UNIT, parquet_profile, 1); |
221 | 50 | _parquet_profile.filtered_bytes = ADD_CHILD_COUNTER_WITH_LEVEL( |
222 | 50 | _profile, "FilteredBytes", TUnit::BYTES, parquet_profile, 1); |
223 | 50 | _parquet_profile.raw_rows_read = ADD_CHILD_COUNTER_WITH_LEVEL( |
224 | 50 | _profile, "RawRowsRead", TUnit::UNIT, parquet_profile, 1); |
225 | 50 | _parquet_profile.column_read_time = |
226 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ColumnReadTime", parquet_profile, 1); |
227 | 50 | _parquet_profile.parse_meta_time = |
228 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseMetaTime", parquet_profile, 1); |
229 | 50 | _parquet_profile.parse_footer_time = |
230 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseFooterTime", parquet_profile, 1); |
231 | 50 | _parquet_profile.file_reader_create_time = |
232 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "FileReaderCreateTime", parquet_profile, 1); |
233 | 50 | _parquet_profile.open_file_num = |
234 | 50 | ADD_CHILD_COUNTER_WITH_LEVEL(_profile, "FileNum", TUnit::UNIT, parquet_profile, 1); |
235 | 50 | _parquet_profile.page_index_read_calls = |
236 | 50 | ADD_COUNTER_WITH_LEVEL(_profile, "PageIndexReadCalls", TUnit::UNIT, 1); |
237 | 50 | _parquet_profile.page_index_filter_time = |
238 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexFilterTime", parquet_profile, 1); |
239 | 50 | _parquet_profile.read_page_index_time = |
240 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexReadTime", parquet_profile, 1); |
241 | 50 | _parquet_profile.parse_page_index_time = |
242 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexParseTime", parquet_profile, 1); |
243 | 50 | _parquet_profile.row_group_filter_time = |
244 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "RowGroupFilterTime", parquet_profile, 1); |
245 | 50 | _parquet_profile.file_footer_read_calls = |
246 | 50 | ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterReadCalls", TUnit::UNIT, 1); |
247 | 50 | _parquet_profile.file_footer_hit_cache = |
248 | 50 | ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterHitCache", TUnit::UNIT, 1); |
249 | 50 | _parquet_profile.decompress_time = |
250 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecompressTime", parquet_profile, 1); |
251 | 50 | _parquet_profile.decompress_cnt = ADD_CHILD_COUNTER_WITH_LEVEL( |
252 | 50 | _profile, "DecompressCount", TUnit::UNIT, parquet_profile, 1); |
253 | 50 | _parquet_profile.page_read_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
254 | 50 | _profile, "PageReadCount", TUnit::UNIT, parquet_profile, 1); |
255 | 50 | _parquet_profile.page_cache_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
256 | 50 | _profile, "PageCacheWriteCount", TUnit::UNIT, parquet_profile, 1); |
257 | 50 | _parquet_profile.page_cache_compressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
258 | 50 | _profile, "PageCacheCompressedWriteCount", TUnit::UNIT, parquet_profile, 1); |
259 | 50 | _parquet_profile.page_cache_decompressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
260 | 50 | _profile, "PageCacheDecompressedWriteCount", TUnit::UNIT, parquet_profile, 1); |
261 | 50 | _parquet_profile.page_cache_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
262 | 50 | _profile, "PageCacheHitCount", TUnit::UNIT, parquet_profile, 1); |
263 | 50 | _parquet_profile.page_cache_missing_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
264 | 50 | _profile, "PageCacheMissingCount", TUnit::UNIT, parquet_profile, 1); |
265 | 50 | _parquet_profile.page_cache_compressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
266 | 50 | _profile, "PageCacheCompressedHitCount", TUnit::UNIT, parquet_profile, 1); |
267 | 50 | _parquet_profile.page_cache_decompressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL( |
268 | 50 | _profile, "PageCacheDecompressedHitCount", TUnit::UNIT, parquet_profile, 1); |
269 | 50 | _parquet_profile.decode_header_time = |
270 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderDecodeTime", parquet_profile, 1); |
271 | 50 | _parquet_profile.read_page_header_time = |
272 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderReadTime", parquet_profile, 1); |
273 | 50 | _parquet_profile.decode_value_time = |
274 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeValueTime", parquet_profile, 1); |
275 | 50 | _parquet_profile.decode_dict_time = |
276 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeDictTime", parquet_profile, 1); |
277 | 50 | _parquet_profile.decode_level_time = |
278 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeLevelTime", parquet_profile, 1); |
279 | 50 | _parquet_profile.decode_null_map_time = |
280 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeNullMapTime", parquet_profile, 1); |
281 | 50 | _parquet_profile.skip_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL( |
282 | 50 | _profile, "SkipPageHeaderNum", TUnit::UNIT, parquet_profile, 1); |
283 | 50 | _parquet_profile.parse_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL( |
284 | 50 | _profile, "ParsePageHeaderNum", TUnit::UNIT, parquet_profile, 1); |
285 | 50 | _parquet_profile.predicate_filter_time = |
286 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PredicateFilterTime", parquet_profile, 1); |
287 | 50 | _parquet_profile.dict_filter_rewrite_time = |
288 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DictFilterRewriteTime", parquet_profile, 1); |
289 | 50 | _parquet_profile.convert_time = |
290 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ConvertTime", parquet_profile, 1); |
291 | 50 | _parquet_profile.bloom_filter_read_time = |
292 | 50 | ADD_CHILD_TIMER_WITH_LEVEL(_profile, "BloomFilterReadTime", parquet_profile, 1); |
293 | 50 | } |
294 | 98 | } |
295 | | |
296 | 14 | Status ParquetReader::close() { |
297 | 14 | _close_internal(); |
298 | 14 | return Status::OK(); |
299 | 14 | } |
300 | | |
301 | 117 | void ParquetReader::_close_internal() { |
302 | 117 | if (!_closed) { |
303 | 103 | _closed = true; |
304 | 103 | } |
305 | 117 | } |
306 | | |
307 | 106 | Status ParquetReader::_open_file() { |
308 | 106 | if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) { |
309 | 0 | return Status::EndOfFile("stop"); |
310 | 0 | } |
311 | 106 | if (_file_reader == nullptr) { |
312 | 15 | SCOPED_RAW_TIMER(&_reader_statistics.file_reader_create_time); |
313 | 15 | ++_reader_statistics.open_file_num; |
314 | 15 | _file_description.mtime = |
315 | 15 | _scan_range.__isset.modification_time ? _scan_range.modification_time : 0; |
316 | 15 | io::FileReaderOptions reader_options = |
317 | 15 | FileFactory::get_reader_options(_state, _file_description); |
318 | 15 | _file_reader = DORIS_TRY(io::DelegateReader::create_file_reader( |
319 | 15 | _profile, _system_properties, _file_description, reader_options, |
320 | 15 | io::DelegateReader::AccessMode::RANDOM, _io_ctx)); |
321 | 15 | _tracing_file_reader = _io_ctx ? std::make_shared<io::TracingFileReader>( |
322 | 15 | _file_reader, _io_ctx->file_reader_stats) |
323 | 15 | : _file_reader; |
324 | 15 | } |
325 | | |
326 | 106 | if (_file_metadata == nullptr) { |
327 | 84 | SCOPED_RAW_TIMER(&_reader_statistics.parse_footer_time); |
328 | 84 | if (_tracing_file_reader->size() <= sizeof(PARQUET_VERSION_NUMBER)) { |
329 | | // Some system may generate parquet file with only 4 bytes: PAR1 |
330 | | // Should consider it as empty file. |
331 | 0 | return Status::EndOfFile("open file failed, empty parquet file {} with size: {}", |
332 | 0 | _scan_range.path, _tracing_file_reader->size()); |
333 | 0 | } |
334 | 84 | size_t meta_size = 0; |
335 | 84 | bool enable_mapping_varbinary = _scan_params.__isset.enable_mapping_varbinary |
336 | 84 | ? _scan_params.enable_mapping_varbinary |
337 | 84 | : false; |
338 | 84 | bool enable_mapping_timestamp_tz = _scan_params.__isset.enable_mapping_timestamp_tz |
339 | 84 | ? _scan_params.enable_mapping_timestamp_tz |
340 | 84 | : false; |
341 | 84 | if (_meta_cache == nullptr) { |
342 | | // wrap _file_metadata with unique ptr, so that it can be released finally. |
343 | 48 | RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr, |
344 | 48 | &meta_size, _io_ctx, enable_mapping_varbinary, |
345 | 48 | enable_mapping_timestamp_tz)); |
346 | 48 | _file_metadata = _file_metadata_ptr.get(); |
347 | | // parse magic number & parse meta data |
348 | 48 | _reader_statistics.file_footer_read_calls += 1; |
349 | 48 | } else { |
350 | 36 | const auto& file_meta_cache_key = |
351 | 36 | FileMetaCache::get_key(_tracing_file_reader, _file_description); |
352 | 36 | if (!_meta_cache->lookup(file_meta_cache_key, &_meta_cache_handle)) { |
353 | 24 | RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr, |
354 | 24 | &meta_size, _io_ctx, enable_mapping_varbinary, |
355 | 24 | enable_mapping_timestamp_tz)); |
356 | | // _file_metadata_ptr.release() : move control of _file_metadata to _meta_cache_handle |
357 | 24 | _meta_cache->insert(file_meta_cache_key, _file_metadata_ptr.release(), |
358 | 24 | &_meta_cache_handle); |
359 | 24 | _file_metadata = _meta_cache_handle.data<FileMetaData>(); |
360 | 24 | _reader_statistics.file_footer_read_calls += 1; |
361 | 24 | } else { |
362 | 12 | _reader_statistics.file_footer_hit_cache++; |
363 | 12 | } |
364 | 36 | _file_metadata = _meta_cache_handle.data<FileMetaData>(); |
365 | 36 | } |
366 | | |
367 | 84 | if (_file_metadata == nullptr) { |
368 | 0 | return Status::InternalError("failed to get file meta data: {}", |
369 | 0 | _file_description.path); |
370 | 0 | } |
371 | 84 | } |
372 | 106 | return Status::OK(); |
373 | 106 | } |
374 | | |
375 | 40 | Status ParquetReader::get_file_metadata_schema(const FieldDescriptor** ptr) { |
376 | 40 | RETURN_IF_ERROR(_open_file()); |
377 | 40 | DCHECK(_file_metadata != nullptr); |
378 | 40 | *ptr = &_file_metadata->schema(); |
379 | 40 | return Status::OK(); |
380 | 40 | } |
381 | | |
382 | 103 | void ParquetReader::_init_system_properties() { |
383 | 103 | if (_scan_range.__isset.file_type) { |
384 | | // for compatibility |
385 | 0 | _system_properties.system_type = _scan_range.file_type; |
386 | 103 | } else { |
387 | 103 | _system_properties.system_type = _scan_params.file_type; |
388 | 103 | } |
389 | 103 | _system_properties.properties = _scan_params.properties; |
390 | 103 | _system_properties.hdfs_params = _scan_params.hdfs_params; |
391 | 103 | if (_scan_params.__isset.broker_addresses) { |
392 | 0 | _system_properties.broker_addresses.assign(_scan_params.broker_addresses.begin(), |
393 | 0 | _scan_params.broker_addresses.end()); |
394 | 0 | } |
395 | 103 | } |
396 | | |
397 | 103 | void ParquetReader::_init_file_description() { |
398 | 103 | _file_description.path = _scan_range.path; |
399 | 103 | _file_description.file_size = _scan_range.__isset.file_size ? _scan_range.file_size : -1; |
400 | 103 | if (_scan_range.__isset.fs_name) { |
401 | 0 | _file_description.fs_name = _scan_range.fs_name; |
402 | 0 | } |
403 | 103 | if (_scan_range.__isset.file_cache_admission) { |
404 | 0 | _file_description.file_cache_admission = _scan_range.file_cache_admission; |
405 | 0 | } |
406 | 103 | } |
407 | | |
408 | 9 | Status ParquetReader::on_before_init_reader(ReaderInitContext* ctx) { |
409 | 9 | _column_descs = ctx->column_descs; |
410 | 9 | _fill_col_name_to_block_idx = ctx->col_name_to_block_idx; |
411 | 9 | RETURN_IF_ERROR( |
412 | 9 | _extract_partition_values(*ctx->range, ctx->tuple_descriptor, _fill_partition_values)); |
413 | 21 | for (auto& desc : *ctx->column_descs) { |
414 | 21 | if (desc.category == ColumnCategory::REGULAR || |
415 | 21 | desc.category == ColumnCategory::GENERATED) { |
416 | 21 | ctx->column_names.push_back(desc.name); |
417 | 21 | } else if (desc.category == ColumnCategory::SYNTHESIZED && |
418 | 0 | desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) { |
419 | 0 | auto topn_row_id_column_iter = _create_topn_row_id_column_iterator(); |
420 | 0 | this->register_synthesized_column_handler( |
421 | 0 | desc.name, |
422 | 0 | [iter = std::move(topn_row_id_column_iter), this, &desc]( |
423 | 0 | Block* block, size_t rows) -> Status { |
424 | 0 | return fill_topn_row_id(iter, desc.name, block, rows); |
425 | 0 | }); |
426 | 0 | continue; |
427 | 0 | } |
428 | 21 | } |
429 | | |
430 | | // Build table_info_node from Parquet file metadata with case-insensitive recursive matching. |
431 | | // File is already opened by init_reader before this hook, so metadata is available. |
432 | | // tuple_descriptor may be null in unit tests that only set column_descs. |
433 | 9 | if (ctx->tuple_descriptor != nullptr) { |
434 | 7 | const FieldDescriptor* field_desc = nullptr; |
435 | 7 | RETURN_IF_ERROR(get_file_metadata_schema(&field_desc)); |
436 | 7 | RETURN_IF_ERROR(TableSchemaChangeHelper::BuildTableInfoUtil::by_parquet_name( |
437 | 7 | ctx->tuple_descriptor, *field_desc, ctx->table_info_node)); |
438 | 7 | auto column_id_result = _create_column_ids_by_name(field_desc, ctx->tuple_descriptor); |
439 | 7 | ctx->column_ids = std::move(column_id_result.column_ids); |
440 | 7 | ctx->filter_column_ids = std::move(column_id_result.filter_column_ids); |
441 | 7 | } |
442 | | |
443 | 9 | return Status::OK(); |
444 | 9 | } |
445 | | |
446 | | ColumnIdResult ParquetReader::_create_column_ids_by_name(const FieldDescriptor* field_desc, |
447 | 7 | const TupleDescriptor* tuple_descriptor) { |
448 | 7 | auto* mutable_field_desc = const_cast<FieldDescriptor*>(field_desc); |
449 | 7 | mutable_field_desc->assign_ids(); |
450 | | |
451 | 7 | std::unordered_map<std::string, const FieldSchema*> table_col_name_to_field_schema_map; |
452 | 21 | for (int i = 0; i < field_desc->size(); ++i) { |
453 | 14 | auto field_schema = field_desc->get_column(i); |
454 | 14 | if (!field_schema) { |
455 | 0 | continue; |
456 | 0 | } |
457 | 14 | table_col_name_to_field_schema_map[field_schema->lower_case_name] = field_schema; |
458 | 14 | } |
459 | | |
460 | 7 | std::set<uint64_t> column_ids; |
461 | 7 | std::set<uint64_t> filter_column_ids; |
462 | | |
463 | 7 | auto process_access_paths = [](const FieldSchema* parquet_field, |
464 | 7 | const std::vector<TColumnAccessPath>& access_paths, |
465 | 7 | std::set<uint64_t>& out_ids) { |
466 | 0 | process_nested_access_paths( |
467 | 0 | parquet_field, access_paths, out_ids, |
468 | 0 | [](const FieldSchema* field) { return field->get_column_id(); }, |
469 | 0 | [](const FieldSchema* field) { return field->get_max_column_id(); }, |
470 | 0 | HiveParquetNestedColumnUtils::extract_nested_column_ids); |
471 | 0 | }; |
472 | | |
473 | 17 | for (const auto* slot : tuple_descriptor->slots()) { |
474 | 17 | auto it = table_col_name_to_field_schema_map.find(slot->col_name_lower_case()); |
475 | 17 | if (it == table_col_name_to_field_schema_map.end()) { |
476 | 5 | continue; |
477 | 5 | } |
478 | 12 | auto field_schema = it->second; |
479 | | |
480 | 12 | if ((slot->col_type() != TYPE_STRUCT && slot->col_type() != TYPE_ARRAY && |
481 | 12 | slot->col_type() != TYPE_MAP && slot->col_type() != TYPE_VARIANT)) { |
482 | 12 | column_ids.insert(field_schema->column_id); |
483 | 12 | if (slot->is_predicate()) { |
484 | 0 | filter_column_ids.insert(field_schema->column_id); |
485 | 0 | } |
486 | 12 | continue; |
487 | 12 | } |
488 | | |
489 | 0 | process_access_paths(field_schema, slot->all_access_paths(), column_ids); |
490 | 0 | if (!slot->predicate_access_paths().empty()) { |
491 | 0 | process_access_paths(field_schema, slot->predicate_access_paths(), filter_column_ids); |
492 | 0 | } |
493 | 0 | } |
494 | | |
495 | 7 | return ColumnIdResult(std::move(column_ids), std::move(filter_column_ids)); |
496 | 7 | } |
497 | | |
498 | 18 | std::string ParquetReader::_selected_leaf_column_paths() const { |
499 | 18 | if (_file_metadata == nullptr) { |
500 | 0 | return ""; |
501 | 0 | } |
502 | | |
503 | 18 | std::vector<std::string> leaf_paths; |
504 | 18 | auto schema_desc = _file_metadata->schema(); |
505 | 18 | std::function<void(const FieldSchema*, const std::string&)> collect = |
506 | 87 | [&](const FieldSchema* field, const std::string& path) { |
507 | 87 | if (!_column_ids.empty() && !_column_ids.contains(field->get_column_id())) { |
508 | 4 | return; |
509 | 4 | } |
510 | | |
511 | 83 | if (field->children.empty()) { |
512 | 70 | if (field->physical_column_index >= 0) { |
513 | 70 | leaf_paths.push_back(path); |
514 | 70 | } |
515 | 70 | return; |
516 | 70 | } |
517 | | |
518 | 28 | for (const auto& child : field->children) { |
519 | 28 | collect(&child, path + "." + child.name); |
520 | 28 | } |
521 | 13 | }; |
522 | | |
523 | 59 | for (const auto& read_col : _read_file_columns) { |
524 | 59 | const FieldSchema* field = schema_desc.get_column(read_col); |
525 | 59 | if (field != nullptr) { |
526 | 59 | collect(field, field->name); |
527 | 59 | } |
528 | 59 | } |
529 | | |
530 | 18 | std::sort(leaf_paths.begin(), leaf_paths.end()); |
531 | 18 | leaf_paths.erase(std::unique(leaf_paths.begin(), leaf_paths.end()), leaf_paths.end()); |
532 | | |
533 | 18 | std::stringstream result; |
534 | 88 | for (size_t i = 0; i < leaf_paths.size(); ++i) { |
535 | 70 | if (i != 0) { |
536 | 52 | result << ", "; |
537 | 52 | } |
538 | 70 | result << leaf_paths[i]; |
539 | 70 | } |
540 | 18 | return result.str(); |
541 | 18 | } |
542 | | |
543 | 66 | Status ParquetReader::_open_file_reader(ReaderInitContext* /*ctx*/) { |
544 | 66 | return _open_file(); |
545 | 66 | } |
546 | | |
547 | 66 | Status ParquetReader::_do_init_reader(ReaderInitContext* base_ctx) { |
548 | 66 | auto* ctx = checked_context_cast<ParquetInitContext>(base_ctx); |
549 | 66 | _col_name_to_block_idx = base_ctx->col_name_to_block_idx; |
550 | 66 | _tuple_descriptor = ctx->tuple_descriptor; |
551 | 66 | _row_descriptor = ctx->row_descriptor; |
552 | 66 | _colname_to_slot_id = ctx->colname_to_slot_id; |
553 | 66 | _not_single_slot_filter_conjuncts = ctx->not_single_slot_filter_conjuncts; |
554 | 66 | _slot_id_to_filter_conjuncts = ctx->slot_id_to_filter_conjuncts; |
555 | 66 | _filter_groups = ctx->filter_groups; |
556 | 66 | _table_info_node_ptr = base_ctx->table_info_node; |
557 | 66 | _column_ids = base_ctx->column_ids; |
558 | 66 | _filter_column_ids = base_ctx->filter_column_ids; |
559 | | |
560 | | // _open_file_reader (called by init_reader NVI before hooks) must have opened the file. |
561 | 66 | DCHECK(_file_metadata != nullptr) |
562 | 0 | << "ParquetReader::_do_init_reader called without _open_file_reader"; |
563 | 66 | _t_metadata = &(_file_metadata->to_thrift()); |
564 | | |
565 | 66 | SCOPED_RAW_TIMER(&_reader_statistics.parse_meta_time); |
566 | 66 | _total_groups = _t_metadata->row_groups.size(); |
567 | 66 | if (_total_groups == 0) { |
568 | 0 | return Status::EndOfFile("init reader failed, empty parquet file: " + _scan_range.path); |
569 | 0 | } |
570 | 66 | _current_row_group_index = RowGroupReader::RowGroupIndex {-1, 0, 0}; |
571 | | |
572 | | // Compute missing columns and file↔table column mapping. |
573 | | // This runs in _do_init_reader (not on_before_init_reader) because table-format readers |
574 | | // (Iceberg, Paimon, Hive, Hudi) override on_before_init_reader completely. |
575 | 66 | if (has_column_descs()) { |
576 | 24 | _fill_missing_cols.clear(); |
577 | 24 | _fill_missing_defaults.clear(); |
578 | 74 | for (const auto& col_name : base_ctx->column_names) { |
579 | 74 | if (!_table_info_node_ptr->children_column_exists(col_name)) { |
580 | 5 | _fill_missing_cols.insert(col_name); |
581 | 5 | } |
582 | 74 | } |
583 | 24 | if (_column_descs && !_fill_missing_cols.empty()) { |
584 | 13 | for (const auto& desc : *_column_descs) { |
585 | 13 | if (_fill_missing_cols.contains(desc.name) && |
586 | 13 | !_fill_partition_values.contains(desc.name)) { |
587 | 0 | _fill_missing_defaults[desc.name] = desc.default_expr; |
588 | 0 | } |
589 | 13 | } |
590 | 5 | } |
591 | 24 | } |
592 | | // Resolve file-column ↔ table-column mapping in file-schema order. |
593 | | // _init_read_columns handles both normal path (missing cols populated above) |
594 | | // and standalone path (_fill_missing_cols empty, _table_info_node_ptr may be null). |
595 | 66 | _init_read_columns(base_ctx->column_names); |
596 | 66 | if (_profile != nullptr) { |
597 | 18 | _profile->add_info_string("ParquetReadColumnPaths", _selected_leaf_column_paths()); |
598 | 18 | } |
599 | | |
600 | | // build column predicates for column lazy read |
601 | 66 | if (ctx->conjuncts != nullptr) { |
602 | 66 | _lazy_read_ctx.conjuncts = *ctx->conjuncts; |
603 | 66 | } |
604 | 66 | if (ctx->slot_id_to_predicates != nullptr) { |
605 | 66 | _lazy_read_ctx.slot_id_to_predicates = *ctx->slot_id_to_predicates; |
606 | 66 | } |
607 | | |
608 | | // ---- Inlined set_fill_columns logic (partition/missing/synthesized classification) ---- |
609 | | |
610 | | // 1. Collect predicate columns from conjuncts for lazy materialization |
611 | 66 | std::unordered_map<std::string, std::pair<uint32_t, int>> predicate_columns; |
612 | 66 | _collect_predicate_columns_from_conjuncts(predicate_columns); |
613 | | |
614 | | // 2. Classify read/partition/missing/synthesized columns into lazy vs predicate groups |
615 | 66 | _classify_columns_for_lazy_read(predicate_columns, _fill_partition_values, |
616 | 66 | _fill_missing_defaults); |
617 | | |
618 | | // 3. Populate col_names vectors for ColumnProcessor path |
619 | 66 | for (auto& kv : _lazy_read_ctx.predicate_partition_columns) { |
620 | 5 | _lazy_read_ctx.predicate_partition_col_names.emplace_back(kv.first); |
621 | 5 | } |
622 | 66 | for (auto& kv : _lazy_read_ctx.predicate_missing_columns) { |
623 | 0 | _lazy_read_ctx.predicate_missing_col_names.emplace_back(kv.first); |
624 | 0 | } |
625 | 66 | for (auto& kv : _lazy_read_ctx.partition_columns) { |
626 | 3 | _lazy_read_ctx.partition_col_names.emplace_back(kv.first); |
627 | 3 | } |
628 | 66 | for (auto& kv : _lazy_read_ctx.missing_columns) { |
629 | 0 | _lazy_read_ctx.missing_col_names.emplace_back(kv.first); |
630 | 0 | } |
631 | | |
632 | 66 | if (_filter_groups && (_total_groups == 0 || _t_metadata->num_rows == 0 || _range_size < 0)) { |
633 | 0 | return Status::EndOfFile("No row group to read"); |
634 | 0 | } |
635 | | |
636 | 66 | return Status::OK(); |
637 | 66 | } |
638 | | |
639 | 66 | void ParquetReader::_init_read_columns(const std::vector<std::string>& column_names) { |
640 | | // Build file_col_name → table_col_name map, skipping missing columns. |
641 | | // Must iterate file schema in physical order so that _generate_random_access_ranges |
642 | | // sees monotonically increasing chunk offsets. |
643 | 66 | auto schema_desc = _file_metadata->schema(); |
644 | 66 | std::map<std::string, std::string> required_file_columns; |
645 | 422 | for (const auto& col_name : column_names) { |
646 | 422 | if (_fill_missing_cols.contains(col_name)) { |
647 | 5 | continue; |
648 | 5 | } |
649 | 417 | std::string file_col = col_name; |
650 | 417 | if (_table_info_node_ptr && _table_info_node_ptr->children_column_exists(col_name)) { |
651 | 417 | file_col = _table_info_node_ptr->children_file_column_name(col_name); |
652 | 417 | } |
653 | 417 | required_file_columns[file_col] = col_name; |
654 | 417 | } |
655 | 725 | for (int i = 0; i < schema_desc.size(); ++i) { |
656 | 659 | const auto& name = schema_desc.get_column(i)->name; |
657 | 659 | if (required_file_columns.contains(name)) { |
658 | 417 | _read_file_columns.emplace_back(name); |
659 | 417 | _read_table_columns.emplace_back(required_file_columns[name]); |
660 | 417 | _read_table_columns_set.insert(required_file_columns[name]); |
661 | 417 | } |
662 | 659 | } |
663 | 66 | } |
664 | | |
665 | 0 | bool ParquetReader::_exists_in_file(const std::string& expr_name) const { |
666 | | // `_read_table_columns_set` is used to ensure that only columns actually read are subject to min-max filtering. |
667 | | // This primarily handles cases where partition columns also exist in a file. The reason it's not modified |
668 | | // in `_table_info_node_ptr` is that Iceberg、Hudi has inconsistent requirements for this node; |
669 | | // Iceberg partition evolution need read partition columns from a file. |
670 | | // hudi set `hoodie.datasource.write.drop.partition.columns=false` not need read partition columns from a file. |
671 | 0 | return _table_info_node_ptr->children_column_exists(expr_name) && |
672 | 0 | _read_table_columns_set.contains(expr_name); |
673 | 0 | } |
674 | | |
675 | 0 | bool ParquetReader::_type_matches(const int cid) const { |
676 | 0 | auto* slot = _tuple_descriptor->slots()[cid]; |
677 | 0 | auto table_col_type = remove_nullable(slot->type()); |
678 | |
|
679 | 0 | const auto& file_col_name = _table_info_node_ptr->children_file_column_name(slot->col_name()); |
680 | 0 | const auto& file_col_type = |
681 | 0 | remove_nullable(_file_metadata->schema().get_column(file_col_name)->data_type); |
682 | |
|
683 | 0 | return (table_col_type->get_primitive_type() == file_col_type->get_primitive_type()) && |
684 | 0 | !is_complex_type(table_col_type->get_primitive_type()); |
685 | 0 | } |
686 | | |
687 | | void ParquetReader::_collect_predicate_columns_from_conjuncts( |
688 | 66 | std::unordered_map<std::string, std::pair<uint32_t, int>>& predicate_columns) { |
689 | 66 | std::function<void(VExpr * expr)> visit_slot = [&](VExpr* expr) { |
690 | 39 | if (expr->is_slot_ref()) { |
691 | 13 | VSlotRef* slot_ref = static_cast<VSlotRef*>(expr); |
692 | 13 | auto expr_name = slot_ref->expr_name(); |
693 | 13 | predicate_columns.emplace(expr_name, |
694 | 13 | std::make_pair(slot_ref->column_id(), slot_ref->slot_id())); |
695 | 13 | if (slot_ref->column_id() == 0) { |
696 | 3 | _lazy_read_ctx.resize_first_column = false; |
697 | 3 | } |
698 | 13 | return; |
699 | 13 | } |
700 | 26 | for (auto& child : expr->children()) { |
701 | 26 | visit_slot(child.get()); |
702 | 26 | } |
703 | 26 | }; |
704 | | |
705 | 66 | for (const auto& conjunct : _lazy_read_ctx.conjuncts) { |
706 | 13 | auto expr = conjunct->root(); |
707 | 13 | if (expr->is_rf_wrapper()) { |
708 | 0 | VRuntimeFilterWrapper* runtime_filter = assert_cast<VRuntimeFilterWrapper*>(expr.get()); |
709 | 0 | auto filter_impl = runtime_filter->get_impl(); |
710 | 0 | visit_slot(filter_impl.get()); |
711 | 13 | } else { |
712 | 13 | visit_slot(expr.get()); |
713 | 13 | } |
714 | 13 | } |
715 | | |
716 | 66 | if (!_lazy_read_ctx.slot_id_to_predicates.empty()) { |
717 | 0 | auto and_pred = AndBlockColumnPredicate::create_unique(); |
718 | 0 | for (const auto& entry : _lazy_read_ctx.slot_id_to_predicates) { |
719 | 0 | for (const auto& pred : entry.second) { |
720 | | // Parquet shares _push_down_predicates for row-group/page min-max pruning and |
721 | | // bloom-filter evaluation, so this flag currently gates both predicate paths. |
722 | 0 | if (!has_column_optimization(pred->col_name(), ColumnOptimizationTypes::MIN_MAX)) { |
723 | 0 | continue; |
724 | 0 | } |
725 | 0 | if (!_exists_in_file(pred->col_name()) || !_type_matches(pred->column_id())) { |
726 | 0 | continue; |
727 | 0 | } |
728 | 0 | and_pred->add_column_predicate( |
729 | 0 | SingleColumnBlockPredicate::create_unique(pred->clone(pred->column_id()))); |
730 | 0 | } |
731 | 0 | } |
732 | 0 | if (and_pred->num_of_column_predicate() > 0) { |
733 | 0 | _push_down_predicates.push_back(std::move(and_pred)); |
734 | 0 | } |
735 | 0 | } |
736 | 66 | } |
737 | | |
738 | | void ParquetReader::_classify_columns_for_lazy_read( |
739 | | const std::unordered_map<std::string, std::pair<uint32_t, int>>& |
740 | | predicate_conjuncts_columns, |
741 | | const std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>& |
742 | | partition_columns, |
743 | 66 | const std::unordered_map<std::string, VExprContextSPtr>& missing_columns) { |
744 | 66 | const FieldDescriptor& schema = _file_metadata->schema(); |
745 | 66 | auto predicate_columns = predicate_conjuncts_columns; |
746 | | #ifndef BE_TEST |
747 | | for (const auto& [col_name, _] : _generated_col_handlers) { |
748 | | int slot_id = -1; |
749 | | for (auto slot : _tuple_descriptor->slots()) { |
750 | | if (slot->col_name() == col_name) { |
751 | | slot_id = slot->id(); |
752 | | break; |
753 | | } |
754 | | } |
755 | | DCHECK(slot_id != -1) << "slot id should not be -1 for generated column: " << col_name; |
756 | | auto column_index = _row_descriptor->get_column_id(slot_id); |
757 | | if (column_index == 0) { |
758 | | _lazy_read_ctx.resize_first_column = false; |
759 | | } |
760 | | // assume generated columns are only used for predicate push down. |
761 | | predicate_columns.emplace(col_name, std::make_pair(column_index, slot_id)); |
762 | | } |
763 | | |
764 | | for (const auto& [col_name, _] : _synthesized_col_handlers) { |
765 | | int slot_id = -1; |
766 | | for (auto slot : _tuple_descriptor->slots()) { |
767 | | if (slot->col_name() == col_name) { |
768 | | slot_id = slot->id(); |
769 | | break; |
770 | | } |
771 | | } |
772 | | DCHECK(slot_id != -1) << "slot id should not be -1 for synthesized column: " << col_name; |
773 | | auto column_index = _row_descriptor->get_column_id(slot_id); |
774 | | if (column_index == 0) { |
775 | | _lazy_read_ctx.resize_first_column = false; |
776 | | } |
777 | | // synthesized columns always fill data on first phase. |
778 | | _lazy_read_ctx.all_predicate_col_ids.emplace_back(column_index); |
779 | | } |
780 | | #endif |
781 | 417 | for (auto& read_table_col : _read_table_columns) { |
782 | 417 | _lazy_read_ctx.all_read_columns.emplace_back(read_table_col); |
783 | | |
784 | 417 | auto file_column_name = _table_info_node_ptr->children_file_column_name(read_table_col); |
785 | 417 | PrimitiveType column_type = |
786 | 417 | schema.get_column(file_column_name)->data_type->get_primitive_type(); |
787 | 417 | if (is_complex_type(column_type)) { |
788 | 2 | _lazy_read_ctx.has_complex_type = true; |
789 | 2 | } |
790 | 417 | if (predicate_columns.size() > 0) { |
791 | 12 | auto iter = predicate_columns.find(read_table_col); |
792 | 12 | if (iter == predicate_columns.end()) { |
793 | 4 | _lazy_read_ctx.lazy_read_columns.emplace_back(read_table_col); |
794 | 8 | } else { |
795 | 8 | _lazy_read_ctx.predicate_columns.first.emplace_back(iter->first); |
796 | 8 | _lazy_read_ctx.predicate_columns.second.emplace_back(iter->second.second); |
797 | 8 | _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first); |
798 | 8 | } |
799 | 12 | } |
800 | 417 | } |
801 | | |
802 | 66 | for (auto& kv : partition_columns) { |
803 | 5 | auto iter = predicate_columns.find(kv.first); |
804 | 5 | if (iter == predicate_columns.end()) { |
805 | 0 | _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second); |
806 | 5 | } else { |
807 | 5 | _lazy_read_ctx.predicate_partition_columns.emplace(kv.first, kv.second); |
808 | 5 | _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first); |
809 | 5 | } |
810 | 5 | } |
811 | | |
812 | 66 | for (auto& kv : missing_columns) { |
813 | 0 | auto iter = predicate_columns.find(kv.first); |
814 | 0 | if (iter != predicate_columns.end()) { |
815 | | //For check missing column : missing column == xx, missing column is null,missing column is not null. |
816 | 0 | if (_slot_id_to_filter_conjuncts->find(iter->second.second) != |
817 | 0 | _slot_id_to_filter_conjuncts->end()) { |
818 | 0 | for (auto& ctx : _slot_id_to_filter_conjuncts->find(iter->second.second)->second) { |
819 | 0 | _lazy_read_ctx.missing_columns_conjuncts.emplace_back(ctx); |
820 | 0 | } |
821 | 0 | } |
822 | 0 | _lazy_read_ctx.predicate_missing_columns.emplace(kv.first, kv.second); |
823 | 0 | _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first); |
824 | 0 | } else { |
825 | 0 | _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second); |
826 | 0 | } |
827 | 0 | } |
828 | | |
829 | 66 | if (_enable_lazy_mat && _lazy_read_ctx.predicate_columns.first.size() > 0 && |
830 | 66 | _lazy_read_ctx.lazy_read_columns.size() > 0) { |
831 | 2 | _lazy_read_ctx.can_lazy_read = true; |
832 | 2 | } |
833 | | |
834 | 66 | if (!_lazy_read_ctx.can_lazy_read) { |
835 | 64 | for (auto& kv : _lazy_read_ctx.predicate_partition_columns) { |
836 | 3 | _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second); |
837 | 3 | } |
838 | 64 | for (auto& kv : _lazy_read_ctx.predicate_missing_columns) { |
839 | 0 | _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second); |
840 | 0 | } |
841 | 64 | } |
842 | 66 | } |
843 | | |
844 | | // init file reader and file metadata for parsing schema |
845 | 0 | Status ParquetReader::init_schema_reader() { |
846 | 0 | RETURN_IF_ERROR(_open_file()); |
847 | 0 | _t_metadata = &(_file_metadata->to_thrift()); |
848 | 0 | return Status::OK(); |
849 | 0 | } |
850 | | |
851 | | Status ParquetReader::get_parsed_schema(std::vector<std::string>* col_names, |
852 | 0 | std::vector<DataTypePtr>* col_types) { |
853 | 0 | _total_groups = _t_metadata->row_groups.size(); |
854 | 0 | auto schema_desc = _file_metadata->schema(); |
855 | 0 | for (int i = 0; i < schema_desc.size(); ++i) { |
856 | | // Get the Column Reader for the boolean column |
857 | 0 | col_names->emplace_back(schema_desc.get_column(i)->name); |
858 | 0 | col_types->emplace_back(make_nullable(schema_desc.get_column(i)->data_type)); |
859 | 0 | } |
860 | 0 | return Status::OK(); |
861 | 0 | } |
862 | | |
863 | | Status ParquetReader::_get_columns_impl( |
864 | 14 | std::unordered_map<std::string, DataTypePtr>* name_to_type) { |
865 | 14 | const auto& schema_desc = _file_metadata->schema(); |
866 | 14 | std::unordered_set<std::string> column_names; |
867 | 14 | schema_desc.get_column_names(&column_names); |
868 | 210 | for (auto& name : column_names) { |
869 | 210 | auto field = schema_desc.get_column(name); |
870 | 210 | name_to_type->emplace(name, field->data_type); |
871 | 210 | } |
872 | 14 | return Status::OK(); |
873 | 14 | } |
874 | | |
875 | 98 | Status ParquetReader::_do_get_next_block(Block* block, size_t* read_rows, bool* eof) { |
876 | 98 | if (_current_group_reader == nullptr || _row_group_eof) { |
877 | 38 | Status st = _next_row_group_reader(); |
878 | 38 | if (!st.ok() && !st.is<ErrorCode::END_OF_FILE>()) { |
879 | 0 | return st; |
880 | 0 | } |
881 | 38 | if (_current_group_reader == nullptr || _row_group_eof || st.is<ErrorCode::END_OF_FILE>()) { |
882 | 0 | _current_group_reader.reset(nullptr); |
883 | 0 | _row_group_eof = true; |
884 | 0 | *read_rows = 0; |
885 | 0 | *eof = true; |
886 | 0 | return Status::OK(); |
887 | 0 | } |
888 | 38 | } |
889 | | |
890 | | // Limit memory per batch for load paths. |
891 | | // _load_bytes_per_row is updated after each batch so the *next* call pre-shrinks _batch_size |
892 | | // before reading, ensuring the current batch is already within the limit (from call 2 onward). |
893 | 98 | const int64_t max_block_bytes = |
894 | 98 | (_state != nullptr && _state->query_type() == TQueryType::LOAD && |
895 | 98 | config::load_reader_max_block_bytes > 0) |
896 | 98 | ? config::load_reader_max_block_bytes |
897 | 98 | : 0; |
898 | 98 | if (max_block_bytes > 0 && _load_bytes_per_row > 0) { |
899 | 0 | _batch_size = std::max((size_t)1, |
900 | 0 | (size_t)((int64_t)max_block_bytes / (int64_t)_load_bytes_per_row)); |
901 | 0 | } |
902 | | |
903 | 98 | SCOPED_RAW_TIMER(&_reader_statistics.column_read_time); |
904 | 98 | Status batch_st = |
905 | 98 | _current_group_reader->next_batch(block, _batch_size, read_rows, &_row_group_eof); |
906 | 98 | if (batch_st.is<ErrorCode::END_OF_FILE>()) { |
907 | 0 | block->clear_column_data(); |
908 | 0 | _current_group_reader.reset(nullptr); |
909 | 0 | *read_rows = 0; |
910 | 0 | *eof = true; |
911 | 0 | return Status::OK(); |
912 | 0 | } |
913 | | |
914 | 98 | if (!batch_st.ok()) { |
915 | 0 | return Status::InternalError("Read parquet file {} failed, reason = {}", _scan_range.path, |
916 | 0 | batch_st.to_string()); |
917 | 0 | } |
918 | | |
919 | 98 | if (max_block_bytes > 0 && *read_rows > 0) { |
920 | 0 | _load_bytes_per_row = block->bytes() / *read_rows; |
921 | 0 | } |
922 | | |
923 | 98 | if (_row_group_eof) { |
924 | 38 | auto column_st = _current_group_reader->merged_column_statistics(); |
925 | 38 | _column_statistics.merge(column_st); |
926 | 38 | _reader_statistics.lazy_read_filtered_rows += |
927 | 38 | _current_group_reader->lazy_read_filtered_rows(); |
928 | 38 | _reader_statistics.predicate_filter_time += _current_group_reader->predicate_filter_time(); |
929 | 38 | _reader_statistics.dict_filter_rewrite_time += |
930 | 38 | _current_group_reader->dict_filter_rewrite_time(); |
931 | 38 | if (_io_ctx) { |
932 | 15 | _io_ctx->condition_cache_filtered_rows += |
933 | 15 | _current_group_reader->condition_cache_filtered_rows(); |
934 | 15 | } |
935 | | |
936 | 38 | if (_current_row_group_index.row_group_id + 1 == _total_groups) { |
937 | 37 | *eof = true; |
938 | 37 | } else { |
939 | 1 | *eof = false; |
940 | 1 | } |
941 | 38 | } |
942 | 98 | return Status::OK(); |
943 | 98 | } |
944 | | |
945 | | RowGroupReader::PositionDeleteContext ParquetReader::_get_position_delete_ctx( |
946 | 38 | const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index) { |
947 | 38 | if (_delete_rows == nullptr) { |
948 | 38 | return RowGroupReader::PositionDeleteContext(row_group.num_rows, row_group_index.first_row); |
949 | 38 | } |
950 | 0 | const int64_t* delete_rows = &(*_delete_rows)[0]; |
951 | 0 | const int64_t* delete_rows_end = delete_rows + _delete_rows->size(); |
952 | 0 | const int64_t* start_pos = std::lower_bound(delete_rows + _delete_rows_index, delete_rows_end, |
953 | 0 | row_group_index.first_row); |
954 | 0 | int64_t start_index = start_pos - delete_rows; |
955 | 0 | const int64_t* end_pos = std::lower_bound(start_pos, delete_rows_end, row_group_index.last_row); |
956 | 0 | int64_t end_index = end_pos - delete_rows; |
957 | 0 | _delete_rows_index = end_index; |
958 | 0 | return RowGroupReader::PositionDeleteContext(*_delete_rows, row_group.num_rows, |
959 | 0 | row_group_index.first_row, start_index, end_index); |
960 | 38 | } |
961 | | |
962 | 38 | Status ParquetReader::_next_row_group_reader() { |
963 | 38 | if (_current_group_reader != nullptr) { |
964 | 1 | _current_group_reader->collect_profile_before_close(); |
965 | 1 | } |
966 | | |
967 | 38 | RowRanges candidate_row_ranges; |
968 | 38 | while (++_current_row_group_index.row_group_id < _total_groups) { |
969 | 38 | const auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id]; |
970 | 38 | _current_row_group_index.first_row = _current_row_group_index.last_row; |
971 | 38 | _current_row_group_index.last_row = _current_row_group_index.last_row + row_group.num_rows; |
972 | | |
973 | 38 | if (_filter_groups && _is_misaligned_range_group(row_group)) { |
974 | 0 | continue; |
975 | 0 | } |
976 | | |
977 | 38 | candidate_row_ranges.clear(); |
978 | | // The range of lines to be read is determined by the push down predicate. |
979 | 38 | RETURN_IF_ERROR(_process_min_max_bloom_filter( |
980 | 38 | _current_row_group_index, row_group, _push_down_predicates, &candidate_row_ranges)); |
981 | | |
982 | 38 | std::function<int64_t(const FieldSchema*)> column_compressed_size = |
983 | 138 | [&row_group, &column_compressed_size](const FieldSchema* field) -> int64_t { |
984 | 138 | if (field->physical_column_index >= 0) { |
985 | 124 | int parquet_col_id = field->physical_column_index; |
986 | 124 | if (row_group.columns[parquet_col_id].__isset.meta_data) { |
987 | 124 | return row_group.columns[parquet_col_id].meta_data.total_compressed_size; |
988 | 124 | } |
989 | 0 | return 0; |
990 | 124 | } |
991 | 14 | int64_t size = 0; |
992 | 30 | for (const FieldSchema& child : field->children) { |
993 | 30 | size += column_compressed_size(&child); |
994 | 30 | } |
995 | 14 | return size; |
996 | 138 | }; |
997 | 38 | int64_t group_size = 0; // only calculate the needed columns |
998 | 108 | for (auto& read_col : _read_file_columns) { |
999 | 108 | const FieldSchema* field = _file_metadata->schema().get_column(read_col); |
1000 | 108 | group_size += column_compressed_size(field); |
1001 | 108 | } |
1002 | | |
1003 | 38 | _reader_statistics.read_rows += candidate_row_ranges.count(); |
1004 | 38 | if (_io_ctx) { |
1005 | 15 | _io_ctx->file_reader_stats->read_rows += candidate_row_ranges.count(); |
1006 | 15 | } |
1007 | | |
1008 | 38 | if (candidate_row_ranges.count() != 0) { |
1009 | | // need read this row group. |
1010 | 38 | _reader_statistics.read_row_groups++; |
1011 | 38 | _reader_statistics.filtered_page_rows += |
1012 | 38 | row_group.num_rows - candidate_row_ranges.count(); |
1013 | 38 | break; |
1014 | 38 | } else { |
1015 | | // this row group be filtered. |
1016 | 0 | _reader_statistics.filtered_row_groups++; |
1017 | 0 | _reader_statistics.filtered_bytes += group_size; |
1018 | 0 | _reader_statistics.filtered_group_rows += row_group.num_rows; |
1019 | 0 | } |
1020 | 38 | } |
1021 | | |
1022 | 38 | if (_current_row_group_index.row_group_id == _total_groups) { |
1023 | 0 | _row_group_eof = true; |
1024 | 0 | _current_group_reader.reset(nullptr); |
1025 | 0 | return Status::EndOfFile("No next RowGroupReader"); |
1026 | 0 | } |
1027 | | |
1028 | | // process page index and generate the ranges to read |
1029 | 38 | auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id]; |
1030 | | |
1031 | 38 | RowGroupReader::PositionDeleteContext position_delete_ctx = |
1032 | 38 | _get_position_delete_ctx(row_group, _current_row_group_index); |
1033 | 38 | io::FileReaderSPtr group_file_reader; |
1034 | 38 | if (typeid_cast<io::InMemoryFileReader*>(_file_reader.get())) { |
1035 | | // InMemoryFileReader has the ability to merge small IO |
1036 | 0 | group_file_reader = _file_reader; |
1037 | 38 | } else { |
1038 | 38 | size_t avg_io_size = 0; |
1039 | 38 | const std::vector<io::PrefetchRange> io_ranges = |
1040 | 38 | _generate_random_access_ranges(_current_row_group_index, &avg_io_size); |
1041 | 38 | int64_t merged_read_slice_size = -1; |
1042 | 38 | if (_state != nullptr && _state->query_options().__isset.merge_read_slice_size) { |
1043 | 26 | merged_read_slice_size = _state->query_options().merge_read_slice_size; |
1044 | 26 | } |
1045 | | // The underlying page reader will prefetch data in column. |
1046 | | // Using both MergeRangeFileReader and BufferedStreamReader simultaneously would waste a lot of memory. |
1047 | 38 | group_file_reader = |
1048 | 38 | avg_io_size < io::MergeRangeFileReader::SMALL_IO |
1049 | 38 | ? std::make_shared<io::MergeRangeFileReader>( |
1050 | 38 | _profile, _file_reader, io_ranges, merged_read_slice_size) |
1051 | 38 | : _file_reader; |
1052 | 38 | } |
1053 | 38 | _current_group_reader.reset(new RowGroupReader( |
1054 | 38 | _io_ctx ? std::make_shared<io::TracingFileReader>(group_file_reader, |
1055 | 15 | _io_ctx->file_reader_stats) |
1056 | 38 | : group_file_reader, |
1057 | 38 | _read_table_columns, _current_row_group_index.row_group_id, row_group, _ctz, _io_ctx, |
1058 | 38 | position_delete_ctx, _lazy_read_ctx, _state, _column_ids, _filter_column_ids)); |
1059 | 38 | _row_group_eof = false; |
1060 | | |
1061 | 38 | _current_group_reader->set_current_row_group_idx(_current_row_group_index); |
1062 | 38 | _current_group_reader->set_col_name_to_block_idx(_col_name_to_block_idx); |
1063 | 38 | if (_condition_cache_ctx) { |
1064 | 0 | _current_group_reader->set_condition_cache_context(_condition_cache_ctx); |
1065 | 0 | } |
1066 | 38 | _current_group_reader->set_table_format_reader(this); |
1067 | | |
1068 | 38 | _current_group_reader->_table_info_node_ptr = _table_info_node_ptr; |
1069 | 38 | return _current_group_reader->init(_file_metadata->schema(), candidate_row_ranges, _col_offsets, |
1070 | 38 | _tuple_descriptor, _row_descriptor, _colname_to_slot_id, |
1071 | 38 | _not_single_slot_filter_conjuncts, |
1072 | 38 | _slot_id_to_filter_conjuncts); |
1073 | 38 | } |
1074 | | |
1075 | | std::vector<io::PrefetchRange> ParquetReader::_generate_random_access_ranges( |
1076 | 38 | const RowGroupReader::RowGroupIndex& group, size_t* avg_io_size) { |
1077 | 38 | std::vector<io::PrefetchRange> result; |
1078 | 38 | int64_t last_chunk_end = -1; |
1079 | 38 | size_t total_io_size = 0; |
1080 | 38 | std::function<void(const FieldSchema*, const tparquet::RowGroup&)> scalar_range = |
1081 | 136 | [&](const FieldSchema* field, const tparquet::RowGroup& row_group) { |
1082 | 136 | if (_column_ids.empty() || |
1083 | 136 | _column_ids.find(field->get_column_id()) != _column_ids.end()) { |
1084 | 132 | if (field->data_type->get_primitive_type() == TYPE_ARRAY) { |
1085 | 2 | scalar_range(&field->children[0], row_group); |
1086 | 130 | } else if (field->data_type->get_primitive_type() == TYPE_MAP) { |
1087 | 0 | scalar_range(&field->children[0], row_group); |
1088 | 0 | scalar_range(&field->children[1], row_group); |
1089 | 130 | } else if (field->data_type->get_primitive_type() == TYPE_STRUCT || |
1090 | 130 | field->data_type->get_primitive_type() == TYPE_VARIANT) { |
1091 | 37 | for (int i = 0; i < field->children.size(); ++i) { |
1092 | 26 | scalar_range(&field->children[i], row_group); |
1093 | 26 | } |
1094 | 119 | } else { |
1095 | 119 | const tparquet::ColumnChunk& chunk = |
1096 | 119 | row_group.columns[field->physical_column_index]; |
1097 | 119 | auto& chunk_meta = chunk.meta_data; |
1098 | 119 | int64_t chunk_start = has_dict_page(chunk_meta) |
1099 | 119 | ? chunk_meta.dictionary_page_offset |
1100 | 119 | : chunk_meta.data_page_offset; |
1101 | 119 | int64_t chunk_end = chunk_start + chunk_meta.total_compressed_size; |
1102 | 119 | DCHECK_GE(chunk_start, last_chunk_end); |
1103 | 119 | result.emplace_back(chunk_start, chunk_end); |
1104 | 119 | total_io_size += chunk_meta.total_compressed_size; |
1105 | 119 | last_chunk_end = chunk_end; |
1106 | 119 | } |
1107 | 132 | } |
1108 | 136 | }; |
1109 | 38 | const tparquet::RowGroup& row_group = _t_metadata->row_groups[group.row_group_id]; |
1110 | 108 | for (const auto& read_col : _read_file_columns) { |
1111 | 108 | const FieldSchema* field = _file_metadata->schema().get_column(read_col); |
1112 | 108 | scalar_range(field, row_group); |
1113 | 108 | } |
1114 | 38 | if (!result.empty()) { |
1115 | 37 | *avg_io_size = total_io_size / result.size(); |
1116 | 37 | } |
1117 | 38 | return result; |
1118 | 38 | } |
1119 | | |
1120 | 37 | bool ParquetReader::_is_misaligned_range_group(const tparquet::RowGroup& row_group) const { |
1121 | 37 | int64_t start_offset = _get_column_start_offset(row_group.columns[0].meta_data); |
1122 | | |
1123 | 37 | auto& last_column = row_group.columns[row_group.columns.size() - 1].meta_data; |
1124 | 37 | int64_t end_offset = _get_column_start_offset(last_column) + last_column.total_compressed_size; |
1125 | | |
1126 | 37 | int64_t row_group_mid = start_offset + (end_offset - start_offset) / 2; |
1127 | 37 | if (!(row_group_mid >= _range_start_offset && |
1128 | 37 | row_group_mid < _range_start_offset + _range_size)) { |
1129 | 0 | return true; |
1130 | 0 | } |
1131 | 37 | return false; |
1132 | 37 | } |
1133 | | |
1134 | 0 | int64_t ParquetReader::get_total_rows() const { |
1135 | 0 | if (!_t_metadata) return 0; |
1136 | 0 | if (!_filter_groups) return _t_metadata->num_rows; |
1137 | 0 | int64_t total = 0; |
1138 | 0 | for (const auto& rg : _t_metadata->row_groups) { |
1139 | 0 | if (!_is_misaligned_range_group(rg)) { |
1140 | 0 | total += rg.num_rows; |
1141 | 0 | } |
1142 | 0 | } |
1143 | 0 | return total; |
1144 | 0 | } |
1145 | | |
1146 | 0 | void ParquetReader::set_condition_cache_context(std::shared_ptr<ConditionCacheContext> ctx) { |
1147 | 0 | _condition_cache_ctx = std::move(ctx); |
1148 | 0 | if (!_condition_cache_ctx || !_t_metadata || !_filter_groups) { |
1149 | 0 | return; |
1150 | 0 | } |
1151 | | // Find the first assigned row group to compute base_granule. |
1152 | 0 | int64_t first_row = 0; |
1153 | 0 | for (const auto& rg : _t_metadata->row_groups) { |
1154 | 0 | if (!_is_misaligned_range_group(rg)) { |
1155 | 0 | _condition_cache_ctx->base_granule = first_row / ConditionCacheContext::GRANULE_SIZE; |
1156 | 0 | return; |
1157 | 0 | } |
1158 | 0 | first_row += rg.num_rows; |
1159 | 0 | } |
1160 | 0 | } |
1161 | | |
1162 | | Status ParquetReader::_process_page_index_filter( |
1163 | | const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index, |
1164 | | const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred, |
1165 | 18 | RowRanges* candidate_row_ranges) { |
1166 | 18 | if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) { |
1167 | 0 | return Status::EndOfFile("stop"); |
1168 | 0 | } |
1169 | | |
1170 | 18 | std::function<void()> read_whole_row_group = [&]() { |
1171 | 18 | candidate_row_ranges->add(RowRange {0, row_group.num_rows}); |
1172 | 18 | }; |
1173 | | |
1174 | | // Check if the page index is available and if it exists. |
1175 | 18 | PageIndex page_index; |
1176 | 18 | if (!config::enable_parquet_page_index || _colname_to_slot_id == nullptr || |
1177 | 18 | !page_index.check_and_get_page_index_ranges(row_group.columns)) { |
1178 | 18 | read_whole_row_group(); |
1179 | 18 | return Status::OK(); |
1180 | 18 | } |
1181 | | |
1182 | 0 | std::vector<int> parquet_col_ids; |
1183 | 0 | for (size_t idx = 0; idx < _read_table_columns.size(); idx++) { |
1184 | 0 | const auto& read_table_col = _read_table_columns[idx]; |
1185 | 0 | const auto& read_file_col = _read_file_columns[idx]; |
1186 | 0 | if (!_colname_to_slot_id->contains(read_table_col)) { |
1187 | 0 | continue; |
1188 | 0 | } |
1189 | 0 | auto* field = _file_metadata->schema().get_column(read_file_col); |
1190 | |
|
1191 | 0 | std::function<void(FieldSchema * field)> f = [&](FieldSchema* field) { |
1192 | 0 | if (!_column_ids.empty() && |
1193 | 0 | _column_ids.find(field->get_column_id()) == _column_ids.end()) { |
1194 | 0 | return; |
1195 | 0 | } |
1196 | | |
1197 | 0 | if (field->data_type->get_primitive_type() == TYPE_ARRAY) { |
1198 | 0 | f(&field->children[0]); |
1199 | 0 | } else if (field->data_type->get_primitive_type() == TYPE_MAP) { |
1200 | 0 | f(&field->children[0]); |
1201 | 0 | f(&field->children[1]); |
1202 | 0 | } else if (field->data_type->get_primitive_type() == TYPE_STRUCT || |
1203 | 0 | field->data_type->get_primitive_type() == TYPE_VARIANT) { |
1204 | 0 | for (int i = 0; i < field->children.size(); ++i) { |
1205 | 0 | f(&field->children[i]); |
1206 | 0 | } |
1207 | 0 | } else { |
1208 | 0 | int parquet_col_id = field->physical_column_index; |
1209 | 0 | if (parquet_col_id >= 0) { |
1210 | 0 | parquet_col_ids.push_back(parquet_col_id); |
1211 | 0 | } |
1212 | 0 | } |
1213 | 0 | }; |
1214 | |
|
1215 | 0 | f(field); |
1216 | 0 | } |
1217 | |
|
1218 | 0 | auto parse_offset_index = [&]() -> Status { |
1219 | 0 | std::vector<uint8_t> off_index_buff(page_index._offset_index_size); |
1220 | 0 | Slice res(off_index_buff.data(), page_index._offset_index_size); |
1221 | 0 | size_t bytes_read = 0; |
1222 | 0 | { |
1223 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time); |
1224 | 0 | RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._offset_index_start, res, |
1225 | 0 | &bytes_read, _io_ctx)); |
1226 | 0 | } |
1227 | 0 | _column_statistics.page_index_read_calls++; |
1228 | 0 | _col_offsets.clear(); |
1229 | |
|
1230 | 0 | for (auto parquet_col_id : parquet_col_ids) { |
1231 | 0 | auto& chunk = row_group.columns[parquet_col_id]; |
1232 | 0 | if (chunk.offset_index_length == 0) [[unlikely]] { |
1233 | 0 | continue; |
1234 | 0 | } |
1235 | 0 | tparquet::OffsetIndex offset_index; |
1236 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time); |
1237 | 0 | RETURN_IF_ERROR( |
1238 | 0 | page_index.parse_offset_index(chunk, off_index_buff.data(), &offset_index)); |
1239 | 0 | _col_offsets[parquet_col_id] = offset_index; |
1240 | 0 | } |
1241 | 0 | return Status::OK(); |
1242 | 0 | }; |
1243 | | |
1244 | | // from https://github.com/apache/doris/pull/55795 |
1245 | 0 | RETURN_IF_ERROR(parse_offset_index()); |
1246 | | |
1247 | | // Check if page index is needed for min-max filter. |
1248 | 0 | if (!_enable_filter_by_min_max || push_down_pred.empty()) { |
1249 | 0 | read_whole_row_group(); |
1250 | 0 | return Status::OK(); |
1251 | 0 | } |
1252 | | |
1253 | | // read column index. |
1254 | 0 | std::vector<uint8_t> col_index_buff(page_index._column_index_size); |
1255 | 0 | size_t bytes_read = 0; |
1256 | 0 | Slice result(col_index_buff.data(), page_index._column_index_size); |
1257 | 0 | { |
1258 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time); |
1259 | 0 | RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._column_index_start, result, |
1260 | 0 | &bytes_read, _io_ctx)); |
1261 | 0 | } |
1262 | 0 | _column_statistics.page_index_read_calls++; |
1263 | |
|
1264 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.page_index_filter_time); |
1265 | | |
1266 | | // Construct a cacheable page index structure to avoid repeatedly reading the page index of the same column. |
1267 | 0 | ParquetPredicate::CachedPageIndexStat cached_page_index; |
1268 | 0 | cached_page_index.ctz = _ctz; |
1269 | 0 | std::function<bool(ParquetPredicate::PageIndexStat**, int)> get_stat_func = |
1270 | 0 | [&](ParquetPredicate::PageIndexStat** ans, const int cid) -> bool { |
1271 | 0 | if (cached_page_index.stats.contains(cid)) { |
1272 | 0 | *ans = &cached_page_index.stats[cid]; |
1273 | 0 | return (*ans)->available; |
1274 | 0 | } |
1275 | 0 | cached_page_index.stats.emplace(cid, ParquetPredicate::PageIndexStat {}); |
1276 | 0 | auto& sig_stat = cached_page_index.stats[cid]; |
1277 | |
|
1278 | 0 | auto* slot = _tuple_descriptor->slots()[cid]; |
1279 | 0 | if (!_table_info_node_ptr->children_column_exists(slot->col_name())) { |
1280 | | // table column not exist in file, may be schema change. |
1281 | 0 | return false; |
1282 | 0 | } |
1283 | | |
1284 | 0 | const auto& file_col_name = |
1285 | 0 | _table_info_node_ptr->children_file_column_name(slot->col_name()); |
1286 | 0 | const FieldSchema* col_schema = _file_metadata->schema().get_column(file_col_name); |
1287 | 0 | int parquet_col_id = col_schema->physical_column_index; |
1288 | |
|
1289 | 0 | if (parquet_col_id < 0) { |
1290 | | // complex type, not support page index yet. |
1291 | 0 | return false; |
1292 | 0 | } |
1293 | 0 | if (!_col_offsets.contains(parquet_col_id)) { |
1294 | | // If the file contains partition columns and the query applies filters on those |
1295 | | // partition columns, then reading the page index is unnecessary. |
1296 | 0 | return false; |
1297 | 0 | } |
1298 | | |
1299 | 0 | auto& column_chunk = row_group.columns[parquet_col_id]; |
1300 | 0 | if (column_chunk.column_index_length == 0 || column_chunk.offset_index_length == 0) { |
1301 | | // column no page index. |
1302 | 0 | return false; |
1303 | 0 | } |
1304 | | |
1305 | 0 | tparquet::ColumnIndex column_index; |
1306 | 0 | { |
1307 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time); |
1308 | 0 | RETURN_IF_ERROR(page_index.parse_column_index(column_chunk, col_index_buff.data(), |
1309 | 0 | &column_index)); |
1310 | 0 | } |
1311 | 0 | const int64_t num_of_pages = column_index.null_pages.size(); |
1312 | 0 | if (num_of_pages <= 0) [[unlikely]] { |
1313 | | // no page. (maybe this row group no data.) |
1314 | 0 | return false; |
1315 | 0 | } |
1316 | 0 | DCHECK_EQ(column_index.min_values.size(), column_index.max_values.size()); |
1317 | 0 | if (!column_index.__isset.null_counts) { |
1318 | | // not set null or null counts; |
1319 | 0 | return false; |
1320 | 0 | } |
1321 | | |
1322 | 0 | auto& offset_index = _col_offsets[parquet_col_id]; |
1323 | 0 | const auto& page_locations = offset_index.page_locations; |
1324 | |
|
1325 | 0 | sig_stat.col_schema = col_schema; |
1326 | 0 | sig_stat.num_of_pages = num_of_pages; |
1327 | 0 | sig_stat.encoded_min_value = column_index.min_values; |
1328 | 0 | sig_stat.encoded_max_value = column_index.max_values; |
1329 | 0 | sig_stat.is_all_null.resize(num_of_pages); |
1330 | 0 | sig_stat.has_null.resize(num_of_pages); |
1331 | 0 | sig_stat.ranges.resize(num_of_pages); |
1332 | |
|
1333 | 0 | for (int page_id = 0; page_id < num_of_pages; page_id++) { |
1334 | 0 | sig_stat.is_all_null[page_id] = column_index.null_pages[page_id]; |
1335 | 0 | sig_stat.has_null[page_id] = column_index.null_counts[page_id] > 0; |
1336 | |
|
1337 | 0 | int64_t from = page_locations[page_id].first_row_index; |
1338 | 0 | int64_t to = 0; |
1339 | 0 | if (page_id == page_locations.size() - 1) { |
1340 | 0 | to = row_group_index.last_row; |
1341 | 0 | } else { |
1342 | 0 | to = page_locations[page_id + 1].first_row_index; |
1343 | 0 | } |
1344 | 0 | sig_stat.ranges[page_id] = RowRange {from, to}; |
1345 | 0 | } |
1346 | |
|
1347 | 0 | sig_stat.available = true; |
1348 | 0 | *ans = &sig_stat; |
1349 | 0 | return true; |
1350 | 0 | }; |
1351 | 0 | cached_page_index.row_group_range = {0, row_group.num_rows}; |
1352 | 0 | cached_page_index.get_stat_func = get_stat_func; |
1353 | |
|
1354 | 0 | candidate_row_ranges->add({0, row_group.num_rows}); |
1355 | 0 | for (const auto& predicate : push_down_pred) { |
1356 | 0 | RowRanges tmp_row_range; |
1357 | 0 | if (!predicate->evaluate_and(&cached_page_index, &tmp_row_range)) { |
1358 | | // no need read this row group. |
1359 | 0 | candidate_row_ranges->clear(); |
1360 | 0 | return Status::OK(); |
1361 | 0 | } |
1362 | 0 | RowRanges::ranges_intersection(*candidate_row_ranges, tmp_row_range, candidate_row_ranges); |
1363 | 0 | } |
1364 | 0 | return Status::OK(); |
1365 | 0 | } |
1366 | | |
1367 | | Status ParquetReader::_process_min_max_bloom_filter( |
1368 | | const RowGroupReader::RowGroupIndex& row_group_index, const tparquet::RowGroup& row_group, |
1369 | | const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred, |
1370 | 38 | RowRanges* row_ranges) { |
1371 | 38 | SCOPED_RAW_TIMER(&_reader_statistics.row_group_filter_time); |
1372 | 38 | if (!_filter_groups) { |
1373 | | // No row group filtering is needed; |
1374 | | // for example, Iceberg reads position delete files. |
1375 | 1 | row_ranges->add({0, row_group.num_rows}); |
1376 | 1 | return Status::OK(); |
1377 | 1 | } |
1378 | | |
1379 | 37 | if (_read_by_rows) { |
1380 | 19 | auto group_start = row_group_index.first_row; |
1381 | 19 | auto group_end = row_group_index.last_row; |
1382 | | |
1383 | 47 | while (!_row_ids.empty()) { |
1384 | 28 | auto v = _row_ids.front(); |
1385 | 28 | if (v < group_start) { |
1386 | 0 | continue; |
1387 | 28 | } else if (v < group_end) { |
1388 | 28 | row_ranges->add(RowRange {v - group_start, v - group_start + 1}); |
1389 | 28 | _row_ids.pop_front(); |
1390 | 28 | } else { |
1391 | 0 | break; |
1392 | 0 | } |
1393 | 28 | } |
1394 | 19 | } else { |
1395 | 18 | bool filter_this_row_group = false; |
1396 | 18 | bool filtered_by_min_max = false; |
1397 | 18 | bool filtered_by_bloom_filter = false; |
1398 | 18 | RETURN_IF_ERROR(_process_column_stat_filter(row_group, push_down_pred, |
1399 | 18 | &filter_this_row_group, &filtered_by_min_max, |
1400 | 18 | &filtered_by_bloom_filter)); |
1401 | | // Update statistics based on filter type |
1402 | 18 | if (filter_this_row_group) { |
1403 | 0 | if (filtered_by_min_max) { |
1404 | 0 | _reader_statistics.filtered_row_groups_by_min_max++; |
1405 | 0 | } |
1406 | 0 | if (filtered_by_bloom_filter) { |
1407 | 0 | _reader_statistics.filtered_row_groups_by_bloom_filter++; |
1408 | 0 | } |
1409 | 0 | } |
1410 | | |
1411 | 18 | if (!filter_this_row_group) { |
1412 | 18 | RETURN_IF_ERROR(_process_page_index_filter(row_group, row_group_index, push_down_pred, |
1413 | 18 | row_ranges)); |
1414 | 18 | } |
1415 | 18 | } |
1416 | | |
1417 | 37 | return Status::OK(); |
1418 | 37 | } |
1419 | | |
1420 | | Status ParquetReader::_process_column_stat_filter( |
1421 | | const tparquet::RowGroup& row_group, |
1422 | | const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred, |
1423 | 20 | bool* filter_group, bool* filtered_by_min_max, bool* filtered_by_bloom_filter) { |
1424 | | // If both filters are disabled, skip filtering |
1425 | 20 | if (!_enable_filter_by_min_max && !_enable_filter_by_bloom_filter) { |
1426 | 0 | return Status::OK(); |
1427 | 0 | } |
1428 | | |
1429 | | // Cache bloom filters for each column to avoid reading the same bloom filter multiple times |
1430 | | // when there are multiple predicates on the same column |
1431 | 20 | std::unordered_map<int, std::unique_ptr<ParquetBlockSplitBloomFilter>> bloom_filter_cache; |
1432 | | |
1433 | | // Initialize output parameters |
1434 | 20 | *filtered_by_min_max = false; |
1435 | 20 | *filtered_by_bloom_filter = false; |
1436 | | |
1437 | 20 | for (const auto& predicate : _push_down_predicates) { |
1438 | 2 | std::function<bool(ParquetPredicate::ColumnStat*, int)> get_stat_func = |
1439 | 4 | [&](ParquetPredicate::ColumnStat* stat, const int cid) { |
1440 | | // Check if min-max filter is enabled |
1441 | 4 | if (!_enable_filter_by_min_max) { |
1442 | 0 | return false; |
1443 | 0 | } |
1444 | 4 | auto* slot = _tuple_descriptor->slots()[cid]; |
1445 | 4 | if (!_table_info_node_ptr->children_column_exists(slot->col_name())) { |
1446 | 0 | return false; |
1447 | 0 | } |
1448 | 4 | const auto& file_col_name = |
1449 | 4 | _table_info_node_ptr->children_file_column_name(slot->col_name()); |
1450 | 4 | const FieldSchema* col_schema = |
1451 | 4 | _file_metadata->schema().get_column(file_col_name); |
1452 | 4 | int parquet_col_id = col_schema->physical_column_index; |
1453 | 4 | auto meta_data = row_group.columns[parquet_col_id].meta_data; |
1454 | 4 | stat->col_schema = col_schema; |
1455 | 4 | return ParquetPredicate::read_column_stats(col_schema, meta_data, |
1456 | 4 | &_ignored_stats, |
1457 | 4 | _t_metadata->created_by, stat) |
1458 | 4 | .ok(); |
1459 | 4 | }; |
1460 | 2 | std::function<bool(ParquetPredicate::ColumnStat*, int)> get_bloom_filter_func = |
1461 | 2 | [&](ParquetPredicate::ColumnStat* stat, const int cid) { |
1462 | 0 | auto* slot = _tuple_descriptor->slots()[cid]; |
1463 | 0 | if (!_table_info_node_ptr->children_column_exists(slot->col_name())) { |
1464 | 0 | return false; |
1465 | 0 | } |
1466 | 0 | const auto& file_col_name = |
1467 | 0 | _table_info_node_ptr->children_file_column_name(slot->col_name()); |
1468 | 0 | const FieldSchema* col_schema = |
1469 | 0 | _file_metadata->schema().get_column(file_col_name); |
1470 | 0 | int parquet_col_id = col_schema->physical_column_index; |
1471 | 0 | auto meta_data = row_group.columns[parquet_col_id].meta_data; |
1472 | 0 | if (!meta_data.__isset.bloom_filter_offset) { |
1473 | 0 | return false; |
1474 | 0 | } |
1475 | 0 | auto primitive_type = |
1476 | 0 | remove_nullable(col_schema->data_type)->get_primitive_type(); |
1477 | 0 | if (!ParquetPredicate::bloom_filter_supported(primitive_type)) { |
1478 | 0 | return false; |
1479 | 0 | } |
1480 | | |
1481 | | // Check if bloom filter is enabled |
1482 | 0 | if (!_enable_filter_by_bloom_filter) { |
1483 | 0 | return false; |
1484 | 0 | } |
1485 | | |
1486 | | // Check cache first |
1487 | 0 | auto cache_iter = bloom_filter_cache.find(parquet_col_id); |
1488 | 0 | if (cache_iter != bloom_filter_cache.end()) { |
1489 | | // Bloom filter already loaded for this column, reuse it |
1490 | 0 | stat->bloom_filter = std::move(cache_iter->second); |
1491 | 0 | bloom_filter_cache.erase(cache_iter); |
1492 | 0 | return stat->bloom_filter != nullptr; |
1493 | 0 | } |
1494 | | |
1495 | 0 | if (!stat->bloom_filter) { |
1496 | 0 | SCOPED_RAW_TIMER(&_reader_statistics.bloom_filter_read_time); |
1497 | 0 | auto st = ParquetPredicate::read_bloom_filter( |
1498 | 0 | meta_data, _tracing_file_reader, _io_ctx, stat); |
1499 | 0 | if (!st.ok()) { |
1500 | 0 | LOG(WARNING) << "Failed to read bloom filter for column " |
1501 | 0 | << col_schema->name << " in file " << _scan_range.path |
1502 | 0 | << ", status: " << st.to_string(); |
1503 | 0 | stat->bloom_filter.reset(); |
1504 | 0 | return false; |
1505 | 0 | } |
1506 | 0 | } |
1507 | 0 | return stat->bloom_filter != nullptr; |
1508 | 0 | }; |
1509 | 2 | ParquetPredicate::ColumnStat stat; |
1510 | 2 | stat.ctz = _ctz; |
1511 | 2 | stat.get_stat_func = &get_stat_func; |
1512 | 2 | stat.get_bloom_filter_func = &get_bloom_filter_func; |
1513 | | |
1514 | 2 | if (!predicate->evaluate_and(&stat)) { |
1515 | 1 | *filter_group = true; |
1516 | | |
1517 | | // Track which filter was used for filtering |
1518 | | // If bloom filter was loaded, it means bloom filter was used |
1519 | 1 | if (stat.bloom_filter) { |
1520 | 0 | *filtered_by_bloom_filter = true; |
1521 | 0 | } |
1522 | | // If col_schema was set but no bloom filter, it means min-max stats were used |
1523 | 1 | if (stat.col_schema && !stat.bloom_filter) { |
1524 | 1 | *filtered_by_min_max = true; |
1525 | 1 | } |
1526 | | |
1527 | 1 | return Status::OK(); |
1528 | 1 | } |
1529 | | |
1530 | | // After evaluating, if the bloom filter was used, cache it for subsequent predicates |
1531 | 1 | if (stat.bloom_filter) { |
1532 | | // Find the column id for caching |
1533 | 0 | for (auto* slot : _tuple_descriptor->slots()) { |
1534 | 0 | if (_table_info_node_ptr->children_column_exists(slot->col_name())) { |
1535 | 0 | const auto& file_col_name = |
1536 | 0 | _table_info_node_ptr->children_file_column_name(slot->col_name()); |
1537 | 0 | const FieldSchema* col_schema = |
1538 | 0 | _file_metadata->schema().get_column(file_col_name); |
1539 | 0 | int parquet_col_id = col_schema->physical_column_index; |
1540 | 0 | if (stat.col_schema == col_schema) { |
1541 | 0 | bloom_filter_cache[parquet_col_id] = std::move(stat.bloom_filter); |
1542 | 0 | break; |
1543 | 0 | } |
1544 | 0 | } |
1545 | 0 | } |
1546 | 0 | } |
1547 | 1 | } |
1548 | | |
1549 | | // Update filter statistics if this row group was not filtered |
1550 | | // The statistics will be updated in _init_row_groups when filter_group is true |
1551 | 19 | return Status::OK(); |
1552 | 20 | } |
1553 | | |
1554 | 74 | int64_t ParquetReader::_get_column_start_offset(const tparquet::ColumnMetaData& column) const { |
1555 | 74 | return has_dict_page(column) ? column.dictionary_page_offset : column.data_page_offset; |
1556 | 74 | } |
1557 | | |
1558 | 14 | void ParquetReader::_collect_profile() { |
1559 | 14 | if (_profile == nullptr) { |
1560 | 0 | return; |
1561 | 0 | } |
1562 | | |
1563 | 14 | if (_current_group_reader != nullptr) { |
1564 | 14 | _current_group_reader->collect_profile_before_close(); |
1565 | 14 | } |
1566 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_row_groups, _reader_statistics.filtered_row_groups); |
1567 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_min_max, |
1568 | 14 | _reader_statistics.filtered_row_groups_by_min_max); |
1569 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_bloom_filter, |
1570 | 14 | _reader_statistics.filtered_row_groups_by_bloom_filter); |
1571 | 14 | COUNTER_UPDATE(_parquet_profile.to_read_row_groups, _reader_statistics.read_row_groups); |
1572 | 14 | COUNTER_UPDATE(_parquet_profile.total_row_groups, _total_groups); |
1573 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_group_rows, _reader_statistics.filtered_group_rows); |
1574 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_page_rows, _reader_statistics.filtered_page_rows); |
1575 | 14 | COUNTER_UPDATE(_parquet_profile.lazy_read_filtered_rows, |
1576 | 14 | _reader_statistics.lazy_read_filtered_rows); |
1577 | 14 | COUNTER_UPDATE(_parquet_profile.filtered_bytes, _reader_statistics.filtered_bytes); |
1578 | 14 | COUNTER_UPDATE(_parquet_profile.raw_rows_read, _reader_statistics.read_rows); |
1579 | 14 | COUNTER_UPDATE(_parquet_profile.column_read_time, _reader_statistics.column_read_time); |
1580 | 14 | COUNTER_UPDATE(_parquet_profile.parse_meta_time, _reader_statistics.parse_meta_time); |
1581 | 14 | COUNTER_UPDATE(_parquet_profile.parse_footer_time, _reader_statistics.parse_footer_time); |
1582 | 14 | COUNTER_UPDATE(_parquet_profile.file_reader_create_time, |
1583 | 14 | _reader_statistics.file_reader_create_time); |
1584 | 14 | COUNTER_UPDATE(_parquet_profile.open_file_num, _reader_statistics.open_file_num); |
1585 | 14 | COUNTER_UPDATE(_parquet_profile.page_index_filter_time, |
1586 | 14 | _reader_statistics.page_index_filter_time); |
1587 | 14 | COUNTER_UPDATE(_parquet_profile.read_page_index_time, _reader_statistics.read_page_index_time); |
1588 | 14 | COUNTER_UPDATE(_parquet_profile.parse_page_index_time, |
1589 | 14 | _reader_statistics.parse_page_index_time); |
1590 | 14 | COUNTER_UPDATE(_parquet_profile.row_group_filter_time, |
1591 | 14 | _reader_statistics.row_group_filter_time); |
1592 | 14 | COUNTER_UPDATE(_parquet_profile.file_footer_read_calls, |
1593 | 14 | _reader_statistics.file_footer_read_calls); |
1594 | 14 | COUNTER_UPDATE(_parquet_profile.file_footer_hit_cache, |
1595 | 14 | _reader_statistics.file_footer_hit_cache); |
1596 | | |
1597 | 14 | COUNTER_UPDATE(_parquet_profile.skip_page_header_num, _column_statistics.skip_page_header_num); |
1598 | 14 | COUNTER_UPDATE(_parquet_profile.parse_page_header_num, |
1599 | 14 | _column_statistics.parse_page_header_num); |
1600 | 14 | COUNTER_UPDATE(_parquet_profile.predicate_filter_time, |
1601 | 14 | _reader_statistics.predicate_filter_time); |
1602 | 14 | COUNTER_UPDATE(_parquet_profile.dict_filter_rewrite_time, |
1603 | 14 | _reader_statistics.dict_filter_rewrite_time); |
1604 | 14 | COUNTER_UPDATE(_parquet_profile.convert_time, _column_statistics.convert_time); |
1605 | 14 | COUNTER_UPDATE(_parquet_profile.bloom_filter_read_time, |
1606 | 14 | _reader_statistics.bloom_filter_read_time); |
1607 | 14 | COUNTER_UPDATE(_parquet_profile.page_index_read_calls, |
1608 | 14 | _column_statistics.page_index_read_calls); |
1609 | 14 | COUNTER_UPDATE(_parquet_profile.decompress_time, _column_statistics.decompress_time); |
1610 | 14 | COUNTER_UPDATE(_parquet_profile.decompress_cnt, _column_statistics.decompress_cnt); |
1611 | 14 | COUNTER_UPDATE(_parquet_profile.page_read_counter, _column_statistics.page_read_counter); |
1612 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_write_counter, |
1613 | 14 | _column_statistics.page_cache_write_counter); |
1614 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_compressed_write_counter, |
1615 | 14 | _column_statistics.page_cache_compressed_write_counter); |
1616 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_write_counter, |
1617 | 14 | _column_statistics.page_cache_decompressed_write_counter); |
1618 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_hit_counter, |
1619 | 14 | _column_statistics.page_cache_hit_counter); |
1620 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_missing_counter, |
1621 | 14 | _column_statistics.page_cache_missing_counter); |
1622 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_compressed_hit_counter, |
1623 | 14 | _column_statistics.page_cache_compressed_hit_counter); |
1624 | 14 | COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_hit_counter, |
1625 | 14 | _column_statistics.page_cache_decompressed_hit_counter); |
1626 | 14 | COUNTER_UPDATE(_parquet_profile.decode_header_time, _column_statistics.decode_header_time); |
1627 | 14 | COUNTER_UPDATE(_parquet_profile.read_page_header_time, |
1628 | 14 | _column_statistics.read_page_header_time); |
1629 | 14 | COUNTER_UPDATE(_parquet_profile.decode_value_time, _column_statistics.decode_value_time); |
1630 | 14 | COUNTER_UPDATE(_parquet_profile.decode_dict_time, _column_statistics.decode_dict_time); |
1631 | 14 | COUNTER_UPDATE(_parquet_profile.decode_level_time, _column_statistics.decode_level_time); |
1632 | 14 | COUNTER_UPDATE(_parquet_profile.decode_null_map_time, _column_statistics.decode_null_map_time); |
1633 | 14 | } |
1634 | | |
1635 | 14 | void ParquetReader::_collect_profile_before_close() { |
1636 | 14 | _collect_profile(); |
1637 | 14 | } |
1638 | | |
1639 | | } // namespace doris |