Coverage Report

Created: 2026-05-17 20:45

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/format/parquet/vparquet_reader.cpp
Line
Count
Source
1
// Licensed to the Apache Software Foundation (ASF) under one
2
// or more contributor license agreements.  See the NOTICE file
3
// distributed with this work for additional information
4
// regarding copyright ownership.  The ASF licenses this file
5
// to you under the Apache License, Version 2.0 (the
6
// "License"); you may not use this file except in compliance
7
// with the License.  You may obtain a copy of the License at
8
//
9
//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
12
// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
14
// KIND, either express or implied.  See the License for the
15
// specific language governing permissions and limitations
16
// under the License.
17
18
#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 <utility>
28
29
#include "common/config.h"
30
#include "common/status.h"
31
#include "core/block/block.h"
32
#include "core/block/column_with_type_and_name.h"
33
#include "core/column/column.h"
34
#include "core/data_type/define_primitive_type.h"
35
#include "core/typeid_cast.h"
36
#include "core/types.h"
37
#include "exec/scan/file_scanner.h"
38
#include "exprs/vbloom_predicate.h"
39
#include "exprs/vdirect_in_predicate.h"
40
#include "exprs/vexpr.h"
41
#include "exprs/vexpr_context.h"
42
#include "exprs/vin_predicate.h"
43
#include "exprs/vruntimefilter_wrapper.h"
44
#include "exprs/vslot_ref.h"
45
#include "exprs/vtopn_pred.h"
46
#include "format/column_type_convert.h"
47
#include "format/parquet/parquet_block_split_bloom_filter.h"
48
#include "format/parquet/parquet_common.h"
49
#include "format/parquet/parquet_predicate.h"
50
#include "format/parquet/parquet_thrift_util.h"
51
#include "format/parquet/schema_desc.h"
52
#include "format/parquet/vparquet_file_metadata.h"
53
#include "format/parquet/vparquet_group_reader.h"
54
#include "format/parquet/vparquet_page_index.h"
55
#include "information_schema/schema_scanner.h"
56
#include "io/file_factory.h"
57
#include "io/fs/buffered_reader.h"
58
#include "io/fs/file_reader.h"
59
#include "io/fs/file_reader_writer_fwd.h"
60
#include "io/fs/tracing_file_reader.h"
61
#include "runtime/descriptors.h"
62
#include "util/slice.h"
63
#include "util/string_util.h"
64
#include "util/timezone_utils.h"
65
66
namespace cctz {
67
class time_zone;
68
} // namespace cctz
69
namespace doris {
70
class RowDescriptor;
71
class RuntimeState;
72
class SlotDescriptor;
73
class TupleDescriptor;
74
namespace io {
75
struct IOContext;
76
enum class FileCachePolicy : uint8_t;
77
} // namespace io
78
class Block;
79
} // namespace doris
80
81
namespace doris {
82
83
ParquetReader::ParquetReader(RuntimeProfile* profile, const TFileScanRangeParams& params,
84
                             const TFileRangeDesc& range, size_t batch_size,
85
                             const cctz::time_zone* ctz, io::IOContext* io_ctx, RuntimeState* state,
86
                             FileMetaCache* meta_cache, bool enable_lazy_mat)
87
98
        : _profile(profile),
88
98
          _scan_params(params),
89
98
          _scan_range(range),
90
98
          _batch_size(std::max(batch_size, 1UL)),
91
98
          _range_start_offset(range.start_offset),
92
98
          _range_size(range.size),
93
98
          _ctz(ctz),
94
98
          _io_ctx(io_ctx),
95
98
          _state(state),
96
98
          _enable_lazy_mat(enable_lazy_mat),
97
          _enable_filter_by_min_max(
98
98
                  state == nullptr ? true
99
98
                                   : state->query_options().enable_parquet_filter_by_min_max),
100
          _enable_filter_by_bloom_filter(
101
98
                  state == nullptr ? true
102
98
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
103
98
    _meta_cache = meta_cache;
104
98
    _init_profile();
105
98
    _init_system_properties();
106
98
    _init_file_description();
107
98
}
108
109
0
void ParquetReader::set_batch_size(size_t batch_size) {
110
0
    if (_batch_size == batch_size) {
111
0
        return;
112
0
    }
113
0
    _batch_size = batch_size;
114
0
}
115
116
ParquetReader::ParquetReader(RuntimeProfile* profile, const TFileScanRangeParams& params,
117
                             const TFileRangeDesc& range, size_t batch_size,
118
                             const cctz::time_zone* ctz,
119
                             std::shared_ptr<io::IOContext> io_ctx_holder, RuntimeState* state,
120
                             FileMetaCache* meta_cache, bool enable_lazy_mat)
121
0
        : _profile(profile),
122
0
          _scan_params(params),
123
0
          _scan_range(range),
124
0
          _batch_size(std::max(batch_size, 1UL)),
125
0
          _range_start_offset(range.start_offset),
126
0
          _range_size(range.size),
127
0
          _ctz(ctz),
128
0
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
129
0
          _io_ctx_holder(std::move(io_ctx_holder)),
130
0
          _state(state),
131
0
          _enable_lazy_mat(enable_lazy_mat),
132
          _enable_filter_by_min_max(
133
0
                  state == nullptr ? true
134
0
                                   : state->query_options().enable_parquet_filter_by_min_max),
135
          _enable_filter_by_bloom_filter(
136
0
                  state == nullptr ? true
137
0
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
138
0
    _meta_cache = meta_cache;
139
0
    _init_profile();
140
0
    _init_system_properties();
141
0
    _init_file_description();
142
0
}
143
144
ParquetReader::ParquetReader(const TFileScanRangeParams& params, const TFileRangeDesc& range,
145
                             io::IOContext* io_ctx, RuntimeState* state, FileMetaCache* meta_cache,
146
                             bool enable_lazy_mat)
147
5
        : _profile(nullptr),
148
5
          _scan_params(params),
149
5
          _scan_range(range),
150
5
          _io_ctx(io_ctx),
151
5
          _state(state),
152
5
          _enable_lazy_mat(enable_lazy_mat),
153
          _enable_filter_by_min_max(
154
5
                  state == nullptr ? true
155
5
                                   : state->query_options().enable_parquet_filter_by_min_max),
156
          _enable_filter_by_bloom_filter(
157
5
                  state == nullptr ? true
158
5
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
159
5
    _meta_cache = meta_cache;
160
5
    _init_system_properties();
161
5
    _init_file_description();
162
5
}
163
164
ParquetReader::ParquetReader(const TFileScanRangeParams& params, const TFileRangeDesc& range,
165
                             std::shared_ptr<io::IOContext> io_ctx_holder, RuntimeState* state,
166
                             FileMetaCache* meta_cache, bool enable_lazy_mat)
167
0
        : _profile(nullptr),
168
0
          _scan_params(params),
169
0
          _scan_range(range),
170
0
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
171
0
          _io_ctx_holder(std::move(io_ctx_holder)),
172
0
          _state(state),
173
0
          _enable_lazy_mat(enable_lazy_mat),
174
          _enable_filter_by_min_max(
175
0
                  state == nullptr ? true
176
0
                                   : state->query_options().enable_parquet_filter_by_min_max),
177
          _enable_filter_by_bloom_filter(
178
0
                  state == nullptr ? true
179
0
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
180
0
    _meta_cache = meta_cache;
181
0
    _init_system_properties();
182
0
    _init_file_description();
183
0
}
184
185
103
ParquetReader::~ParquetReader() {
186
103
    _close_internal();
187
103
}
188
189
#ifdef BE_TEST
190
// for unit test
191
void ParquetReader::set_file_reader(io::FileReaderSPtr file_reader) {
192
    _file_reader = file_reader;
193
    _tracing_file_reader = file_reader;
194
}
195
#endif
196
197
98
void ParquetReader::_init_profile() {
198
98
    if (_profile != nullptr) {
199
50
        static const char* parquet_profile = "ParquetReader";
200
50
        ADD_TIMER_WITH_LEVEL(_profile, parquet_profile, 1);
201
202
50
        _parquet_profile.filtered_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
203
50
                _profile, "RowGroupsFiltered", TUnit::UNIT, parquet_profile, 1);
204
50
        _parquet_profile.filtered_row_groups_by_min_max = ADD_CHILD_COUNTER_WITH_LEVEL(
205
50
                _profile, "RowGroupsFilteredByMinMax", TUnit::UNIT, parquet_profile, 1);
206
50
        _parquet_profile.filtered_row_groups_by_bloom_filter = ADD_CHILD_COUNTER_WITH_LEVEL(
207
50
                _profile, "RowGroupsFilteredByBloomFilter", TUnit::UNIT, parquet_profile, 1);
208
50
        _parquet_profile.to_read_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
209
50
                _profile, "RowGroupsReadNum", TUnit::UNIT, parquet_profile, 1);
210
50
        _parquet_profile.total_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
211
50
                _profile, "RowGroupsTotalNum", TUnit::UNIT, parquet_profile, 1);
212
50
        _parquet_profile.filtered_group_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
213
50
                _profile, "FilteredRowsByGroup", TUnit::UNIT, parquet_profile, 1);
214
50
        _parquet_profile.filtered_page_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
215
50
                _profile, "FilteredRowsByPage", TUnit::UNIT, parquet_profile, 1);
216
50
        _parquet_profile.lazy_read_filtered_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
217
50
                _profile, "FilteredRowsByLazyRead", TUnit::UNIT, parquet_profile, 1);
218
50
        _parquet_profile.filtered_bytes = ADD_CHILD_COUNTER_WITH_LEVEL(
219
50
                _profile, "FilteredBytes", TUnit::BYTES, parquet_profile, 1);
220
50
        _parquet_profile.raw_rows_read = ADD_CHILD_COUNTER_WITH_LEVEL(
221
50
                _profile, "RawRowsRead", TUnit::UNIT, parquet_profile, 1);
222
50
        _parquet_profile.column_read_time =
223
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ColumnReadTime", parquet_profile, 1);
224
50
        _parquet_profile.parse_meta_time =
225
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseMetaTime", parquet_profile, 1);
226
50
        _parquet_profile.parse_footer_time =
227
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseFooterTime", parquet_profile, 1);
228
50
        _parquet_profile.file_reader_create_time =
229
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "FileReaderCreateTime", parquet_profile, 1);
230
50
        _parquet_profile.open_file_num =
231
50
                ADD_CHILD_COUNTER_WITH_LEVEL(_profile, "FileNum", TUnit::UNIT, parquet_profile, 1);
232
50
        _parquet_profile.page_index_read_calls =
233
50
                ADD_COUNTER_WITH_LEVEL(_profile, "PageIndexReadCalls", TUnit::UNIT, 1);
234
50
        _parquet_profile.page_index_filter_time =
235
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexFilterTime", parquet_profile, 1);
236
50
        _parquet_profile.read_page_index_time =
237
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexReadTime", parquet_profile, 1);
238
50
        _parquet_profile.parse_page_index_time =
239
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexParseTime", parquet_profile, 1);
240
50
        _parquet_profile.row_group_filter_time =
241
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "RowGroupFilterTime", parquet_profile, 1);
242
50
        _parquet_profile.file_footer_read_calls =
243
50
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterReadCalls", TUnit::UNIT, 1);
244
50
        _parquet_profile.file_footer_hit_cache =
245
50
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterHitCache", TUnit::UNIT, 1);
246
50
        _parquet_profile.decompress_time =
247
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecompressTime", parquet_profile, 1);
248
50
        _parquet_profile.decompress_cnt = ADD_CHILD_COUNTER_WITH_LEVEL(
249
50
                _profile, "DecompressCount", TUnit::UNIT, parquet_profile, 1);
250
50
        _parquet_profile.page_read_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
251
50
                _profile, "PageReadCount", TUnit::UNIT, parquet_profile, 1);
252
50
        _parquet_profile.page_cache_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
253
50
                _profile, "PageCacheWriteCount", TUnit::UNIT, parquet_profile, 1);
254
50
        _parquet_profile.page_cache_compressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
255
50
                _profile, "PageCacheCompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
256
50
        _parquet_profile.page_cache_decompressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
257
50
                _profile, "PageCacheDecompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
258
50
        _parquet_profile.page_cache_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
259
50
                _profile, "PageCacheHitCount", TUnit::UNIT, parquet_profile, 1);
260
50
        _parquet_profile.page_cache_missing_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
261
50
                _profile, "PageCacheMissingCount", TUnit::UNIT, parquet_profile, 1);
262
50
        _parquet_profile.page_cache_compressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
263
50
                _profile, "PageCacheCompressedHitCount", TUnit::UNIT, parquet_profile, 1);
264
50
        _parquet_profile.page_cache_decompressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
265
50
                _profile, "PageCacheDecompressedHitCount", TUnit::UNIT, parquet_profile, 1);
266
50
        _parquet_profile.decode_header_time =
267
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderDecodeTime", parquet_profile, 1);
268
50
        _parquet_profile.read_page_header_time =
269
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderReadTime", parquet_profile, 1);
270
50
        _parquet_profile.decode_value_time =
271
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeValueTime", parquet_profile, 1);
272
50
        _parquet_profile.decode_dict_time =
273
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeDictTime", parquet_profile, 1);
274
50
        _parquet_profile.decode_level_time =
275
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeLevelTime", parquet_profile, 1);
276
50
        _parquet_profile.decode_null_map_time =
277
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeNullMapTime", parquet_profile, 1);
278
50
        _parquet_profile.skip_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
279
50
                _profile, "SkipPageHeaderNum", TUnit::UNIT, parquet_profile, 1);
280
50
        _parquet_profile.parse_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
281
50
                _profile, "ParsePageHeaderNum", TUnit::UNIT, parquet_profile, 1);
282
50
        _parquet_profile.predicate_filter_time =
283
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PredicateFilterTime", parquet_profile, 1);
284
50
        _parquet_profile.dict_filter_rewrite_time =
285
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DictFilterRewriteTime", parquet_profile, 1);
286
50
        _parquet_profile.convert_time =
287
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ConvertTime", parquet_profile, 1);
288
50
        _parquet_profile.bloom_filter_read_time =
289
50
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "BloomFilterReadTime", parquet_profile, 1);
290
50
    }
291
98
}
292
293
14
Status ParquetReader::close() {
294
14
    _close_internal();
295
14
    return Status::OK();
296
14
}
297
298
117
void ParquetReader::_close_internal() {
299
117
    if (!_closed) {
300
103
        _current_group_reader.reset();
301
103
        _tracing_file_reader.reset();
302
103
        _file_reader.reset();
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
    }
439
440
9
    return Status::OK();
441
9
}
442
443
66
Status ParquetReader::_open_file_reader(ReaderInitContext* /*ctx*/) {
444
66
    return _open_file();
445
66
}
446
447
66
Status ParquetReader::_do_init_reader(ReaderInitContext* base_ctx) {
448
66
    auto* ctx = checked_context_cast<ParquetInitContext>(base_ctx);
449
66
    _col_name_to_block_idx = base_ctx->col_name_to_block_idx;
450
66
    _tuple_descriptor = ctx->tuple_descriptor;
451
66
    _row_descriptor = ctx->row_descriptor;
452
66
    _colname_to_slot_id = ctx->colname_to_slot_id;
453
66
    _not_single_slot_filter_conjuncts = ctx->not_single_slot_filter_conjuncts;
454
66
    _slot_id_to_filter_conjuncts = ctx->slot_id_to_filter_conjuncts;
455
66
    _filter_groups = ctx->filter_groups;
456
66
    _table_info_node_ptr = base_ctx->table_info_node;
457
66
    _column_ids = base_ctx->column_ids;
458
66
    _filter_column_ids = base_ctx->filter_column_ids;
459
460
    // _open_file_reader (called by init_reader NVI before hooks) must have opened the file.
461
66
    DCHECK(_file_metadata != nullptr)
462
0
            << "ParquetReader::_do_init_reader called without _open_file_reader";
463
66
    _t_metadata = &(_file_metadata->to_thrift());
464
465
66
    SCOPED_RAW_TIMER(&_reader_statistics.parse_meta_time);
466
66
    _total_groups = _t_metadata->row_groups.size();
467
66
    if (_total_groups == 0) {
468
0
        return Status::EndOfFile("init reader failed, empty parquet file: " + _scan_range.path);
469
0
    }
470
66
    _current_row_group_index = RowGroupReader::RowGroupIndex {-1, 0, 0};
471
472
    // Compute missing columns and file↔table column mapping.
473
    // This runs in _do_init_reader (not on_before_init_reader) because table-format readers
474
    // (Iceberg, Paimon, Hive, Hudi) override on_before_init_reader completely.
475
66
    if (has_column_descs()) {
476
24
        _fill_missing_cols.clear();
477
24
        _fill_missing_defaults.clear();
478
74
        for (const auto& col_name : base_ctx->column_names) {
479
74
            if (!_table_info_node_ptr->children_column_exists(col_name)) {
480
5
                _fill_missing_cols.insert(col_name);
481
5
            }
482
74
        }
483
24
        if (_column_descs && !_fill_missing_cols.empty()) {
484
13
            for (const auto& desc : *_column_descs) {
485
13
                if (_fill_missing_cols.contains(desc.name) &&
486
13
                    !_fill_partition_values.contains(desc.name)) {
487
0
                    _fill_missing_defaults[desc.name] = desc.default_expr;
488
0
                }
489
13
            }
490
5
        }
491
24
    }
492
    // Resolve file-column ↔ table-column mapping in file-schema order.
493
    // _init_read_columns handles both normal path (missing cols populated above)
494
    // and standalone path (_fill_missing_cols empty, _table_info_node_ptr may be null).
495
66
    _init_read_columns(base_ctx->column_names);
496
497
    // build column predicates for column lazy read
498
66
    if (ctx->conjuncts != nullptr) {
499
66
        _lazy_read_ctx.conjuncts = *ctx->conjuncts;
500
66
    }
501
66
    if (ctx->slot_id_to_predicates != nullptr) {
502
66
        _lazy_read_ctx.slot_id_to_predicates = *ctx->slot_id_to_predicates;
503
66
    }
504
505
    // ---- Inlined set_fill_columns logic (partition/missing/synthesized classification) ----
506
507
    // 1. Collect predicate columns from conjuncts for lazy materialization
508
66
    std::unordered_map<std::string, std::pair<uint32_t, int>> predicate_columns;
509
66
    _collect_predicate_columns_from_conjuncts(predicate_columns);
510
511
    // 2. Classify read/partition/missing/synthesized columns into lazy vs predicate groups
512
66
    _classify_columns_for_lazy_read(predicate_columns, _fill_partition_values,
513
66
                                    _fill_missing_defaults);
514
515
    // 3. Populate col_names vectors for ColumnProcessor path
516
66
    for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
517
5
        _lazy_read_ctx.predicate_partition_col_names.emplace_back(kv.first);
518
5
    }
519
66
    for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
520
0
        _lazy_read_ctx.predicate_missing_col_names.emplace_back(kv.first);
521
0
    }
522
66
    for (auto& kv : _lazy_read_ctx.partition_columns) {
523
3
        _lazy_read_ctx.partition_col_names.emplace_back(kv.first);
524
3
    }
525
66
    for (auto& kv : _lazy_read_ctx.missing_columns) {
526
0
        _lazy_read_ctx.missing_col_names.emplace_back(kv.first);
527
0
    }
528
529
66
    if (_filter_groups && (_total_groups == 0 || _t_metadata->num_rows == 0 || _range_size < 0)) {
530
0
        return Status::EndOfFile("No row group to read");
531
0
    }
532
533
66
    return Status::OK();
534
66
}
535
536
66
void ParquetReader::_init_read_columns(const std::vector<std::string>& column_names) {
537
    // Build file_col_name → table_col_name map, skipping missing columns.
538
    // Must iterate file schema in physical order so that _generate_random_access_ranges
539
    // sees monotonically increasing chunk offsets.
540
66
    auto schema_desc = _file_metadata->schema();
541
66
    std::map<std::string, std::string> required_file_columns;
542
422
    for (const auto& col_name : column_names) {
543
422
        if (_fill_missing_cols.contains(col_name)) {
544
5
            continue;
545
5
        }
546
417
        std::string file_col = col_name;
547
417
        if (_table_info_node_ptr && _table_info_node_ptr->children_column_exists(col_name)) {
548
417
            file_col = _table_info_node_ptr->children_file_column_name(col_name);
549
417
        }
550
417
        required_file_columns[file_col] = col_name;
551
417
    }
552
725
    for (int i = 0; i < schema_desc.size(); ++i) {
553
659
        const auto& name = schema_desc.get_column(i)->name;
554
659
        if (required_file_columns.contains(name)) {
555
417
            _read_file_columns.emplace_back(name);
556
417
            _read_table_columns.emplace_back(required_file_columns[name]);
557
417
            _read_table_columns_set.insert(required_file_columns[name]);
558
417
        }
559
659
    }
560
66
}
561
562
0
bool ParquetReader::_exists_in_file(const std::string& expr_name) const {
563
    // `_read_table_columns_set` is used to ensure that only columns actually read are subject to min-max filtering.
564
    // This primarily handles cases where partition columns also exist in a file. The reason it's not modified
565
    // in `_table_info_node_ptr` is that Iceberg、Hudi has inconsistent requirements for this node;
566
    // Iceberg partition evolution need read partition columns from a file.
567
    // hudi set `hoodie.datasource.write.drop.partition.columns=false` not need read partition columns from a file.
568
0
    return _table_info_node_ptr->children_column_exists(expr_name) &&
569
0
           _read_table_columns_set.contains(expr_name);
570
0
}
571
572
0
bool ParquetReader::_type_matches(const int cid) const {
573
0
    auto* slot = _tuple_descriptor->slots()[cid];
574
0
    auto table_col_type = remove_nullable(slot->type());
575
576
0
    const auto& file_col_name = _table_info_node_ptr->children_file_column_name(slot->col_name());
577
0
    const auto& file_col_type =
578
0
            remove_nullable(_file_metadata->schema().get_column(file_col_name)->data_type);
579
580
0
    return (table_col_type->get_primitive_type() == file_col_type->get_primitive_type()) &&
581
0
           !is_complex_type(table_col_type->get_primitive_type());
582
0
}
583
584
void ParquetReader::_collect_predicate_columns_from_conjuncts(
585
66
        std::unordered_map<std::string, std::pair<uint32_t, int>>& predicate_columns) {
586
66
    std::function<void(VExpr * expr)> visit_slot = [&](VExpr* expr) {
587
39
        if (expr->is_slot_ref()) {
588
13
            VSlotRef* slot_ref = static_cast<VSlotRef*>(expr);
589
13
            auto expr_name = slot_ref->expr_name();
590
13
            predicate_columns.emplace(expr_name,
591
13
                                      std::make_pair(slot_ref->column_id(), slot_ref->slot_id()));
592
13
            if (slot_ref->column_id() == 0) {
593
3
                _lazy_read_ctx.resize_first_column = false;
594
3
            }
595
13
            return;
596
13
        }
597
26
        for (auto& child : expr->children()) {
598
26
            visit_slot(child.get());
599
26
        }
600
26
    };
601
602
66
    for (const auto& conjunct : _lazy_read_ctx.conjuncts) {
603
13
        auto expr = conjunct->root();
604
13
        if (expr->is_rf_wrapper()) {
605
0
            VRuntimeFilterWrapper* runtime_filter = assert_cast<VRuntimeFilterWrapper*>(expr.get());
606
0
            auto filter_impl = runtime_filter->get_impl();
607
0
            visit_slot(filter_impl.get());
608
13
        } else {
609
13
            visit_slot(expr.get());
610
13
        }
611
13
    }
612
613
66
    if (!_lazy_read_ctx.slot_id_to_predicates.empty()) {
614
0
        auto and_pred = AndBlockColumnPredicate::create_unique();
615
0
        for (const auto& entry : _lazy_read_ctx.slot_id_to_predicates) {
616
0
            for (const auto& pred : entry.second) {
617
                // Parquet shares _push_down_predicates for row-group/page min-max pruning and
618
                // bloom-filter evaluation, so this flag currently gates both predicate paths.
619
0
                if (!has_column_optimization(pred->col_name(), ColumnOptimizationTypes::MIN_MAX)) {
620
0
                    continue;
621
0
                }
622
0
                if (!_exists_in_file(pred->col_name()) || !_type_matches(pred->column_id())) {
623
0
                    continue;
624
0
                }
625
0
                and_pred->add_column_predicate(
626
0
                        SingleColumnBlockPredicate::create_unique(pred->clone(pred->column_id())));
627
0
            }
628
0
        }
629
0
        if (and_pred->num_of_column_predicate() > 0) {
630
0
            _push_down_predicates.push_back(std::move(and_pred));
631
0
        }
632
0
    }
633
66
}
634
635
void ParquetReader::_classify_columns_for_lazy_read(
636
        const std::unordered_map<std::string, std::pair<uint32_t, int>>&
637
                predicate_conjuncts_columns,
638
        const std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>&
639
                partition_columns,
640
0
        const std::unordered_map<std::string, VExprContextSPtr>& missing_columns) {
641
0
    const FieldDescriptor& schema = _file_metadata->schema();
642
0
    auto predicate_columns = predicate_conjuncts_columns;
643
0
#ifndef BE_TEST
644
0
    for (const auto& [col_name, _] : _generated_col_handlers) {
645
0
        int slot_id = -1;
646
0
        for (auto slot : _tuple_descriptor->slots()) {
647
0
            if (slot->col_name() == col_name) {
648
0
                slot_id = slot->id();
649
0
                break;
650
0
            }
651
0
        }
652
0
        DCHECK(slot_id != -1) << "slot id should not be -1 for generated column: " << col_name;
653
0
        auto column_index = _row_descriptor->get_column_id(slot_id);
654
0
        if (column_index == 0) {
655
0
            _lazy_read_ctx.resize_first_column = false;
656
0
        }
657
        // assume generated columns are only used for predicate push down.
658
0
        predicate_columns.emplace(col_name, std::make_pair(column_index, slot_id));
659
0
    }
660
661
0
    for (const auto& [col_name, _] : _synthesized_col_handlers) {
662
0
        int slot_id = -1;
663
0
        for (auto slot : _tuple_descriptor->slots()) {
664
0
            if (slot->col_name() == col_name) {
665
0
                slot_id = slot->id();
666
0
                break;
667
0
            }
668
0
        }
669
0
        DCHECK(slot_id != -1) << "slot id should not be -1 for synthesized column: " << col_name;
670
0
        auto column_index = _row_descriptor->get_column_id(slot_id);
671
0
        if (column_index == 0) {
672
0
            _lazy_read_ctx.resize_first_column = false;
673
0
        }
674
        // synthesized columns always fill data on first phase.
675
0
        _lazy_read_ctx.all_predicate_col_ids.emplace_back(column_index);
676
0
    }
677
0
#endif
678
0
    for (auto& read_table_col : _read_table_columns) {
679
0
        _lazy_read_ctx.all_read_columns.emplace_back(read_table_col);
680
681
0
        auto file_column_name = _table_info_node_ptr->children_file_column_name(read_table_col);
682
0
        PrimitiveType column_type =
683
0
                schema.get_column(file_column_name)->data_type->get_primitive_type();
684
0
        if (is_complex_type(column_type)) {
685
0
            _lazy_read_ctx.has_complex_type = true;
686
0
        }
687
0
        if (predicate_columns.size() > 0) {
688
0
            auto iter = predicate_columns.find(read_table_col);
689
0
            if (iter == predicate_columns.end()) {
690
0
                _lazy_read_ctx.lazy_read_columns.emplace_back(read_table_col);
691
0
            } else {
692
0
                _lazy_read_ctx.predicate_columns.first.emplace_back(iter->first);
693
0
                _lazy_read_ctx.predicate_columns.second.emplace_back(iter->second.second);
694
0
                _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
695
0
            }
696
0
        }
697
0
    }
698
699
0
    for (auto& kv : partition_columns) {
700
0
        auto iter = predicate_columns.find(kv.first);
701
0
        if (iter == predicate_columns.end()) {
702
0
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
703
0
        } else {
704
0
            _lazy_read_ctx.predicate_partition_columns.emplace(kv.first, kv.second);
705
0
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
706
0
        }
707
0
    }
708
709
0
    for (auto& kv : missing_columns) {
710
0
        auto iter = predicate_columns.find(kv.first);
711
0
        if (iter != predicate_columns.end()) {
712
            //For check missing column :   missing column == xx, missing column is null,missing column is not null.
713
0
            if (_slot_id_to_filter_conjuncts->find(iter->second.second) !=
714
0
                _slot_id_to_filter_conjuncts->end()) {
715
0
                for (auto& ctx : _slot_id_to_filter_conjuncts->find(iter->second.second)->second) {
716
0
                    _lazy_read_ctx.missing_columns_conjuncts.emplace_back(ctx);
717
0
                }
718
0
            }
719
0
            _lazy_read_ctx.predicate_missing_columns.emplace(kv.first, kv.second);
720
0
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
721
0
        } else {
722
0
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
723
0
        }
724
0
    }
725
726
0
    if (_enable_lazy_mat && _lazy_read_ctx.predicate_columns.first.size() > 0 &&
727
0
        _lazy_read_ctx.lazy_read_columns.size() > 0) {
728
0
        _lazy_read_ctx.can_lazy_read = true;
729
0
    }
730
731
0
    if (!_lazy_read_ctx.can_lazy_read) {
732
0
        for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
733
0
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
734
0
        }
735
0
        for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
736
0
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
737
0
        }
738
0
    }
739
0
}
740
741
// init file reader and file metadata for parsing schema
742
0
Status ParquetReader::init_schema_reader() {
743
0
    RETURN_IF_ERROR(_open_file());
744
0
    _t_metadata = &(_file_metadata->to_thrift());
745
0
    return Status::OK();
746
0
}
747
748
Status ParquetReader::get_parsed_schema(std::vector<std::string>* col_names,
749
0
                                        std::vector<DataTypePtr>* col_types) {
750
0
    _total_groups = _t_metadata->row_groups.size();
751
0
    auto schema_desc = _file_metadata->schema();
752
0
    for (int i = 0; i < schema_desc.size(); ++i) {
753
        // Get the Column Reader for the boolean column
754
0
        col_names->emplace_back(schema_desc.get_column(i)->name);
755
0
        col_types->emplace_back(make_nullable(schema_desc.get_column(i)->data_type));
756
0
    }
757
0
    return Status::OK();
758
0
}
759
760
Status ParquetReader::_get_columns_impl(
761
14
        std::unordered_map<std::string, DataTypePtr>* name_to_type) {
762
14
    const auto& schema_desc = _file_metadata->schema();
763
14
    std::unordered_set<std::string> column_names;
764
14
    schema_desc.get_column_names(&column_names);
765
210
    for (auto& name : column_names) {
766
210
        auto field = schema_desc.get_column(name);
767
210
        name_to_type->emplace(name, field->data_type);
768
210
    }
769
14
    return Status::OK();
770
14
}
771
772
98
Status ParquetReader::_do_get_next_block(Block* block, size_t* read_rows, bool* eof) {
773
98
    if (_current_group_reader == nullptr || _row_group_eof) {
774
38
        Status st = _next_row_group_reader();
775
38
        if (!st.ok() && !st.is<ErrorCode::END_OF_FILE>()) {
776
0
            return st;
777
0
        }
778
38
        if (_current_group_reader == nullptr || _row_group_eof || st.is<ErrorCode::END_OF_FILE>()) {
779
0
            _current_group_reader.reset(nullptr);
780
0
            _row_group_eof = true;
781
0
            *read_rows = 0;
782
0
            *eof = true;
783
0
            return Status::OK();
784
0
        }
785
38
    }
786
787
    // Limit memory per batch for load paths.
788
    // _load_bytes_per_row is updated after each batch so the *next* call pre-shrinks _batch_size
789
    // before reading, ensuring the current batch is already within the limit (from call 2 onward).
790
98
    const int64_t max_block_bytes =
791
98
            (_state != nullptr && _state->query_type() == TQueryType::LOAD &&
792
98
             config::load_reader_max_block_bytes > 0)
793
98
                    ? config::load_reader_max_block_bytes
794
98
                    : 0;
795
98
    if (max_block_bytes > 0 && _load_bytes_per_row > 0) {
796
0
        _batch_size = std::max((size_t)1,
797
0
                               (size_t)((int64_t)max_block_bytes / (int64_t)_load_bytes_per_row));
798
0
    }
799
800
98
    SCOPED_RAW_TIMER(&_reader_statistics.column_read_time);
801
98
    Status batch_st =
802
98
            _current_group_reader->next_batch(block, _batch_size, read_rows, &_row_group_eof);
803
98
    if (batch_st.is<ErrorCode::END_OF_FILE>()) {
804
0
        block->clear_column_data();
805
0
        _current_group_reader.reset(nullptr);
806
0
        *read_rows = 0;
807
0
        *eof = true;
808
0
        return Status::OK();
809
0
    }
810
811
98
    if (!batch_st.ok()) {
812
0
        return Status::InternalError("Read parquet file {} failed, reason = {}", _scan_range.path,
813
0
                                     batch_st.to_string());
814
0
    }
815
816
98
    if (max_block_bytes > 0 && *read_rows > 0) {
817
0
        _load_bytes_per_row = block->bytes() / *read_rows;
818
0
    }
819
820
98
    if (_row_group_eof) {
821
38
        auto column_st = _current_group_reader->merged_column_statistics();
822
38
        _column_statistics.merge(column_st);
823
38
        _reader_statistics.lazy_read_filtered_rows +=
824
38
                _current_group_reader->lazy_read_filtered_rows();
825
38
        _reader_statistics.predicate_filter_time += _current_group_reader->predicate_filter_time();
826
38
        _reader_statistics.dict_filter_rewrite_time +=
827
38
                _current_group_reader->dict_filter_rewrite_time();
828
38
        if (_io_ctx) {
829
15
            _io_ctx->condition_cache_filtered_rows +=
830
15
                    _current_group_reader->condition_cache_filtered_rows();
831
15
        }
832
833
38
        if (_current_row_group_index.row_group_id + 1 == _total_groups) {
834
37
            *eof = true;
835
37
        } else {
836
1
            *eof = false;
837
1
        }
838
38
    }
839
98
    return Status::OK();
840
98
}
841
842
RowGroupReader::PositionDeleteContext ParquetReader::_get_position_delete_ctx(
843
38
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index) {
844
38
    if (_delete_rows == nullptr) {
845
38
        return RowGroupReader::PositionDeleteContext(row_group.num_rows, row_group_index.first_row);
846
38
    }
847
0
    const int64_t* delete_rows = &(*_delete_rows)[0];
848
0
    const int64_t* delete_rows_end = delete_rows + _delete_rows->size();
849
0
    const int64_t* start_pos = std::lower_bound(delete_rows + _delete_rows_index, delete_rows_end,
850
0
                                                row_group_index.first_row);
851
0
    int64_t start_index = start_pos - delete_rows;
852
0
    const int64_t* end_pos = std::lower_bound(start_pos, delete_rows_end, row_group_index.last_row);
853
0
    int64_t end_index = end_pos - delete_rows;
854
0
    _delete_rows_index = end_index;
855
0
    return RowGroupReader::PositionDeleteContext(*_delete_rows, row_group.num_rows,
856
0
                                                 row_group_index.first_row, start_index, end_index);
857
38
}
858
859
38
Status ParquetReader::_next_row_group_reader() {
860
38
    if (_current_group_reader != nullptr) {
861
1
        _current_group_reader->collect_profile_before_close();
862
1
    }
863
864
38
    RowRanges candidate_row_ranges;
865
38
    while (++_current_row_group_index.row_group_id < _total_groups) {
866
38
        const auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
867
38
        _current_row_group_index.first_row = _current_row_group_index.last_row;
868
38
        _current_row_group_index.last_row = _current_row_group_index.last_row + row_group.num_rows;
869
870
38
        if (_filter_groups && _is_misaligned_range_group(row_group)) {
871
0
            continue;
872
0
        }
873
874
38
        candidate_row_ranges.clear();
875
        // The range of lines to be read is determined by the push down predicate.
876
38
        RETURN_IF_ERROR(_process_min_max_bloom_filter(
877
38
                _current_row_group_index, row_group, _push_down_predicates, &candidate_row_ranges));
878
879
38
        std::function<int64_t(const FieldSchema*)> column_compressed_size =
880
138
                [&row_group, &column_compressed_size](const FieldSchema* field) -> int64_t {
881
138
            if (field->physical_column_index >= 0) {
882
124
                int parquet_col_id = field->physical_column_index;
883
124
                if (row_group.columns[parquet_col_id].__isset.meta_data) {
884
124
                    return row_group.columns[parquet_col_id].meta_data.total_compressed_size;
885
124
                }
886
0
                return 0;
887
124
            }
888
14
            int64_t size = 0;
889
30
            for (const FieldSchema& child : field->children) {
890
30
                size += column_compressed_size(&child);
891
30
            }
892
14
            return size;
893
138
        };
894
38
        int64_t group_size = 0; // only calculate the needed columns
895
108
        for (auto& read_col : _read_file_columns) {
896
108
            const FieldSchema* field = _file_metadata->schema().get_column(read_col);
897
108
            group_size += column_compressed_size(field);
898
108
        }
899
900
38
        _reader_statistics.read_rows += candidate_row_ranges.count();
901
38
        if (_io_ctx) {
902
15
            _io_ctx->file_reader_stats->read_rows += candidate_row_ranges.count();
903
15
        }
904
905
38
        if (candidate_row_ranges.count() != 0) {
906
            // need read this row group.
907
38
            _reader_statistics.read_row_groups++;
908
38
            _reader_statistics.filtered_page_rows +=
909
38
                    row_group.num_rows - candidate_row_ranges.count();
910
38
            break;
911
38
        } else {
912
            // this row group be filtered.
913
0
            _reader_statistics.filtered_row_groups++;
914
0
            _reader_statistics.filtered_bytes += group_size;
915
0
            _reader_statistics.filtered_group_rows += row_group.num_rows;
916
0
        }
917
38
    }
918
919
38
    if (_current_row_group_index.row_group_id == _total_groups) {
920
0
        _row_group_eof = true;
921
0
        _current_group_reader.reset(nullptr);
922
0
        return Status::EndOfFile("No next RowGroupReader");
923
0
    }
924
925
    // process page index and generate the ranges to read
926
38
    auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
927
928
38
    RowGroupReader::PositionDeleteContext position_delete_ctx =
929
38
            _get_position_delete_ctx(row_group, _current_row_group_index);
930
38
    io::FileReaderSPtr group_file_reader;
931
38
    if (typeid_cast<io::InMemoryFileReader*>(_file_reader.get())) {
932
        // InMemoryFileReader has the ability to merge small IO
933
0
        group_file_reader = _file_reader;
934
38
    } else {
935
38
        size_t avg_io_size = 0;
936
38
        const std::vector<io::PrefetchRange> io_ranges =
937
38
                _generate_random_access_ranges(_current_row_group_index, &avg_io_size);
938
38
        int64_t merged_read_slice_size = -1;
939
38
        if (_state != nullptr && _state->query_options().__isset.merge_read_slice_size) {
940
26
            merged_read_slice_size = _state->query_options().merge_read_slice_size;
941
26
        }
942
        // The underlying page reader will prefetch data in column.
943
        // Using both MergeRangeFileReader and BufferedStreamReader simultaneously would waste a lot of memory.
944
38
        group_file_reader =
945
38
                avg_io_size < io::MergeRangeFileReader::SMALL_IO
946
38
                        ? std::make_shared<io::MergeRangeFileReader>(
947
38
                                  _profile, _file_reader, io_ranges, merged_read_slice_size)
948
38
                        : _file_reader;
949
38
    }
950
38
    _current_group_reader.reset(new RowGroupReader(
951
38
            _io_ctx ? std::make_shared<io::TracingFileReader>(group_file_reader,
952
15
                                                              _io_ctx->file_reader_stats)
953
38
                    : group_file_reader,
954
38
            _read_table_columns, _current_row_group_index.row_group_id, row_group, _ctz, _io_ctx,
955
38
            position_delete_ctx, _lazy_read_ctx, _state, _column_ids, _filter_column_ids));
956
38
    _row_group_eof = false;
957
958
38
    _current_group_reader->set_current_row_group_idx(_current_row_group_index);
959
38
    _current_group_reader->set_col_name_to_block_idx(_col_name_to_block_idx);
960
38
    if (_condition_cache_ctx) {
961
0
        _current_group_reader->set_condition_cache_context(_condition_cache_ctx);
962
0
    }
963
38
    _current_group_reader->set_table_format_reader(this);
964
965
38
    _current_group_reader->_table_info_node_ptr = _table_info_node_ptr;
966
38
    return _current_group_reader->init(_file_metadata->schema(), candidate_row_ranges, _col_offsets,
967
38
                                       _tuple_descriptor, _row_descriptor, _colname_to_slot_id,
968
38
                                       _not_single_slot_filter_conjuncts,
969
38
                                       _slot_id_to_filter_conjuncts);
970
38
}
971
972
std::vector<io::PrefetchRange> ParquetReader::_generate_random_access_ranges(
973
38
        const RowGroupReader::RowGroupIndex& group, size_t* avg_io_size) {
974
38
    std::vector<io::PrefetchRange> result;
975
38
    int64_t last_chunk_end = -1;
976
38
    size_t total_io_size = 0;
977
38
    std::function<void(const FieldSchema*, const tparquet::RowGroup&)> scalar_range =
978
136
            [&](const FieldSchema* field, const tparquet::RowGroup& row_group) {
979
136
                if (_column_ids.empty() ||
980
136
                    _column_ids.find(field->get_column_id()) != _column_ids.end()) {
981
132
                    if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
982
2
                        scalar_range(&field->children[0], row_group);
983
130
                    } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
984
0
                        scalar_range(&field->children[0], row_group);
985
0
                        scalar_range(&field->children[1], row_group);
986
130
                    } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
987
37
                        for (int i = 0; i < field->children.size(); ++i) {
988
26
                            scalar_range(&field->children[i], row_group);
989
26
                        }
990
119
                    } else {
991
119
                        const tparquet::ColumnChunk& chunk =
992
119
                                row_group.columns[field->physical_column_index];
993
119
                        auto& chunk_meta = chunk.meta_data;
994
119
                        int64_t chunk_start = has_dict_page(chunk_meta)
995
119
                                                      ? chunk_meta.dictionary_page_offset
996
119
                                                      : chunk_meta.data_page_offset;
997
119
                        int64_t chunk_end = chunk_start + chunk_meta.total_compressed_size;
998
119
                        DCHECK_GE(chunk_start, last_chunk_end);
999
119
                        result.emplace_back(chunk_start, chunk_end);
1000
119
                        total_io_size += chunk_meta.total_compressed_size;
1001
119
                        last_chunk_end = chunk_end;
1002
119
                    }
1003
132
                }
1004
136
            };
1005
38
    const tparquet::RowGroup& row_group = _t_metadata->row_groups[group.row_group_id];
1006
108
    for (const auto& read_col : _read_file_columns) {
1007
108
        const FieldSchema* field = _file_metadata->schema().get_column(read_col);
1008
108
        scalar_range(field, row_group);
1009
108
    }
1010
38
    if (!result.empty()) {
1011
37
        *avg_io_size = total_io_size / result.size();
1012
37
    }
1013
38
    return result;
1014
38
}
1015
1016
37
bool ParquetReader::_is_misaligned_range_group(const tparquet::RowGroup& row_group) const {
1017
37
    int64_t start_offset = _get_column_start_offset(row_group.columns[0].meta_data);
1018
1019
37
    auto& last_column = row_group.columns[row_group.columns.size() - 1].meta_data;
1020
37
    int64_t end_offset = _get_column_start_offset(last_column) + last_column.total_compressed_size;
1021
1022
37
    int64_t row_group_mid = start_offset + (end_offset - start_offset) / 2;
1023
37
    if (!(row_group_mid >= _range_start_offset &&
1024
37
          row_group_mid < _range_start_offset + _range_size)) {
1025
0
        return true;
1026
0
    }
1027
37
    return false;
1028
37
}
1029
1030
0
int64_t ParquetReader::get_total_rows() const {
1031
0
    if (!_t_metadata) return 0;
1032
0
    if (!_filter_groups) return _t_metadata->num_rows;
1033
0
    int64_t total = 0;
1034
0
    for (const auto& rg : _t_metadata->row_groups) {
1035
0
        if (!_is_misaligned_range_group(rg)) {
1036
0
            total += rg.num_rows;
1037
0
        }
1038
0
    }
1039
0
    return total;
1040
0
}
1041
1042
0
void ParquetReader::set_condition_cache_context(std::shared_ptr<ConditionCacheContext> ctx) {
1043
0
    _condition_cache_ctx = std::move(ctx);
1044
0
    if (!_condition_cache_ctx || !_t_metadata || !_filter_groups) {
1045
0
        return;
1046
0
    }
1047
    // Find the first assigned row group to compute base_granule.
1048
0
    int64_t first_row = 0;
1049
0
    for (const auto& rg : _t_metadata->row_groups) {
1050
0
        if (!_is_misaligned_range_group(rg)) {
1051
0
            _condition_cache_ctx->base_granule = first_row / ConditionCacheContext::GRANULE_SIZE;
1052
0
            return;
1053
0
        }
1054
0
        first_row += rg.num_rows;
1055
0
    }
1056
0
}
1057
1058
Status ParquetReader::_process_page_index_filter(
1059
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index,
1060
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1061
18
        RowRanges* candidate_row_ranges) {
1062
18
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
1063
0
        return Status::EndOfFile("stop");
1064
0
    }
1065
1066
18
    std::function<void()> read_whole_row_group = [&]() {
1067
18
        candidate_row_ranges->add(RowRange {0, row_group.num_rows});
1068
18
    };
1069
1070
    // Check if the page index is available and if it exists.
1071
18
    PageIndex page_index;
1072
18
    if (!config::enable_parquet_page_index || _colname_to_slot_id == nullptr ||
1073
18
        !page_index.check_and_get_page_index_ranges(row_group.columns)) {
1074
18
        read_whole_row_group();
1075
18
        return Status::OK();
1076
18
    }
1077
1078
0
    std::vector<int> parquet_col_ids;
1079
0
    for (size_t idx = 0; idx < _read_table_columns.size(); idx++) {
1080
0
        const auto& read_table_col = _read_table_columns[idx];
1081
0
        const auto& read_file_col = _read_file_columns[idx];
1082
0
        if (!_colname_to_slot_id->contains(read_table_col)) {
1083
0
            continue;
1084
0
        }
1085
0
        auto* field = _file_metadata->schema().get_column(read_file_col);
1086
1087
0
        std::function<void(FieldSchema * field)> f = [&](FieldSchema* field) {
1088
0
            if (!_column_ids.empty() &&
1089
0
                _column_ids.find(field->get_column_id()) == _column_ids.end()) {
1090
0
                return;
1091
0
            }
1092
1093
0
            if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
1094
0
                f(&field->children[0]);
1095
0
            } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
1096
0
                f(&field->children[0]);
1097
0
                f(&field->children[1]);
1098
0
            } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
1099
0
                for (int i = 0; i < field->children.size(); ++i) {
1100
0
                    f(&field->children[i]);
1101
0
                }
1102
0
            } else {
1103
0
                int parquet_col_id = field->physical_column_index;
1104
0
                if (parquet_col_id >= 0) {
1105
0
                    parquet_col_ids.push_back(parquet_col_id);
1106
0
                }
1107
0
            }
1108
0
        };
1109
1110
0
        f(field);
1111
0
    }
1112
1113
0
    auto parse_offset_index = [&]() -> Status {
1114
0
        std::vector<uint8_t> off_index_buff(page_index._offset_index_size);
1115
0
        Slice res(off_index_buff.data(), page_index._offset_index_size);
1116
0
        size_t bytes_read = 0;
1117
0
        {
1118
0
            SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1119
0
            RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._offset_index_start, res,
1120
0
                                                          &bytes_read, _io_ctx));
1121
0
        }
1122
0
        _column_statistics.page_index_read_calls++;
1123
0
        _col_offsets.clear();
1124
1125
0
        for (auto parquet_col_id : parquet_col_ids) {
1126
0
            auto& chunk = row_group.columns[parquet_col_id];
1127
0
            if (chunk.offset_index_length == 0) [[unlikely]] {
1128
0
                continue;
1129
0
            }
1130
0
            tparquet::OffsetIndex offset_index;
1131
0
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1132
0
            RETURN_IF_ERROR(
1133
0
                    page_index.parse_offset_index(chunk, off_index_buff.data(), &offset_index));
1134
0
            _col_offsets[parquet_col_id] = offset_index;
1135
0
        }
1136
0
        return Status::OK();
1137
0
    };
1138
1139
    // from https://github.com/apache/doris/pull/55795
1140
0
    RETURN_IF_ERROR(parse_offset_index());
1141
1142
    // Check if page index is needed for min-max filter.
1143
0
    if (!_enable_filter_by_min_max || push_down_pred.empty()) {
1144
0
        read_whole_row_group();
1145
0
        return Status::OK();
1146
0
    }
1147
1148
    // read column index.
1149
0
    std::vector<uint8_t> col_index_buff(page_index._column_index_size);
1150
0
    size_t bytes_read = 0;
1151
0
    Slice result(col_index_buff.data(), page_index._column_index_size);
1152
0
    {
1153
0
        SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1154
0
        RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._column_index_start, result,
1155
0
                                                      &bytes_read, _io_ctx));
1156
0
    }
1157
0
    _column_statistics.page_index_read_calls++;
1158
1159
0
    SCOPED_RAW_TIMER(&_reader_statistics.page_index_filter_time);
1160
1161
    // Construct a cacheable page index structure to avoid repeatedly reading the page index of the same column.
1162
0
    ParquetPredicate::CachedPageIndexStat cached_page_index;
1163
0
    cached_page_index.ctz = _ctz;
1164
0
    std::function<bool(ParquetPredicate::PageIndexStat**, int)> get_stat_func =
1165
0
            [&](ParquetPredicate::PageIndexStat** ans, const int cid) -> bool {
1166
0
        if (cached_page_index.stats.contains(cid)) {
1167
0
            *ans = &cached_page_index.stats[cid];
1168
0
            return (*ans)->available;
1169
0
        }
1170
0
        cached_page_index.stats.emplace(cid, ParquetPredicate::PageIndexStat {});
1171
0
        auto& sig_stat = cached_page_index.stats[cid];
1172
1173
0
        auto* slot = _tuple_descriptor->slots()[cid];
1174
0
        if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1175
            // table column not exist in file, may be schema change.
1176
0
            return false;
1177
0
        }
1178
1179
0
        const auto& file_col_name =
1180
0
                _table_info_node_ptr->children_file_column_name(slot->col_name());
1181
0
        const FieldSchema* col_schema = _file_metadata->schema().get_column(file_col_name);
1182
0
        int parquet_col_id = col_schema->physical_column_index;
1183
1184
0
        if (parquet_col_id < 0) {
1185
            // complex type, not support page index yet.
1186
0
            return false;
1187
0
        }
1188
0
        if (!_col_offsets.contains(parquet_col_id)) {
1189
            // If the file contains partition columns and the query applies filters on those
1190
            // partition columns, then reading the page index is unnecessary.
1191
0
            return false;
1192
0
        }
1193
1194
0
        auto& column_chunk = row_group.columns[parquet_col_id];
1195
0
        if (column_chunk.column_index_length == 0 || column_chunk.offset_index_length == 0) {
1196
            // column no page index.
1197
0
            return false;
1198
0
        }
1199
1200
0
        tparquet::ColumnIndex column_index;
1201
0
        {
1202
0
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1203
0
            RETURN_IF_ERROR(page_index.parse_column_index(column_chunk, col_index_buff.data(),
1204
0
                                                          &column_index));
1205
0
        }
1206
0
        const int64_t num_of_pages = column_index.null_pages.size();
1207
0
        if (num_of_pages <= 0) [[unlikely]] {
1208
            // no page. (maybe this row group no data.)
1209
0
            return false;
1210
0
        }
1211
0
        DCHECK_EQ(column_index.min_values.size(), column_index.max_values.size());
1212
0
        if (!column_index.__isset.null_counts) {
1213
            // not set null or null counts;
1214
0
            return false;
1215
0
        }
1216
1217
0
        auto& offset_index = _col_offsets[parquet_col_id];
1218
0
        const auto& page_locations = offset_index.page_locations;
1219
1220
0
        sig_stat.col_schema = col_schema;
1221
0
        sig_stat.num_of_pages = num_of_pages;
1222
0
        sig_stat.encoded_min_value = column_index.min_values;
1223
0
        sig_stat.encoded_max_value = column_index.max_values;
1224
0
        sig_stat.is_all_null.resize(num_of_pages);
1225
0
        sig_stat.has_null.resize(num_of_pages);
1226
0
        sig_stat.ranges.resize(num_of_pages);
1227
1228
0
        for (int page_id = 0; page_id < num_of_pages; page_id++) {
1229
0
            sig_stat.is_all_null[page_id] = column_index.null_pages[page_id];
1230
0
            sig_stat.has_null[page_id] = column_index.null_counts[page_id] > 0;
1231
1232
0
            int64_t from = page_locations[page_id].first_row_index;
1233
0
            int64_t to = 0;
1234
0
            if (page_id == page_locations.size() - 1) {
1235
0
                to = row_group_index.last_row;
1236
0
            } else {
1237
0
                to = page_locations[page_id + 1].first_row_index;
1238
0
            }
1239
0
            sig_stat.ranges[page_id] = RowRange {from, to};
1240
0
        }
1241
1242
0
        sig_stat.available = true;
1243
0
        *ans = &sig_stat;
1244
0
        return true;
1245
0
    };
1246
0
    cached_page_index.row_group_range = {0, row_group.num_rows};
1247
0
    cached_page_index.get_stat_func = get_stat_func;
1248
1249
0
    candidate_row_ranges->add({0, row_group.num_rows});
1250
0
    for (const auto& predicate : push_down_pred) {
1251
0
        RowRanges tmp_row_range;
1252
0
        if (!predicate->evaluate_and(&cached_page_index, &tmp_row_range)) {
1253
            // no need read this row group.
1254
0
            candidate_row_ranges->clear();
1255
0
            return Status::OK();
1256
0
        }
1257
0
        RowRanges::ranges_intersection(*candidate_row_ranges, tmp_row_range, candidate_row_ranges);
1258
0
    }
1259
0
    return Status::OK();
1260
0
}
1261
1262
Status ParquetReader::_process_min_max_bloom_filter(
1263
        const RowGroupReader::RowGroupIndex& row_group_index, const tparquet::RowGroup& row_group,
1264
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1265
38
        RowRanges* row_ranges) {
1266
38
    SCOPED_RAW_TIMER(&_reader_statistics.row_group_filter_time);
1267
38
    if (!_filter_groups) {
1268
        // No row group filtering is needed;
1269
        // for example, Iceberg reads position delete files.
1270
1
        row_ranges->add({0, row_group.num_rows});
1271
1
        return Status::OK();
1272
1
    }
1273
1274
37
    if (_read_by_rows) {
1275
19
        auto group_start = row_group_index.first_row;
1276
19
        auto group_end = row_group_index.last_row;
1277
1278
47
        while (!_row_ids.empty()) {
1279
28
            auto v = _row_ids.front();
1280
28
            if (v < group_start) {
1281
0
                continue;
1282
28
            } else if (v < group_end) {
1283
28
                row_ranges->add(RowRange {v - group_start, v - group_start + 1});
1284
28
                _row_ids.pop_front();
1285
28
            } else {
1286
0
                break;
1287
0
            }
1288
28
        }
1289
19
    } else {
1290
18
        bool filter_this_row_group = false;
1291
18
        bool filtered_by_min_max = false;
1292
18
        bool filtered_by_bloom_filter = false;
1293
18
        RETURN_IF_ERROR(_process_column_stat_filter(row_group, push_down_pred,
1294
18
                                                    &filter_this_row_group, &filtered_by_min_max,
1295
18
                                                    &filtered_by_bloom_filter));
1296
        // Update statistics based on filter type
1297
18
        if (filter_this_row_group) {
1298
0
            if (filtered_by_min_max) {
1299
0
                _reader_statistics.filtered_row_groups_by_min_max++;
1300
0
            }
1301
0
            if (filtered_by_bloom_filter) {
1302
0
                _reader_statistics.filtered_row_groups_by_bloom_filter++;
1303
0
            }
1304
0
        }
1305
1306
18
        if (!filter_this_row_group) {
1307
18
            RETURN_IF_ERROR(_process_page_index_filter(row_group, row_group_index, push_down_pred,
1308
18
                                                       row_ranges));
1309
18
        }
1310
18
    }
1311
1312
37
    return Status::OK();
1313
37
}
1314
1315
Status ParquetReader::_process_column_stat_filter(
1316
        const tparquet::RowGroup& row_group,
1317
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1318
20
        bool* filter_group, bool* filtered_by_min_max, bool* filtered_by_bloom_filter) {
1319
    // If both filters are disabled, skip filtering
1320
20
    if (!_enable_filter_by_min_max && !_enable_filter_by_bloom_filter) {
1321
0
        return Status::OK();
1322
0
    }
1323
1324
    // Cache bloom filters for each column to avoid reading the same bloom filter multiple times
1325
    // when there are multiple predicates on the same column
1326
20
    std::unordered_map<int, std::unique_ptr<ParquetBlockSplitBloomFilter>> bloom_filter_cache;
1327
1328
    // Initialize output parameters
1329
20
    *filtered_by_min_max = false;
1330
20
    *filtered_by_bloom_filter = false;
1331
1332
20
    for (const auto& predicate : _push_down_predicates) {
1333
2
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_stat_func =
1334
4
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1335
                    // Check if min-max filter is enabled
1336
4
                    if (!_enable_filter_by_min_max) {
1337
0
                        return false;
1338
0
                    }
1339
4
                    auto* slot = _tuple_descriptor->slots()[cid];
1340
4
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1341
0
                        return false;
1342
0
                    }
1343
4
                    const auto& file_col_name =
1344
4
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1345
4
                    const FieldSchema* col_schema =
1346
4
                            _file_metadata->schema().get_column(file_col_name);
1347
4
                    int parquet_col_id = col_schema->physical_column_index;
1348
4
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1349
4
                    stat->col_schema = col_schema;
1350
4
                    return ParquetPredicate::read_column_stats(col_schema, meta_data,
1351
4
                                                               &_ignored_stats,
1352
4
                                                               _t_metadata->created_by, stat)
1353
4
                            .ok();
1354
4
                };
1355
2
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_bloom_filter_func =
1356
2
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1357
0
                    auto* slot = _tuple_descriptor->slots()[cid];
1358
0
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1359
0
                        return false;
1360
0
                    }
1361
0
                    const auto& file_col_name =
1362
0
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1363
0
                    const FieldSchema* col_schema =
1364
0
                            _file_metadata->schema().get_column(file_col_name);
1365
0
                    int parquet_col_id = col_schema->physical_column_index;
1366
0
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1367
0
                    if (!meta_data.__isset.bloom_filter_offset) {
1368
0
                        return false;
1369
0
                    }
1370
0
                    auto primitive_type =
1371
0
                            remove_nullable(col_schema->data_type)->get_primitive_type();
1372
0
                    if (!ParquetPredicate::bloom_filter_supported(primitive_type)) {
1373
0
                        return false;
1374
0
                    }
1375
1376
                    // Check if bloom filter is enabled
1377
0
                    if (!_enable_filter_by_bloom_filter) {
1378
0
                        return false;
1379
0
                    }
1380
1381
                    // Check cache first
1382
0
                    auto cache_iter = bloom_filter_cache.find(parquet_col_id);
1383
0
                    if (cache_iter != bloom_filter_cache.end()) {
1384
                        // Bloom filter already loaded for this column, reuse it
1385
0
                        stat->bloom_filter = std::move(cache_iter->second);
1386
0
                        bloom_filter_cache.erase(cache_iter);
1387
0
                        return stat->bloom_filter != nullptr;
1388
0
                    }
1389
1390
0
                    if (!stat->bloom_filter) {
1391
0
                        SCOPED_RAW_TIMER(&_reader_statistics.bloom_filter_read_time);
1392
0
                        auto st = ParquetPredicate::read_bloom_filter(
1393
0
                                meta_data, _tracing_file_reader, _io_ctx, stat);
1394
0
                        if (!st.ok()) {
1395
0
                            LOG(WARNING) << "Failed to read bloom filter for column "
1396
0
                                         << col_schema->name << " in file " << _scan_range.path
1397
0
                                         << ", status: " << st.to_string();
1398
0
                            stat->bloom_filter.reset();
1399
0
                            return false;
1400
0
                        }
1401
0
                    }
1402
0
                    return stat->bloom_filter != nullptr;
1403
0
                };
1404
2
        ParquetPredicate::ColumnStat stat;
1405
2
        stat.ctz = _ctz;
1406
2
        stat.get_stat_func = &get_stat_func;
1407
2
        stat.get_bloom_filter_func = &get_bloom_filter_func;
1408
1409
2
        if (!predicate->evaluate_and(&stat)) {
1410
1
            *filter_group = true;
1411
1412
            // Track which filter was used for filtering
1413
            // If bloom filter was loaded, it means bloom filter was used
1414
1
            if (stat.bloom_filter) {
1415
0
                *filtered_by_bloom_filter = true;
1416
0
            }
1417
            // If col_schema was set but no bloom filter, it means min-max stats were used
1418
1
            if (stat.col_schema && !stat.bloom_filter) {
1419
1
                *filtered_by_min_max = true;
1420
1
            }
1421
1422
1
            return Status::OK();
1423
1
        }
1424
1425
        // After evaluating, if the bloom filter was used, cache it for subsequent predicates
1426
1
        if (stat.bloom_filter) {
1427
            // Find the column id for caching
1428
0
            for (auto* slot : _tuple_descriptor->slots()) {
1429
0
                if (_table_info_node_ptr->children_column_exists(slot->col_name())) {
1430
0
                    const auto& file_col_name =
1431
0
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1432
0
                    const FieldSchema* col_schema =
1433
0
                            _file_metadata->schema().get_column(file_col_name);
1434
0
                    int parquet_col_id = col_schema->physical_column_index;
1435
0
                    if (stat.col_schema == col_schema) {
1436
0
                        bloom_filter_cache[parquet_col_id] = std::move(stat.bloom_filter);
1437
0
                        break;
1438
0
                    }
1439
0
                }
1440
0
            }
1441
0
        }
1442
1
    }
1443
1444
    // Update filter statistics if this row group was not filtered
1445
    // The statistics will be updated in _init_row_groups when filter_group is true
1446
19
    return Status::OK();
1447
20
}
1448
1449
74
int64_t ParquetReader::_get_column_start_offset(const tparquet::ColumnMetaData& column) const {
1450
74
    return has_dict_page(column) ? column.dictionary_page_offset : column.data_page_offset;
1451
74
}
1452
1453
14
void ParquetReader::_collect_profile() {
1454
14
    if (_profile == nullptr) {
1455
0
        return;
1456
0
    }
1457
1458
14
    if (_current_group_reader != nullptr) {
1459
14
        _current_group_reader->collect_profile_before_close();
1460
14
    }
1461
14
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups, _reader_statistics.filtered_row_groups);
1462
14
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_min_max,
1463
14
                   _reader_statistics.filtered_row_groups_by_min_max);
1464
14
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_bloom_filter,
1465
14
                   _reader_statistics.filtered_row_groups_by_bloom_filter);
1466
14
    COUNTER_UPDATE(_parquet_profile.to_read_row_groups, _reader_statistics.read_row_groups);
1467
14
    COUNTER_UPDATE(_parquet_profile.total_row_groups, _total_groups);
1468
14
    COUNTER_UPDATE(_parquet_profile.filtered_group_rows, _reader_statistics.filtered_group_rows);
1469
14
    COUNTER_UPDATE(_parquet_profile.filtered_page_rows, _reader_statistics.filtered_page_rows);
1470
14
    COUNTER_UPDATE(_parquet_profile.lazy_read_filtered_rows,
1471
14
                   _reader_statistics.lazy_read_filtered_rows);
1472
14
    COUNTER_UPDATE(_parquet_profile.filtered_bytes, _reader_statistics.filtered_bytes);
1473
14
    COUNTER_UPDATE(_parquet_profile.raw_rows_read, _reader_statistics.read_rows);
1474
14
    COUNTER_UPDATE(_parquet_profile.column_read_time, _reader_statistics.column_read_time);
1475
14
    COUNTER_UPDATE(_parquet_profile.parse_meta_time, _reader_statistics.parse_meta_time);
1476
14
    COUNTER_UPDATE(_parquet_profile.parse_footer_time, _reader_statistics.parse_footer_time);
1477
14
    COUNTER_UPDATE(_parquet_profile.file_reader_create_time,
1478
14
                   _reader_statistics.file_reader_create_time);
1479
14
    COUNTER_UPDATE(_parquet_profile.open_file_num, _reader_statistics.open_file_num);
1480
14
    COUNTER_UPDATE(_parquet_profile.page_index_filter_time,
1481
14
                   _reader_statistics.page_index_filter_time);
1482
14
    COUNTER_UPDATE(_parquet_profile.read_page_index_time, _reader_statistics.read_page_index_time);
1483
14
    COUNTER_UPDATE(_parquet_profile.parse_page_index_time,
1484
14
                   _reader_statistics.parse_page_index_time);
1485
14
    COUNTER_UPDATE(_parquet_profile.row_group_filter_time,
1486
14
                   _reader_statistics.row_group_filter_time);
1487
14
    COUNTER_UPDATE(_parquet_profile.file_footer_read_calls,
1488
14
                   _reader_statistics.file_footer_read_calls);
1489
14
    COUNTER_UPDATE(_parquet_profile.file_footer_hit_cache,
1490
14
                   _reader_statistics.file_footer_hit_cache);
1491
1492
14
    COUNTER_UPDATE(_parquet_profile.skip_page_header_num, _column_statistics.skip_page_header_num);
1493
14
    COUNTER_UPDATE(_parquet_profile.parse_page_header_num,
1494
14
                   _column_statistics.parse_page_header_num);
1495
14
    COUNTER_UPDATE(_parquet_profile.predicate_filter_time,
1496
14
                   _reader_statistics.predicate_filter_time);
1497
14
    COUNTER_UPDATE(_parquet_profile.dict_filter_rewrite_time,
1498
14
                   _reader_statistics.dict_filter_rewrite_time);
1499
14
    COUNTER_UPDATE(_parquet_profile.convert_time, _column_statistics.convert_time);
1500
14
    COUNTER_UPDATE(_parquet_profile.bloom_filter_read_time,
1501
14
                   _reader_statistics.bloom_filter_read_time);
1502
14
    COUNTER_UPDATE(_parquet_profile.page_index_read_calls,
1503
14
                   _column_statistics.page_index_read_calls);
1504
14
    COUNTER_UPDATE(_parquet_profile.decompress_time, _column_statistics.decompress_time);
1505
14
    COUNTER_UPDATE(_parquet_profile.decompress_cnt, _column_statistics.decompress_cnt);
1506
14
    COUNTER_UPDATE(_parquet_profile.page_read_counter, _column_statistics.page_read_counter);
1507
14
    COUNTER_UPDATE(_parquet_profile.page_cache_write_counter,
1508
14
                   _column_statistics.page_cache_write_counter);
1509
14
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_write_counter,
1510
14
                   _column_statistics.page_cache_compressed_write_counter);
1511
14
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_write_counter,
1512
14
                   _column_statistics.page_cache_decompressed_write_counter);
1513
14
    COUNTER_UPDATE(_parquet_profile.page_cache_hit_counter,
1514
14
                   _column_statistics.page_cache_hit_counter);
1515
14
    COUNTER_UPDATE(_parquet_profile.page_cache_missing_counter,
1516
14
                   _column_statistics.page_cache_missing_counter);
1517
14
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_hit_counter,
1518
14
                   _column_statistics.page_cache_compressed_hit_counter);
1519
14
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_hit_counter,
1520
14
                   _column_statistics.page_cache_decompressed_hit_counter);
1521
14
    COUNTER_UPDATE(_parquet_profile.decode_header_time, _column_statistics.decode_header_time);
1522
14
    COUNTER_UPDATE(_parquet_profile.read_page_header_time,
1523
14
                   _column_statistics.read_page_header_time);
1524
14
    COUNTER_UPDATE(_parquet_profile.decode_value_time, _column_statistics.decode_value_time);
1525
14
    COUNTER_UPDATE(_parquet_profile.decode_dict_time, _column_statistics.decode_dict_time);
1526
14
    COUNTER_UPDATE(_parquet_profile.decode_level_time, _column_statistics.decode_level_time);
1527
14
    COUNTER_UPDATE(_parquet_profile.decode_null_map_time, _column_statistics.decode_null_map_time);
1528
14
}
1529
1530
14
void ParquetReader::_collect_profile_before_close() {
1531
14
    _collect_profile();
1532
14
}
1533
1534
} // namespace doris