Coverage Report

Created: 2026-05-31 08:39

next uncovered line (L), next uncovered region (R), next uncovered branch (B)
be/src/format/parquet/vparquet_reader.cpp
Line
Count
Source
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// 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
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//
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
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// 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/runtime_filter_expr.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/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
19.2k
        : _profile(profile),
88
19.2k
          _scan_params(params),
89
19.2k
          _scan_range(range),
90
19.2k
          _batch_size(std::max(batch_size, 1UL)),
91
19.2k
          _range_start_offset(range.start_offset),
92
19.2k
          _range_size(range.size),
93
19.2k
          _ctz(ctz),
94
19.2k
          _io_ctx(io_ctx),
95
19.2k
          _state(state),
96
19.2k
          _enable_lazy_mat(enable_lazy_mat),
97
          _enable_filter_by_min_max(
98
19.2k
                  state == nullptr ? true
99
19.2k
                                   : state->query_options().enable_parquet_filter_by_min_max),
100
          _enable_filter_by_bloom_filter(
101
19.2k
                  state == nullptr ? true
102
19.2k
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
103
19.2k
    _meta_cache = meta_cache;
104
19.2k
    _init_profile();
105
19.2k
    _init_system_properties();
106
19.2k
    _init_file_description();
107
19.2k
}
108
109
37.6k
void ParquetReader::set_batch_size(size_t batch_size) {
110
37.6k
    if (_batch_size == batch_size) {
111
19.1k
        return;
112
19.1k
    }
113
18.5k
    _batch_size = batch_size;
114
18.5k
}
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
1.28k
        : _profile(nullptr),
168
1.28k
          _scan_params(params),
169
1.28k
          _scan_range(range),
170
18.4E
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
171
1.28k
          _io_ctx_holder(std::move(io_ctx_holder)),
172
1.28k
          _state(state),
173
1.28k
          _enable_lazy_mat(enable_lazy_mat),
174
          _enable_filter_by_min_max(
175
1.28k
                  state == nullptr ? true
176
1.28k
                                   : state->query_options().enable_parquet_filter_by_min_max),
177
          _enable_filter_by_bloom_filter(
178
1.28k
                  state == nullptr ? true
179
1.28k
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
180
1.28k
    _meta_cache = meta_cache;
181
1.28k
    _init_system_properties();
182
1.28k
    _init_file_description();
183
1.28k
}
184
185
20.5k
ParquetReader::~ParquetReader() {
186
20.5k
    _close_internal();
187
20.5k
}
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
19.2k
void ParquetReader::_init_profile() {
198
19.2k
    if (_profile != nullptr) {
199
19.1k
        static const char* parquet_profile = "ParquetReader";
200
19.1k
        ADD_TIMER_WITH_LEVEL(_profile, parquet_profile, 1);
201
202
19.1k
        _parquet_profile.filtered_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
203
19.1k
                _profile, "RowGroupsFiltered", TUnit::UNIT, parquet_profile, 1);
204
19.1k
        _parquet_profile.filtered_row_groups_by_min_max = ADD_CHILD_COUNTER_WITH_LEVEL(
205
19.1k
                _profile, "RowGroupsFilteredByMinMax", TUnit::UNIT, parquet_profile, 1);
206
19.1k
        _parquet_profile.filtered_row_groups_by_bloom_filter = ADD_CHILD_COUNTER_WITH_LEVEL(
207
19.1k
                _profile, "RowGroupsFilteredByBloomFilter", TUnit::UNIT, parquet_profile, 1);
208
19.1k
        _parquet_profile.to_read_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
209
19.1k
                _profile, "RowGroupsReadNum", TUnit::UNIT, parquet_profile, 1);
210
19.1k
        _parquet_profile.total_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
211
19.1k
                _profile, "RowGroupsTotalNum", TUnit::UNIT, parquet_profile, 1);
212
19.1k
        _parquet_profile.filtered_group_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
213
19.1k
                _profile, "FilteredRowsByGroup", TUnit::UNIT, parquet_profile, 1);
214
19.1k
        _parquet_profile.filtered_page_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
215
19.1k
                _profile, "FilteredRowsByPage", TUnit::UNIT, parquet_profile, 1);
216
19.1k
        _parquet_profile.lazy_read_filtered_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
217
19.1k
                _profile, "FilteredRowsByLazyRead", TUnit::UNIT, parquet_profile, 1);
218
19.1k
        _parquet_profile.filtered_bytes = ADD_CHILD_COUNTER_WITH_LEVEL(
219
19.1k
                _profile, "FilteredBytes", TUnit::BYTES, parquet_profile, 1);
220
19.1k
        _parquet_profile.raw_rows_read = ADD_CHILD_COUNTER_WITH_LEVEL(
221
19.1k
                _profile, "RawRowsRead", TUnit::UNIT, parquet_profile, 1);
222
19.1k
        _parquet_profile.column_read_time =
223
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ColumnReadTime", parquet_profile, 1);
224
19.1k
        _parquet_profile.parse_meta_time =
225
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseMetaTime", parquet_profile, 1);
226
19.1k
        _parquet_profile.parse_footer_time =
227
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseFooterTime", parquet_profile, 1);
228
19.1k
        _parquet_profile.file_reader_create_time =
229
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "FileReaderCreateTime", parquet_profile, 1);
230
19.1k
        _parquet_profile.open_file_num =
231
19.1k
                ADD_CHILD_COUNTER_WITH_LEVEL(_profile, "FileNum", TUnit::UNIT, parquet_profile, 1);
232
19.1k
        _parquet_profile.page_index_read_calls =
233
19.1k
                ADD_COUNTER_WITH_LEVEL(_profile, "PageIndexReadCalls", TUnit::UNIT, 1);
234
19.1k
        _parquet_profile.page_index_filter_time =
235
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexFilterTime", parquet_profile, 1);
236
19.1k
        _parquet_profile.read_page_index_time =
237
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexReadTime", parquet_profile, 1);
238
19.1k
        _parquet_profile.parse_page_index_time =
239
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexParseTime", parquet_profile, 1);
240
19.1k
        _parquet_profile.row_group_filter_time =
241
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "RowGroupFilterTime", parquet_profile, 1);
242
19.1k
        _parquet_profile.file_footer_read_calls =
243
19.1k
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterReadCalls", TUnit::UNIT, 1);
244
19.1k
        _parquet_profile.file_footer_hit_cache =
245
19.1k
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterHitCache", TUnit::UNIT, 1);
246
19.1k
        _parquet_profile.decompress_time =
247
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecompressTime", parquet_profile, 1);
248
19.1k
        _parquet_profile.decompress_cnt = ADD_CHILD_COUNTER_WITH_LEVEL(
249
19.1k
                _profile, "DecompressCount", TUnit::UNIT, parquet_profile, 1);
250
19.1k
        _parquet_profile.page_read_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
251
19.1k
                _profile, "PageReadCount", TUnit::UNIT, parquet_profile, 1);
252
19.1k
        _parquet_profile.page_cache_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
253
19.1k
                _profile, "PageCacheWriteCount", TUnit::UNIT, parquet_profile, 1);
254
19.1k
        _parquet_profile.page_cache_compressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
255
19.1k
                _profile, "PageCacheCompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
256
19.1k
        _parquet_profile.page_cache_decompressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
257
19.1k
                _profile, "PageCacheDecompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
258
19.1k
        _parquet_profile.page_cache_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
259
19.1k
                _profile, "PageCacheHitCount", TUnit::UNIT, parquet_profile, 1);
260
19.1k
        _parquet_profile.page_cache_missing_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
261
19.1k
                _profile, "PageCacheMissingCount", TUnit::UNIT, parquet_profile, 1);
262
19.1k
        _parquet_profile.page_cache_compressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
263
19.1k
                _profile, "PageCacheCompressedHitCount", TUnit::UNIT, parquet_profile, 1);
264
19.1k
        _parquet_profile.page_cache_decompressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
265
19.1k
                _profile, "PageCacheDecompressedHitCount", TUnit::UNIT, parquet_profile, 1);
266
19.1k
        _parquet_profile.decode_header_time =
267
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderDecodeTime", parquet_profile, 1);
268
19.1k
        _parquet_profile.read_page_header_time =
269
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderReadTime", parquet_profile, 1);
270
19.1k
        _parquet_profile.decode_value_time =
271
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeValueTime", parquet_profile, 1);
272
19.1k
        _parquet_profile.decode_dict_time =
273
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeDictTime", parquet_profile, 1);
274
19.1k
        _parquet_profile.decode_level_time =
275
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeLevelTime", parquet_profile, 1);
276
19.1k
        _parquet_profile.decode_null_map_time =
277
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeNullMapTime", parquet_profile, 1);
278
19.1k
        _parquet_profile.skip_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
279
19.1k
                _profile, "SkipPageHeaderNum", TUnit::UNIT, parquet_profile, 1);
280
19.1k
        _parquet_profile.parse_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
281
19.1k
                _profile, "ParsePageHeaderNum", TUnit::UNIT, parquet_profile, 1);
282
19.1k
        _parquet_profile.predicate_filter_time =
283
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PredicateFilterTime", parquet_profile, 1);
284
19.1k
        _parquet_profile.dict_filter_rewrite_time =
285
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DictFilterRewriteTime", parquet_profile, 1);
286
19.1k
        _parquet_profile.convert_time =
287
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ConvertTime", parquet_profile, 1);
288
19.1k
        _parquet_profile.bloom_filter_read_time =
289
19.1k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "BloomFilterReadTime", parquet_profile, 1);
290
19.1k
    }
291
19.2k
}
292
293
17.3k
Status ParquetReader::close() {
294
17.3k
    _close_internal();
295
17.3k
    return Status::OK();
296
17.3k
}
297
298
37.8k
void ParquetReader::_close_internal() {
299
37.8k
    if (!_closed) {
300
20.5k
        _current_group_reader.reset();
301
20.5k
        _tracing_file_reader.reset();
302
20.5k
        _file_reader.reset();
303
20.5k
        _closed = true;
304
20.5k
    }
305
37.8k
}
306
307
38.7k
Status ParquetReader::_open_file() {
308
38.7k
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
309
0
        return Status::EndOfFile("stop");
310
0
    }
311
38.7k
    if (_file_reader == nullptr) {
312
19.8k
        SCOPED_RAW_TIMER(&_reader_statistics.file_reader_create_time);
313
19.8k
        ++_reader_statistics.open_file_num;
314
19.8k
        _file_description.mtime =
315
19.8k
                _scan_range.__isset.modification_time ? _scan_range.modification_time : 0;
316
19.8k
        io::FileReaderOptions reader_options =
317
19.8k
                FileFactory::get_reader_options(_state, _file_description);
318
19.8k
        _file_reader = DORIS_TRY(io::DelegateReader::create_file_reader(
319
19.8k
                _profile, _system_properties, _file_description, reader_options,
320
19.8k
                io::DelegateReader::AccessMode::RANDOM, _io_ctx));
321
19.8k
        _tracing_file_reader = _io_ctx ? std::make_shared<io::TracingFileReader>(
322
19.7k
                                                 _file_reader, _io_ctx->file_reader_stats)
323
19.8k
                                       : _file_reader;
324
19.8k
    }
325
326
38.7k
    if (_file_metadata == nullptr) {
327
19.8k
        SCOPED_RAW_TIMER(&_reader_statistics.parse_footer_time);
328
19.8k
        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
19.8k
        size_t meta_size = 0;
335
19.8k
        bool enable_mapping_varbinary = _scan_params.__isset.enable_mapping_varbinary
336
19.8k
                                                ? _scan_params.enable_mapping_varbinary
337
19.8k
                                                : false;
338
19.8k
        bool enable_mapping_timestamp_tz = _scan_params.__isset.enable_mapping_timestamp_tz
339
19.8k
                                                   ? _scan_params.enable_mapping_timestamp_tz
340
19.8k
                                                   : false;
341
19.8k
        if (_meta_cache == nullptr) {
342
            // wrap _file_metadata with unique ptr, so that it can be released finally.
343
1.32k
            RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
344
1.32k
                                                &meta_size, _io_ctx, enable_mapping_varbinary,
345
1.32k
                                                enable_mapping_timestamp_tz));
346
1.32k
            _file_metadata = _file_metadata_ptr.get();
347
            // parse magic number & parse meta data
348
1.32k
            _reader_statistics.file_footer_read_calls += 1;
349
18.5k
        } else {
350
18.5k
            const auto& file_meta_cache_key =
351
18.5k
                    FileMetaCache::get_key(_tracing_file_reader, _file_description);
352
18.5k
            if (!_meta_cache->lookup(file_meta_cache_key, &_meta_cache_handle)) {
353
4.49k
                RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
354
4.49k
                                                    &meta_size, _io_ctx, enable_mapping_varbinary,
355
4.49k
                                                    enable_mapping_timestamp_tz));
356
                // _file_metadata_ptr.release() : move control of _file_metadata to _meta_cache_handle
357
4.49k
                _meta_cache->insert(file_meta_cache_key, _file_metadata_ptr.release(),
358
4.49k
                                    &_meta_cache_handle);
359
4.49k
                _file_metadata = _meta_cache_handle.data<FileMetaData>();
360
4.49k
                _reader_statistics.file_footer_read_calls += 1;
361
14.0k
            } else {
362
14.0k
                _reader_statistics.file_footer_hit_cache++;
363
14.0k
            }
364
18.5k
            _file_metadata = _meta_cache_handle.data<FileMetaData>();
365
18.5k
        }
366
367
19.8k
        if (_file_metadata == nullptr) {
368
0
            return Status::InternalError("failed to get file meta data: {}",
369
0
                                         _file_description.path);
370
0
        }
371
19.8k
    }
372
38.7k
    return Status::OK();
373
38.7k
}
374
375
18.0k
Status ParquetReader::get_file_metadata_schema(const FieldDescriptor** ptr) {
376
18.0k
    RETURN_IF_ERROR(_open_file());
377
18.0k
    DCHECK(_file_metadata != nullptr);
378
18.0k
    *ptr = &_file_metadata->schema();
379
18.0k
    return Status::OK();
380
18.0k
}
381
382
20.5k
void ParquetReader::_init_system_properties() {
383
20.5k
    if (_scan_range.__isset.file_type) {
384
        // for compatibility
385
19.1k
        _system_properties.system_type = _scan_range.file_type;
386
19.1k
    } else {
387
1.37k
        _system_properties.system_type = _scan_params.file_type;
388
1.37k
    }
389
20.5k
    _system_properties.properties = _scan_params.properties;
390
20.5k
    _system_properties.hdfs_params = _scan_params.hdfs_params;
391
20.5k
    if (_scan_params.__isset.broker_addresses) {
392
22
        _system_properties.broker_addresses.assign(_scan_params.broker_addresses.begin(),
393
22
                                                   _scan_params.broker_addresses.end());
394
22
    }
395
20.5k
}
396
397
20.5k
void ParquetReader::_init_file_description() {
398
20.5k
    _file_description.path = _scan_range.path;
399
20.5k
    _file_description.file_size = _scan_range.__isset.file_size ? _scan_range.file_size : -1;
400
20.5k
    if (_scan_range.__isset.fs_name) {
401
8.55k
        _file_description.fs_name = _scan_range.fs_name;
402
8.55k
    }
403
20.5k
    if (_scan_range.__isset.file_cache_admission) {
404
17.9k
        _file_description.file_cache_admission = _scan_range.file_cache_admission;
405
17.9k
    }
406
20.5k
}
407
408
1.66k
Status ParquetReader::on_before_init_reader(ReaderInitContext* ctx) {
409
1.66k
    _column_descs = ctx->column_descs;
410
1.66k
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
411
1.66k
    RETURN_IF_ERROR(
412
1.66k
            _extract_partition_values(*ctx->range, ctx->tuple_descriptor, _fill_partition_values));
413
7.27k
    for (auto& desc : *ctx->column_descs) {
414
7.27k
        if (desc.category == ColumnCategory::REGULAR ||
415
7.27k
            desc.category == ColumnCategory::GENERATED) {
416
7.24k
            ctx->column_names.push_back(desc.name);
417
7.24k
        } else if (desc.category == ColumnCategory::SYNTHESIZED &&
418
32
                   desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
419
30
            auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
420
30
            this->register_synthesized_column_handler(
421
30
                    desc.name,
422
30
                    [iter = std::move(topn_row_id_column_iter), this, &desc](
423
183
                            Block* block, size_t rows) -> Status {
424
183
                        return fill_topn_row_id(iter, desc.name, block, rows);
425
183
                    });
426
30
            continue;
427
30
        }
428
7.27k
    }
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
1.66k
    if (ctx->tuple_descriptor != nullptr) {
434
1.65k
        const FieldDescriptor* field_desc = nullptr;
435
1.65k
        RETURN_IF_ERROR(get_file_metadata_schema(&field_desc));
436
1.65k
        RETURN_IF_ERROR(TableSchemaChangeHelper::BuildTableInfoUtil::by_parquet_name(
437
1.65k
                ctx->tuple_descriptor, *field_desc, ctx->table_info_node));
438
1.65k
    }
439
440
1.66k
    return Status::OK();
441
1.66k
}
442
443
18.5k
Status ParquetReader::_open_file_reader(ReaderInitContext* /*ctx*/) {
444
18.5k
    return _open_file();
445
18.5k
}
446
447
18.4k
Status ParquetReader::_do_init_reader(ReaderInitContext* base_ctx) {
448
18.4k
    auto* ctx = checked_context_cast<ParquetInitContext>(base_ctx);
449
18.4k
    _col_name_to_block_idx = base_ctx->col_name_to_block_idx;
450
18.4k
    _tuple_descriptor = ctx->tuple_descriptor;
451
18.4k
    _row_descriptor = ctx->row_descriptor;
452
18.4k
    _colname_to_slot_id = ctx->colname_to_slot_id;
453
18.4k
    _not_single_slot_filter_conjuncts = ctx->not_single_slot_filter_conjuncts;
454
18.4k
    _slot_id_to_filter_conjuncts = ctx->slot_id_to_filter_conjuncts;
455
18.4k
    _filter_groups = ctx->filter_groups;
456
18.4k
    _table_info_node_ptr = base_ctx->table_info_node;
457
18.4k
    _column_ids = base_ctx->column_ids;
458
18.4k
    _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
18.4E
    DCHECK(_file_metadata != nullptr)
462
18.4E
            << "ParquetReader::_do_init_reader called without _open_file_reader";
463
18.4k
    _t_metadata = &(_file_metadata->to_thrift());
464
465
18.4k
    SCOPED_RAW_TIMER(&_reader_statistics.parse_meta_time);
466
18.4k
    _total_groups = _t_metadata->row_groups.size();
467
18.4k
    if (_total_groups == 0) {
468
6
        return Status::EndOfFile("init reader failed, empty parquet file: " + _scan_range.path);
469
6
    }
470
18.4k
    _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
18.4k
    if (has_column_descs()) {
476
17.3k
        _fill_missing_cols.clear();
477
17.3k
        _fill_missing_defaults.clear();
478
63.2k
        for (const auto& col_name : base_ctx->column_names) {
479
63.2k
            if (!_table_info_node_ptr->children_column_exists(col_name)) {
480
2.09k
                _fill_missing_cols.insert(col_name);
481
2.09k
            }
482
63.2k
        }
483
17.3k
        if (_column_descs && !_fill_missing_cols.empty()) {
484
6.58k
            for (const auto& desc : *_column_descs) {
485
6.58k
                if (_fill_missing_cols.contains(desc.name) &&
486
6.58k
                    !_fill_partition_values.contains(desc.name)) {
487
2.09k
                    _fill_missing_defaults[desc.name] = desc.default_expr;
488
2.09k
                }
489
6.58k
            }
490
1.52k
        }
491
17.3k
    }
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
18.4k
    _init_read_columns(base_ctx->column_names);
496
497
    // build column predicates for column lazy read
498
18.5k
    if (ctx->conjuncts != nullptr) {
499
18.5k
        _lazy_read_ctx.conjuncts = *ctx->conjuncts;
500
18.5k
    }
501
18.5k
    if (ctx->slot_id_to_predicates != nullptr) {
502
18.5k
        _lazy_read_ctx.slot_id_to_predicates = *ctx->slot_id_to_predicates;
503
18.5k
    }
504
505
    // ---- Inlined set_fill_columns logic (partition/missing/synthesized classification) ----
506
507
    // 1. Collect predicate columns from conjuncts for lazy materialization
508
18.4k
    std::unordered_map<std::string, std::pair<uint32_t, int>> predicate_columns;
509
18.4k
    _collect_predicate_columns_from_conjuncts(predicate_columns);
510
511
    // 2. Classify read/partition/missing/synthesized columns into lazy vs predicate groups
512
18.4k
    _classify_columns_for_lazy_read(predicate_columns, _fill_partition_values,
513
18.4k
                                    _fill_missing_defaults);
514
515
    // 3. Populate col_names vectors for ColumnProcessor path
516
18.4k
    for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
517
183
        _lazy_read_ctx.predicate_partition_col_names.emplace_back(kv.first);
518
183
    }
519
18.4k
    for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
520
722
        _lazy_read_ctx.predicate_missing_col_names.emplace_back(kv.first);
521
722
    }
522
18.4k
    for (auto& kv : _lazy_read_ctx.partition_columns) {
523
2.11k
        _lazy_read_ctx.partition_col_names.emplace_back(kv.first);
524
2.11k
    }
525
18.4k
    for (auto& kv : _lazy_read_ctx.missing_columns) {
526
2.03k
        _lazy_read_ctx.missing_col_names.emplace_back(kv.first);
527
2.03k
    }
528
529
18.4k
    if (_filter_groups && (_total_groups == 0 || _t_metadata->num_rows == 0 || _range_size < 0)) {
530
2
        return Status::EndOfFile("No row group to read");
531
2
    }
532
533
18.4k
    return Status::OK();
534
18.4k
}
535
536
18.4k
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
18.4k
    auto schema_desc = _file_metadata->schema();
541
18.4k
    std::map<std::string, std::string> required_file_columns;
542
65.6k
    for (const auto& col_name : column_names) {
543
65.6k
        if (_fill_missing_cols.contains(col_name)) {
544
2.09k
            continue;
545
2.09k
        }
546
63.5k
        std::string file_col = col_name;
547
63.5k
        if (_table_info_node_ptr && _table_info_node_ptr->children_column_exists(col_name)) {
548
63.5k
            file_col = _table_info_node_ptr->children_file_column_name(col_name);
549
63.5k
        }
550
63.5k
        required_file_columns[file_col] = col_name;
551
63.5k
    }
552
171k
    for (int i = 0; i < schema_desc.size(); ++i) {
553
153k
        const auto& name = schema_desc.get_column(i)->name;
554
153k
        if (required_file_columns.contains(name)) {
555
63.5k
            _read_file_columns.emplace_back(name);
556
63.5k
            _read_table_columns.emplace_back(required_file_columns[name]);
557
63.5k
            _read_table_columns_set.insert(required_file_columns[name]);
558
63.5k
        }
559
153k
    }
560
18.4k
}
561
562
7.98k
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
7.98k
    return _table_info_node_ptr->children_column_exists(expr_name) &&
569
7.98k
           _read_table_columns_set.contains(expr_name);
570
7.98k
}
571
572
7.65k
bool ParquetReader::_type_matches(const int cid) const {
573
7.65k
    auto* slot = _tuple_descriptor->slots()[cid];
574
7.65k
    auto table_col_type = remove_nullable(slot->type());
575
576
7.65k
    const auto& file_col_name = _table_info_node_ptr->children_file_column_name(slot->col_name());
577
7.65k
    const auto& file_col_type =
578
7.65k
            remove_nullable(_file_metadata->schema().get_column(file_col_name)->data_type);
579
580
7.65k
    return (table_col_type->get_primitive_type() == file_col_type->get_primitive_type()) &&
581
7.65k
           !is_complex_type(table_col_type->get_primitive_type());
582
7.65k
}
583
584
void ParquetReader::_collect_predicate_columns_from_conjuncts(
585
18.4k
        std::unordered_map<std::string, std::pair<uint32_t, int>>& predicate_columns) {
586
36.8k
    std::function<void(VExpr * expr)> visit_slot = [&](VExpr* expr) {
587
36.8k
        if (expr->is_slot_ref()) {
588
11.4k
            VSlotRef* slot_ref = static_cast<VSlotRef*>(expr);
589
11.4k
            auto expr_name = slot_ref->expr_name();
590
11.4k
            predicate_columns.emplace(expr_name,
591
11.4k
                                      std::make_pair(slot_ref->column_id(), slot_ref->slot_id()));
592
11.4k
            if (slot_ref->column_id() == 0) {
593
8.12k
                _lazy_read_ctx.resize_first_column = false;
594
8.12k
            }
595
11.4k
            return;
596
11.4k
        }
597
25.7k
        for (auto& child : expr->children()) {
598
25.7k
            visit_slot(child.get());
599
25.7k
        }
600
25.3k
    };
601
602
18.4k
    for (const auto& conjunct : _lazy_read_ctx.conjuncts) {
603
11.2k
        auto expr = conjunct->root();
604
11.2k
        if (expr->is_rf_wrapper()) {
605
3.63k
            RuntimeFilterExpr* runtime_filter = assert_cast<RuntimeFilterExpr*>(expr.get());
606
3.63k
            auto filter_impl = runtime_filter->get_impl();
607
3.63k
            visit_slot(filter_impl.get());
608
7.57k
        } else {
609
7.57k
            visit_slot(expr.get());
610
7.57k
        }
611
11.2k
    }
612
613
18.4k
    if (!_lazy_read_ctx.slot_id_to_predicates.empty()) {
614
16.6k
        auto and_pred = AndBlockColumnPredicate::create_unique();
615
63.6k
        for (const auto& entry : _lazy_read_ctx.slot_id_to_predicates) {
616
63.6k
            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
8.07k
                if (!has_column_optimization(pred->col_name(), ColumnOptimizationTypes::MIN_MAX)) {
620
13
                    continue;
621
13
                }
622
8.06k
                if (!_exists_in_file(pred->col_name()) || !_type_matches(pred->column_id())) {
623
574
                    continue;
624
574
                }
625
7.48k
                and_pred->add_column_predicate(
626
7.48k
                        SingleColumnBlockPredicate::create_unique(pred->clone(pred->column_id())));
627
7.48k
            }
628
63.6k
        }
629
16.6k
        if (and_pred->num_of_column_predicate() > 0) {
630
4.68k
            _push_down_predicates.push_back(std::move(and_pred));
631
4.68k
        }
632
16.6k
    }
633
18.4k
}
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
18.3k
        const std::unordered_map<std::string, VExprContextSPtr>& missing_columns) {
641
18.3k
    const FieldDescriptor& schema = _file_metadata->schema();
642
18.3k
    auto predicate_columns = predicate_conjuncts_columns;
643
18.3k
#ifndef BE_TEST
644
18.3k
    for (const auto& [col_name, _] : _generated_col_handlers) {
645
218
        int slot_id = -1;
646
697
        for (auto slot : _tuple_descriptor->slots()) {
647
697
            if (slot->col_name() == col_name) {
648
217
                slot_id = slot->id();
649
217
                break;
650
217
            }
651
697
        }
652
218
        DCHECK(slot_id != -1) << "slot id should not be -1 for generated column: " << col_name;
653
218
        auto column_index = _row_descriptor->get_column_id(slot_id);
654
218
        if (column_index == 0) {
655
11
            _lazy_read_ctx.resize_first_column = false;
656
11
        }
657
        // assume generated columns are only used for predicate push down.
658
218
        predicate_columns.emplace(col_name, std::make_pair(column_index, slot_id));
659
218
    }
660
661
18.3k
    for (const auto& [col_name, _] : _synthesized_col_handlers) {
662
1.10k
        int slot_id = -1;
663
2.68k
        for (auto slot : _tuple_descriptor->slots()) {
664
2.68k
            if (slot->col_name() == col_name) {
665
1.10k
                slot_id = slot->id();
666
1.10k
                break;
667
1.10k
            }
668
2.68k
        }
669
1.10k
        DCHECK(slot_id != -1) << "slot id should not be -1 for synthesized column: " << col_name;
670
1.10k
        auto column_index = _row_descriptor->get_column_id(slot_id);
671
1.10k
        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
1.10k
        _lazy_read_ctx.all_predicate_col_ids.emplace_back(column_index);
676
1.10k
    }
677
18.3k
#endif
678
63.0k
    for (auto& read_table_col : _read_table_columns) {
679
63.0k
        _lazy_read_ctx.all_read_columns.emplace_back(read_table_col);
680
681
63.0k
        auto file_column_name = _table_info_node_ptr->children_file_column_name(read_table_col);
682
63.0k
        PrimitiveType column_type =
683
63.0k
                schema.get_column(file_column_name)->data_type->get_primitive_type();
684
63.0k
        if (is_complex_type(column_type)) {
685
16.6k
            _lazy_read_ctx.has_complex_type = true;
686
16.6k
        }
687
63.0k
        if (predicate_columns.size() > 0) {
688
19.6k
            auto iter = predicate_columns.find(read_table_col);
689
19.6k
            if (iter == predicate_columns.end()) {
690
11.9k
                _lazy_read_ctx.lazy_read_columns.emplace_back(read_table_col);
691
11.9k
            } else {
692
7.67k
                _lazy_read_ctx.predicate_columns.first.emplace_back(iter->first);
693
7.67k
                _lazy_read_ctx.predicate_columns.second.emplace_back(iter->second.second);
694
7.67k
                _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
695
7.67k
            }
696
19.6k
        }
697
63.0k
    }
698
699
18.3k
    for (auto& kv : partition_columns) {
700
2.15k
        auto iter = predicate_columns.find(kv.first);
701
2.15k
        if (iter == predicate_columns.end()) {
702
1.97k
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
703
1.97k
        } else {
704
177
            _lazy_read_ctx.predicate_partition_columns.emplace(kv.first, kv.second);
705
177
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
706
177
        }
707
2.15k
    }
708
709
18.3k
    for (auto& kv : missing_columns) {
710
2.09k
        auto iter = predicate_columns.find(kv.first);
711
2.09k
        if (iter != predicate_columns.end()) {
712
            //For check missing column :   missing column == xx, missing column is null,missing column is not null.
713
721
            if (_slot_id_to_filter_conjuncts->find(iter->second.second) !=
714
721
                _slot_id_to_filter_conjuncts->end()) {
715
413
                for (auto& ctx : _slot_id_to_filter_conjuncts->find(iter->second.second)->second) {
716
413
                    _lazy_read_ctx.missing_columns_conjuncts.emplace_back(ctx);
717
413
                }
718
408
            }
719
721
            _lazy_read_ctx.predicate_missing_columns.emplace(kv.first, kv.second);
720
721
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
721
1.37k
        } else {
722
1.37k
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
723
1.37k
        }
724
2.09k
    }
725
726
18.4k
    if (_enable_lazy_mat && _lazy_read_ctx.predicate_columns.first.size() > 0 &&
727
18.3k
        _lazy_read_ctx.lazy_read_columns.size() > 0) {
728
3.70k
        _lazy_read_ctx.can_lazy_read = true;
729
3.70k
    }
730
731
18.3k
    if (!_lazy_read_ctx.can_lazy_read) {
732
14.7k
        for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
733
151
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
734
151
        }
735
14.7k
        for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
736
669
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
737
669
        }
738
14.7k
    }
739
18.3k
}
740
741
// init file reader and file metadata for parsing schema
742
2.04k
Status ParquetReader::init_schema_reader() {
743
2.04k
    RETURN_IF_ERROR(_open_file());
744
2.04k
    _t_metadata = &(_file_metadata->to_thrift());
745
2.04k
    return Status::OK();
746
2.04k
}
747
748
Status ParquetReader::get_parsed_schema(std::vector<std::string>* col_names,
749
1.28k
                                        std::vector<DataTypePtr>* col_types) {
750
1.28k
    _total_groups = _t_metadata->row_groups.size();
751
1.28k
    auto schema_desc = _file_metadata->schema();
752
8.29k
    for (int i = 0; i < schema_desc.size(); ++i) {
753
        // Get the Column Reader for the boolean column
754
7.01k
        col_names->emplace_back(schema_desc.get_column(i)->name);
755
7.01k
        col_types->emplace_back(make_nullable(schema_desc.get_column(i)->data_type));
756
7.01k
    }
757
1.28k
    return Status::OK();
758
1.28k
}
759
760
Status ParquetReader::_get_columns_impl(
761
17.1k
        std::unordered_map<std::string, DataTypePtr>* name_to_type) {
762
17.1k
    const auto& schema_desc = _file_metadata->schema();
763
17.1k
    std::unordered_set<std::string> column_names;
764
17.1k
    schema_desc.get_column_names(&column_names);
765
151k
    for (auto& name : column_names) {
766
151k
        auto field = schema_desc.get_column(name);
767
151k
        name_to_type->emplace(name, field->data_type);
768
151k
    }
769
17.1k
    return Status::OK();
770
17.1k
}
771
772
40.4k
Status ParquetReader::_do_get_next_block(Block* block, size_t* read_rows, bool* eof) {
773
40.4k
    if (_current_group_reader == nullptr || _row_group_eof) {
774
22.4k
        Status st = _next_row_group_reader();
775
22.4k
        if (!st.ok() && !st.is<ErrorCode::END_OF_FILE>()) {
776
0
            return st;
777
0
        }
778
22.4k
        if (_current_group_reader == nullptr || _row_group_eof || st.is<ErrorCode::END_OF_FILE>()) {
779
2.92k
            _current_group_reader.reset(nullptr);
780
2.92k
            _row_group_eof = true;
781
2.92k
            *read_rows = 0;
782
2.92k
            *eof = true;
783
2.92k
            return Status::OK();
784
2.92k
        }
785
22.4k
    }
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
37.4k
    const int64_t max_block_bytes =
791
37.5k
            (_state != nullptr && _state->query_type() == TQueryType::LOAD &&
792
37.4k
             config::load_reader_max_block_bytes > 0)
793
37.4k
                    ? config::load_reader_max_block_bytes
794
37.4k
                    : 0;
795
37.4k
    if (max_block_bytes > 0 && _load_bytes_per_row > 0) {
796
95
        _batch_size = std::max((size_t)1,
797
95
                               (size_t)((int64_t)max_block_bytes / (int64_t)_load_bytes_per_row));
798
95
    }
799
800
37.4k
    SCOPED_RAW_TIMER(&_reader_statistics.column_read_time);
801
37.4k
    Status batch_st =
802
37.4k
            _current_group_reader->next_batch(block, _batch_size, read_rows, &_row_group_eof);
803
37.4k
    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
37.4k
    if (!batch_st.ok()) {
812
10
        return Status::InternalError("Read parquet file {} failed, reason = {}", _scan_range.path,
813
10
                                     batch_st.to_string());
814
10
    }
815
816
37.4k
    if (max_block_bytes > 0 && *read_rows > 0) {
817
1.06k
        _load_bytes_per_row = block->bytes() / *read_rows;
818
1.06k
    }
819
820
37.4k
    if (_row_group_eof) {
821
19.4k
        auto column_st = _current_group_reader->merged_column_statistics();
822
19.4k
        _column_statistics.merge(column_st);
823
19.4k
        _reader_statistics.lazy_read_filtered_rows +=
824
19.4k
                _current_group_reader->lazy_read_filtered_rows();
825
19.4k
        _reader_statistics.predicate_filter_time += _current_group_reader->predicate_filter_time();
826
19.4k
        _reader_statistics.dict_filter_rewrite_time +=
827
19.4k
                _current_group_reader->dict_filter_rewrite_time();
828
19.4k
        if (_io_ctx) {
829
19.3k
            _io_ctx->condition_cache_filtered_rows +=
830
19.3k
                    _current_group_reader->condition_cache_filtered_rows();
831
19.3k
        }
832
833
19.4k
        if (_current_row_group_index.row_group_id + 1 == _total_groups) {
834
15.1k
            *eof = true;
835
15.1k
        } else {
836
4.22k
            *eof = false;
837
4.22k
        }
838
19.4k
    }
839
37.4k
    return Status::OK();
840
37.4k
}
841
842
RowGroupReader::PositionDeleteContext ParquetReader::_get_position_delete_ctx(
843
19.5k
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index) {
844
19.5k
    if (_delete_rows == nullptr) {
845
18.0k
        return RowGroupReader::PositionDeleteContext(row_group.num_rows, row_group_index.first_row);
846
18.0k
    }
847
1.51k
    const int64_t* delete_rows = &(*_delete_rows)[0];
848
1.51k
    const int64_t* delete_rows_end = delete_rows + _delete_rows->size();
849
1.51k
    const int64_t* start_pos = std::lower_bound(delete_rows + _delete_rows_index, delete_rows_end,
850
1.51k
                                                row_group_index.first_row);
851
1.51k
    int64_t start_index = start_pos - delete_rows;
852
1.51k
    const int64_t* end_pos = std::lower_bound(start_pos, delete_rows_end, row_group_index.last_row);
853
1.51k
    int64_t end_index = end_pos - delete_rows;
854
1.51k
    _delete_rows_index = end_index;
855
1.51k
    return RowGroupReader::PositionDeleteContext(*_delete_rows, row_group.num_rows,
856
1.51k
                                                 row_group_index.first_row, start_index, end_index);
857
19.5k
}
858
859
22.4k
Status ParquetReader::_next_row_group_reader() {
860
22.4k
    if (_current_group_reader != nullptr) {
861
4.20k
        _current_group_reader->collect_profile_before_close();
862
4.20k
    }
863
864
22.4k
    RowRanges candidate_row_ranges;
865
51.9k
    while (++_current_row_group_index.row_group_id < _total_groups) {
866
48.9k
        const auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
867
48.9k
        _current_row_group_index.first_row = _current_row_group_index.last_row;
868
48.9k
        _current_row_group_index.last_row = _current_row_group_index.last_row + row_group.num_rows;
869
870
48.9k
        if (_filter_groups && _is_misaligned_range_group(row_group)) {
871
25.7k
            continue;
872
25.7k
        }
873
874
23.2k
        candidate_row_ranges.clear();
875
        // The range of lines to be read is determined by the push down predicate.
876
23.2k
        RETURN_IF_ERROR(_process_min_max_bloom_filter(
877
23.2k
                _current_row_group_index, row_group, _push_down_predicates, &candidate_row_ranges));
878
879
23.2k
        std::function<int64_t(const FieldSchema*)> column_compressed_size =
880
128k
                [&row_group, &column_compressed_size](const FieldSchema* field) -> int64_t {
881
128k
            if (field->physical_column_index >= 0) {
882
104k
                int parquet_col_id = field->physical_column_index;
883
104k
                if (row_group.columns[parquet_col_id].__isset.meta_data) {
884
104k
                    return row_group.columns[parquet_col_id].meta_data.total_compressed_size;
885
104k
                }
886
18.4E
                return 0;
887
104k
            }
888
23.3k
            int64_t size = 0;
889
39.4k
            for (const FieldSchema& child : field->children) {
890
39.4k
                size += column_compressed_size(&child);
891
39.4k
            }
892
23.3k
            return size;
893
128k
        };
894
23.2k
        int64_t group_size = 0; // only calculate the needed columns
895
88.8k
        for (auto& read_col : _read_file_columns) {
896
88.8k
            const FieldSchema* field = _file_metadata->schema().get_column(read_col);
897
88.8k
            group_size += column_compressed_size(field);
898
88.8k
        }
899
900
23.2k
        _reader_statistics.read_rows += candidate_row_ranges.count();
901
23.2k
        if (_io_ctx) {
902
23.2k
            _io_ctx->file_reader_stats->read_rows += candidate_row_ranges.count();
903
23.2k
        }
904
905
23.2k
        if (candidate_row_ranges.count() != 0) {
906
            // need read this row group.
907
19.5k
            _reader_statistics.read_row_groups++;
908
19.5k
            _reader_statistics.filtered_page_rows +=
909
19.5k
                    row_group.num_rows - candidate_row_ranges.count();
910
19.5k
            break;
911
19.5k
        } else {
912
            // this row group be filtered.
913
3.72k
            _reader_statistics.filtered_row_groups++;
914
3.72k
            _reader_statistics.filtered_bytes += group_size;
915
3.72k
            _reader_statistics.filtered_group_rows += row_group.num_rows;
916
3.72k
        }
917
23.2k
    }
918
919
22.4k
    if (_current_row_group_index.row_group_id == _total_groups) {
920
2.93k
        _row_group_eof = true;
921
2.93k
        _current_group_reader.reset(nullptr);
922
2.93k
        return Status::EndOfFile("No next RowGroupReader");
923
2.93k
    }
924
925
    // process page index and generate the ranges to read
926
19.5k
    auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
927
928
19.5k
    RowGroupReader::PositionDeleteContext position_delete_ctx =
929
19.5k
            _get_position_delete_ctx(row_group, _current_row_group_index);
930
19.5k
    io::FileReaderSPtr group_file_reader;
931
19.5k
    if (typeid_cast<io::InMemoryFileReader*>(_file_reader.get())) {
932
        // InMemoryFileReader has the ability to merge small IO
933
11.1k
        group_file_reader = _file_reader;
934
11.1k
    } else {
935
8.41k
        size_t avg_io_size = 0;
936
8.41k
        const std::vector<io::PrefetchRange> io_ranges =
937
8.41k
                _generate_random_access_ranges(_current_row_group_index, &avg_io_size);
938
8.41k
        int64_t merged_read_slice_size = -1;
939
8.41k
        if (_state != nullptr && _state->query_options().__isset.merge_read_slice_size) {
940
8.37k
            merged_read_slice_size = _state->query_options().merge_read_slice_size;
941
8.37k
        }
942
        // The underlying page reader will prefetch data in column.
943
        // Using both MergeRangeFileReader and BufferedStreamReader simultaneously would waste a lot of memory.
944
8.41k
        group_file_reader =
945
8.41k
                avg_io_size < io::MergeRangeFileReader::SMALL_IO
946
8.41k
                        ? std::make_shared<io::MergeRangeFileReader>(
947
8.35k
                                  _profile, _file_reader, io_ranges, merged_read_slice_size)
948
8.41k
                        : _file_reader;
949
8.41k
    }
950
19.5k
    _current_group_reader.reset(new RowGroupReader(
951
19.5k
            _io_ctx ? std::make_shared<io::TracingFileReader>(group_file_reader,
952
19.3k
                                                              _io_ctx->file_reader_stats)
953
19.5k
                    : group_file_reader,
954
19.5k
            _read_table_columns, _current_row_group_index.row_group_id, row_group, _ctz, _io_ctx,
955
19.5k
            position_delete_ctx, _lazy_read_ctx, _state, _column_ids, _filter_column_ids));
956
19.5k
    _row_group_eof = false;
957
958
19.5k
    _current_group_reader->set_current_row_group_idx(_current_row_group_index);
959
19.5k
    _current_group_reader->set_col_name_to_block_idx(_col_name_to_block_idx);
960
19.5k
    if (_condition_cache_ctx) {
961
4.24k
        _current_group_reader->set_condition_cache_context(_condition_cache_ctx);
962
4.24k
    }
963
19.5k
    _current_group_reader->set_table_format_reader(this);
964
965
19.5k
    _current_group_reader->_table_info_node_ptr = _table_info_node_ptr;
966
19.5k
    return _current_group_reader->init(_file_metadata->schema(), candidate_row_ranges, _col_offsets,
967
19.5k
                                       _tuple_descriptor, _row_descriptor, _colname_to_slot_id,
968
19.5k
                                       _not_single_slot_filter_conjuncts,
969
19.5k
                                       _slot_id_to_filter_conjuncts);
970
22.4k
}
971
972
std::vector<io::PrefetchRange> ParquetReader::_generate_random_access_ranges(
973
8.35k
        const RowGroupReader::RowGroupIndex& group, size_t* avg_io_size) {
974
8.35k
    std::vector<io::PrefetchRange> result;
975
8.35k
    int64_t last_chunk_end = -1;
976
8.35k
    size_t total_io_size = 0;
977
8.35k
    std::function<void(const FieldSchema*, const tparquet::RowGroup&)> scalar_range =
978
65.6k
            [&](const FieldSchema* field, const tparquet::RowGroup& row_group) {
979
65.6k
                if (_column_ids.empty() ||
980
65.7k
                    _column_ids.find(field->get_column_id()) != _column_ids.end()) {
981
65.7k
                    if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
982
7.30k
                        scalar_range(&field->children[0], row_group);
983
58.4k
                    } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
984
4.97k
                        scalar_range(&field->children[0], row_group);
985
4.97k
                        scalar_range(&field->children[1], row_group);
986
53.5k
                    } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
987
10.0k
                        for (int i = 0; i < field->children.size(); ++i) {
988
6.84k
                            scalar_range(&field->children[i], row_group);
989
6.84k
                        }
990
50.2k
                    } else {
991
50.2k
                        const tparquet::ColumnChunk& chunk =
992
50.2k
                                row_group.columns[field->physical_column_index];
993
50.2k
                        auto& chunk_meta = chunk.meta_data;
994
50.2k
                        int64_t chunk_start = has_dict_page(chunk_meta)
995
50.2k
                                                      ? chunk_meta.dictionary_page_offset
996
50.2k
                                                      : chunk_meta.data_page_offset;
997
50.2k
                        int64_t chunk_end = chunk_start + chunk_meta.total_compressed_size;
998
50.2k
                        DCHECK_GE(chunk_start, last_chunk_end);
999
50.2k
                        result.emplace_back(chunk_start, chunk_end);
1000
50.2k
                        total_io_size += chunk_meta.total_compressed_size;
1001
50.2k
                        last_chunk_end = chunk_end;
1002
50.2k
                    }
1003
65.7k
                }
1004
65.6k
            };
1005
8.35k
    const tparquet::RowGroup& row_group = _t_metadata->row_groups[group.row_group_id];
1006
42.0k
    for (const auto& read_col : _read_file_columns) {
1007
42.0k
        const FieldSchema* field = _file_metadata->schema().get_column(read_col);
1008
42.0k
        scalar_range(field, row_group);
1009
42.0k
    }
1010
8.35k
    if (!result.empty()) {
1011
8.13k
        *avg_io_size = total_io_size / result.size();
1012
8.13k
    }
1013
8.35k
    return result;
1014
8.35k
}
1015
1016
57.6k
bool ParquetReader::_is_misaligned_range_group(const tparquet::RowGroup& row_group) const {
1017
57.6k
    int64_t start_offset = _get_column_start_offset(row_group.columns[0].meta_data);
1018
1019
57.6k
    auto& last_column = row_group.columns[row_group.columns.size() - 1].meta_data;
1020
57.6k
    int64_t end_offset = _get_column_start_offset(last_column) + last_column.total_compressed_size;
1021
1022
57.6k
    int64_t row_group_mid = start_offset + (end_offset - start_offset) / 2;
1023
57.6k
    if (!(row_group_mid >= _range_start_offset &&
1024
57.6k
          row_group_mid < _range_start_offset + _range_size)) {
1025
27.0k
        return true;
1026
27.0k
    }
1027
30.5k
    return false;
1028
57.6k
}
1029
1030
2.84k
int64_t ParquetReader::get_total_rows() const {
1031
2.84k
    if (!_t_metadata) return 0;
1032
2.84k
    if (!_filter_groups) return _t_metadata->num_rows;
1033
2.84k
    int64_t total = 0;
1034
5.42k
    for (const auto& rg : _t_metadata->row_groups) {
1035
5.42k
        if (!_is_misaligned_range_group(rg)) {
1036
4.07k
            total += rg.num_rows;
1037
4.07k
        }
1038
5.42k
    }
1039
2.84k
    return total;
1040
2.84k
}
1041
1042
4.34k
void ParquetReader::set_condition_cache_context(std::shared_ptr<ConditionCacheContext> ctx) {
1043
4.34k
    _condition_cache_ctx = std::move(ctx);
1044
4.34k
    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
4.34k
    int64_t first_row = 0;
1049
4.34k
    for (const auto& rg : _t_metadata->row_groups) {
1050
4.34k
        if (!_is_misaligned_range_group(rg)) {
1051
4.33k
            _condition_cache_ctx->base_granule = first_row / ConditionCacheContext::GRANULE_SIZE;
1052
4.33k
            return;
1053
4.33k
        }
1054
8
        first_row += rg.num_rows;
1055
8
    }
1056
4.34k
}
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
17.5k
        RowRanges* candidate_row_ranges) {
1062
17.5k
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
1063
0
        return Status::EndOfFile("stop");
1064
0
    }
1065
1066
17.5k
    std::function<void()> read_whole_row_group = [&]() {
1067
15.1k
        candidate_row_ranges->add(RowRange {0, row_group.num_rows});
1068
15.1k
    };
1069
1070
    // Check if the page index is available and if it exists.
1071
17.5k
    PageIndex page_index;
1072
17.6k
    if (!config::enable_parquet_page_index || _colname_to_slot_id == nullptr ||
1073
17.6k
        !page_index.check_and_get_page_index_ranges(row_group.columns)) {
1074
8.86k
        read_whole_row_group();
1075
8.86k
        return Status::OK();
1076
8.86k
    }
1077
1078
8.69k
    std::vector<int> parquet_col_ids;
1079
31.6k
    for (size_t idx = 0; idx < _read_table_columns.size(); idx++) {
1080
22.9k
        const auto& read_table_col = _read_table_columns[idx];
1081
22.9k
        const auto& read_file_col = _read_file_columns[idx];
1082
22.9k
        if (!_colname_to_slot_id->contains(read_table_col)) {
1083
423
            continue;
1084
423
        }
1085
22.5k
        auto* field = _file_metadata->schema().get_column(read_file_col);
1086
1087
38.0k
        std::function<void(FieldSchema * field)> f = [&](FieldSchema* field) {
1088
38.0k
            if (!_column_ids.empty() &&
1089
38.0k
                _column_ids.find(field->get_column_id()) == _column_ids.end()) {
1090
1.28k
                return;
1091
1.28k
            }
1092
1093
36.7k
            if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
1094
2.14k
                f(&field->children[0]);
1095
34.5k
            } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
1096
1.73k
                f(&field->children[0]);
1097
1.73k
                f(&field->children[1]);
1098
32.8k
            } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
1099
13.9k
                for (int i = 0; i < field->children.size(); ++i) {
1100
9.92k
                    f(&field->children[i]);
1101
9.92k
                }
1102
28.8k
            } else {
1103
28.8k
                int parquet_col_id = field->physical_column_index;
1104
28.8k
                if (parquet_col_id >= 0) {
1105
28.8k
                    parquet_col_ids.push_back(parquet_col_id);
1106
28.8k
                }
1107
28.8k
            }
1108
36.7k
        };
1109
1110
22.5k
        f(field);
1111
22.5k
    }
1112
1113
8.76k
    auto parse_offset_index = [&]() -> Status {
1114
8.76k
        std::vector<uint8_t> off_index_buff(page_index._offset_index_size);
1115
8.76k
        Slice res(off_index_buff.data(), page_index._offset_index_size);
1116
8.76k
        size_t bytes_read = 0;
1117
8.76k
        {
1118
8.76k
            SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1119
8.76k
            RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._offset_index_start, res,
1120
8.76k
                                                          &bytes_read, _io_ctx));
1121
8.76k
        }
1122
8.76k
        _column_statistics.page_index_read_calls++;
1123
8.76k
        _col_offsets.clear();
1124
1125
28.8k
        for (auto parquet_col_id : parquet_col_ids) {
1126
28.8k
            auto& chunk = row_group.columns[parquet_col_id];
1127
28.8k
            if (chunk.offset_index_length == 0) [[unlikely]] {
1128
0
                continue;
1129
0
            }
1130
28.8k
            tparquet::OffsetIndex offset_index;
1131
28.8k
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1132
28.8k
            RETURN_IF_ERROR(
1133
28.8k
                    page_index.parse_offset_index(chunk, off_index_buff.data(), &offset_index));
1134
28.8k
            _col_offsets[parquet_col_id] = offset_index;
1135
28.8k
        }
1136
8.76k
        return Status::OK();
1137
8.76k
    };
1138
1139
    // from https://github.com/apache/doris/pull/55795
1140
8.69k
    RETURN_IF_ERROR(parse_offset_index());
1141
1142
    // Check if page index is needed for min-max filter.
1143
8.72k
    if (!_enable_filter_by_min_max || push_down_pred.empty()) {
1144
6.25k
        read_whole_row_group();
1145
6.25k
        return Status::OK();
1146
6.25k
    }
1147
1148
    // read column index.
1149
2.44k
    std::vector<uint8_t> col_index_buff(page_index._column_index_size);
1150
2.44k
    size_t bytes_read = 0;
1151
2.44k
    Slice result(col_index_buff.data(), page_index._column_index_size);
1152
2.44k
    {
1153
2.44k
        SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1154
2.44k
        RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._column_index_start, result,
1155
2.44k
                                                      &bytes_read, _io_ctx));
1156
2.44k
    }
1157
2.44k
    _column_statistics.page_index_read_calls++;
1158
1159
2.44k
    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
2.44k
    ParquetPredicate::CachedPageIndexStat cached_page_index;
1163
2.44k
    cached_page_index.ctz = _ctz;
1164
2.44k
    std::function<bool(ParquetPredicate::PageIndexStat**, int)> get_stat_func =
1165
2.44k
            [&](ParquetPredicate::PageIndexStat** ans, const int cid) -> bool {
1166
2.27k
        if (cached_page_index.stats.contains(cid)) {
1167
968
            *ans = &cached_page_index.stats[cid];
1168
968
            return (*ans)->available;
1169
968
        }
1170
1.30k
        cached_page_index.stats.emplace(cid, ParquetPredicate::PageIndexStat {});
1171
1.30k
        auto& sig_stat = cached_page_index.stats[cid];
1172
1173
1.30k
        auto* slot = _tuple_descriptor->slots()[cid];
1174
1.30k
        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
1.30k
        const auto& file_col_name =
1180
1.30k
                _table_info_node_ptr->children_file_column_name(slot->col_name());
1181
1.30k
        const FieldSchema* col_schema = _file_metadata->schema().get_column(file_col_name);
1182
1.30k
        int parquet_col_id = col_schema->physical_column_index;
1183
1184
1.30k
        if (parquet_col_id < 0) {
1185
            // complex type, not support page index yet.
1186
0
            return false;
1187
0
        }
1188
1.30k
        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
1.30k
        auto& column_chunk = row_group.columns[parquet_col_id];
1195
1.30k
        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
1.30k
        tparquet::ColumnIndex column_index;
1201
1.30k
        {
1202
1.30k
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1203
1.30k
            RETURN_IF_ERROR(page_index.parse_column_index(column_chunk, col_index_buff.data(),
1204
1.30k
                                                          &column_index));
1205
1.30k
        }
1206
1.30k
        const int64_t num_of_pages = column_index.null_pages.size();
1207
1.30k
        if (num_of_pages <= 0) [[unlikely]] {
1208
            // no page. (maybe this row group no data.)
1209
0
            return false;
1210
0
        }
1211
1.30k
        DCHECK_EQ(column_index.min_values.size(), column_index.max_values.size());
1212
1.30k
        if (!column_index.__isset.null_counts) {
1213
            // not set null or null counts;
1214
0
            return false;
1215
0
        }
1216
1217
1.30k
        auto& offset_index = _col_offsets[parquet_col_id];
1218
1.30k
        const auto& page_locations = offset_index.page_locations;
1219
1220
1.30k
        sig_stat.col_schema = col_schema;
1221
1.30k
        sig_stat.num_of_pages = num_of_pages;
1222
1.30k
        sig_stat.encoded_min_value = column_index.min_values;
1223
1.30k
        sig_stat.encoded_max_value = column_index.max_values;
1224
1.30k
        sig_stat.is_all_null.resize(num_of_pages);
1225
1.30k
        sig_stat.has_null.resize(num_of_pages);
1226
1.30k
        sig_stat.ranges.resize(num_of_pages);
1227
1228
11.2k
        for (int page_id = 0; page_id < num_of_pages; page_id++) {
1229
9.97k
            sig_stat.is_all_null[page_id] = column_index.null_pages[page_id];
1230
9.97k
            sig_stat.has_null[page_id] = column_index.null_counts[page_id] > 0;
1231
1232
9.97k
            int64_t from = page_locations[page_id].first_row_index;
1233
9.97k
            int64_t to = 0;
1234
9.97k
            if (page_id == page_locations.size() - 1) {
1235
1.30k
                to = row_group_index.last_row;
1236
8.67k
            } else {
1237
8.67k
                to = page_locations[page_id + 1].first_row_index;
1238
8.67k
            }
1239
9.97k
            sig_stat.ranges[page_id] = RowRange {from, to};
1240
9.97k
        }
1241
1242
1.30k
        sig_stat.available = true;
1243
1.30k
        *ans = &sig_stat;
1244
1.30k
        return true;
1245
1.30k
    };
1246
2.44k
    cached_page_index.row_group_range = {0, row_group.num_rows};
1247
2.44k
    cached_page_index.get_stat_func = get_stat_func;
1248
1249
2.44k
    candidate_row_ranges->add({0, row_group.num_rows});
1250
2.48k
    for (const auto& predicate : push_down_pred) {
1251
2.48k
        RowRanges tmp_row_range;
1252
2.48k
        if (!predicate->evaluate_and(&cached_page_index, &tmp_row_range)) {
1253
            // no need read this row group.
1254
11
            candidate_row_ranges->clear();
1255
11
            return Status::OK();
1256
11
        }
1257
2.47k
        RowRanges::ranges_intersection(*candidate_row_ranges, tmp_row_range, candidate_row_ranges);
1258
2.47k
    }
1259
2.43k
    return Status::OK();
1260
2.44k
}
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
23.2k
        RowRanges* row_ranges) {
1266
23.2k
    SCOPED_RAW_TIMER(&_reader_statistics.row_group_filter_time);
1267
23.2k
    if (!_filter_groups) {
1268
        // No row group filtering is needed;
1269
        // for example, Iceberg reads position delete files.
1270
1.15k
        row_ranges->add({0, row_group.num_rows});
1271
1.15k
        return Status::OK();
1272
1.15k
    }
1273
1274
22.0k
    if (_read_by_rows) {
1275
1.08k
        auto group_start = row_group_index.first_row;
1276
1.08k
        auto group_end = row_group_index.last_row;
1277
1278
2.99k
        while (!_row_ids.empty()) {
1279
2.12k
            auto v = _row_ids.front();
1280
2.12k
            if (v < group_start) {
1281
0
                continue;
1282
2.12k
            } else if (v < group_end) {
1283
1.91k
                row_ranges->add(RowRange {v - group_start, v - group_start + 1});
1284
1.91k
                _row_ids.pop_front();
1285
1.91k
            } else {
1286
212
                break;
1287
212
            }
1288
2.12k
        }
1289
20.9k
    } else {
1290
20.9k
        bool filter_this_row_group = false;
1291
20.9k
        bool filtered_by_min_max = false;
1292
20.9k
        bool filtered_by_bloom_filter = false;
1293
20.9k
        RETURN_IF_ERROR(_process_column_stat_filter(row_group, push_down_pred,
1294
20.9k
                                                    &filter_this_row_group, &filtered_by_min_max,
1295
20.9k
                                                    &filtered_by_bloom_filter));
1296
        // Update statistics based on filter type
1297
20.9k
        if (filter_this_row_group) {
1298
3.40k
            if (filtered_by_min_max) {
1299
3.40k
                _reader_statistics.filtered_row_groups_by_min_max++;
1300
3.40k
            }
1301
3.40k
            if (filtered_by_bloom_filter) {
1302
0
                _reader_statistics.filtered_row_groups_by_bloom_filter++;
1303
0
            }
1304
3.40k
        }
1305
1306
20.9k
        if (!filter_this_row_group) {
1307
17.6k
            RETURN_IF_ERROR(_process_page_index_filter(row_group, row_group_index, push_down_pred,
1308
17.6k
                                                       row_ranges));
1309
17.6k
        }
1310
20.9k
    }
1311
1312
22.0k
    return Status::OK();
1313
22.0k
}
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
20.9k
        bool* filter_group, bool* filtered_by_min_max, bool* filtered_by_bloom_filter) {
1319
    // If both filters are disabled, skip filtering
1320
20.9k
    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
20.9k
    std::unordered_map<int, std::unique_ptr<ParquetBlockSplitBloomFilter>> bloom_filter_cache;
1327
1328
    // Initialize output parameters
1329
20.9k
    *filtered_by_min_max = false;
1330
20.9k
    *filtered_by_bloom_filter = false;
1331
1332
20.9k
    for (const auto& predicate : _push_down_predicates) {
1333
8.94k
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_stat_func =
1334
9.76k
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1335
                    // Check if min-max filter is enabled
1336
9.76k
                    if (!_enable_filter_by_min_max) {
1337
957
                        return false;
1338
957
                    }
1339
8.81k
                    auto* slot = _tuple_descriptor->slots()[cid];
1340
8.81k
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1341
0
                        return false;
1342
0
                    }
1343
8.81k
                    const auto& file_col_name =
1344
8.81k
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1345
8.81k
                    const FieldSchema* col_schema =
1346
8.81k
                            _file_metadata->schema().get_column(file_col_name);
1347
8.81k
                    int parquet_col_id = col_schema->physical_column_index;
1348
8.81k
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1349
8.81k
                    stat->col_schema = col_schema;
1350
8.81k
                    return ParquetPredicate::read_column_stats(col_schema, meta_data,
1351
8.81k
                                                               &_ignored_stats,
1352
8.81k
                                                               _t_metadata->created_by, stat)
1353
8.81k
                            .ok();
1354
8.81k
                };
1355
8.94k
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_bloom_filter_func =
1356
8.94k
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1357
2.50k
                    auto* slot = _tuple_descriptor->slots()[cid];
1358
2.50k
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1359
0
                        return false;
1360
0
                    }
1361
2.50k
                    const auto& file_col_name =
1362
2.50k
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1363
2.50k
                    const FieldSchema* col_schema =
1364
2.50k
                            _file_metadata->schema().get_column(file_col_name);
1365
2.50k
                    int parquet_col_id = col_schema->physical_column_index;
1366
2.50k
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1367
2.50k
                    if (!meta_data.__isset.bloom_filter_offset) {
1368
2.49k
                        return false;
1369
2.49k
                    }
1370
10
                    auto primitive_type =
1371
10
                            remove_nullable(col_schema->data_type)->get_primitive_type();
1372
10
                    if (!ParquetPredicate::bloom_filter_supported(primitive_type)) {
1373
5
                        return false;
1374
5
                    }
1375
1376
                    // Check if bloom filter is enabled
1377
5
                    if (!_enable_filter_by_bloom_filter) {
1378
0
                        return false;
1379
0
                    }
1380
1381
                    // Check cache first
1382
5
                    auto cache_iter = bloom_filter_cache.find(parquet_col_id);
1383
5
                    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
5
                    if (!stat->bloom_filter) {
1391
5
                        SCOPED_RAW_TIMER(&_reader_statistics.bloom_filter_read_time);
1392
5
                        auto st = ParquetPredicate::read_bloom_filter(
1393
5
                                meta_data, _tracing_file_reader, _io_ctx, stat);
1394
5
                        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
5
                    }
1402
5
                    return stat->bloom_filter != nullptr;
1403
5
                };
1404
8.94k
        ParquetPredicate::ColumnStat stat;
1405
8.94k
        stat.ctz = _ctz;
1406
8.94k
        stat.get_stat_func = &get_stat_func;
1407
8.94k
        stat.get_bloom_filter_func = &get_bloom_filter_func;
1408
1409
8.94k
        if (!predicate->evaluate_and(&stat)) {
1410
3.40k
            *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
3.40k
            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
3.40k
            if (stat.col_schema && !stat.bloom_filter) {
1419
3.40k
                *filtered_by_min_max = true;
1420
3.40k
            }
1421
1422
3.40k
            return Status::OK();
1423
3.40k
        }
1424
1425
        // After evaluating, if the bloom filter was used, cache it for subsequent predicates
1426
5.53k
        if (stat.bloom_filter) {
1427
            // Find the column id for caching
1428
26
            for (auto* slot : _tuple_descriptor->slots()) {
1429
26
                if (_table_info_node_ptr->children_column_exists(slot->col_name())) {
1430
26
                    const auto& file_col_name =
1431
26
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1432
26
                    const FieldSchema* col_schema =
1433
26
                            _file_metadata->schema().get_column(file_col_name);
1434
26
                    int parquet_col_id = col_schema->physical_column_index;
1435
26
                    if (stat.col_schema == col_schema) {
1436
5
                        bloom_filter_cache[parquet_col_id] = std::move(stat.bloom_filter);
1437
5
                        break;
1438
5
                    }
1439
26
                }
1440
26
            }
1441
5
        }
1442
5.53k
    }
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
17.5k
    return Status::OK();
1447
20.9k
}
1448
1449
115k
int64_t ParquetReader::_get_column_start_offset(const tparquet::ColumnMetaData& column) const {
1450
115k
    return has_dict_page(column) ? column.dictionary_page_offset : column.data_page_offset;
1451
115k
}
1452
1453
17.3k
void ParquetReader::_collect_profile() {
1454
17.3k
    if (_profile == nullptr) {
1455
0
        return;
1456
0
    }
1457
1458
17.3k
    if (_current_group_reader != nullptr) {
1459
14.2k
        _current_group_reader->collect_profile_before_close();
1460
14.2k
    }
1461
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups, _reader_statistics.filtered_row_groups);
1462
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_min_max,
1463
17.3k
                   _reader_statistics.filtered_row_groups_by_min_max);
1464
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_bloom_filter,
1465
17.3k
                   _reader_statistics.filtered_row_groups_by_bloom_filter);
1466
17.3k
    COUNTER_UPDATE(_parquet_profile.to_read_row_groups, _reader_statistics.read_row_groups);
1467
17.3k
    COUNTER_UPDATE(_parquet_profile.total_row_groups, _total_groups);
1468
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_group_rows, _reader_statistics.filtered_group_rows);
1469
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_page_rows, _reader_statistics.filtered_page_rows);
1470
17.3k
    COUNTER_UPDATE(_parquet_profile.lazy_read_filtered_rows,
1471
17.3k
                   _reader_statistics.lazy_read_filtered_rows);
1472
17.3k
    COUNTER_UPDATE(_parquet_profile.filtered_bytes, _reader_statistics.filtered_bytes);
1473
17.3k
    COUNTER_UPDATE(_parquet_profile.raw_rows_read, _reader_statistics.read_rows);
1474
17.3k
    COUNTER_UPDATE(_parquet_profile.column_read_time, _reader_statistics.column_read_time);
1475
17.3k
    COUNTER_UPDATE(_parquet_profile.parse_meta_time, _reader_statistics.parse_meta_time);
1476
17.3k
    COUNTER_UPDATE(_parquet_profile.parse_footer_time, _reader_statistics.parse_footer_time);
1477
17.3k
    COUNTER_UPDATE(_parquet_profile.file_reader_create_time,
1478
17.3k
                   _reader_statistics.file_reader_create_time);
1479
17.3k
    COUNTER_UPDATE(_parquet_profile.open_file_num, _reader_statistics.open_file_num);
1480
17.3k
    COUNTER_UPDATE(_parquet_profile.page_index_filter_time,
1481
17.3k
                   _reader_statistics.page_index_filter_time);
1482
17.3k
    COUNTER_UPDATE(_parquet_profile.read_page_index_time, _reader_statistics.read_page_index_time);
1483
17.3k
    COUNTER_UPDATE(_parquet_profile.parse_page_index_time,
1484
17.3k
                   _reader_statistics.parse_page_index_time);
1485
17.3k
    COUNTER_UPDATE(_parquet_profile.row_group_filter_time,
1486
17.3k
                   _reader_statistics.row_group_filter_time);
1487
17.3k
    COUNTER_UPDATE(_parquet_profile.file_footer_read_calls,
1488
17.3k
                   _reader_statistics.file_footer_read_calls);
1489
17.3k
    COUNTER_UPDATE(_parquet_profile.file_footer_hit_cache,
1490
17.3k
                   _reader_statistics.file_footer_hit_cache);
1491
1492
17.3k
    COUNTER_UPDATE(_parquet_profile.skip_page_header_num, _column_statistics.skip_page_header_num);
1493
17.3k
    COUNTER_UPDATE(_parquet_profile.parse_page_header_num,
1494
17.3k
                   _column_statistics.parse_page_header_num);
1495
17.3k
    COUNTER_UPDATE(_parquet_profile.predicate_filter_time,
1496
17.3k
                   _reader_statistics.predicate_filter_time);
1497
17.3k
    COUNTER_UPDATE(_parquet_profile.dict_filter_rewrite_time,
1498
17.3k
                   _reader_statistics.dict_filter_rewrite_time);
1499
17.3k
    COUNTER_UPDATE(_parquet_profile.convert_time, _column_statistics.convert_time);
1500
17.3k
    COUNTER_UPDATE(_parquet_profile.bloom_filter_read_time,
1501
17.3k
                   _reader_statistics.bloom_filter_read_time);
1502
17.3k
    COUNTER_UPDATE(_parquet_profile.page_index_read_calls,
1503
17.3k
                   _column_statistics.page_index_read_calls);
1504
17.3k
    COUNTER_UPDATE(_parquet_profile.decompress_time, _column_statistics.decompress_time);
1505
17.3k
    COUNTER_UPDATE(_parquet_profile.decompress_cnt, _column_statistics.decompress_cnt);
1506
17.3k
    COUNTER_UPDATE(_parquet_profile.page_read_counter, _column_statistics.page_read_counter);
1507
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_write_counter,
1508
17.3k
                   _column_statistics.page_cache_write_counter);
1509
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_write_counter,
1510
17.3k
                   _column_statistics.page_cache_compressed_write_counter);
1511
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_write_counter,
1512
17.3k
                   _column_statistics.page_cache_decompressed_write_counter);
1513
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_hit_counter,
1514
17.3k
                   _column_statistics.page_cache_hit_counter);
1515
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_missing_counter,
1516
17.3k
                   _column_statistics.page_cache_missing_counter);
1517
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_hit_counter,
1518
17.3k
                   _column_statistics.page_cache_compressed_hit_counter);
1519
17.3k
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_hit_counter,
1520
17.3k
                   _column_statistics.page_cache_decompressed_hit_counter);
1521
17.3k
    COUNTER_UPDATE(_parquet_profile.decode_header_time, _column_statistics.decode_header_time);
1522
17.3k
    COUNTER_UPDATE(_parquet_profile.read_page_header_time,
1523
17.3k
                   _column_statistics.read_page_header_time);
1524
17.3k
    COUNTER_UPDATE(_parquet_profile.decode_value_time, _column_statistics.decode_value_time);
1525
17.3k
    COUNTER_UPDATE(_parquet_profile.decode_dict_time, _column_statistics.decode_dict_time);
1526
17.3k
    COUNTER_UPDATE(_parquet_profile.decode_level_time, _column_statistics.decode_level_time);
1527
17.3k
    COUNTER_UPDATE(_parquet_profile.decode_null_map_time, _column_statistics.decode_null_map_time);
1528
17.3k
}
1529
1530
17.3k
void ParquetReader::_collect_profile_before_close() {
1531
17.3k
    _collect_profile();
1532
17.3k
}
1533
1534
} // namespace doris