Coverage Report

Created: 2026-06-04 06:55

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
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// distributed with this work for additional information
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// 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
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// with the License.  You may obtain a copy of the License at
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//
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//   http://www.apache.org/licenses/LICENSE-2.0
10
//
11
// Unless required by applicable law or agreed to in writing,
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// software distributed under the License is distributed on an
13
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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// KIND, either express or implied.  See the License for the
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// specific language governing permissions and limitations
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// under the License.
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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
1.22k
        : _profile(profile),
88
1.22k
          _scan_params(params),
89
1.22k
          _scan_range(range),
90
1.22k
          _batch_size(std::max(batch_size, 1UL)),
91
1.22k
          _range_start_offset(range.start_offset),
92
1.22k
          _range_size(range.size),
93
1.22k
          _ctz(ctz),
94
1.22k
          _io_ctx(io_ctx),
95
1.22k
          _state(state),
96
1.22k
          _enable_lazy_mat(enable_lazy_mat),
97
          _enable_filter_by_min_max(
98
1.22k
                  state == nullptr ? true
99
1.22k
                                   : state->query_options().enable_parquet_filter_by_min_max),
100
          _enable_filter_by_bloom_filter(
101
1.22k
                  state == nullptr ? true
102
1.22k
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
103
1.22k
    _meta_cache = meta_cache;
104
1.22k
    _init_profile();
105
1.22k
    _init_system_properties();
106
1.22k
    _init_file_description();
107
1.22k
}
108
109
36.7k
void ParquetReader::set_batch_size(size_t batch_size) {
110
36.7k
    if (_batch_size == batch_size) {
111
18.4k
        return;
112
18.4k
    }
113
18.3k
    _batch_size = batch_size;
114
18.3k
}
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
17.7k
        : _profile(profile),
122
17.7k
          _scan_params(params),
123
17.7k
          _scan_range(range),
124
17.7k
          _batch_size(std::max(batch_size, 1UL)),
125
17.7k
          _range_start_offset(range.start_offset),
126
17.7k
          _range_size(range.size),
127
17.7k
          _ctz(ctz),
128
17.7k
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
129
17.7k
          _io_ctx_holder(std::move(io_ctx_holder)),
130
17.7k
          _state(state),
131
17.7k
          _enable_lazy_mat(enable_lazy_mat),
132
          _enable_filter_by_min_max(
133
17.7k
                  state == nullptr ? true
134
17.7k
                                   : state->query_options().enable_parquet_filter_by_min_max),
135
          _enable_filter_by_bloom_filter(
136
17.7k
                  state == nullptr ? true
137
17.7k
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
138
17.7k
    _meta_cache = meta_cache;
139
17.7k
    _init_profile();
140
17.7k
    _init_system_properties();
141
17.7k
    _init_file_description();
142
17.7k
}
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
1.27k
        : _profile(nullptr),
168
1.27k
          _scan_params(params),
169
1.27k
          _scan_range(range),
170
1.27k
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
171
1.27k
          _io_ctx_holder(std::move(io_ctx_holder)),
172
1.27k
          _state(state),
173
1.27k
          _enable_lazy_mat(enable_lazy_mat),
174
          _enable_filter_by_min_max(
175
1.27k
                  state == nullptr ? true
176
1.27k
                                   : state->query_options().enable_parquet_filter_by_min_max),
177
          _enable_filter_by_bloom_filter(
178
1.27k
                  state == nullptr ? true
179
1.27k
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
180
1.27k
    _meta_cache = meta_cache;
181
1.27k
    _init_system_properties();
182
1.27k
    _init_file_description();
183
1.27k
}
184
185
20.2k
ParquetReader::~ParquetReader() {
186
20.2k
    _close_internal();
187
20.2k
}
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
19.0k
void ParquetReader::_init_profile() {
198
19.0k
    if (_profile != nullptr) {
199
18.9k
        static const char* parquet_profile = "ParquetReader";
200
18.9k
        ADD_TIMER_WITH_LEVEL(_profile, parquet_profile, 1);
201
202
18.9k
        _parquet_profile.filtered_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
203
18.9k
                _profile, "RowGroupsFiltered", TUnit::UNIT, parquet_profile, 1);
204
18.9k
        _parquet_profile.filtered_row_groups_by_min_max = ADD_CHILD_COUNTER_WITH_LEVEL(
205
18.9k
                _profile, "RowGroupsFilteredByMinMax", TUnit::UNIT, parquet_profile, 1);
206
18.9k
        _parquet_profile.filtered_row_groups_by_bloom_filter = ADD_CHILD_COUNTER_WITH_LEVEL(
207
18.9k
                _profile, "RowGroupsFilteredByBloomFilter", TUnit::UNIT, parquet_profile, 1);
208
18.9k
        _parquet_profile.to_read_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
209
18.9k
                _profile, "RowGroupsReadNum", TUnit::UNIT, parquet_profile, 1);
210
18.9k
        _parquet_profile.total_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
211
18.9k
                _profile, "RowGroupsTotalNum", TUnit::UNIT, parquet_profile, 1);
212
18.9k
        _parquet_profile.filtered_group_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
213
18.9k
                _profile, "FilteredRowsByGroup", TUnit::UNIT, parquet_profile, 1);
214
18.9k
        _parquet_profile.filtered_page_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
215
18.9k
                _profile, "FilteredRowsByPage", TUnit::UNIT, parquet_profile, 1);
216
18.9k
        _parquet_profile.lazy_read_filtered_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
217
18.9k
                _profile, "FilteredRowsByLazyRead", TUnit::UNIT, parquet_profile, 1);
218
18.9k
        _parquet_profile.filtered_bytes = ADD_CHILD_COUNTER_WITH_LEVEL(
219
18.9k
                _profile, "FilteredBytes", TUnit::BYTES, parquet_profile, 1);
220
18.9k
        _parquet_profile.raw_rows_read = ADD_CHILD_COUNTER_WITH_LEVEL(
221
18.9k
                _profile, "RawRowsRead", TUnit::UNIT, parquet_profile, 1);
222
18.9k
        _parquet_profile.column_read_time =
223
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ColumnReadTime", parquet_profile, 1);
224
18.9k
        _parquet_profile.parse_meta_time =
225
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseMetaTime", parquet_profile, 1);
226
18.9k
        _parquet_profile.parse_footer_time =
227
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseFooterTime", parquet_profile, 1);
228
18.9k
        _parquet_profile.file_reader_create_time =
229
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "FileReaderCreateTime", parquet_profile, 1);
230
18.9k
        _parquet_profile.open_file_num =
231
18.9k
                ADD_CHILD_COUNTER_WITH_LEVEL(_profile, "FileNum", TUnit::UNIT, parquet_profile, 1);
232
18.9k
        _parquet_profile.page_index_read_calls =
233
18.9k
                ADD_COUNTER_WITH_LEVEL(_profile, "PageIndexReadCalls", TUnit::UNIT, 1);
234
18.9k
        _parquet_profile.page_index_filter_time =
235
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexFilterTime", parquet_profile, 1);
236
18.9k
        _parquet_profile.read_page_index_time =
237
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexReadTime", parquet_profile, 1);
238
18.9k
        _parquet_profile.parse_page_index_time =
239
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexParseTime", parquet_profile, 1);
240
18.9k
        _parquet_profile.row_group_filter_time =
241
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "RowGroupFilterTime", parquet_profile, 1);
242
18.9k
        _parquet_profile.file_footer_read_calls =
243
18.9k
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterReadCalls", TUnit::UNIT, 1);
244
18.9k
        _parquet_profile.file_footer_hit_cache =
245
18.9k
                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterHitCache", TUnit::UNIT, 1);
246
18.9k
        _parquet_profile.decompress_time =
247
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecompressTime", parquet_profile, 1);
248
18.9k
        _parquet_profile.decompress_cnt = ADD_CHILD_COUNTER_WITH_LEVEL(
249
18.9k
                _profile, "DecompressCount", TUnit::UNIT, parquet_profile, 1);
250
18.9k
        _parquet_profile.page_read_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
251
18.9k
                _profile, "PageReadCount", TUnit::UNIT, parquet_profile, 1);
252
18.9k
        _parquet_profile.page_cache_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
253
18.9k
                _profile, "PageCacheWriteCount", TUnit::UNIT, parquet_profile, 1);
254
18.9k
        _parquet_profile.page_cache_compressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
255
18.9k
                _profile, "PageCacheCompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
256
18.9k
        _parquet_profile.page_cache_decompressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
257
18.9k
                _profile, "PageCacheDecompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
258
18.9k
        _parquet_profile.page_cache_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
259
18.9k
                _profile, "PageCacheHitCount", TUnit::UNIT, parquet_profile, 1);
260
18.9k
        _parquet_profile.page_cache_missing_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
261
18.9k
                _profile, "PageCacheMissingCount", TUnit::UNIT, parquet_profile, 1);
262
18.9k
        _parquet_profile.page_cache_compressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
263
18.9k
                _profile, "PageCacheCompressedHitCount", TUnit::UNIT, parquet_profile, 1);
264
18.9k
        _parquet_profile.page_cache_decompressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
265
18.9k
                _profile, "PageCacheDecompressedHitCount", TUnit::UNIT, parquet_profile, 1);
266
18.9k
        _parquet_profile.decode_header_time =
267
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderDecodeTime", parquet_profile, 1);
268
18.9k
        _parquet_profile.read_page_header_time =
269
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderReadTime", parquet_profile, 1);
270
18.9k
        _parquet_profile.decode_value_time =
271
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeValueTime", parquet_profile, 1);
272
18.9k
        _parquet_profile.decode_dict_time =
273
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeDictTime", parquet_profile, 1);
274
18.9k
        _parquet_profile.decode_level_time =
275
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeLevelTime", parquet_profile, 1);
276
18.9k
        _parquet_profile.decode_null_map_time =
277
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeNullMapTime", parquet_profile, 1);
278
18.9k
        _parquet_profile.skip_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
279
18.9k
                _profile, "SkipPageHeaderNum", TUnit::UNIT, parquet_profile, 1);
280
18.9k
        _parquet_profile.parse_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
281
18.9k
                _profile, "ParsePageHeaderNum", TUnit::UNIT, parquet_profile, 1);
282
18.9k
        _parquet_profile.predicate_filter_time =
283
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PredicateFilterTime", parquet_profile, 1);
284
18.9k
        _parquet_profile.dict_filter_rewrite_time =
285
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DictFilterRewriteTime", parquet_profile, 1);
286
18.9k
        _parquet_profile.convert_time =
287
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ConvertTime", parquet_profile, 1);
288
18.9k
        _parquet_profile.bloom_filter_read_time =
289
18.9k
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "BloomFilterReadTime", parquet_profile, 1);
290
18.9k
    }
291
19.0k
}
292
293
17.1k
Status ParquetReader::close() {
294
17.1k
    _close_internal();
295
17.1k
    return Status::OK();
296
17.1k
}
297
298
37.4k
void ParquetReader::_close_internal() {
299
37.4k
    if (!_closed) {
300
20.2k
        _current_group_reader.reset();
301
20.2k
        _tracing_file_reader.reset();
302
20.2k
        _file_reader.reset();
303
20.2k
        _closed = true;
304
20.2k
    }
305
37.4k
}
306
307
38.2k
Status ParquetReader::_open_file() {
308
38.2k
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
309
0
        return Status::EndOfFile("stop");
310
0
    }
311
38.2k
    if (_file_reader == nullptr) {
312
19.5k
        SCOPED_RAW_TIMER(&_reader_statistics.file_reader_create_time);
313
19.5k
        ++_reader_statistics.open_file_num;
314
19.5k
        _file_description.mtime =
315
19.5k
                _scan_range.__isset.modification_time ? _scan_range.modification_time : 0;
316
19.5k
        io::FileReaderOptions reader_options =
317
19.5k
                FileFactory::get_reader_options(_state, _file_description);
318
19.5k
        if (_io_ctx_holder) {
319
18.4k
            _file_reader = DORIS_TRY(io::DelegateReader::create_file_reader(
320
18.4k
                    _profile, _system_properties, _file_description, reader_options,
321
18.4k
                    io::DelegateReader::AccessMode::RANDOM,
322
18.4k
                    std::static_pointer_cast<const io::IOContext>(_io_ctx_holder)));
323
18.4k
        } else {
324
1.16k
            _file_reader = DORIS_TRY(io::DelegateReader::create_file_reader(
325
1.16k
                    _profile, _system_properties, _file_description, reader_options,
326
1.16k
                    io::DelegateReader::AccessMode::RANDOM, _io_ctx));
327
1.16k
        }
328
19.5k
        _tracing_file_reader = _io_ctx && _io_ctx->file_reader_stats
329
19.5k
                                       ? std::make_shared<io::TracingFileReader>(
330
19.5k
                                                 _file_reader, _io_ctx->file_reader_stats)
331
18.4E
                                       : _file_reader;
332
19.5k
    }
333
334
38.2k
    if (_file_metadata == nullptr) {
335
19.6k
        SCOPED_RAW_TIMER(&_reader_statistics.parse_footer_time);
336
19.6k
        if (_tracing_file_reader->size() <= sizeof(PARQUET_VERSION_NUMBER)) {
337
            // Some system may generate parquet file with only 4 bytes: PAR1
338
            // Should consider it as empty file.
339
0
            return Status::EndOfFile("open file failed, empty parquet file {} with size: {}",
340
0
                                     _scan_range.path, _tracing_file_reader->size());
341
0
        }
342
19.6k
        size_t meta_size = 0;
343
19.6k
        bool enable_mapping_varbinary = _scan_params.__isset.enable_mapping_varbinary
344
19.6k
                                                ? _scan_params.enable_mapping_varbinary
345
19.6k
                                                : false;
346
19.6k
        bool enable_mapping_timestamp_tz = _scan_params.__isset.enable_mapping_timestamp_tz
347
19.6k
                                                   ? _scan_params.enable_mapping_timestamp_tz
348
19.6k
                                                   : false;
349
19.6k
        if (_meta_cache == nullptr) {
350
            // wrap _file_metadata with unique ptr, so that it can be released finally.
351
1.32k
            RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
352
1.32k
                                                &meta_size, _io_ctx, enable_mapping_varbinary,
353
1.32k
                                                enable_mapping_timestamp_tz));
354
1.32k
            _file_metadata = _file_metadata_ptr.get();
355
            // parse magic number & parse meta data
356
1.32k
            _reader_statistics.file_footer_read_calls += 1;
357
18.3k
        } else {
358
18.3k
            const auto& file_meta_cache_key =
359
18.3k
                    FileMetaCache::get_key(_tracing_file_reader, _file_description);
360
18.3k
            if (!_meta_cache->lookup(file_meta_cache_key, &_meta_cache_handle)) {
361
4.51k
                RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
362
4.51k
                                                    &meta_size, _io_ctx, enable_mapping_varbinary,
363
4.51k
                                                    enable_mapping_timestamp_tz));
364
                // _file_metadata_ptr.release() : move control of _file_metadata to _meta_cache_handle
365
4.51k
                _meta_cache->insert(file_meta_cache_key, _file_metadata_ptr.release(),
366
4.51k
                                    &_meta_cache_handle);
367
4.51k
                _file_metadata = _meta_cache_handle.data<FileMetaData>();
368
4.51k
                _reader_statistics.file_footer_read_calls += 1;
369
13.8k
            } else {
370
13.8k
                _reader_statistics.file_footer_hit_cache++;
371
13.8k
            }
372
18.3k
            _file_metadata = _meta_cache_handle.data<FileMetaData>();
373
18.3k
        }
374
375
19.6k
        if (_file_metadata == nullptr) {
376
0
            return Status::InternalError("failed to get file meta data: {}",
377
0
                                         _file_description.path);
378
0
        }
379
19.6k
    }
380
38.2k
    return Status::OK();
381
38.2k
}
382
383
17.9k
Status ParquetReader::get_file_metadata_schema(const FieldDescriptor** ptr) {
384
17.9k
    RETURN_IF_ERROR(_open_file());
385
17.9k
    DCHECK(_file_metadata != nullptr);
386
17.9k
    *ptr = &_file_metadata->schema();
387
17.9k
    return Status::OK();
388
17.9k
}
389
390
20.2k
void ParquetReader::_init_system_properties() {
391
20.2k
    if (_scan_range.__isset.file_type) {
392
        // for compatibility
393
18.9k
        _system_properties.system_type = _scan_range.file_type;
394
18.9k
    } else {
395
1.37k
        _system_properties.system_type = _scan_params.file_type;
396
1.37k
    }
397
20.2k
    _system_properties.properties = _scan_params.properties;
398
20.2k
    _system_properties.hdfs_params = _scan_params.hdfs_params;
399
20.2k
    if (_scan_params.__isset.broker_addresses) {
400
22
        _system_properties.broker_addresses.assign(_scan_params.broker_addresses.begin(),
401
22
                                                   _scan_params.broker_addresses.end());
402
22
    }
403
20.2k
}
404
405
20.2k
void ParquetReader::_init_file_description() {
406
20.2k
    _file_description.path = _scan_range.path;
407
20.2k
    _file_description.file_size = _scan_range.__isset.file_size ? _scan_range.file_size : -1;
408
20.2k
    if (_scan_range.__isset.fs_name) {
409
8.55k
        _file_description.fs_name = _scan_range.fs_name;
410
8.55k
    }
411
20.2k
    if (_scan_range.__isset.file_cache_admission) {
412
17.7k
        _file_description.file_cache_admission = _scan_range.file_cache_admission;
413
17.7k
    }
414
20.2k
}
415
416
1.66k
Status ParquetReader::on_before_init_reader(ReaderInitContext* ctx) {
417
1.66k
    _column_descs = ctx->column_descs;
418
1.66k
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
419
1.66k
    RETURN_IF_ERROR(_extract_partition_values(*ctx->range, ctx->tuple_descriptor,
420
1.66k
                                              _fill_partition_values,
421
1.66k
                                              &_fill_partition_value_is_null));
422
7.27k
    for (const auto& desc : *ctx->column_descs) {
423
7.27k
        if (desc.category == ColumnCategory::REGULAR ||
424
7.27k
            desc.category == ColumnCategory::GENERATED) {
425
7.24k
            ctx->column_names.push_back(desc.name);
426
7.24k
        } else if (desc.category == ColumnCategory::SYNTHESIZED &&
427
32
                   desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
428
30
            auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
429
30
            this->register_synthesized_column_handler(
430
30
                    desc.name,
431
30
                    [iter = std::move(topn_row_id_column_iter), this, &desc](
432
183
                            Block* block, size_t rows) -> Status {
433
183
                        return fill_topn_row_id(iter, desc.name, block, rows);
434
183
                    });
435
30
            continue;
436
30
        }
437
7.27k
    }
438
439
    // Build table_info_node from Parquet file metadata with case-insensitive recursive matching.
440
    // File is already opened by init_reader before this hook, so metadata is available.
441
    // tuple_descriptor may be null in unit tests that only set column_descs.
442
1.66k
    if (ctx->tuple_descriptor != nullptr) {
443
1.65k
        const FieldDescriptor* field_desc = nullptr;
444
1.65k
        RETURN_IF_ERROR(get_file_metadata_schema(&field_desc));
445
1.65k
        RETURN_IF_ERROR(TableSchemaChangeHelper::BuildTableInfoUtil::by_parquet_name(
446
1.65k
                ctx->tuple_descriptor, *field_desc, ctx->table_info_node));
447
1.65k
    }
448
449
1.66k
    return Status::OK();
450
1.66k
}
451
452
18.3k
Status ParquetReader::_open_file_reader(ReaderInitContext* /*ctx*/) {
453
18.3k
    return _open_file();
454
18.3k
}
455
456
18.2k
Status ParquetReader::_do_init_reader(ReaderInitContext* base_ctx) {
457
18.2k
    auto* ctx = checked_context_cast<ParquetInitContext>(base_ctx);
458
18.2k
    _col_name_to_block_idx = base_ctx->col_name_to_block_idx;
459
18.2k
    _tuple_descriptor = ctx->tuple_descriptor;
460
18.2k
    _row_descriptor = ctx->row_descriptor;
461
18.2k
    _colname_to_slot_id = ctx->colname_to_slot_id;
462
18.2k
    _not_single_slot_filter_conjuncts = ctx->not_single_slot_filter_conjuncts;
463
18.2k
    _slot_id_to_filter_conjuncts = ctx->slot_id_to_filter_conjuncts;
464
18.2k
    _filter_groups = ctx->filter_groups;
465
18.2k
    _table_info_node_ptr = base_ctx->table_info_node;
466
18.2k
    _column_ids = base_ctx->column_ids;
467
18.2k
    _filter_column_ids = base_ctx->filter_column_ids;
468
469
    // _open_file_reader (called by init_reader NVI before hooks) must have opened the file.
470
18.4E
    DCHECK(_file_metadata != nullptr)
471
18.4E
            << "ParquetReader::_do_init_reader called without _open_file_reader";
472
18.2k
    _t_metadata = &(_file_metadata->to_thrift());
473
474
18.2k
    SCOPED_RAW_TIMER(&_reader_statistics.parse_meta_time);
475
18.2k
    _total_groups = _t_metadata->row_groups.size();
476
18.2k
    if (_total_groups == 0) {
477
6
        return Status::EndOfFile("init reader failed, empty parquet file: " + _scan_range.path);
478
6
    }
479
18.2k
    _current_row_group_index = RowGroupReader::RowGroupIndex {-1, 0, 0};
480
481
    // Compute missing columns and file↔table column mapping.
482
    // This runs in _do_init_reader (not on_before_init_reader) because table-format readers
483
    // (Iceberg, Paimon, Hive, Hudi) override on_before_init_reader completely.
484
18.2k
    if (has_column_descs()) {
485
17.1k
        _fill_missing_cols.clear();
486
17.1k
        _fill_missing_defaults.clear();
487
62.3k
        for (const auto& col_name : base_ctx->column_names) {
488
62.3k
            if (!_table_info_node_ptr->children_column_exists(col_name)) {
489
2.10k
                _fill_missing_cols.insert(col_name);
490
2.10k
            }
491
62.3k
        }
492
17.1k
        if (_column_descs && !_fill_missing_cols.empty()) {
493
6.58k
            for (const auto& desc : *_column_descs) {
494
6.58k
                if (_fill_missing_cols.contains(desc.name) &&
495
6.58k
                    !_fill_partition_values.contains(desc.name)) {
496
2.09k
                    _fill_missing_defaults[desc.name] = desc.default_expr;
497
2.09k
                }
498
6.58k
            }
499
1.52k
        }
500
17.1k
    }
501
    // Resolve file-column ↔ table-column mapping in file-schema order.
502
    // _init_read_columns handles both normal path (missing cols populated above)
503
    // and standalone path (_fill_missing_cols empty, _table_info_node_ptr may be null).
504
18.2k
    _init_read_columns(base_ctx->column_names);
505
506
    // build column predicates for column lazy read
507
18.3k
    if (ctx->conjuncts != nullptr) {
508
18.3k
        _lazy_read_ctx.conjuncts = *ctx->conjuncts;
509
18.3k
    }
510
18.3k
    if (ctx->slot_id_to_predicates != nullptr) {
511
18.3k
        _lazy_read_ctx.slot_id_to_predicates = *ctx->slot_id_to_predicates;
512
18.3k
    }
513
514
    // ---- Inlined set_fill_columns logic (partition/missing/synthesized classification) ----
515
516
    // 1. Collect predicate columns from conjuncts for lazy materialization
517
18.2k
    std::unordered_map<std::string, std::pair<uint32_t, int>> predicate_columns;
518
18.2k
    _collect_predicate_columns_from_conjuncts(predicate_columns);
519
520
    // 2. Classify read/partition/missing/synthesized columns into lazy vs predicate groups
521
18.2k
    _classify_columns_for_lazy_read(predicate_columns, _fill_partition_values,
522
18.2k
                                    _fill_missing_defaults);
523
524
    // 3. Populate col_names vectors for ColumnProcessor path
525
18.2k
    for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
526
650
        _lazy_read_ctx.predicate_partition_col_names.emplace_back(kv.first);
527
650
    }
528
18.2k
    for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
529
727
        _lazy_read_ctx.predicate_missing_col_names.emplace_back(kv.first);
530
727
    }
531
18.2k
    for (auto& kv : _lazy_read_ctx.partition_columns) {
532
2.78k
        _lazy_read_ctx.partition_col_names.emplace_back(kv.first);
533
2.78k
    }
534
18.2k
    for (auto& kv : _lazy_read_ctx.missing_columns) {
535
2.04k
        _lazy_read_ctx.missing_col_names.emplace_back(kv.first);
536
2.04k
    }
537
538
18.2k
    if (_filter_groups && (_total_groups == 0 || _t_metadata->num_rows == 0 || _range_size < 0)) {
539
2
        return Status::EndOfFile("No row group to read");
540
2
    }
541
542
18.2k
    return Status::OK();
543
18.2k
}
544
545
18.3k
void ParquetReader::_init_read_columns(const std::vector<std::string>& column_names) {
546
    // Build file_col_name → table_col_name map, skipping missing columns.
547
    // Must iterate file schema in physical order so that _generate_random_access_ranges
548
    // sees monotonically increasing chunk offsets.
549
18.3k
    auto schema_desc = _file_metadata->schema();
550
18.3k
    std::map<std::string, std::string> required_file_columns;
551
64.7k
    for (const auto& col_name : column_names) {
552
64.7k
        if (_fill_missing_cols.contains(col_name)) {
553
2.10k
            continue;
554
2.10k
        }
555
62.6k
        std::string file_col = col_name;
556
62.6k
        if (_table_info_node_ptr && _table_info_node_ptr->children_column_exists(col_name)) {
557
62.6k
            file_col = _table_info_node_ptr->children_file_column_name(col_name);
558
62.6k
        }
559
62.6k
        required_file_columns[file_col] = col_name;
560
62.6k
    }
561
171k
    for (int i = 0; i < schema_desc.size(); ++i) {
562
152k
        const auto& name = schema_desc.get_column(i)->name;
563
152k
        if (required_file_columns.contains(name)) {
564
62.6k
            _read_file_columns.emplace_back(name);
565
62.6k
            _read_table_columns.emplace_back(required_file_columns[name]);
566
62.6k
            _read_table_columns_set.insert(required_file_columns[name]);
567
62.6k
        }
568
152k
    }
569
18.3k
}
570
571
7.49k
bool ParquetReader::_exists_in_file(const std::string& expr_name) const {
572
    // `_read_table_columns_set` is used to ensure that only columns actually read are subject to min-max filtering.
573
    // This primarily handles cases where partition columns also exist in a file. The reason it's not modified
574
    // in `_table_info_node_ptr` is that Iceberg、Hudi has inconsistent requirements for this node;
575
    // Iceberg partition evolution need read partition columns from a file.
576
    // hudi set `hoodie.datasource.write.drop.partition.columns=false` not need read partition columns from a file.
577
7.49k
    return _table_info_node_ptr->children_column_exists(expr_name) &&
578
7.49k
           _read_table_columns_set.contains(expr_name);
579
7.49k
}
580
581
6.30k
bool ParquetReader::_type_matches(const int cid) const {
582
6.30k
    auto* slot = _tuple_descriptor->slots()[cid];
583
6.30k
    auto table_col_type = remove_nullable(slot->type());
584
585
6.30k
    const auto& file_col_name = _table_info_node_ptr->children_file_column_name(slot->col_name());
586
6.30k
    const auto& file_col_type =
587
6.30k
            remove_nullable(_file_metadata->schema().get_column(file_col_name)->data_type);
588
589
6.30k
    return (table_col_type->get_primitive_type() == file_col_type->get_primitive_type()) &&
590
6.30k
           !is_complex_type(table_col_type->get_primitive_type());
591
6.30k
}
592
593
void ParquetReader::_collect_predicate_columns_from_conjuncts(
594
18.2k
        std::unordered_map<std::string, std::pair<uint32_t, int>>& predicate_columns) {
595
35.3k
    std::function<void(VExpr * expr)> visit_slot = [&](VExpr* expr) {
596
35.3k
        if (expr->is_slot_ref()) {
597
10.9k
            VSlotRef* slot_ref = static_cast<VSlotRef*>(expr);
598
10.9k
            auto expr_name = slot_ref->expr_name();
599
10.9k
            predicate_columns.emplace(expr_name,
600
10.9k
                                      std::make_pair(slot_ref->column_id(), slot_ref->slot_id()));
601
10.9k
            if (slot_ref->column_id() == 0) {
602
7.59k
                _lazy_read_ctx.resize_first_column = false;
603
7.59k
            }
604
10.9k
            return;
605
10.9k
        }
606
24.7k
        for (auto& child : expr->children()) {
607
24.7k
            visit_slot(child.get());
608
24.7k
        }
609
24.4k
    };
610
611
18.2k
    for (const auto& conjunct : _lazy_read_ctx.conjuncts) {
612
10.6k
        auto expr = conjunct->root();
613
10.6k
        if (expr->is_rf_wrapper()) {
614
3.02k
            RuntimeFilterExpr* runtime_filter = assert_cast<RuntimeFilterExpr*>(expr.get());
615
3.02k
            auto filter_impl = runtime_filter->get_impl();
616
3.02k
            visit_slot(filter_impl.get());
617
7.63k
        } else {
618
7.63k
            visit_slot(expr.get());
619
7.63k
        }
620
10.6k
    }
621
622
18.2k
    if (!_lazy_read_ctx.slot_id_to_predicates.empty()) {
623
16.4k
        auto and_pred = AndBlockColumnPredicate::create_unique();
624
63.4k
        for (const auto& entry : _lazy_read_ctx.slot_id_to_predicates) {
625
63.4k
            for (const auto& pred : entry.second) {
626
                // Parquet shares _push_down_predicates for row-group/page min-max pruning and
627
                // bloom-filter evaluation, so this flag currently gates both predicate paths.
628
7.54k
                if (!has_column_optimization(pred->col_name(), ColumnOptimizationTypes::MIN_MAX)) {
629
10
                    continue;
630
10
                }
631
7.53k
                if (!_exists_in_file(pred->col_name()) || !_type_matches(pred->column_id())) {
632
1.41k
                    continue;
633
1.41k
                }
634
6.12k
                and_pred->add_column_predicate(
635
6.12k
                        SingleColumnBlockPredicate::create_unique(pred->clone(pred->column_id())));
636
6.12k
            }
637
63.4k
        }
638
16.4k
        if (and_pred->num_of_column_predicate() > 0) {
639
4.05k
            _push_down_predicates.push_back(std::move(and_pred));
640
4.05k
        }
641
16.4k
    }
642
18.2k
}
643
644
void ParquetReader::_classify_columns_for_lazy_read(
645
        const std::unordered_map<std::string, std::pair<uint32_t, int>>&
646
                predicate_conjuncts_columns,
647
        const std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>&
648
                partition_columns,
649
18.1k
        const std::unordered_map<std::string, VExprContextSPtr>& missing_columns) {
650
18.1k
    const FieldDescriptor& schema = _file_metadata->schema();
651
18.1k
    auto predicate_columns = predicate_conjuncts_columns;
652
18.1k
#ifndef BE_TEST
653
18.1k
    for (const auto& [col_name, _] : _generated_col_handlers) {
654
220
        int slot_id = -1;
655
661
        for (auto slot : _tuple_descriptor->slots()) {
656
661
            if (slot->col_name() == col_name) {
657
218
                slot_id = slot->id();
658
218
                break;
659
218
            }
660
661
        }
661
220
        DCHECK(slot_id != -1) << "slot id should not be -1 for generated column: " << col_name;
662
220
        auto column_index = _row_descriptor->get_column_id(slot_id);
663
220
        if (column_index == 0) {
664
20
            _lazy_read_ctx.resize_first_column = false;
665
20
        }
666
        // assume generated columns are only used for predicate push down.
667
220
        predicate_columns.emplace(col_name, std::make_pair(column_index, slot_id));
668
220
    }
669
670
18.1k
    for (const auto& [col_name, _] : _synthesized_col_handlers) {
671
1.10k
        int slot_id = -1;
672
2.67k
        for (auto slot : _tuple_descriptor->slots()) {
673
2.67k
            if (slot->col_name() == col_name) {
674
1.10k
                slot_id = slot->id();
675
1.10k
                break;
676
1.10k
            }
677
2.67k
        }
678
1.10k
        DCHECK(slot_id != -1) << "slot id should not be -1 for synthesized column: " << col_name;
679
1.10k
        auto column_index = _row_descriptor->get_column_id(slot_id);
680
1.10k
        if (column_index == 0) {
681
0
            _lazy_read_ctx.resize_first_column = false;
682
0
        }
683
        // synthesized columns always fill data on first phase.
684
1.10k
        _lazy_read_ctx.all_predicate_col_ids.emplace_back(column_index);
685
1.10k
    }
686
18.1k
#endif
687
62.1k
    for (auto& read_table_col : _read_table_columns) {
688
62.1k
        _lazy_read_ctx.all_read_columns.emplace_back(read_table_col);
689
690
62.1k
        auto file_column_name = _table_info_node_ptr->children_file_column_name(read_table_col);
691
62.1k
        PrimitiveType column_type =
692
62.1k
                schema.get_column(file_column_name)->data_type->get_primitive_type();
693
62.1k
        if (is_complex_type(column_type)) {
694
16.6k
            _lazy_read_ctx.has_complex_type = true;
695
16.6k
        }
696
62.1k
        if (predicate_columns.size() > 0) {
697
18.8k
            auto iter = predicate_columns.find(read_table_col);
698
18.8k
            if (iter == predicate_columns.end()) {
699
11.7k
                _lazy_read_ctx.lazy_read_columns.emplace_back(read_table_col);
700
11.7k
            } else {
701
7.04k
                _lazy_read_ctx.predicate_columns.first.emplace_back(iter->first);
702
7.04k
                _lazy_read_ctx.predicate_columns.second.emplace_back(iter->second.second);
703
7.04k
                _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
704
7.04k
            }
705
18.8k
        }
706
62.1k
    }
707
708
18.1k
    for (auto& kv : partition_columns) {
709
2.82k
        auto iter = predicate_columns.find(kv.first);
710
2.82k
        if (iter == predicate_columns.end()) {
711
2.17k
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
712
2.17k
        } else {
713
649
            _lazy_read_ctx.predicate_partition_columns.emplace(kv.first, kv.second);
714
649
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
715
649
        }
716
2.82k
    }
717
718
18.1k
    for (auto& kv : missing_columns) {
719
2.09k
        auto iter = predicate_columns.find(kv.first);
720
2.09k
        if (iter != predicate_columns.end()) {
721
            //For check missing column :   missing column == xx, missing column is null,missing column is not null.
722
727
            if (_slot_id_to_filter_conjuncts->find(iter->second.second) !=
723
727
                _slot_id_to_filter_conjuncts->end()) {
724
410
                for (auto& ctx : _slot_id_to_filter_conjuncts->find(iter->second.second)->second) {
725
410
                    _lazy_read_ctx.missing_columns_conjuncts.emplace_back(ctx);
726
410
                }
727
406
            }
728
727
            _lazy_read_ctx.predicate_missing_columns.emplace(kv.first, kv.second);
729
727
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
730
1.36k
        } else {
731
1.36k
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
732
1.36k
        }
733
2.09k
    }
734
735
18.2k
    if (_enable_lazy_mat && _lazy_read_ctx.predicate_columns.first.size() > 0 &&
736
18.1k
        _lazy_read_ctx.lazy_read_columns.size() > 0) {
737
3.57k
        _lazy_read_ctx.can_lazy_read = true;
738
3.57k
    }
739
740
18.1k
    if (!_lazy_read_ctx.can_lazy_read) {
741
14.6k
        for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
742
619
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
743
619
        }
744
14.6k
        for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
745
674
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
746
674
        }
747
14.6k
    }
748
18.1k
}
749
750
// init file reader and file metadata for parsing schema
751
2.04k
Status ParquetReader::init_schema_reader() {
752
2.04k
    RETURN_IF_ERROR(_open_file());
753
2.03k
    _t_metadata = &(_file_metadata->to_thrift());
754
2.03k
    return Status::OK();
755
2.04k
}
756
757
Status ParquetReader::get_parsed_schema(std::vector<std::string>* col_names,
758
1.27k
                                        std::vector<DataTypePtr>* col_types) {
759
1.27k
    _total_groups = _t_metadata->row_groups.size();
760
1.27k
    auto schema_desc = _file_metadata->schema();
761
8.28k
    for (int i = 0; i < schema_desc.size(); ++i) {
762
        // Get the Column Reader for the boolean column
763
7.01k
        col_names->emplace_back(schema_desc.get_column(i)->name);
764
7.01k
        col_types->emplace_back(make_nullable(schema_desc.get_column(i)->data_type));
765
7.01k
    }
766
1.27k
    return Status::OK();
767
1.27k
}
768
769
Status ParquetReader::_get_columns_impl(
770
17.0k
        std::unordered_map<std::string, DataTypePtr>* name_to_type) {
771
17.0k
    const auto& schema_desc = _file_metadata->schema();
772
17.0k
    std::unordered_set<std::string> column_names;
773
17.0k
    schema_desc.get_column_names(&column_names);
774
150k
    for (auto& name : column_names) {
775
150k
        auto field = schema_desc.get_column(name);
776
150k
        name_to_type->emplace(name, field->data_type);
777
150k
    }
778
17.0k
    return Status::OK();
779
17.0k
}
780
781
39.4k
Status ParquetReader::_do_get_next_block(Block* block, size_t* read_rows, bool* eof) {
782
39.4k
    if (_current_group_reader == nullptr || _row_group_eof) {
783
22.2k
        Status st = _next_row_group_reader();
784
22.2k
        if (!st.ok() && !st.is<ErrorCode::END_OF_FILE>()) {
785
0
            return st;
786
0
        }
787
22.2k
        if (_current_group_reader == nullptr || _row_group_eof || st.is<ErrorCode::END_OF_FILE>()) {
788
2.66k
            _current_group_reader.reset(nullptr);
789
2.66k
            _row_group_eof = true;
790
2.66k
            *read_rows = 0;
791
2.66k
            *eof = true;
792
2.66k
            return Status::OK();
793
2.66k
        }
794
22.2k
    }
795
796
    // Limit memory per batch for load paths.
797
    // _load_bytes_per_row is updated after each batch so the *next* call pre-shrinks _batch_size
798
    // before reading, ensuring the current batch is already within the limit (from call 2 onward).
799
36.7k
    const int64_t max_block_bytes =
800
36.8k
            (_state != nullptr && _state->query_type() == TQueryType::LOAD &&
801
36.7k
             config::load_reader_max_block_bytes > 0)
802
36.7k
                    ? config::load_reader_max_block_bytes
803
36.7k
                    : 0;
804
36.7k
    if (max_block_bytes > 0 && _load_bytes_per_row > 0) {
805
95
        _batch_size = std::max((size_t)1,
806
95
                               (size_t)((int64_t)max_block_bytes / (int64_t)_load_bytes_per_row));
807
95
    }
808
809
36.7k
    SCOPED_RAW_TIMER(&_reader_statistics.column_read_time);
810
36.7k
    Status batch_st =
811
36.7k
            _current_group_reader->next_batch(block, _batch_size, read_rows, &_row_group_eof);
812
36.7k
    if (batch_st.is<ErrorCode::END_OF_FILE>()) {
813
1
        block->clear_column_data();
814
1
        _current_group_reader.reset(nullptr);
815
1
        *read_rows = 0;
816
1
        *eof = true;
817
1
        return Status::OK();
818
1
    }
819
820
36.7k
    if (!batch_st.ok()) {
821
10
        return Status::InternalError("Read parquet file {} failed, reason = {}", _scan_range.path,
822
10
                                     batch_st.to_string());
823
10
    }
824
825
36.7k
    if (max_block_bytes > 0 && *read_rows > 0) {
826
1.06k
        _load_bytes_per_row = block->bytes() / *read_rows;
827
1.06k
    }
828
829
36.7k
    if (_row_group_eof) {
830
19.4k
        auto column_st = _current_group_reader->merged_column_statistics();
831
19.4k
        _column_statistics.merge(column_st);
832
19.4k
        _reader_statistics.lazy_read_filtered_rows +=
833
19.4k
                _current_group_reader->lazy_read_filtered_rows();
834
19.4k
        _reader_statistics.predicate_filter_time += _current_group_reader->predicate_filter_time();
835
19.4k
        _reader_statistics.dict_filter_rewrite_time +=
836
19.4k
                _current_group_reader->dict_filter_rewrite_time();
837
19.4k
        if (_io_ctx) {
838
19.4k
            _io_ctx->condition_cache_filtered_rows +=
839
19.4k
                    _current_group_reader->condition_cache_filtered_rows();
840
19.4k
        }
841
842
19.4k
        if (_current_row_group_index.row_group_id + 1 == _total_groups) {
843
15.2k
            *eof = true;
844
15.2k
        } else {
845
4.23k
            *eof = false;
846
4.23k
        }
847
19.4k
    }
848
36.7k
    return Status::OK();
849
36.7k
}
850
851
RowGroupReader::PositionDeleteContext ParquetReader::_get_position_delete_ctx(
852
19.6k
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index) {
853
19.6k
    if (_delete_rows == nullptr) {
854
18.1k
        return RowGroupReader::PositionDeleteContext(row_group.num_rows, row_group_index.first_row);
855
18.1k
    }
856
1.49k
    const int64_t* delete_rows = &(*_delete_rows)[0];
857
1.49k
    const int64_t* delete_rows_end = delete_rows + _delete_rows->size();
858
1.49k
    const int64_t* start_pos = std::lower_bound(delete_rows + _delete_rows_index, delete_rows_end,
859
1.49k
                                                row_group_index.first_row);
860
1.49k
    int64_t start_index = start_pos - delete_rows;
861
1.49k
    const int64_t* end_pos = std::lower_bound(start_pos, delete_rows_end, row_group_index.last_row);
862
1.49k
    int64_t end_index = end_pos - delete_rows;
863
1.49k
    _delete_rows_index = end_index;
864
1.49k
    return RowGroupReader::PositionDeleteContext(*_delete_rows, row_group.num_rows,
865
1.49k
                                                 row_group_index.first_row, start_index, end_index);
866
19.6k
}
867
868
22.2k
Status ParquetReader::_next_row_group_reader() {
869
22.2k
    if (_current_group_reader != nullptr) {
870
4.22k
        _current_group_reader->collect_profile_before_close();
871
4.22k
    }
872
873
22.2k
    RowRanges candidate_row_ranges;
874
51.4k
    while (++_current_row_group_index.row_group_id < _total_groups) {
875
48.7k
        const auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
876
48.7k
        _current_row_group_index.first_row = _current_row_group_index.last_row;
877
48.7k
        _current_row_group_index.last_row = _current_row_group_index.last_row + row_group.num_rows;
878
879
48.7k
        if (_filter_groups && _is_misaligned_range_group(row_group)) {
880
25.7k
            continue;
881
25.7k
        }
882
883
23.0k
        candidate_row_ranges.clear();
884
        // The range of lines to be read is determined by the push down predicate.
885
23.0k
        RETURN_IF_ERROR(_process_min_max_bloom_filter(
886
23.0k
                _current_row_group_index, row_group, _push_down_predicates, &candidate_row_ranges));
887
888
23.0k
        std::function<int64_t(const FieldSchema*)> column_compressed_size =
889
127k
                [&row_group, &column_compressed_size](const FieldSchema* field) -> int64_t {
890
127k
            if (field->physical_column_index >= 0) {
891
104k
                int parquet_col_id = field->physical_column_index;
892
104k
                if (row_group.columns[parquet_col_id].__isset.meta_data) {
893
104k
                    return row_group.columns[parquet_col_id].meta_data.total_compressed_size;
894
104k
                }
895
18.4E
                return 0;
896
104k
            }
897
23.5k
            int64_t size = 0;
898
39.6k
            for (const FieldSchema& child : field->children) {
899
39.6k
                size += column_compressed_size(&child);
900
39.6k
            }
901
23.5k
            return size;
902
127k
        };
903
23.0k
        int64_t group_size = 0; // only calculate the needed columns
904
88.0k
        for (auto& read_col : _read_file_columns) {
905
88.0k
            const FieldSchema* field = _file_metadata->schema().get_column(read_col);
906
88.0k
            group_size += column_compressed_size(field);
907
88.0k
        }
908
909
23.0k
        _reader_statistics.read_rows += candidate_row_ranges.count();
910
23.0k
        if (_io_ctx && _io_ctx->file_reader_stats) {
911
23.0k
            _io_ctx->file_reader_stats->read_rows += candidate_row_ranges.count();
912
23.0k
        }
913
914
23.0k
        if (candidate_row_ranges.count() != 0) {
915
            // need read this row group.
916
19.6k
            _reader_statistics.read_row_groups++;
917
19.6k
            _reader_statistics.filtered_page_rows +=
918
19.6k
                    row_group.num_rows - candidate_row_ranges.count();
919
19.6k
            break;
920
19.6k
        } else {
921
            // this row group be filtered.
922
3.43k
            _reader_statistics.filtered_row_groups++;
923
3.43k
            _reader_statistics.filtered_bytes += group_size;
924
3.43k
            _reader_statistics.filtered_group_rows += row_group.num_rows;
925
3.43k
        }
926
23.0k
    }
927
928
22.2k
    if (_current_row_group_index.row_group_id == _total_groups) {
929
2.66k
        _row_group_eof = true;
930
2.66k
        _current_group_reader.reset(nullptr);
931
2.66k
        return Status::EndOfFile("No next RowGroupReader");
932
2.66k
    }
933
934
    // process page index and generate the ranges to read
935
19.6k
    auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
936
937
19.6k
    RowGroupReader::PositionDeleteContext position_delete_ctx =
938
19.6k
            _get_position_delete_ctx(row_group, _current_row_group_index);
939
19.6k
    io::FileReaderSPtr group_file_reader;
940
19.6k
    if (typeid_cast<io::InMemoryFileReader*>(_file_reader.get())) {
941
        // InMemoryFileReader has the ability to merge small IO
942
11.1k
        group_file_reader = _file_reader;
943
11.1k
    } else {
944
8.49k
        size_t avg_io_size = 0;
945
8.49k
        const std::vector<io::PrefetchRange> io_ranges =
946
8.49k
                _generate_random_access_ranges(_current_row_group_index, &avg_io_size);
947
8.49k
        int64_t merged_read_slice_size = -1;
948
8.49k
        if (_state != nullptr && _state->query_options().__isset.merge_read_slice_size) {
949
8.46k
            merged_read_slice_size = _state->query_options().merge_read_slice_size;
950
8.46k
        }
951
        // The underlying page reader will prefetch data in column.
952
        // Using both MergeRangeFileReader and BufferedStreamReader simultaneously would waste a lot of memory.
953
8.49k
        group_file_reader =
954
8.49k
                avg_io_size < io::MergeRangeFileReader::SMALL_IO
955
8.49k
                        ? std::make_shared<io::MergeRangeFileReader>(
956
8.45k
                                  _profile, _file_reader, io_ranges, merged_read_slice_size)
957
8.49k
                        : _file_reader;
958
8.49k
    }
959
19.6k
    _current_group_reader.reset(new RowGroupReader(
960
19.6k
            _io_ctx && _io_ctx->file_reader_stats
961
19.6k
                    ? std::make_shared<io::TracingFileReader>(group_file_reader,
962
19.5k
                                                              _io_ctx->file_reader_stats)
963
19.6k
                    : group_file_reader,
964
19.6k
            _read_table_columns, _current_row_group_index.row_group_id, row_group, _ctz, _io_ctx,
965
19.6k
            position_delete_ctx, _lazy_read_ctx, _state, _column_ids, _filter_column_ids));
966
19.6k
    _row_group_eof = false;
967
968
19.6k
    _current_group_reader->set_current_row_group_idx(_current_row_group_index);
969
19.6k
    _current_group_reader->set_col_name_to_block_idx(_col_name_to_block_idx);
970
19.6k
    if (_condition_cache_ctx) {
971
3.68k
        _current_group_reader->set_condition_cache_context(_condition_cache_ctx);
972
3.68k
    }
973
19.6k
    _current_group_reader->set_table_format_reader(this);
974
975
19.6k
    _current_group_reader->_table_info_node_ptr = _table_info_node_ptr;
976
19.6k
    return _current_group_reader->init(_file_metadata->schema(), candidate_row_ranges, _col_offsets,
977
19.6k
                                       _tuple_descriptor, _row_descriptor, _colname_to_slot_id,
978
19.6k
                                       _not_single_slot_filter_conjuncts,
979
19.6k
                                       _slot_id_to_filter_conjuncts);
980
22.2k
}
981
982
std::vector<io::PrefetchRange> ParquetReader::_generate_random_access_ranges(
983
8.46k
        const RowGroupReader::RowGroupIndex& group, size_t* avg_io_size) {
984
8.46k
    std::vector<io::PrefetchRange> result;
985
8.46k
    int64_t last_chunk_end = -1;
986
8.46k
    size_t total_io_size = 0;
987
8.46k
    std::function<void(const FieldSchema*, const tparquet::RowGroup&)> scalar_range =
988
66.3k
            [&](const FieldSchema* field, const tparquet::RowGroup& row_group) {
989
66.3k
                if (_column_ids.empty() ||
990
66.4k
                    _column_ids.find(field->get_column_id()) != _column_ids.end()) {
991
66.4k
                    if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
992
7.30k
                        scalar_range(&field->children[0], row_group);
993
59.1k
                    } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
994
4.97k
                        scalar_range(&field->children[0], row_group);
995
4.97k
                        scalar_range(&field->children[1], row_group);
996
54.1k
                    } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
997
10.0k
                        for (int i = 0; i < field->children.size(); ++i) {
998
6.84k
                            scalar_range(&field->children[i], row_group);
999
6.84k
                        }
1000
50.9k
                    } else {
1001
50.9k
                        const tparquet::ColumnChunk& chunk =
1002
50.9k
                                row_group.columns[field->physical_column_index];
1003
50.9k
                        auto& chunk_meta = chunk.meta_data;
1004
50.9k
                        int64_t chunk_start = has_dict_page(chunk_meta)
1005
50.9k
                                                      ? chunk_meta.dictionary_page_offset
1006
50.9k
                                                      : chunk_meta.data_page_offset;
1007
50.9k
                        int64_t chunk_end = chunk_start + chunk_meta.total_compressed_size;
1008
50.9k
                        DCHECK_GE(chunk_start, last_chunk_end);
1009
50.9k
                        result.emplace_back(chunk_start, chunk_end);
1010
50.9k
                        total_io_size += chunk_meta.total_compressed_size;
1011
50.9k
                        last_chunk_end = chunk_end;
1012
50.9k
                    }
1013
66.4k
                }
1014
66.3k
            };
1015
8.46k
    const tparquet::RowGroup& row_group = _t_metadata->row_groups[group.row_group_id];
1016
42.3k
    for (const auto& read_col : _read_file_columns) {
1017
42.3k
        const FieldSchema* field = _file_metadata->schema().get_column(read_col);
1018
42.3k
        scalar_range(field, row_group);
1019
42.3k
    }
1020
8.46k
    if (!result.empty()) {
1021
8.22k
        *avg_io_size = total_io_size / result.size();
1022
8.22k
    }
1023
8.46k
    return result;
1024
8.46k
}
1025
1026
54.3k
bool ParquetReader::_is_misaligned_range_group(const tparquet::RowGroup& row_group) const {
1027
54.3k
    int64_t start_offset = _get_column_start_offset(row_group.columns[0].meta_data);
1028
1029
54.3k
    auto& last_column = row_group.columns[row_group.columns.size() - 1].meta_data;
1030
54.3k
    int64_t end_offset = _get_column_start_offset(last_column) + last_column.total_compressed_size;
1031
1032
54.3k
    int64_t row_group_mid = start_offset + (end_offset - start_offset) / 2;
1033
54.3k
    if (!(row_group_mid >= _range_start_offset &&
1034
54.3k
          row_group_mid < _range_start_offset + _range_size)) {
1035
25.8k
        return true;
1036
25.8k
    }
1037
28.4k
    return false;
1038
54.3k
}
1039
1040
2.30k
int64_t ParquetReader::get_total_rows() const {
1041
2.30k
    if (!_t_metadata) return 0;
1042
2.30k
    if (!_filter_groups) return _t_metadata->num_rows;
1043
2.30k
    int64_t total = 0;
1044
3.47k
    for (const auto& rg : _t_metadata->row_groups) {
1045
3.47k
        if (!_is_misaligned_range_group(rg)) {
1046
3.32k
            total += rg.num_rows;
1047
3.32k
        }
1048
3.47k
    }
1049
2.30k
    return total;
1050
2.30k
}
1051
1052
3.24k
void ParquetReader::set_condition_cache_context(std::shared_ptr<ConditionCacheContext> ctx) {
1053
3.24k
    _condition_cache_ctx = std::move(ctx);
1054
3.24k
    if (!_condition_cache_ctx || !_t_metadata || !_filter_groups) {
1055
0
        return;
1056
0
    }
1057
    // Find the first assigned row group to compute base_granule.
1058
3.24k
    int64_t first_row = 0;
1059
3.24k
    for (const auto& rg : _t_metadata->row_groups) {
1060
3.24k
        if (!_is_misaligned_range_group(rg)) {
1061
3.23k
            _condition_cache_ctx->base_granule = first_row / ConditionCacheContext::GRANULE_SIZE;
1062
3.23k
            return;
1063
3.23k
        }
1064
4
        first_row += rg.num_rows;
1065
4
    }
1066
3.24k
}
1067
1068
Status ParquetReader::_process_page_index_filter(
1069
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index,
1070
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1071
17.6k
        RowRanges* candidate_row_ranges) {
1072
17.6k
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
1073
0
        return Status::EndOfFile("stop");
1074
0
    }
1075
1076
17.6k
    std::function<void()> read_whole_row_group = [&]() {
1077
15.5k
        candidate_row_ranges->add(RowRange {0, row_group.num_rows});
1078
15.5k
    };
1079
1080
    // Check if the page index is available and if it exists.
1081
17.6k
    PageIndex page_index;
1082
17.7k
    if (!config::enable_parquet_page_index || _colname_to_slot_id == nullptr ||
1083
17.7k
        !page_index.check_and_get_page_index_ranges(row_group.columns)) {
1084
8.89k
        read_whole_row_group();
1085
8.89k
        return Status::OK();
1086
8.89k
    }
1087
1088
8.76k
    std::vector<int> parquet_col_ids;
1089
31.0k
    for (size_t idx = 0; idx < _read_table_columns.size(); idx++) {
1090
22.2k
        const auto& read_table_col = _read_table_columns[idx];
1091
22.2k
        const auto& read_file_col = _read_file_columns[idx];
1092
22.2k
        if (!_colname_to_slot_id->contains(read_table_col)) {
1093
422
            continue;
1094
422
        }
1095
21.8k
        auto* field = _file_metadata->schema().get_column(read_file_col);
1096
1097
37.3k
        std::function<void(FieldSchema * field)> f = [&](FieldSchema* field) {
1098
37.3k
            if (!_column_ids.empty() &&
1099
37.3k
                _column_ids.find(field->get_column_id()) == _column_ids.end()) {
1100
1.27k
                return;
1101
1.27k
            }
1102
1103
36.0k
            if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
1104
2.14k
                f(&field->children[0]);
1105
33.8k
            } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
1106
1.73k
                f(&field->children[0]);
1107
1.73k
                f(&field->children[1]);
1108
32.1k
            } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
1109
13.9k
                for (int i = 0; i < field->children.size(); ++i) {
1110
9.93k
                    f(&field->children[i]);
1111
9.93k
                }
1112
28.1k
            } else {
1113
28.1k
                int parquet_col_id = field->physical_column_index;
1114
28.1k
                if (parquet_col_id >= 0) {
1115
28.1k
                    parquet_col_ids.push_back(parquet_col_id);
1116
28.1k
                }
1117
28.1k
            }
1118
36.0k
        };
1119
1120
21.8k
        f(field);
1121
21.8k
    }
1122
1123
8.81k
    auto parse_offset_index = [&]() -> Status {
1124
8.81k
        std::vector<uint8_t> off_index_buff(page_index._offset_index_size);
1125
8.81k
        Slice res(off_index_buff.data(), page_index._offset_index_size);
1126
8.81k
        size_t bytes_read = 0;
1127
8.81k
        {
1128
8.81k
            SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1129
8.81k
            RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._offset_index_start, res,
1130
8.81k
                                                          &bytes_read, _io_ctx));
1131
8.81k
        }
1132
8.81k
        _column_statistics.page_index_read_calls++;
1133
8.81k
        _col_offsets.clear();
1134
1135
28.1k
        for (auto parquet_col_id : parquet_col_ids) {
1136
28.1k
            auto& chunk = row_group.columns[parquet_col_id];
1137
28.1k
            if (chunk.offset_index_length == 0) [[unlikely]] {
1138
0
                continue;
1139
0
            }
1140
28.1k
            tparquet::OffsetIndex offset_index;
1141
28.1k
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1142
28.1k
            RETURN_IF_ERROR(
1143
28.1k
                    page_index.parse_offset_index(chunk, off_index_buff.data(), &offset_index));
1144
28.1k
            _col_offsets[parquet_col_id] = offset_index;
1145
28.1k
        }
1146
8.81k
        return Status::OK();
1147
8.81k
    };
1148
1149
    // from https://github.com/apache/doris/pull/55795
1150
8.76k
    RETURN_IF_ERROR(parse_offset_index());
1151
1152
    // Check if page index is needed for min-max filter.
1153
8.78k
    if (!_enable_filter_by_min_max || push_down_pred.empty()) {
1154
6.66k
        read_whole_row_group();
1155
6.66k
        return Status::OK();
1156
6.66k
    }
1157
1158
    // read column index.
1159
2.10k
    std::vector<uint8_t> col_index_buff(page_index._column_index_size);
1160
2.10k
    size_t bytes_read = 0;
1161
2.10k
    Slice result(col_index_buff.data(), page_index._column_index_size);
1162
2.10k
    {
1163
2.10k
        SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1164
2.10k
        RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._column_index_start, result,
1165
2.10k
                                                      &bytes_read, _io_ctx));
1166
2.10k
    }
1167
2.10k
    _column_statistics.page_index_read_calls++;
1168
1169
2.10k
    SCOPED_RAW_TIMER(&_reader_statistics.page_index_filter_time);
1170
1171
    // Construct a cacheable page index structure to avoid repeatedly reading the page index of the same column.
1172
2.10k
    ParquetPredicate::CachedPageIndexStat cached_page_index;
1173
2.10k
    cached_page_index.ctz = _ctz;
1174
2.10k
    std::function<bool(ParquetPredicate::PageIndexStat**, int)> get_stat_func =
1175
2.10k
            [&](ParquetPredicate::PageIndexStat** ans, const int cid) -> bool {
1176
1.89k
        if (cached_page_index.stats.contains(cid)) {
1177
755
            *ans = &cached_page_index.stats[cid];
1178
755
            return (*ans)->available;
1179
755
        }
1180
1.14k
        cached_page_index.stats.emplace(cid, ParquetPredicate::PageIndexStat {});
1181
1.14k
        auto& sig_stat = cached_page_index.stats[cid];
1182
1183
1.14k
        auto* slot = _tuple_descriptor->slots()[cid];
1184
1.14k
        if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1185
            // table column not exist in file, may be schema change.
1186
0
            return false;
1187
0
        }
1188
1189
1.14k
        const auto& file_col_name =
1190
1.14k
                _table_info_node_ptr->children_file_column_name(slot->col_name());
1191
1.14k
        const FieldSchema* col_schema = _file_metadata->schema().get_column(file_col_name);
1192
1.14k
        int parquet_col_id = col_schema->physical_column_index;
1193
1194
1.14k
        if (parquet_col_id < 0) {
1195
            // complex type, not support page index yet.
1196
0
            return false;
1197
0
        }
1198
1.14k
        if (!_col_offsets.contains(parquet_col_id)) {
1199
            // If the file contains partition columns and the query applies filters on those
1200
            // partition columns, then reading the page index is unnecessary.
1201
0
            return false;
1202
0
        }
1203
1204
1.14k
        auto& column_chunk = row_group.columns[parquet_col_id];
1205
1.14k
        if (column_chunk.column_index_length == 0 || column_chunk.offset_index_length == 0) {
1206
            // column no page index.
1207
0
            return false;
1208
0
        }
1209
1210
1.14k
        tparquet::ColumnIndex column_index;
1211
1.14k
        {
1212
1.14k
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1213
1.14k
            RETURN_IF_ERROR(page_index.parse_column_index(column_chunk, col_index_buff.data(),
1214
1.14k
                                                          &column_index));
1215
1.14k
        }
1216
1.14k
        const int64_t num_of_pages = column_index.null_pages.size();
1217
1.14k
        if (num_of_pages <= 0) [[unlikely]] {
1218
            // no page. (maybe this row group no data.)
1219
0
            return false;
1220
0
        }
1221
1.14k
        DCHECK_EQ(column_index.min_values.size(), column_index.max_values.size());
1222
1.14k
        if (!column_index.__isset.null_counts) {
1223
            // not set null or null counts;
1224
0
            return false;
1225
0
        }
1226
1227
1.14k
        auto& offset_index = _col_offsets[parquet_col_id];
1228
1.14k
        const auto& page_locations = offset_index.page_locations;
1229
1230
1.14k
        sig_stat.col_schema = col_schema;
1231
1.14k
        sig_stat.num_of_pages = num_of_pages;
1232
1.14k
        sig_stat.encoded_min_value = column_index.min_values;
1233
1.14k
        sig_stat.encoded_max_value = column_index.max_values;
1234
1.14k
        sig_stat.is_all_null.resize(num_of_pages);
1235
1.14k
        sig_stat.has_null.resize(num_of_pages);
1236
1.14k
        sig_stat.ranges.resize(num_of_pages);
1237
1238
10.6k
        for (int page_id = 0; page_id < num_of_pages; page_id++) {
1239
9.52k
            sig_stat.is_all_null[page_id] = column_index.null_pages[page_id];
1240
9.52k
            sig_stat.has_null[page_id] = column_index.null_counts[page_id] > 0;
1241
1242
9.52k
            int64_t from = page_locations[page_id].first_row_index;
1243
9.52k
            int64_t to = 0;
1244
9.52k
            if (page_id == page_locations.size() - 1) {
1245
1.14k
                to = row_group_index.last_row;
1246
8.38k
            } else {
1247
8.38k
                to = page_locations[page_id + 1].first_row_index;
1248
8.38k
            }
1249
9.52k
            sig_stat.ranges[page_id] = RowRange {from, to};
1250
9.52k
        }
1251
1252
1.14k
        sig_stat.available = true;
1253
1.14k
        *ans = &sig_stat;
1254
1.14k
        return true;
1255
1.14k
    };
1256
2.10k
    cached_page_index.row_group_range = {0, row_group.num_rows};
1257
2.10k
    cached_page_index.get_stat_func = get_stat_func;
1258
1259
2.10k
    candidate_row_ranges->add({0, row_group.num_rows});
1260
2.14k
    for (const auto& predicate : push_down_pred) {
1261
2.14k
        RowRanges tmp_row_range;
1262
2.14k
        if (!predicate->evaluate_and(&cached_page_index, &tmp_row_range)) {
1263
            // no need read this row group.
1264
12
            candidate_row_ranges->clear();
1265
12
            return Status::OK();
1266
12
        }
1267
2.13k
        RowRanges::ranges_intersection(*candidate_row_ranges, tmp_row_range, candidate_row_ranges);
1268
2.13k
    }
1269
2.09k
    return Status::OK();
1270
2.10k
}
1271
1272
Status ParquetReader::_process_min_max_bloom_filter(
1273
        const RowGroupReader::RowGroupIndex& row_group_index, const tparquet::RowGroup& row_group,
1274
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1275
23.0k
        RowRanges* row_ranges) {
1276
23.0k
    SCOPED_RAW_TIMER(&_reader_statistics.row_group_filter_time);
1277
23.0k
    if (!_filter_groups) {
1278
        // No row group filtering is needed;
1279
        // for example, Iceberg reads position delete files.
1280
1.15k
        row_ranges->add({0, row_group.num_rows});
1281
1.15k
        return Status::OK();
1282
1.15k
    }
1283
1284
21.8k
    if (_read_by_rows) {
1285
1.08k
        auto group_start = row_group_index.first_row;
1286
1.08k
        auto group_end = row_group_index.last_row;
1287
1288
2.99k
        while (!_row_ids.empty()) {
1289
2.12k
            auto v = _row_ids.front();
1290
2.12k
            if (v < group_start) {
1291
0
                continue;
1292
2.12k
            } else if (v < group_end) {
1293
1.90k
                row_ranges->add(RowRange {v - group_start, v - group_start + 1});
1294
1.90k
                _row_ids.pop_front();
1295
1.90k
            } else {
1296
214
                break;
1297
214
            }
1298
2.12k
        }
1299
20.8k
    } else {
1300
20.8k
        bool filter_this_row_group = false;
1301
20.8k
        bool filtered_by_min_max = false;
1302
20.8k
        bool filtered_by_bloom_filter = false;
1303
20.8k
        RETURN_IF_ERROR(_process_column_stat_filter(row_group, push_down_pred,
1304
20.8k
                                                    &filter_this_row_group, &filtered_by_min_max,
1305
20.8k
                                                    &filtered_by_bloom_filter));
1306
        // Update statistics based on filter type
1307
20.8k
        if (filter_this_row_group) {
1308
3.14k
            if (filtered_by_min_max) {
1309
3.14k
                _reader_statistics.filtered_row_groups_by_min_max++;
1310
3.14k
            }
1311
3.14k
            if (filtered_by_bloom_filter) {
1312
0
                _reader_statistics.filtered_row_groups_by_bloom_filter++;
1313
0
            }
1314
3.14k
        }
1315
1316
20.8k
        if (!filter_this_row_group) {
1317
17.7k
            RETURN_IF_ERROR(_process_page_index_filter(row_group, row_group_index, push_down_pred,
1318
17.7k
                                                       row_ranges));
1319
17.7k
        }
1320
20.8k
    }
1321
1322
21.8k
    return Status::OK();
1323
21.8k
}
1324
1325
Status ParquetReader::_process_column_stat_filter(
1326
        const tparquet::RowGroup& row_group,
1327
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1328
20.7k
        bool* filter_group, bool* filtered_by_min_max, bool* filtered_by_bloom_filter) {
1329
    // If both filters are disabled, skip filtering
1330
20.7k
    if (!_enable_filter_by_min_max && !_enable_filter_by_bloom_filter) {
1331
0
        return Status::OK();
1332
0
    }
1333
1334
    // Cache bloom filters for each column to avoid reading the same bloom filter multiple times
1335
    // when there are multiple predicates on the same column
1336
20.7k
    std::unordered_map<int, std::unique_ptr<ParquetBlockSplitBloomFilter>> bloom_filter_cache;
1337
1338
    // Initialize output parameters
1339
20.7k
    *filtered_by_min_max = false;
1340
20.7k
    *filtered_by_bloom_filter = false;
1341
1342
20.7k
    for (const auto& predicate : _push_down_predicates) {
1343
8.32k
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_stat_func =
1344
8.95k
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1345
                    // Check if min-max filter is enabled
1346
8.95k
                    if (!_enable_filter_by_min_max) {
1347
960
                        return false;
1348
960
                    }
1349
7.99k
                    auto* slot = _tuple_descriptor->slots()[cid];
1350
7.99k
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1351
0
                        return false;
1352
0
                    }
1353
7.99k
                    const auto& file_col_name =
1354
7.99k
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1355
7.99k
                    const FieldSchema* col_schema =
1356
7.99k
                            _file_metadata->schema().get_column(file_col_name);
1357
7.99k
                    int parquet_col_id = col_schema->physical_column_index;
1358
7.99k
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1359
7.99k
                    stat->col_schema = col_schema;
1360
7.99k
                    return ParquetPredicate::read_column_stats(col_schema, meta_data,
1361
7.99k
                                                               &_ignored_stats,
1362
7.99k
                                                               _t_metadata->created_by, stat)
1363
7.99k
                            .ok();
1364
7.99k
                };
1365
8.32k
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_bloom_filter_func =
1366
8.32k
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1367
2.37k
                    auto* slot = _tuple_descriptor->slots()[cid];
1368
2.37k
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1369
0
                        return false;
1370
0
                    }
1371
2.37k
                    const auto& file_col_name =
1372
2.37k
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1373
2.37k
                    const FieldSchema* col_schema =
1374
2.37k
                            _file_metadata->schema().get_column(file_col_name);
1375
2.37k
                    int parquet_col_id = col_schema->physical_column_index;
1376
2.37k
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1377
2.37k
                    if (!meta_data.__isset.bloom_filter_offset) {
1378
2.36k
                        return false;
1379
2.36k
                    }
1380
10
                    auto primitive_type =
1381
10
                            remove_nullable(col_schema->data_type)->get_primitive_type();
1382
10
                    if (!ParquetPredicate::bloom_filter_supported(primitive_type)) {
1383
5
                        return false;
1384
5
                    }
1385
1386
                    // Check if bloom filter is enabled
1387
5
                    if (!_enable_filter_by_bloom_filter) {
1388
0
                        return false;
1389
0
                    }
1390
1391
                    // Check cache first
1392
5
                    auto cache_iter = bloom_filter_cache.find(parquet_col_id);
1393
5
                    if (cache_iter != bloom_filter_cache.end()) {
1394
                        // Bloom filter already loaded for this column, reuse it
1395
0
                        stat->bloom_filter = std::move(cache_iter->second);
1396
0
                        bloom_filter_cache.erase(cache_iter);
1397
0
                        return stat->bloom_filter != nullptr;
1398
0
                    }
1399
1400
5
                    if (!stat->bloom_filter) {
1401
5
                        SCOPED_RAW_TIMER(&_reader_statistics.bloom_filter_read_time);
1402
5
                        auto st = ParquetPredicate::read_bloom_filter(
1403
5
                                meta_data, _tracing_file_reader, _io_ctx, stat);
1404
5
                        if (!st.ok()) {
1405
0
                            LOG(WARNING) << "Failed to read bloom filter for column "
1406
0
                                         << col_schema->name << " in file " << _scan_range.path
1407
0
                                         << ", status: " << st.to_string();
1408
0
                            stat->bloom_filter.reset();
1409
0
                            return false;
1410
0
                        }
1411
5
                    }
1412
5
                    return stat->bloom_filter != nullptr;
1413
5
                };
1414
8.32k
        ParquetPredicate::ColumnStat stat;
1415
8.32k
        stat.ctz = _ctz;
1416
8.32k
        stat.get_stat_func = &get_stat_func;
1417
8.32k
        stat.get_bloom_filter_func = &get_bloom_filter_func;
1418
1419
8.32k
        if (!predicate->evaluate_and(&stat)) {
1420
3.14k
            *filter_group = true;
1421
1422
            // Track which filter was used for filtering
1423
            // If bloom filter was loaded, it means bloom filter was used
1424
3.14k
            if (stat.bloom_filter) {
1425
0
                *filtered_by_bloom_filter = true;
1426
0
            }
1427
            // If col_schema was set but no bloom filter, it means min-max stats were used
1428
3.14k
            if (stat.col_schema && !stat.bloom_filter) {
1429
3.14k
                *filtered_by_min_max = true;
1430
3.14k
            }
1431
1432
3.14k
            return Status::OK();
1433
3.14k
        }
1434
1435
        // After evaluating, if the bloom filter was used, cache it for subsequent predicates
1436
5.18k
        if (stat.bloom_filter) {
1437
            // Find the column id for caching
1438
26
            for (auto* slot : _tuple_descriptor->slots()) {
1439
26
                if (_table_info_node_ptr->children_column_exists(slot->col_name())) {
1440
26
                    const auto& file_col_name =
1441
26
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1442
26
                    const FieldSchema* col_schema =
1443
26
                            _file_metadata->schema().get_column(file_col_name);
1444
26
                    int parquet_col_id = col_schema->physical_column_index;
1445
26
                    if (stat.col_schema == col_schema) {
1446
5
                        bloom_filter_cache[parquet_col_id] = std::move(stat.bloom_filter);
1447
5
                        break;
1448
5
                    }
1449
26
                }
1450
26
            }
1451
5
        }
1452
5.18k
    }
1453
1454
    // Update filter statistics if this row group was not filtered
1455
    // The statistics will be updated in _init_row_groups when filter_group is true
1456
17.6k
    return Status::OK();
1457
20.7k
}
1458
1459
108k
int64_t ParquetReader::_get_column_start_offset(const tparquet::ColumnMetaData& column) const {
1460
108k
    return has_dict_page(column) ? column.dictionary_page_offset : column.data_page_offset;
1461
108k
}
1462
1463
17.1k
void ParquetReader::_collect_profile() {
1464
17.1k
    if (_profile == nullptr) {
1465
0
        return;
1466
0
    }
1467
1468
17.1k
    if (_current_group_reader != nullptr) {
1469
14.2k
        _current_group_reader->collect_profile_before_close();
1470
14.2k
    }
1471
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups, _reader_statistics.filtered_row_groups);
1472
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_min_max,
1473
17.1k
                   _reader_statistics.filtered_row_groups_by_min_max);
1474
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_bloom_filter,
1475
17.1k
                   _reader_statistics.filtered_row_groups_by_bloom_filter);
1476
17.1k
    COUNTER_UPDATE(_parquet_profile.to_read_row_groups, _reader_statistics.read_row_groups);
1477
17.1k
    COUNTER_UPDATE(_parquet_profile.total_row_groups, _total_groups);
1478
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_group_rows, _reader_statistics.filtered_group_rows);
1479
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_page_rows, _reader_statistics.filtered_page_rows);
1480
17.1k
    COUNTER_UPDATE(_parquet_profile.lazy_read_filtered_rows,
1481
17.1k
                   _reader_statistics.lazy_read_filtered_rows);
1482
17.1k
    COUNTER_UPDATE(_parquet_profile.filtered_bytes, _reader_statistics.filtered_bytes);
1483
17.1k
    COUNTER_UPDATE(_parquet_profile.raw_rows_read, _reader_statistics.read_rows);
1484
17.1k
    COUNTER_UPDATE(_parquet_profile.column_read_time, _reader_statistics.column_read_time);
1485
17.1k
    COUNTER_UPDATE(_parquet_profile.parse_meta_time, _reader_statistics.parse_meta_time);
1486
17.1k
    COUNTER_UPDATE(_parquet_profile.parse_footer_time, _reader_statistics.parse_footer_time);
1487
17.1k
    COUNTER_UPDATE(_parquet_profile.file_reader_create_time,
1488
17.1k
                   _reader_statistics.file_reader_create_time);
1489
17.1k
    COUNTER_UPDATE(_parquet_profile.open_file_num, _reader_statistics.open_file_num);
1490
17.1k
    COUNTER_UPDATE(_parquet_profile.page_index_filter_time,
1491
17.1k
                   _reader_statistics.page_index_filter_time);
1492
17.1k
    COUNTER_UPDATE(_parquet_profile.read_page_index_time, _reader_statistics.read_page_index_time);
1493
17.1k
    COUNTER_UPDATE(_parquet_profile.parse_page_index_time,
1494
17.1k
                   _reader_statistics.parse_page_index_time);
1495
17.1k
    COUNTER_UPDATE(_parquet_profile.row_group_filter_time,
1496
17.1k
                   _reader_statistics.row_group_filter_time);
1497
17.1k
    COUNTER_UPDATE(_parquet_profile.file_footer_read_calls,
1498
17.1k
                   _reader_statistics.file_footer_read_calls);
1499
17.1k
    COUNTER_UPDATE(_parquet_profile.file_footer_hit_cache,
1500
17.1k
                   _reader_statistics.file_footer_hit_cache);
1501
1502
17.1k
    COUNTER_UPDATE(_parquet_profile.skip_page_header_num, _column_statistics.skip_page_header_num);
1503
17.1k
    COUNTER_UPDATE(_parquet_profile.parse_page_header_num,
1504
17.1k
                   _column_statistics.parse_page_header_num);
1505
17.1k
    COUNTER_UPDATE(_parquet_profile.predicate_filter_time,
1506
17.1k
                   _reader_statistics.predicate_filter_time);
1507
17.1k
    COUNTER_UPDATE(_parquet_profile.dict_filter_rewrite_time,
1508
17.1k
                   _reader_statistics.dict_filter_rewrite_time);
1509
17.1k
    COUNTER_UPDATE(_parquet_profile.convert_time, _column_statistics.convert_time);
1510
17.1k
    COUNTER_UPDATE(_parquet_profile.bloom_filter_read_time,
1511
17.1k
                   _reader_statistics.bloom_filter_read_time);
1512
17.1k
    COUNTER_UPDATE(_parquet_profile.page_index_read_calls,
1513
17.1k
                   _column_statistics.page_index_read_calls);
1514
17.1k
    COUNTER_UPDATE(_parquet_profile.decompress_time, _column_statistics.decompress_time);
1515
17.1k
    COUNTER_UPDATE(_parquet_profile.decompress_cnt, _column_statistics.decompress_cnt);
1516
17.1k
    COUNTER_UPDATE(_parquet_profile.page_read_counter, _column_statistics.page_read_counter);
1517
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_write_counter,
1518
17.1k
                   _column_statistics.page_cache_write_counter);
1519
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_write_counter,
1520
17.1k
                   _column_statistics.page_cache_compressed_write_counter);
1521
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_write_counter,
1522
17.1k
                   _column_statistics.page_cache_decompressed_write_counter);
1523
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_hit_counter,
1524
17.1k
                   _column_statistics.page_cache_hit_counter);
1525
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_missing_counter,
1526
17.1k
                   _column_statistics.page_cache_missing_counter);
1527
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_hit_counter,
1528
17.1k
                   _column_statistics.page_cache_compressed_hit_counter);
1529
17.1k
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_hit_counter,
1530
17.1k
                   _column_statistics.page_cache_decompressed_hit_counter);
1531
17.1k
    COUNTER_UPDATE(_parquet_profile.decode_header_time, _column_statistics.decode_header_time);
1532
17.1k
    COUNTER_UPDATE(_parquet_profile.read_page_header_time,
1533
17.1k
                   _column_statistics.read_page_header_time);
1534
17.1k
    COUNTER_UPDATE(_parquet_profile.decode_value_time, _column_statistics.decode_value_time);
1535
17.1k
    COUNTER_UPDATE(_parquet_profile.decode_dict_time, _column_statistics.decode_dict_time);
1536
17.1k
    COUNTER_UPDATE(_parquet_profile.decode_level_time, _column_statistics.decode_level_time);
1537
17.1k
    COUNTER_UPDATE(_parquet_profile.decode_null_map_time, _column_statistics.decode_null_map_time);
1538
17.1k
}
1539
1540
17.1k
void ParquetReader::_collect_profile_before_close() {
1541
17.1k
    _collect_profile();
1542
17.1k
}
1543
1544
} // namespace doris