Coverage Report

Created: 2026-04-09 21:24

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