Coverage Report

Created: 2026-05-25 02:15

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
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// "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
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// "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"
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#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
232
        : _profile(profile),
88
232
          _scan_params(params),
89
232
          _scan_range(range),
90
232
          _batch_size(std::max(batch_size, 1UL)),
91
232
          _range_start_offset(range.start_offset),
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232
          _range_size(range.size),
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232
          _ctz(ctz),
94
232
          _io_ctx(io_ctx),
95
232
          _state(state),
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232
          _enable_lazy_mat(enable_lazy_mat),
97
          _enable_filter_by_min_max(
98
232
                  state == nullptr ? true
99
232
                                   : state->query_options().enable_parquet_filter_by_min_max),
100
          _enable_filter_by_bloom_filter(
101
232
                  state == nullptr ? true
102
232
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
103
232
    _meta_cache = meta_cache;
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232
    _init_profile();
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232
    _init_system_properties();
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232
    _init_file_description();
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232
}
108
109
147
void ParquetReader::set_batch_size(size_t batch_size) {
110
147
    if (_batch_size == batch_size) {
111
4
        return;
112
4
    }
113
143
    _batch_size = batch_size;
114
143
}
115
116
ParquetReader::ParquetReader(RuntimeProfile* profile, const TFileScanRangeParams& params,
117
                             const TFileRangeDesc& range, size_t batch_size,
118
                             const cctz::time_zone* ctz,
119
                             std::shared_ptr<io::IOContext> io_ctx_holder, RuntimeState* state,
120
                             FileMetaCache* meta_cache, bool enable_lazy_mat)
121
0
        : _profile(profile),
122
0
          _scan_params(params),
123
0
          _scan_range(range),
124
0
          _batch_size(std::max(batch_size, 1UL)),
125
0
          _range_start_offset(range.start_offset),
126
0
          _range_size(range.size),
127
0
          _ctz(ctz),
128
0
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
129
0
          _io_ctx_holder(std::move(io_ctx_holder)),
130
0
          _state(state),
131
0
          _enable_lazy_mat(enable_lazy_mat),
132
          _enable_filter_by_min_max(
133
0
                  state == nullptr ? true
134
0
                                   : state->query_options().enable_parquet_filter_by_min_max),
135
          _enable_filter_by_bloom_filter(
136
0
                  state == nullptr ? true
137
0
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
138
0
    _meta_cache = meta_cache;
139
0
    _init_profile();
140
0
    _init_system_properties();
141
0
    _init_file_description();
142
0
}
143
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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
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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
113
        : _profile(nullptr),
168
113
          _scan_params(params),
169
113
          _scan_range(range),
170
113
          _io_ctx(io_ctx_holder ? io_ctx_holder.get() : nullptr),
171
113
          _io_ctx_holder(std::move(io_ctx_holder)),
172
113
          _state(state),
173
113
          _enable_lazy_mat(enable_lazy_mat),
174
          _enable_filter_by_min_max(
175
113
                  state == nullptr ? true
176
113
                                   : state->query_options().enable_parquet_filter_by_min_max),
177
          _enable_filter_by_bloom_filter(
178
113
                  state == nullptr ? true
179
113
                                   : state->query_options().enable_parquet_filter_by_bloom_filter) {
180
113
    _meta_cache = meta_cache;
181
113
    _init_system_properties();
182
113
    _init_file_description();
183
113
}
184
185
350
ParquetReader::~ParquetReader() {
186
350
    _close_internal();
187
350
}
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
232
void ParquetReader::_init_profile() {
198
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    if (_profile != nullptr) {
199
184
        static const char* parquet_profile = "ParquetReader";
200
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        ADD_TIMER_WITH_LEVEL(_profile, parquet_profile, 1);
201
202
184
        _parquet_profile.filtered_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
203
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                _profile, "RowGroupsFiltered", TUnit::UNIT, parquet_profile, 1);
204
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        _parquet_profile.filtered_row_groups_by_min_max = ADD_CHILD_COUNTER_WITH_LEVEL(
205
184
                _profile, "RowGroupsFilteredByMinMax", TUnit::UNIT, parquet_profile, 1);
206
184
        _parquet_profile.filtered_row_groups_by_bloom_filter = ADD_CHILD_COUNTER_WITH_LEVEL(
207
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                _profile, "RowGroupsFilteredByBloomFilter", TUnit::UNIT, parquet_profile, 1);
208
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        _parquet_profile.to_read_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
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                _profile, "RowGroupsReadNum", TUnit::UNIT, parquet_profile, 1);
210
184
        _parquet_profile.total_row_groups = ADD_CHILD_COUNTER_WITH_LEVEL(
211
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                _profile, "RowGroupsTotalNum", TUnit::UNIT, parquet_profile, 1);
212
184
        _parquet_profile.filtered_group_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
213
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                _profile, "FilteredRowsByGroup", TUnit::UNIT, parquet_profile, 1);
214
184
        _parquet_profile.filtered_page_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
215
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                _profile, "FilteredRowsByPage", TUnit::UNIT, parquet_profile, 1);
216
184
        _parquet_profile.lazy_read_filtered_rows = ADD_CHILD_COUNTER_WITH_LEVEL(
217
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                _profile, "FilteredRowsByLazyRead", TUnit::UNIT, parquet_profile, 1);
218
184
        _parquet_profile.filtered_bytes = ADD_CHILD_COUNTER_WITH_LEVEL(
219
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                _profile, "FilteredBytes", TUnit::BYTES, parquet_profile, 1);
220
184
        _parquet_profile.raw_rows_read = ADD_CHILD_COUNTER_WITH_LEVEL(
221
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                _profile, "RawRowsRead", TUnit::UNIT, parquet_profile, 1);
222
184
        _parquet_profile.column_read_time =
223
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ColumnReadTime", parquet_profile, 1);
224
184
        _parquet_profile.parse_meta_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseMetaTime", parquet_profile, 1);
226
184
        _parquet_profile.parse_footer_time =
227
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ParseFooterTime", parquet_profile, 1);
228
184
        _parquet_profile.file_reader_create_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "FileReaderCreateTime", parquet_profile, 1);
230
184
        _parquet_profile.open_file_num =
231
184
                ADD_CHILD_COUNTER_WITH_LEVEL(_profile, "FileNum", TUnit::UNIT, parquet_profile, 1);
232
184
        _parquet_profile.page_index_read_calls =
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184
                ADD_COUNTER_WITH_LEVEL(_profile, "PageIndexReadCalls", TUnit::UNIT, 1);
234
184
        _parquet_profile.page_index_filter_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexFilterTime", parquet_profile, 1);
236
184
        _parquet_profile.read_page_index_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexReadTime", parquet_profile, 1);
238
184
        _parquet_profile.parse_page_index_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageIndexParseTime", parquet_profile, 1);
240
184
        _parquet_profile.row_group_filter_time =
241
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "RowGroupFilterTime", parquet_profile, 1);
242
184
        _parquet_profile.file_footer_read_calls =
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                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterReadCalls", TUnit::UNIT, 1);
244
184
        _parquet_profile.file_footer_hit_cache =
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                ADD_COUNTER_WITH_LEVEL(_profile, "FileFooterHitCache", TUnit::UNIT, 1);
246
184
        _parquet_profile.decompress_time =
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                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecompressTime", parquet_profile, 1);
248
184
        _parquet_profile.decompress_cnt = ADD_CHILD_COUNTER_WITH_LEVEL(
249
184
                _profile, "DecompressCount", TUnit::UNIT, parquet_profile, 1);
250
184
        _parquet_profile.page_read_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
251
184
                _profile, "PageReadCount", TUnit::UNIT, parquet_profile, 1);
252
184
        _parquet_profile.page_cache_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
253
184
                _profile, "PageCacheWriteCount", TUnit::UNIT, parquet_profile, 1);
254
184
        _parquet_profile.page_cache_compressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
255
184
                _profile, "PageCacheCompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
256
184
        _parquet_profile.page_cache_decompressed_write_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
257
184
                _profile, "PageCacheDecompressedWriteCount", TUnit::UNIT, parquet_profile, 1);
258
184
        _parquet_profile.page_cache_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
259
184
                _profile, "PageCacheHitCount", TUnit::UNIT, parquet_profile, 1);
260
184
        _parquet_profile.page_cache_missing_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
261
184
                _profile, "PageCacheMissingCount", TUnit::UNIT, parquet_profile, 1);
262
184
        _parquet_profile.page_cache_compressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
263
184
                _profile, "PageCacheCompressedHitCount", TUnit::UNIT, parquet_profile, 1);
264
184
        _parquet_profile.page_cache_decompressed_hit_counter = ADD_CHILD_COUNTER_WITH_LEVEL(
265
184
                _profile, "PageCacheDecompressedHitCount", TUnit::UNIT, parquet_profile, 1);
266
184
        _parquet_profile.decode_header_time =
267
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderDecodeTime", parquet_profile, 1);
268
184
        _parquet_profile.read_page_header_time =
269
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PageHeaderReadTime", parquet_profile, 1);
270
184
        _parquet_profile.decode_value_time =
271
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeValueTime", parquet_profile, 1);
272
184
        _parquet_profile.decode_dict_time =
273
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeDictTime", parquet_profile, 1);
274
184
        _parquet_profile.decode_level_time =
275
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeLevelTime", parquet_profile, 1);
276
184
        _parquet_profile.decode_null_map_time =
277
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DecodeNullMapTime", parquet_profile, 1);
278
184
        _parquet_profile.skip_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
279
184
                _profile, "SkipPageHeaderNum", TUnit::UNIT, parquet_profile, 1);
280
184
        _parquet_profile.parse_page_header_num = ADD_CHILD_COUNTER_WITH_LEVEL(
281
184
                _profile, "ParsePageHeaderNum", TUnit::UNIT, parquet_profile, 1);
282
184
        _parquet_profile.predicate_filter_time =
283
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "PredicateFilterTime", parquet_profile, 1);
284
184
        _parquet_profile.dict_filter_rewrite_time =
285
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "DictFilterRewriteTime", parquet_profile, 1);
286
184
        _parquet_profile.convert_time =
287
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "ConvertTime", parquet_profile, 1);
288
184
        _parquet_profile.bloom_filter_read_time =
289
184
                ADD_CHILD_TIMER_WITH_LEVEL(_profile, "BloomFilterReadTime", parquet_profile, 1);
290
184
    }
291
232
}
292
293
148
Status ParquetReader::close() {
294
148
    _close_internal();
295
148
    return Status::OK();
296
148
}
297
298
498
void ParquetReader::_close_internal() {
299
498
    if (!_closed) {
300
350
        _closed = true;
301
350
    }
302
498
}
303
304
487
Status ParquetReader::_open_file() {
305
487
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
306
0
        return Status::EndOfFile("stop");
307
0
    }
308
487
    if (_file_reader == nullptr) {
309
262
        SCOPED_RAW_TIMER(&_reader_statistics.file_reader_create_time);
310
262
        ++_reader_statistics.open_file_num;
311
262
        _file_description.mtime =
312
262
                _scan_range.__isset.modification_time ? _scan_range.modification_time : 0;
313
262
        io::FileReaderOptions reader_options =
314
262
                FileFactory::get_reader_options(_state, _file_description);
315
262
        _file_reader = DORIS_TRY(io::DelegateReader::create_file_reader(
316
262
                _profile, _system_properties, _file_description, reader_options,
317
262
                io::DelegateReader::AccessMode::RANDOM, _io_ctx));
318
262
        _tracing_file_reader = _io_ctx ? std::make_shared<io::TracingFileReader>(
319
262
                                                 _file_reader, _io_ctx->file_reader_stats)
320
262
                                       : _file_reader;
321
262
    }
322
323
487
    if (_file_metadata == nullptr) {
324
331
        SCOPED_RAW_TIMER(&_reader_statistics.parse_footer_time);
325
331
        if (_tracing_file_reader->size() <= sizeof(PARQUET_VERSION_NUMBER)) {
326
            // Some system may generate parquet file with only 4 bytes: PAR1
327
            // Should consider it as empty file.
328
0
            return Status::EndOfFile("open file failed, empty parquet file {} with size: {}",
329
0
                                     _scan_range.path, _tracing_file_reader->size());
330
0
        }
331
331
        size_t meta_size = 0;
332
331
        bool enable_mapping_varbinary = _scan_params.__isset.enable_mapping_varbinary
333
331
                                                ? _scan_params.enable_mapping_varbinary
334
331
                                                : false;
335
331
        bool enable_mapping_timestamp_tz = _scan_params.__isset.enable_mapping_timestamp_tz
336
331
                                                   ? _scan_params.enable_mapping_timestamp_tz
337
331
                                                   : false;
338
331
        if (_meta_cache == nullptr) {
339
            // wrap _file_metadata with unique ptr, so that it can be released finally.
340
161
            RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
341
161
                                                &meta_size, _io_ctx, enable_mapping_varbinary,
342
161
                                                enable_mapping_timestamp_tz));
343
160
            _file_metadata = _file_metadata_ptr.get();
344
            // parse magic number & parse meta data
345
160
            _reader_statistics.file_footer_read_calls += 1;
346
170
        } else {
347
170
            const auto& file_meta_cache_key =
348
170
                    FileMetaCache::get_key(_tracing_file_reader, _file_description);
349
170
            if (!_meta_cache->lookup(file_meta_cache_key, &_meta_cache_handle)) {
350
133
                RETURN_IF_ERROR(parse_thrift_footer(_tracing_file_reader, &_file_metadata_ptr,
351
133
                                                    &meta_size, _io_ctx, enable_mapping_varbinary,
352
133
                                                    enable_mapping_timestamp_tz));
353
                // _file_metadata_ptr.release() : move control of _file_metadata to _meta_cache_handle
354
133
                _meta_cache->insert(file_meta_cache_key, _file_metadata_ptr.release(),
355
133
                                    &_meta_cache_handle);
356
133
                _file_metadata = _meta_cache_handle.data<FileMetaData>();
357
133
                _reader_statistics.file_footer_read_calls += 1;
358
133
            } else {
359
37
                _reader_statistics.file_footer_hit_cache++;
360
37
            }
361
170
            _file_metadata = _meta_cache_handle.data<FileMetaData>();
362
170
        }
363
364
330
        if (_file_metadata == nullptr) {
365
0
            return Status::InternalError("failed to get file meta data: {}",
366
0
                                         _file_description.path);
367
0
        }
368
330
    }
369
486
    return Status::OK();
370
487
}
371
372
174
Status ParquetReader::get_file_metadata_schema(const FieldDescriptor** ptr) {
373
174
    RETURN_IF_ERROR(_open_file());
374
174
    DCHECK(_file_metadata != nullptr);
375
174
    *ptr = &_file_metadata->schema();
376
174
    return Status::OK();
377
174
}
378
379
350
void ParquetReader::_init_system_properties() {
380
350
    if (_scan_range.__isset.file_type) {
381
        // for compatibility
382
227
        _system_properties.system_type = _scan_range.file_type;
383
227
    } else {
384
123
        _system_properties.system_type = _scan_params.file_type;
385
123
    }
386
350
    _system_properties.properties = _scan_params.properties;
387
350
    _system_properties.hdfs_params = _scan_params.hdfs_params;
388
350
    if (_scan_params.__isset.broker_addresses) {
389
20
        _system_properties.broker_addresses.assign(_scan_params.broker_addresses.begin(),
390
20
                                                   _scan_params.broker_addresses.end());
391
20
    }
392
350
}
393
394
350
void ParquetReader::_init_file_description() {
395
350
    _file_description.path = _scan_range.path;
396
350
    _file_description.file_size = _scan_range.__isset.file_size ? _scan_range.file_size : -1;
397
350
    if (_scan_range.__isset.fs_name) {
398
0
        _file_description.fs_name = _scan_range.fs_name;
399
0
    }
400
350
    if (_scan_range.__isset.file_cache_admission) {
401
114
        _file_description.file_cache_admission = _scan_range.file_cache_admission;
402
114
    }
403
350
}
404
405
143
Status ParquetReader::on_before_init_reader(ReaderInitContext* ctx) {
406
143
    _column_descs = ctx->column_descs;
407
143
    _fill_col_name_to_block_idx = ctx->col_name_to_block_idx;
408
143
    RETURN_IF_ERROR(
409
143
            _extract_partition_values(*ctx->range, ctx->tuple_descriptor, _fill_partition_values));
410
940
    for (auto& desc : *ctx->column_descs) {
411
940
        if (desc.category == ColumnCategory::REGULAR ||
412
940
            desc.category == ColumnCategory::GENERATED) {
413
930
            ctx->column_names.push_back(desc.name);
414
930
        } else if (desc.category == ColumnCategory::SYNTHESIZED &&
415
10
                   desc.name.starts_with(BeConsts::GLOBAL_ROWID_COL)) {
416
8
            auto topn_row_id_column_iter = _create_topn_row_id_column_iterator();
417
8
            this->register_synthesized_column_handler(
418
8
                    desc.name,
419
8
                    [iter = std::move(topn_row_id_column_iter), this, &desc](
420
13
                            Block* block, size_t rows) -> Status {
421
13
                        return fill_topn_row_id(iter, desc.name, block, rows);
422
13
                    });
423
8
            continue;
424
8
        }
425
940
    }
426
427
    // Build table_info_node from Parquet file metadata with case-insensitive recursive matching.
428
    // File is already opened by init_reader before this hook, so metadata is available.
429
    // tuple_descriptor may be null in unit tests that only set column_descs.
430
143
    if (ctx->tuple_descriptor != nullptr) {
431
141
        const FieldDescriptor* field_desc = nullptr;
432
141
        RETURN_IF_ERROR(get_file_metadata_schema(&field_desc));
433
141
        RETURN_IF_ERROR(TableSchemaChangeHelper::BuildTableInfoUtil::by_parquet_name(
434
141
                ctx->tuple_descriptor, *field_desc, ctx->table_info_node));
435
141
    }
436
437
143
    return Status::OK();
438
143
}
439
440
200
Status ParquetReader::_open_file_reader(ReaderInitContext* /*ctx*/) {
441
200
    return _open_file();
442
200
}
443
444
200
Status ParquetReader::_do_init_reader(ReaderInitContext* base_ctx) {
445
200
    auto* ctx = checked_context_cast<ParquetInitContext>(base_ctx);
446
200
    _col_name_to_block_idx = base_ctx->col_name_to_block_idx;
447
200
    _tuple_descriptor = ctx->tuple_descriptor;
448
200
    _row_descriptor = ctx->row_descriptor;
449
200
    _colname_to_slot_id = ctx->colname_to_slot_id;
450
200
    _not_single_slot_filter_conjuncts = ctx->not_single_slot_filter_conjuncts;
451
200
    _slot_id_to_filter_conjuncts = ctx->slot_id_to_filter_conjuncts;
452
200
    _filter_groups = ctx->filter_groups;
453
200
    _table_info_node_ptr = base_ctx->table_info_node;
454
200
    _column_ids = base_ctx->column_ids;
455
200
    _filter_column_ids = base_ctx->filter_column_ids;
456
457
    // _open_file_reader (called by init_reader NVI before hooks) must have opened the file.
458
200
    DCHECK(_file_metadata != nullptr)
459
0
            << "ParquetReader::_do_init_reader called without _open_file_reader";
460
200
    _t_metadata = &(_file_metadata->to_thrift());
461
462
200
    SCOPED_RAW_TIMER(&_reader_statistics.parse_meta_time);
463
200
    _total_groups = _t_metadata->row_groups.size();
464
200
    if (_total_groups == 0) {
465
0
        return Status::EndOfFile("init reader failed, empty parquet file: " + _scan_range.path);
466
0
    }
467
200
    _current_row_group_index = RowGroupReader::RowGroupIndex {-1, 0, 0};
468
469
    // Compute missing columns and file↔table column mapping.
470
    // This runs in _do_init_reader (not on_before_init_reader) because table-format readers
471
    // (Iceberg, Paimon, Hive, Hudi) override on_before_init_reader completely.
472
200
    if (has_column_descs()) {
473
158
        _fill_missing_cols.clear();
474
158
        _fill_missing_defaults.clear();
475
983
        for (const auto& col_name : base_ctx->column_names) {
476
983
            if (!_table_info_node_ptr->children_column_exists(col_name)) {
477
6
                _fill_missing_cols.insert(col_name);
478
6
            }
479
983
        }
480
158
        if (_column_descs && !_fill_missing_cols.empty()) {
481
16
            for (const auto& desc : *_column_descs) {
482
16
                if (_fill_missing_cols.contains(desc.name) &&
483
16
                    !_fill_partition_values.contains(desc.name)) {
484
1
                    _fill_missing_defaults[desc.name] = desc.default_expr;
485
1
                }
486
16
            }
487
6
        }
488
158
    }
489
    // Resolve file-column ↔ table-column mapping in file-schema order.
490
    // _init_read_columns handles both normal path (missing cols populated above)
491
    // and standalone path (_fill_missing_cols empty, _table_info_node_ptr may be null).
492
200
    _init_read_columns(base_ctx->column_names);
493
494
    // build column predicates for column lazy read
495
200
    if (ctx->conjuncts != nullptr) {
496
200
        _lazy_read_ctx.conjuncts = *ctx->conjuncts;
497
200
    }
498
200
    if (ctx->slot_id_to_predicates != nullptr) {
499
200
        _lazy_read_ctx.slot_id_to_predicates = *ctx->slot_id_to_predicates;
500
200
    }
501
502
    // ---- Inlined set_fill_columns logic (partition/missing/synthesized classification) ----
503
504
    // 1. Collect predicate columns from conjuncts for lazy materialization
505
200
    std::unordered_map<std::string, std::pair<uint32_t, int>> predicate_columns;
506
200
    _collect_predicate_columns_from_conjuncts(predicate_columns);
507
508
    // 2. Classify read/partition/missing/synthesized columns into lazy vs predicate groups
509
200
    _classify_columns_for_lazy_read(predicate_columns, _fill_partition_values,
510
200
                                    _fill_missing_defaults);
511
512
    // 3. Populate col_names vectors for ColumnProcessor path
513
200
    for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
514
5
        _lazy_read_ctx.predicate_partition_col_names.emplace_back(kv.first);
515
5
    }
516
200
    for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
517
0
        _lazy_read_ctx.predicate_missing_col_names.emplace_back(kv.first);
518
0
    }
519
200
    for (auto& kv : _lazy_read_ctx.partition_columns) {
520
5
        _lazy_read_ctx.partition_col_names.emplace_back(kv.first);
521
5
    }
522
200
    for (auto& kv : _lazy_read_ctx.missing_columns) {
523
1
        _lazy_read_ctx.missing_col_names.emplace_back(kv.first);
524
1
    }
525
526
200
    if (_filter_groups && (_total_groups == 0 || _t_metadata->num_rows == 0 || _range_size < 0)) {
527
0
        return Status::EndOfFile("No row group to read");
528
0
    }
529
530
200
    return Status::OK();
531
200
}
532
533
200
void ParquetReader::_init_read_columns(const std::vector<std::string>& column_names) {
534
    // Build file_col_name → table_col_name map, skipping missing columns.
535
    // Must iterate file schema in physical order so that _generate_random_access_ranges
536
    // sees monotonically increasing chunk offsets.
537
200
    auto schema_desc = _file_metadata->schema();
538
200
    std::map<std::string, std::string> required_file_columns;
539
1.33k
    for (const auto& col_name : column_names) {
540
1.33k
        if (_fill_missing_cols.contains(col_name)) {
541
6
            continue;
542
6
        }
543
1.32k
        std::string file_col = col_name;
544
1.32k
        if (_table_info_node_ptr && _table_info_node_ptr->children_column_exists(col_name)) {
545
1.32k
            file_col = _table_info_node_ptr->children_file_column_name(col_name);
546
1.32k
        }
547
1.32k
        required_file_columns[file_col] = col_name;
548
1.32k
    }
549
1.98k
    for (int i = 0; i < schema_desc.size(); ++i) {
550
1.78k
        const auto& name = schema_desc.get_column(i)->name;
551
1.78k
        if (required_file_columns.contains(name)) {
552
1.32k
            _read_file_columns.emplace_back(name);
553
1.32k
            _read_table_columns.emplace_back(required_file_columns[name]);
554
1.32k
            _read_table_columns_set.insert(required_file_columns[name]);
555
1.32k
        }
556
1.78k
    }
557
200
}
558
559
2
bool ParquetReader::_exists_in_file(const std::string& expr_name) const {
560
    // `_read_table_columns_set` is used to ensure that only columns actually read are subject to min-max filtering.
561
    // This primarily handles cases where partition columns also exist in a file. The reason it's not modified
562
    // in `_table_info_node_ptr` is that Iceberg、Hudi has inconsistent requirements for this node;
563
    // Iceberg partition evolution need read partition columns from a file.
564
    // hudi set `hoodie.datasource.write.drop.partition.columns=false` not need read partition columns from a file.
565
2
    return _table_info_node_ptr->children_column_exists(expr_name) &&
566
2
           _read_table_columns_set.contains(expr_name);
567
2
}
568
569
2
bool ParquetReader::_type_matches(const int cid) const {
570
2
    auto* slot = _tuple_descriptor->slots()[cid];
571
2
    auto table_col_type = remove_nullable(slot->type());
572
573
2
    const auto& file_col_name = _table_info_node_ptr->children_file_column_name(slot->col_name());
574
2
    const auto& file_col_type =
575
2
            remove_nullable(_file_metadata->schema().get_column(file_col_name)->data_type);
576
577
2
    return (table_col_type->get_primitive_type() == file_col_type->get_primitive_type()) &&
578
2
           !is_complex_type(table_col_type->get_primitive_type());
579
2
}
580
581
void ParquetReader::_collect_predicate_columns_from_conjuncts(
582
200
        std::unordered_map<std::string, std::pair<uint32_t, int>>& predicate_columns) {
583
200
    std::function<void(VExpr * expr)> visit_slot = [&](VExpr* expr) {
584
44
        if (expr->is_slot_ref()) {
585
15
            VSlotRef* slot_ref = static_cast<VSlotRef*>(expr);
586
15
            auto expr_name = slot_ref->expr_name();
587
15
            predicate_columns.emplace(expr_name,
588
15
                                      std::make_pair(slot_ref->column_id(), slot_ref->slot_id()));
589
15
            if (slot_ref->column_id() == 0) {
590
5
                _lazy_read_ctx.resize_first_column = false;
591
5
            }
592
15
            return;
593
15
        }
594
29
        for (auto& child : expr->children()) {
595
29
            visit_slot(child.get());
596
29
        }
597
29
    };
598
599
200
    for (const auto& conjunct : _lazy_read_ctx.conjuncts) {
600
15
        auto expr = conjunct->root();
601
15
        if (expr->is_rf_wrapper()) {
602
0
            RuntimeFilterExpr* runtime_filter = assert_cast<RuntimeFilterExpr*>(expr.get());
603
0
            auto filter_impl = runtime_filter->get_impl();
604
0
            visit_slot(filter_impl.get());
605
15
        } else {
606
15
            visit_slot(expr.get());
607
15
        }
608
15
    }
609
610
200
    if (!_lazy_read_ctx.slot_id_to_predicates.empty()) {
611
126
        auto and_pred = AndBlockColumnPredicate::create_unique();
612
873
        for (const auto& entry : _lazy_read_ctx.slot_id_to_predicates) {
613
873
            for (const auto& pred : entry.second) {
614
                // Parquet shares _push_down_predicates for row-group/page min-max pruning and
615
                // bloom-filter evaluation, so this flag currently gates both predicate paths.
616
2
                if (!has_column_optimization(pred->col_name(), ColumnOptimizationTypes::MIN_MAX)) {
617
0
                    continue;
618
0
                }
619
2
                if (!_exists_in_file(pred->col_name()) || !_type_matches(pred->column_id())) {
620
0
                    continue;
621
0
                }
622
2
                and_pred->add_column_predicate(
623
2
                        SingleColumnBlockPredicate::create_unique(pred->clone(pred->column_id())));
624
2
            }
625
873
        }
626
126
        if (and_pred->num_of_column_predicate() > 0) {
627
2
            _push_down_predicates.push_back(std::move(and_pred));
628
2
        }
629
126
    }
630
200
}
631
632
void ParquetReader::_classify_columns_for_lazy_read(
633
        const std::unordered_map<std::string, std::pair<uint32_t, int>>&
634
                predicate_conjuncts_columns,
635
        const std::unordered_map<std::string, std::tuple<std::string, const SlotDescriptor*>>&
636
                partition_columns,
637
134
        const std::unordered_map<std::string, VExprContextSPtr>& missing_columns) {
638
134
    const FieldDescriptor& schema = _file_metadata->schema();
639
134
    auto predicate_columns = predicate_conjuncts_columns;
640
134
#ifndef BE_TEST
641
134
    for (const auto& [col_name, _] : _generated_col_handlers) {
642
0
        int slot_id = -1;
643
0
        for (auto slot : _tuple_descriptor->slots()) {
644
0
            if (slot->col_name() == col_name) {
645
0
                slot_id = slot->id();
646
0
                break;
647
0
            }
648
0
        }
649
0
        DCHECK(slot_id != -1) << "slot id should not be -1 for generated column: " << col_name;
650
0
        auto column_index = _row_descriptor->get_column_id(slot_id);
651
0
        if (column_index == 0) {
652
0
            _lazy_read_ctx.resize_first_column = false;
653
0
        }
654
        // assume generated columns are only used for predicate push down.
655
0
        predicate_columns.emplace(col_name, std::make_pair(column_index, slot_id));
656
0
    }
657
658
134
    for (const auto& [col_name, _] : _synthesized_col_handlers) {
659
8
        int slot_id = -1;
660
29
        for (auto slot : _tuple_descriptor->slots()) {
661
29
            if (slot->col_name() == col_name) {
662
8
                slot_id = slot->id();
663
8
                break;
664
8
            }
665
29
        }
666
8
        DCHECK(slot_id != -1) << "slot id should not be -1 for synthesized column: " << col_name;
667
8
        auto column_index = _row_descriptor->get_column_id(slot_id);
668
8
        if (column_index == 0) {
669
0
            _lazy_read_ctx.resize_first_column = false;
670
0
        }
671
        // synthesized columns always fill data on first phase.
672
8
        _lazy_read_ctx.all_predicate_col_ids.emplace_back(column_index);
673
8
    }
674
134
#endif
675
908
    for (auto& read_table_col : _read_table_columns) {
676
908
        _lazy_read_ctx.all_read_columns.emplace_back(read_table_col);
677
678
908
        auto file_column_name = _table_info_node_ptr->children_file_column_name(read_table_col);
679
908
        PrimitiveType column_type =
680
908
                schema.get_column(file_column_name)->data_type->get_primitive_type();
681
908
        if (is_complex_type(column_type)) {
682
210
            _lazy_read_ctx.has_complex_type = true;
683
210
        }
684
908
        if (predicate_columns.size() > 0) {
685
2
            auto iter = predicate_columns.find(read_table_col);
686
2
            if (iter == predicate_columns.end()) {
687
0
                _lazy_read_ctx.lazy_read_columns.emplace_back(read_table_col);
688
2
            } else {
689
2
                _lazy_read_ctx.predicate_columns.first.emplace_back(iter->first);
690
2
                _lazy_read_ctx.predicate_columns.second.emplace_back(iter->second.second);
691
2
                _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
692
2
            }
693
2
        }
694
908
    }
695
696
134
    for (auto& kv : partition_columns) {
697
2
        auto iter = predicate_columns.find(kv.first);
698
2
        if (iter == predicate_columns.end()) {
699
2
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
700
2
        } else {
701
0
            _lazy_read_ctx.predicate_partition_columns.emplace(kv.first, kv.second);
702
0
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
703
0
        }
704
2
    }
705
706
134
    for (auto& kv : missing_columns) {
707
1
        auto iter = predicate_columns.find(kv.first);
708
1
        if (iter != predicate_columns.end()) {
709
            //For check missing column :   missing column == xx, missing column is null,missing column is not null.
710
0
            if (_slot_id_to_filter_conjuncts->find(iter->second.second) !=
711
0
                _slot_id_to_filter_conjuncts->end()) {
712
0
                for (auto& ctx : _slot_id_to_filter_conjuncts->find(iter->second.second)->second) {
713
0
                    _lazy_read_ctx.missing_columns_conjuncts.emplace_back(ctx);
714
0
                }
715
0
            }
716
0
            _lazy_read_ctx.predicate_missing_columns.emplace(kv.first, kv.second);
717
0
            _lazy_read_ctx.all_predicate_col_ids.emplace_back(iter->second.first);
718
1
        } else {
719
1
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
720
1
        }
721
1
    }
722
723
134
    if (_enable_lazy_mat && _lazy_read_ctx.predicate_columns.first.size() > 0 &&
724
134
        _lazy_read_ctx.lazy_read_columns.size() > 0) {
725
0
        _lazy_read_ctx.can_lazy_read = true;
726
0
    }
727
728
134
    if (!_lazy_read_ctx.can_lazy_read) {
729
134
        for (auto& kv : _lazy_read_ctx.predicate_partition_columns) {
730
0
            _lazy_read_ctx.partition_columns.emplace(kv.first, kv.second);
731
0
        }
732
134
        for (auto& kv : _lazy_read_ctx.predicate_missing_columns) {
733
0
            _lazy_read_ctx.missing_columns.emplace(kv.first, kv.second);
734
0
        }
735
134
    }
736
134
}
737
738
// init file reader and file metadata for parsing schema
739
113
Status ParquetReader::init_schema_reader() {
740
113
    RETURN_IF_ERROR(_open_file());
741
112
    _t_metadata = &(_file_metadata->to_thrift());
742
112
    return Status::OK();
743
113
}
744
745
Status ParquetReader::get_parsed_schema(std::vector<std::string>* col_names,
746
112
                                        std::vector<DataTypePtr>* col_types) {
747
112
    _total_groups = _t_metadata->row_groups.size();
748
112
    auto schema_desc = _file_metadata->schema();
749
675
    for (int i = 0; i < schema_desc.size(); ++i) {
750
        // Get the Column Reader for the boolean column
751
563
        col_names->emplace_back(schema_desc.get_column(i)->name);
752
563
        col_types->emplace_back(make_nullable(schema_desc.get_column(i)->data_type));
753
563
    }
754
112
    return Status::OK();
755
112
}
756
757
Status ParquetReader::_get_columns_impl(
758
148
        std::unordered_map<std::string, DataTypePtr>* name_to_type) {
759
148
    const auto& schema_desc = _file_metadata->schema();
760
148
    std::unordered_set<std::string> column_names;
761
148
    schema_desc.get_column_names(&column_names);
762
1.33k
    for (auto& name : column_names) {
763
1.33k
        auto field = schema_desc.get_column(name);
764
1.33k
        name_to_type->emplace(name, field->data_type);
765
1.33k
    }
766
148
    return Status::OK();
767
148
}
768
769
262
Status ParquetReader::_do_get_next_block(Block* block, size_t* read_rows, bool* eof) {
770
262
    if (_current_group_reader == nullptr || _row_group_eof) {
771
186
        Status st = _next_row_group_reader();
772
186
        if (!st.ok() && !st.is<ErrorCode::END_OF_FILE>()) {
773
0
            return st;
774
0
        }
775
186
        if (_current_group_reader == nullptr || _row_group_eof || st.is<ErrorCode::END_OF_FILE>()) {
776
0
            _current_group_reader.reset(nullptr);
777
0
            _row_group_eof = true;
778
0
            *read_rows = 0;
779
0
            *eof = true;
780
0
            return Status::OK();
781
0
        }
782
186
    }
783
784
    // Limit memory per batch for load paths.
785
    // _load_bytes_per_row is updated after each batch so the *next* call pre-shrinks _batch_size
786
    // before reading, ensuring the current batch is already within the limit (from call 2 onward).
787
262
    const int64_t max_block_bytes =
788
262
            (_state != nullptr && _state->query_type() == TQueryType::LOAD &&
789
262
             config::load_reader_max_block_bytes > 0)
790
262
                    ? config::load_reader_max_block_bytes
791
262
                    : 0;
792
262
    if (max_block_bytes > 0 && _load_bytes_per_row > 0) {
793
12
        _batch_size = std::max((size_t)1,
794
12
                               (size_t)((int64_t)max_block_bytes / (int64_t)_load_bytes_per_row));
795
12
    }
796
797
262
    SCOPED_RAW_TIMER(&_reader_statistics.column_read_time);
798
262
    Status batch_st =
799
262
            _current_group_reader->next_batch(block, _batch_size, read_rows, &_row_group_eof);
800
262
    if (batch_st.is<ErrorCode::END_OF_FILE>()) {
801
0
        block->clear_column_data();
802
0
        _current_group_reader.reset(nullptr);
803
0
        *read_rows = 0;
804
0
        *eof = true;
805
0
        return Status::OK();
806
0
    }
807
808
262
    if (!batch_st.ok()) {
809
0
        return Status::InternalError("Read parquet file {} failed, reason = {}", _scan_range.path,
810
0
                                     batch_st.to_string());
811
0
    }
812
813
262
    if (max_block_bytes > 0 && *read_rows > 0) {
814
40
        _load_bytes_per_row = block->bytes() / *read_rows;
815
40
    }
816
817
262
    if (_row_group_eof) {
818
186
        auto column_st = _current_group_reader->merged_column_statistics();
819
186
        _column_statistics.merge(column_st);
820
186
        _reader_statistics.lazy_read_filtered_rows +=
821
186
                _current_group_reader->lazy_read_filtered_rows();
822
186
        _reader_statistics.predicate_filter_time += _current_group_reader->predicate_filter_time();
823
186
        _reader_statistics.dict_filter_rewrite_time +=
824
186
                _current_group_reader->dict_filter_rewrite_time();
825
186
        if (_io_ctx) {
826
163
            _io_ctx->condition_cache_filtered_rows +=
827
163
                    _current_group_reader->condition_cache_filtered_rows();
828
163
        }
829
830
186
        if (_current_row_group_index.row_group_id + 1 == _total_groups) {
831
171
            *eof = true;
832
171
        } else {
833
15
            *eof = false;
834
15
        }
835
186
    }
836
262
    return Status::OK();
837
262
}
838
839
RowGroupReader::PositionDeleteContext ParquetReader::_get_position_delete_ctx(
840
186
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index) {
841
186
    if (_delete_rows == nullptr) {
842
186
        return RowGroupReader::PositionDeleteContext(row_group.num_rows, row_group_index.first_row);
843
186
    }
844
0
    const int64_t* delete_rows = &(*_delete_rows)[0];
845
0
    const int64_t* delete_rows_end = delete_rows + _delete_rows->size();
846
0
    const int64_t* start_pos = std::lower_bound(delete_rows + _delete_rows_index, delete_rows_end,
847
0
                                                row_group_index.first_row);
848
0
    int64_t start_index = start_pos - delete_rows;
849
0
    const int64_t* end_pos = std::lower_bound(start_pos, delete_rows_end, row_group_index.last_row);
850
0
    int64_t end_index = end_pos - delete_rows;
851
0
    _delete_rows_index = end_index;
852
0
    return RowGroupReader::PositionDeleteContext(*_delete_rows, row_group.num_rows,
853
0
                                                 row_group_index.first_row, start_index, end_index);
854
186
}
855
856
186
Status ParquetReader::_next_row_group_reader() {
857
186
    if (_current_group_reader != nullptr) {
858
15
        _current_group_reader->collect_profile_before_close();
859
15
    }
860
861
186
    RowRanges candidate_row_ranges;
862
187
    while (++_current_row_group_index.row_group_id < _total_groups) {
863
187
        const auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
864
187
        _current_row_group_index.first_row = _current_row_group_index.last_row;
865
187
        _current_row_group_index.last_row = _current_row_group_index.last_row + row_group.num_rows;
866
867
187
        if (_filter_groups && _is_misaligned_range_group(row_group)) {
868
0
            continue;
869
0
        }
870
871
187
        candidate_row_ranges.clear();
872
        // The range of lines to be read is determined by the push down predicate.
873
187
        RETURN_IF_ERROR(_process_min_max_bloom_filter(
874
187
                _current_row_group_index, row_group, _push_down_predicates, &candidate_row_ranges));
875
876
187
        std::function<int64_t(const FieldSchema*)> column_compressed_size =
877
1.79k
                [&row_group, &column_compressed_size](const FieldSchema* field) -> int64_t {
878
1.79k
            if (field->physical_column_index >= 0) {
879
1.32k
                int parquet_col_id = field->physical_column_index;
880
1.32k
                if (row_group.columns[parquet_col_id].__isset.meta_data) {
881
1.32k
                    return row_group.columns[parquet_col_id].meta_data.total_compressed_size;
882
1.32k
                }
883
0
                return 0;
884
1.32k
            }
885
478
            int64_t size = 0;
886
602
            for (const FieldSchema& child : field->children) {
887
602
                size += column_compressed_size(&child);
888
602
            }
889
478
            return size;
890
1.79k
        };
891
187
        int64_t group_size = 0; // only calculate the needed columns
892
1.19k
        for (auto& read_col : _read_file_columns) {
893
1.19k
            const FieldSchema* field = _file_metadata->schema().get_column(read_col);
894
1.19k
            group_size += column_compressed_size(field);
895
1.19k
        }
896
897
187
        _reader_statistics.read_rows += candidate_row_ranges.count();
898
187
        if (_io_ctx) {
899
164
            _io_ctx->file_reader_stats->read_rows += candidate_row_ranges.count();
900
164
        }
901
902
187
        if (candidate_row_ranges.count() != 0) {
903
            // need read this row group.
904
186
            _reader_statistics.read_row_groups++;
905
186
            _reader_statistics.filtered_page_rows +=
906
186
                    row_group.num_rows - candidate_row_ranges.count();
907
186
            break;
908
186
        } else {
909
            // this row group be filtered.
910
1
            _reader_statistics.filtered_row_groups++;
911
1
            _reader_statistics.filtered_bytes += group_size;
912
1
            _reader_statistics.filtered_group_rows += row_group.num_rows;
913
1
        }
914
187
    }
915
916
186
    if (_current_row_group_index.row_group_id == _total_groups) {
917
0
        _row_group_eof = true;
918
0
        _current_group_reader.reset(nullptr);
919
0
        return Status::EndOfFile("No next RowGroupReader");
920
0
    }
921
922
    // process page index and generate the ranges to read
923
186
    auto& row_group = _t_metadata->row_groups[_current_row_group_index.row_group_id];
924
925
186
    RowGroupReader::PositionDeleteContext position_delete_ctx =
926
186
            _get_position_delete_ctx(row_group, _current_row_group_index);
927
186
    io::FileReaderSPtr group_file_reader;
928
186
    if (typeid_cast<io::InMemoryFileReader*>(_file_reader.get())) {
929
        // InMemoryFileReader has the ability to merge small IO
930
106
        group_file_reader = _file_reader;
931
106
    } else {
932
80
        size_t avg_io_size = 0;
933
80
        const std::vector<io::PrefetchRange> io_ranges =
934
80
                _generate_random_access_ranges(_current_row_group_index, &avg_io_size);
935
80
        int64_t merged_read_slice_size = -1;
936
80
        if (_state != nullptr && _state->query_options().__isset.merge_read_slice_size) {
937
68
            merged_read_slice_size = _state->query_options().merge_read_slice_size;
938
68
        }
939
        // The underlying page reader will prefetch data in column.
940
        // Using both MergeRangeFileReader and BufferedStreamReader simultaneously would waste a lot of memory.
941
80
        group_file_reader =
942
80
                avg_io_size < io::MergeRangeFileReader::SMALL_IO
943
80
                        ? std::make_shared<io::MergeRangeFileReader>(
944
80
                                  _profile, _file_reader, io_ranges, merged_read_slice_size)
945
80
                        : _file_reader;
946
80
    }
947
186
    _current_group_reader.reset(new RowGroupReader(
948
186
            _io_ctx ? std::make_shared<io::TracingFileReader>(group_file_reader,
949
163
                                                              _io_ctx->file_reader_stats)
950
186
                    : group_file_reader,
951
186
            _read_table_columns, _current_row_group_index.row_group_id, row_group, _ctz, _io_ctx,
952
186
            position_delete_ctx, _lazy_read_ctx, _state, _column_ids, _filter_column_ids));
953
186
    _row_group_eof = false;
954
955
186
    _current_group_reader->set_current_row_group_idx(_current_row_group_index);
956
186
    _current_group_reader->set_col_name_to_block_idx(_col_name_to_block_idx);
957
186
    if (_condition_cache_ctx) {
958
7
        _current_group_reader->set_condition_cache_context(_condition_cache_ctx);
959
7
    }
960
186
    _current_group_reader->set_table_format_reader(this);
961
962
186
    _current_group_reader->_table_info_node_ptr = _table_info_node_ptr;
963
186
    return _current_group_reader->init(_file_metadata->schema(), candidate_row_ranges, _col_offsets,
964
186
                                       _tuple_descriptor, _row_descriptor, _colname_to_slot_id,
965
186
                                       _not_single_slot_filter_conjuncts,
966
186
                                       _slot_id_to_filter_conjuncts);
967
186
}
968
969
std::vector<io::PrefetchRange> ParquetReader::_generate_random_access_ranges(
970
80
        const RowGroupReader::RowGroupIndex& group, size_t* avg_io_size) {
971
80
    std::vector<io::PrefetchRange> result;
972
80
    int64_t last_chunk_end = -1;
973
80
    size_t total_io_size = 0;
974
80
    std::function<void(const FieldSchema*, const tparquet::RowGroup&)> scalar_range =
975
1.13k
            [&](const FieldSchema* field, const tparquet::RowGroup& row_group) {
976
1.13k
                if (_column_ids.empty() ||
977
1.13k
                    _column_ids.find(field->get_column_id()) != _column_ids.end()) {
978
1.12k
                    if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
979
296
                        scalar_range(&field->children[0], row_group);
980
830
                    } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
981
38
                        scalar_range(&field->children[0], row_group);
982
38
                        scalar_range(&field->children[1], row_group);
983
792
                    } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
984
37
                        for (int i = 0; i < field->children.size(); ++i) {
985
26
                            scalar_range(&field->children[i], row_group);
986
26
                        }
987
781
                    } else {
988
781
                        const tparquet::ColumnChunk& chunk =
989
781
                                row_group.columns[field->physical_column_index];
990
781
                        auto& chunk_meta = chunk.meta_data;
991
781
                        int64_t chunk_start = has_dict_page(chunk_meta)
992
781
                                                      ? chunk_meta.dictionary_page_offset
993
781
                                                      : chunk_meta.data_page_offset;
994
781
                        int64_t chunk_end = chunk_start + chunk_meta.total_compressed_size;
995
781
                        DCHECK_GE(chunk_start, last_chunk_end);
996
781
                        result.emplace_back(chunk_start, chunk_end);
997
781
                        total_io_size += chunk_meta.total_compressed_size;
998
781
                        last_chunk_end = chunk_end;
999
781
                    }
1000
1.12k
                }
1001
1.13k
            };
1002
80
    const tparquet::RowGroup& row_group = _t_metadata->row_groups[group.row_group_id];
1003
732
    for (const auto& read_col : _read_file_columns) {
1004
732
        const FieldSchema* field = _file_metadata->schema().get_column(read_col);
1005
732
        scalar_range(field, row_group);
1006
732
    }
1007
80
    if (!result.empty()) {
1008
79
        *avg_io_size = total_io_size / result.size();
1009
79
    }
1010
80
    return result;
1011
80
}
1012
1013
195
bool ParquetReader::_is_misaligned_range_group(const tparquet::RowGroup& row_group) const {
1014
195
    int64_t start_offset = _get_column_start_offset(row_group.columns[0].meta_data);
1015
1016
195
    auto& last_column = row_group.columns[row_group.columns.size() - 1].meta_data;
1017
195
    int64_t end_offset = _get_column_start_offset(last_column) + last_column.total_compressed_size;
1018
1019
195
    int64_t row_group_mid = start_offset + (end_offset - start_offset) / 2;
1020
195
    if (!(row_group_mid >= _range_start_offset &&
1021
195
          row_group_mid < _range_start_offset + _range_size)) {
1022
0
        return true;
1023
0
    }
1024
195
    return false;
1025
195
}
1026
1027
2
int64_t ParquetReader::get_total_rows() const {
1028
2
    if (!_t_metadata) return 0;
1029
2
    if (!_filter_groups) return _t_metadata->num_rows;
1030
2
    int64_t total = 0;
1031
7
    for (const auto& rg : _t_metadata->row_groups) {
1032
7
        if (!_is_misaligned_range_group(rg)) {
1033
7
            total += rg.num_rows;
1034
7
        }
1035
7
    }
1036
2
    return total;
1037
2
}
1038
1039
2
void ParquetReader::set_condition_cache_context(std::shared_ptr<ConditionCacheContext> ctx) {
1040
2
    _condition_cache_ctx = std::move(ctx);
1041
2
    if (!_condition_cache_ctx || !_t_metadata || !_filter_groups) {
1042
0
        return;
1043
0
    }
1044
    // Find the first assigned row group to compute base_granule.
1045
2
    int64_t first_row = 0;
1046
2
    for (const auto& rg : _t_metadata->row_groups) {
1047
2
        if (!_is_misaligned_range_group(rg)) {
1048
2
            _condition_cache_ctx->base_granule = first_row / ConditionCacheContext::GRANULE_SIZE;
1049
2
            return;
1050
2
        }
1051
0
        first_row += rg.num_rows;
1052
0
    }
1053
2
}
1054
1055
Status ParquetReader::_process_page_index_filter(
1056
        const tparquet::RowGroup& row_group, const RowGroupReader::RowGroupIndex& row_group_index,
1057
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1058
154
        RowRanges* candidate_row_ranges) {
1059
154
    if (UNLIKELY(_io_ctx && _io_ctx->should_stop)) {
1060
0
        return Status::EndOfFile("stop");
1061
0
    }
1062
1063
154
    std::function<void()> read_whole_row_group = [&]() {
1064
154
        candidate_row_ranges->add(RowRange {0, row_group.num_rows});
1065
154
    };
1066
1067
    // Check if the page index is available and if it exists.
1068
154
    PageIndex page_index;
1069
154
    if (!config::enable_parquet_page_index || _colname_to_slot_id == nullptr ||
1070
154
        !page_index.check_and_get_page_index_ranges(row_group.columns)) {
1071
148
        read_whole_row_group();
1072
148
        return Status::OK();
1073
148
    }
1074
1075
6
    std::vector<int> parquet_col_ids;
1076
284
    for (size_t idx = 0; idx < _read_table_columns.size(); idx++) {
1077
278
        const auto& read_table_col = _read_table_columns[idx];
1078
278
        const auto& read_file_col = _read_file_columns[idx];
1079
278
        if (!_colname_to_slot_id->contains(read_table_col)) {
1080
264
            continue;
1081
264
        }
1082
14
        auto* field = _file_metadata->schema().get_column(read_file_col);
1083
1084
14
        std::function<void(FieldSchema * field)> f = [&](FieldSchema* field) {
1085
14
            if (!_column_ids.empty() &&
1086
14
                _column_ids.find(field->get_column_id()) == _column_ids.end()) {
1087
0
                return;
1088
0
            }
1089
1090
14
            if (field->data_type->get_primitive_type() == TYPE_ARRAY) {
1091
0
                f(&field->children[0]);
1092
14
            } else if (field->data_type->get_primitive_type() == TYPE_MAP) {
1093
0
                f(&field->children[0]);
1094
0
                f(&field->children[1]);
1095
14
            } else if (field->data_type->get_primitive_type() == TYPE_STRUCT) {
1096
0
                for (int i = 0; i < field->children.size(); ++i) {
1097
0
                    f(&field->children[i]);
1098
0
                }
1099
14
            } else {
1100
14
                int parquet_col_id = field->physical_column_index;
1101
14
                if (parquet_col_id >= 0) {
1102
14
                    parquet_col_ids.push_back(parquet_col_id);
1103
14
                }
1104
14
            }
1105
14
        };
1106
1107
14
        f(field);
1108
14
    }
1109
1110
6
    auto parse_offset_index = [&]() -> Status {
1111
6
        std::vector<uint8_t> off_index_buff(page_index._offset_index_size);
1112
6
        Slice res(off_index_buff.data(), page_index._offset_index_size);
1113
6
        size_t bytes_read = 0;
1114
6
        {
1115
6
            SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1116
6
            RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._offset_index_start, res,
1117
6
                                                          &bytes_read, _io_ctx));
1118
6
        }
1119
6
        _column_statistics.page_index_read_calls++;
1120
6
        _col_offsets.clear();
1121
1122
14
        for (auto parquet_col_id : parquet_col_ids) {
1123
14
            auto& chunk = row_group.columns[parquet_col_id];
1124
14
            if (chunk.offset_index_length == 0) [[unlikely]] {
1125
0
                continue;
1126
0
            }
1127
14
            tparquet::OffsetIndex offset_index;
1128
14
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1129
14
            RETURN_IF_ERROR(
1130
14
                    page_index.parse_offset_index(chunk, off_index_buff.data(), &offset_index));
1131
14
            _col_offsets[parquet_col_id] = offset_index;
1132
14
        }
1133
6
        return Status::OK();
1134
6
    };
1135
1136
    // from https://github.com/apache/doris/pull/55795
1137
6
    RETURN_IF_ERROR(parse_offset_index());
1138
1139
    // Check if page index is needed for min-max filter.
1140
6
    if (!_enable_filter_by_min_max || push_down_pred.empty()) {
1141
6
        read_whole_row_group();
1142
6
        return Status::OK();
1143
6
    }
1144
1145
    // read column index.
1146
0
    std::vector<uint8_t> col_index_buff(page_index._column_index_size);
1147
0
    size_t bytes_read = 0;
1148
0
    Slice result(col_index_buff.data(), page_index._column_index_size);
1149
0
    {
1150
0
        SCOPED_RAW_TIMER(&_reader_statistics.read_page_index_time);
1151
0
        RETURN_IF_ERROR(_tracing_file_reader->read_at(page_index._column_index_start, result,
1152
0
                                                      &bytes_read, _io_ctx));
1153
0
    }
1154
0
    _column_statistics.page_index_read_calls++;
1155
1156
0
    SCOPED_RAW_TIMER(&_reader_statistics.page_index_filter_time);
1157
1158
    // Construct a cacheable page index structure to avoid repeatedly reading the page index of the same column.
1159
0
    ParquetPredicate::CachedPageIndexStat cached_page_index;
1160
0
    cached_page_index.ctz = _ctz;
1161
0
    std::function<bool(ParquetPredicate::PageIndexStat**, int)> get_stat_func =
1162
0
            [&](ParquetPredicate::PageIndexStat** ans, const int cid) -> bool {
1163
0
        if (cached_page_index.stats.contains(cid)) {
1164
0
            *ans = &cached_page_index.stats[cid];
1165
0
            return (*ans)->available;
1166
0
        }
1167
0
        cached_page_index.stats.emplace(cid, ParquetPredicate::PageIndexStat {});
1168
0
        auto& sig_stat = cached_page_index.stats[cid];
1169
1170
0
        auto* slot = _tuple_descriptor->slots()[cid];
1171
0
        if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1172
            // table column not exist in file, may be schema change.
1173
0
            return false;
1174
0
        }
1175
1176
0
        const auto& file_col_name =
1177
0
                _table_info_node_ptr->children_file_column_name(slot->col_name());
1178
0
        const FieldSchema* col_schema = _file_metadata->schema().get_column(file_col_name);
1179
0
        int parquet_col_id = col_schema->physical_column_index;
1180
1181
0
        if (parquet_col_id < 0) {
1182
            // complex type, not support page index yet.
1183
0
            return false;
1184
0
        }
1185
0
        if (!_col_offsets.contains(parquet_col_id)) {
1186
            // If the file contains partition columns and the query applies filters on those
1187
            // partition columns, then reading the page index is unnecessary.
1188
0
            return false;
1189
0
        }
1190
1191
0
        auto& column_chunk = row_group.columns[parquet_col_id];
1192
0
        if (column_chunk.column_index_length == 0 || column_chunk.offset_index_length == 0) {
1193
            // column no page index.
1194
0
            return false;
1195
0
        }
1196
1197
0
        tparquet::ColumnIndex column_index;
1198
0
        {
1199
0
            SCOPED_RAW_TIMER(&_reader_statistics.parse_page_index_time);
1200
0
            RETURN_IF_ERROR(page_index.parse_column_index(column_chunk, col_index_buff.data(),
1201
0
                                                          &column_index));
1202
0
        }
1203
0
        const int64_t num_of_pages = column_index.null_pages.size();
1204
0
        if (num_of_pages <= 0) [[unlikely]] {
1205
            // no page. (maybe this row group no data.)
1206
0
            return false;
1207
0
        }
1208
0
        DCHECK_EQ(column_index.min_values.size(), column_index.max_values.size());
1209
0
        if (!column_index.__isset.null_counts) {
1210
            // not set null or null counts;
1211
0
            return false;
1212
0
        }
1213
1214
0
        auto& offset_index = _col_offsets[parquet_col_id];
1215
0
        const auto& page_locations = offset_index.page_locations;
1216
1217
0
        sig_stat.col_schema = col_schema;
1218
0
        sig_stat.num_of_pages = num_of_pages;
1219
0
        sig_stat.encoded_min_value = column_index.min_values;
1220
0
        sig_stat.encoded_max_value = column_index.max_values;
1221
0
        sig_stat.is_all_null.resize(num_of_pages);
1222
0
        sig_stat.has_null.resize(num_of_pages);
1223
0
        sig_stat.ranges.resize(num_of_pages);
1224
1225
0
        for (int page_id = 0; page_id < num_of_pages; page_id++) {
1226
0
            sig_stat.is_all_null[page_id] = column_index.null_pages[page_id];
1227
0
            sig_stat.has_null[page_id] = column_index.null_counts[page_id] > 0;
1228
1229
0
            int64_t from = page_locations[page_id].first_row_index;
1230
0
            int64_t to = 0;
1231
0
            if (page_id == page_locations.size() - 1) {
1232
0
                to = row_group_index.last_row;
1233
0
            } else {
1234
0
                to = page_locations[page_id + 1].first_row_index;
1235
0
            }
1236
0
            sig_stat.ranges[page_id] = RowRange {from, to};
1237
0
        }
1238
1239
0
        sig_stat.available = true;
1240
0
        *ans = &sig_stat;
1241
0
        return true;
1242
0
    };
1243
0
    cached_page_index.row_group_range = {0, row_group.num_rows};
1244
0
    cached_page_index.get_stat_func = get_stat_func;
1245
1246
0
    candidate_row_ranges->add({0, row_group.num_rows});
1247
0
    for (const auto& predicate : push_down_pred) {
1248
0
        RowRanges tmp_row_range;
1249
0
        if (!predicate->evaluate_and(&cached_page_index, &tmp_row_range)) {
1250
            // no need read this row group.
1251
0
            candidate_row_ranges->clear();
1252
0
            return Status::OK();
1253
0
        }
1254
0
        RowRanges::ranges_intersection(*candidate_row_ranges, tmp_row_range, candidate_row_ranges);
1255
0
    }
1256
0
    return Status::OK();
1257
0
}
1258
1259
Status ParquetReader::_process_min_max_bloom_filter(
1260
        const RowGroupReader::RowGroupIndex& row_group_index, const tparquet::RowGroup& row_group,
1261
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1262
187
        RowRanges* row_ranges) {
1263
187
    SCOPED_RAW_TIMER(&_reader_statistics.row_group_filter_time);
1264
187
    if (!_filter_groups) {
1265
        // No row group filtering is needed;
1266
        // for example, Iceberg reads position delete files.
1267
1
        row_ranges->add({0, row_group.num_rows});
1268
1
        return Status::OK();
1269
1
    }
1270
1271
186
    if (_read_by_rows) {
1272
32
        auto group_start = row_group_index.first_row;
1273
32
        auto group_end = row_group_index.last_row;
1274
1275
77
        while (!_row_ids.empty()) {
1276
50
            auto v = _row_ids.front();
1277
50
            if (v < group_start) {
1278
0
                continue;
1279
50
            } else if (v < group_end) {
1280
45
                row_ranges->add(RowRange {v - group_start, v - group_start + 1});
1281
45
                _row_ids.pop_front();
1282
45
            } else {
1283
5
                break;
1284
5
            }
1285
50
        }
1286
154
    } else {
1287
154
        bool filter_this_row_group = false;
1288
154
        bool filtered_by_min_max = false;
1289
154
        bool filtered_by_bloom_filter = false;
1290
154
        RETURN_IF_ERROR(_process_column_stat_filter(row_group, push_down_pred,
1291
154
                                                    &filter_this_row_group, &filtered_by_min_max,
1292
154
                                                    &filtered_by_bloom_filter));
1293
        // Update statistics based on filter type
1294
154
        if (filter_this_row_group) {
1295
0
            if (filtered_by_min_max) {
1296
0
                _reader_statistics.filtered_row_groups_by_min_max++;
1297
0
            }
1298
0
            if (filtered_by_bloom_filter) {
1299
0
                _reader_statistics.filtered_row_groups_by_bloom_filter++;
1300
0
            }
1301
0
        }
1302
1303
154
        if (!filter_this_row_group) {
1304
154
            RETURN_IF_ERROR(_process_page_index_filter(row_group, row_group_index, push_down_pred,
1305
154
                                                       row_ranges));
1306
154
        }
1307
154
    }
1308
1309
186
    return Status::OK();
1310
186
}
1311
1312
Status ParquetReader::_process_column_stat_filter(
1313
        const tparquet::RowGroup& row_group,
1314
        const std::vector<std::unique_ptr<MutilColumnBlockPredicate>>& push_down_pred,
1315
156
        bool* filter_group, bool* filtered_by_min_max, bool* filtered_by_bloom_filter) {
1316
    // If both filters are disabled, skip filtering
1317
156
    if (!_enable_filter_by_min_max && !_enable_filter_by_bloom_filter) {
1318
0
        return Status::OK();
1319
0
    }
1320
1321
    // Cache bloom filters for each column to avoid reading the same bloom filter multiple times
1322
    // when there are multiple predicates on the same column
1323
156
    std::unordered_map<int, std::unique_ptr<ParquetBlockSplitBloomFilter>> bloom_filter_cache;
1324
1325
    // Initialize output parameters
1326
156
    *filtered_by_min_max = false;
1327
156
    *filtered_by_bloom_filter = false;
1328
1329
156
    for (const auto& predicate : _push_down_predicates) {
1330
9
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_stat_func =
1331
11
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1332
                    // Check if min-max filter is enabled
1333
11
                    if (!_enable_filter_by_min_max) {
1334
0
                        return false;
1335
0
                    }
1336
11
                    auto* slot = _tuple_descriptor->slots()[cid];
1337
11
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1338
0
                        return false;
1339
0
                    }
1340
11
                    const auto& file_col_name =
1341
11
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1342
11
                    const FieldSchema* col_schema =
1343
11
                            _file_metadata->schema().get_column(file_col_name);
1344
11
                    int parquet_col_id = col_schema->physical_column_index;
1345
11
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1346
11
                    stat->col_schema = col_schema;
1347
11
                    return ParquetPredicate::read_column_stats(col_schema, meta_data,
1348
11
                                                               &_ignored_stats,
1349
11
                                                               _t_metadata->created_by, stat)
1350
11
                            .ok();
1351
11
                };
1352
9
        std::function<bool(ParquetPredicate::ColumnStat*, int)> get_bloom_filter_func =
1353
9
                [&](ParquetPredicate::ColumnStat* stat, const int cid) {
1354
1
                    auto* slot = _tuple_descriptor->slots()[cid];
1355
1
                    if (!_table_info_node_ptr->children_column_exists(slot->col_name())) {
1356
0
                        return false;
1357
0
                    }
1358
1
                    const auto& file_col_name =
1359
1
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1360
1
                    const FieldSchema* col_schema =
1361
1
                            _file_metadata->schema().get_column(file_col_name);
1362
1
                    int parquet_col_id = col_schema->physical_column_index;
1363
1
                    auto meta_data = row_group.columns[parquet_col_id].meta_data;
1364
1
                    if (!meta_data.__isset.bloom_filter_offset) {
1365
1
                        return false;
1366
1
                    }
1367
0
                    auto primitive_type =
1368
0
                            remove_nullable(col_schema->data_type)->get_primitive_type();
1369
0
                    if (!ParquetPredicate::bloom_filter_supported(primitive_type)) {
1370
0
                        return false;
1371
0
                    }
1372
1373
                    // Check if bloom filter is enabled
1374
0
                    if (!_enable_filter_by_bloom_filter) {
1375
0
                        return false;
1376
0
                    }
1377
1378
                    // Check cache first
1379
0
                    auto cache_iter = bloom_filter_cache.find(parquet_col_id);
1380
0
                    if (cache_iter != bloom_filter_cache.end()) {
1381
                        // Bloom filter already loaded for this column, reuse it
1382
0
                        stat->bloom_filter = std::move(cache_iter->second);
1383
0
                        bloom_filter_cache.erase(cache_iter);
1384
0
                        return stat->bloom_filter != nullptr;
1385
0
                    }
1386
1387
0
                    if (!stat->bloom_filter) {
1388
0
                        SCOPED_RAW_TIMER(&_reader_statistics.bloom_filter_read_time);
1389
0
                        auto st = ParquetPredicate::read_bloom_filter(
1390
0
                                meta_data, _tracing_file_reader, _io_ctx, stat);
1391
0
                        if (!st.ok()) {
1392
0
                            LOG(WARNING) << "Failed to read bloom filter for column "
1393
0
                                         << col_schema->name << " in file " << _scan_range.path
1394
0
                                         << ", status: " << st.to_string();
1395
0
                            stat->bloom_filter.reset();
1396
0
                            return false;
1397
0
                        }
1398
0
                    }
1399
0
                    return stat->bloom_filter != nullptr;
1400
0
                };
1401
9
        ParquetPredicate::ColumnStat stat;
1402
9
        stat.ctz = _ctz;
1403
9
        stat.get_stat_func = &get_stat_func;
1404
9
        stat.get_bloom_filter_func = &get_bloom_filter_func;
1405
1406
9
        if (!predicate->evaluate_and(&stat)) {
1407
1
            *filter_group = true;
1408
1409
            // Track which filter was used for filtering
1410
            // If bloom filter was loaded, it means bloom filter was used
1411
1
            if (stat.bloom_filter) {
1412
0
                *filtered_by_bloom_filter = true;
1413
0
            }
1414
            // If col_schema was set but no bloom filter, it means min-max stats were used
1415
1
            if (stat.col_schema && !stat.bloom_filter) {
1416
1
                *filtered_by_min_max = true;
1417
1
            }
1418
1419
1
            return Status::OK();
1420
1
        }
1421
1422
        // After evaluating, if the bloom filter was used, cache it for subsequent predicates
1423
8
        if (stat.bloom_filter) {
1424
            // Find the column id for caching
1425
0
            for (auto* slot : _tuple_descriptor->slots()) {
1426
0
                if (_table_info_node_ptr->children_column_exists(slot->col_name())) {
1427
0
                    const auto& file_col_name =
1428
0
                            _table_info_node_ptr->children_file_column_name(slot->col_name());
1429
0
                    const FieldSchema* col_schema =
1430
0
                            _file_metadata->schema().get_column(file_col_name);
1431
0
                    int parquet_col_id = col_schema->physical_column_index;
1432
0
                    if (stat.col_schema == col_schema) {
1433
0
                        bloom_filter_cache[parquet_col_id] = std::move(stat.bloom_filter);
1434
0
                        break;
1435
0
                    }
1436
0
                }
1437
0
            }
1438
0
        }
1439
8
    }
1440
1441
    // Update filter statistics if this row group was not filtered
1442
    // The statistics will be updated in _init_row_groups when filter_group is true
1443
155
    return Status::OK();
1444
156
}
1445
1446
390
int64_t ParquetReader::_get_column_start_offset(const tparquet::ColumnMetaData& column) const {
1447
390
    return has_dict_page(column) ? column.dictionary_page_offset : column.data_page_offset;
1448
390
}
1449
1450
148
void ParquetReader::_collect_profile() {
1451
148
    if (_profile == nullptr) {
1452
0
        return;
1453
0
    }
1454
1455
148
    if (_current_group_reader != nullptr) {
1456
148
        _current_group_reader->collect_profile_before_close();
1457
148
    }
1458
148
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups, _reader_statistics.filtered_row_groups);
1459
148
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_min_max,
1460
148
                   _reader_statistics.filtered_row_groups_by_min_max);
1461
148
    COUNTER_UPDATE(_parquet_profile.filtered_row_groups_by_bloom_filter,
1462
148
                   _reader_statistics.filtered_row_groups_by_bloom_filter);
1463
148
    COUNTER_UPDATE(_parquet_profile.to_read_row_groups, _reader_statistics.read_row_groups);
1464
148
    COUNTER_UPDATE(_parquet_profile.total_row_groups, _total_groups);
1465
148
    COUNTER_UPDATE(_parquet_profile.filtered_group_rows, _reader_statistics.filtered_group_rows);
1466
148
    COUNTER_UPDATE(_parquet_profile.filtered_page_rows, _reader_statistics.filtered_page_rows);
1467
148
    COUNTER_UPDATE(_parquet_profile.lazy_read_filtered_rows,
1468
148
                   _reader_statistics.lazy_read_filtered_rows);
1469
148
    COUNTER_UPDATE(_parquet_profile.filtered_bytes, _reader_statistics.filtered_bytes);
1470
148
    COUNTER_UPDATE(_parquet_profile.raw_rows_read, _reader_statistics.read_rows);
1471
148
    COUNTER_UPDATE(_parquet_profile.column_read_time, _reader_statistics.column_read_time);
1472
148
    COUNTER_UPDATE(_parquet_profile.parse_meta_time, _reader_statistics.parse_meta_time);
1473
148
    COUNTER_UPDATE(_parquet_profile.parse_footer_time, _reader_statistics.parse_footer_time);
1474
148
    COUNTER_UPDATE(_parquet_profile.file_reader_create_time,
1475
148
                   _reader_statistics.file_reader_create_time);
1476
148
    COUNTER_UPDATE(_parquet_profile.open_file_num, _reader_statistics.open_file_num);
1477
148
    COUNTER_UPDATE(_parquet_profile.page_index_filter_time,
1478
148
                   _reader_statistics.page_index_filter_time);
1479
148
    COUNTER_UPDATE(_parquet_profile.read_page_index_time, _reader_statistics.read_page_index_time);
1480
148
    COUNTER_UPDATE(_parquet_profile.parse_page_index_time,
1481
148
                   _reader_statistics.parse_page_index_time);
1482
148
    COUNTER_UPDATE(_parquet_profile.row_group_filter_time,
1483
148
                   _reader_statistics.row_group_filter_time);
1484
148
    COUNTER_UPDATE(_parquet_profile.file_footer_read_calls,
1485
148
                   _reader_statistics.file_footer_read_calls);
1486
148
    COUNTER_UPDATE(_parquet_profile.file_footer_hit_cache,
1487
148
                   _reader_statistics.file_footer_hit_cache);
1488
1489
148
    COUNTER_UPDATE(_parquet_profile.skip_page_header_num, _column_statistics.skip_page_header_num);
1490
148
    COUNTER_UPDATE(_parquet_profile.parse_page_header_num,
1491
148
                   _column_statistics.parse_page_header_num);
1492
148
    COUNTER_UPDATE(_parquet_profile.predicate_filter_time,
1493
148
                   _reader_statistics.predicate_filter_time);
1494
148
    COUNTER_UPDATE(_parquet_profile.dict_filter_rewrite_time,
1495
148
                   _reader_statistics.dict_filter_rewrite_time);
1496
148
    COUNTER_UPDATE(_parquet_profile.convert_time, _column_statistics.convert_time);
1497
148
    COUNTER_UPDATE(_parquet_profile.bloom_filter_read_time,
1498
148
                   _reader_statistics.bloom_filter_read_time);
1499
148
    COUNTER_UPDATE(_parquet_profile.page_index_read_calls,
1500
148
                   _column_statistics.page_index_read_calls);
1501
148
    COUNTER_UPDATE(_parquet_profile.decompress_time, _column_statistics.decompress_time);
1502
148
    COUNTER_UPDATE(_parquet_profile.decompress_cnt, _column_statistics.decompress_cnt);
1503
148
    COUNTER_UPDATE(_parquet_profile.page_read_counter, _column_statistics.page_read_counter);
1504
148
    COUNTER_UPDATE(_parquet_profile.page_cache_write_counter,
1505
148
                   _column_statistics.page_cache_write_counter);
1506
148
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_write_counter,
1507
148
                   _column_statistics.page_cache_compressed_write_counter);
1508
148
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_write_counter,
1509
148
                   _column_statistics.page_cache_decompressed_write_counter);
1510
148
    COUNTER_UPDATE(_parquet_profile.page_cache_hit_counter,
1511
148
                   _column_statistics.page_cache_hit_counter);
1512
148
    COUNTER_UPDATE(_parquet_profile.page_cache_missing_counter,
1513
148
                   _column_statistics.page_cache_missing_counter);
1514
148
    COUNTER_UPDATE(_parquet_profile.page_cache_compressed_hit_counter,
1515
148
                   _column_statistics.page_cache_compressed_hit_counter);
1516
148
    COUNTER_UPDATE(_parquet_profile.page_cache_decompressed_hit_counter,
1517
148
                   _column_statistics.page_cache_decompressed_hit_counter);
1518
148
    COUNTER_UPDATE(_parquet_profile.decode_header_time, _column_statistics.decode_header_time);
1519
148
    COUNTER_UPDATE(_parquet_profile.read_page_header_time,
1520
148
                   _column_statistics.read_page_header_time);
1521
148
    COUNTER_UPDATE(_parquet_profile.decode_value_time, _column_statistics.decode_value_time);
1522
148
    COUNTER_UPDATE(_parquet_profile.decode_dict_time, _column_statistics.decode_dict_time);
1523
148
    COUNTER_UPDATE(_parquet_profile.decode_level_time, _column_statistics.decode_level_time);
1524
148
    COUNTER_UPDATE(_parquet_profile.decode_null_map_time, _column_statistics.decode_null_map_time);
1525
148
}
1526
1527
148
void ParquetReader::_collect_profile_before_close() {
1528
148
    _collect_profile();
1529
148
}
1530
1531
} // namespace doris