be/src/format/parquet/schema_desc.cpp
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1 | | // Licensed to the Apache Software Foundation (ASF) under one |
2 | | // or more contributor license agreements. See the NOTICE file |
3 | | // distributed with this work for additional information |
4 | | // regarding copyright ownership. The ASF licenses this file |
5 | | // to you under the Apache License, Version 2.0 (the |
6 | | // "License"); you may not use this file except in compliance |
7 | | // with the License. You may obtain a copy of the License at |
8 | | // |
9 | | // http://www.apache.org/licenses/LICENSE-2.0 |
10 | | // |
11 | | // Unless required by applicable law or agreed to in writing, |
12 | | // software distributed under the License is distributed on an |
13 | | // "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
14 | | // KIND, either express or implied. See the License for the |
15 | | // specific language governing permissions and limitations |
16 | | // under the License. |
17 | | |
18 | | #include "format/parquet/schema_desc.h" |
19 | | |
20 | | #include <ctype.h> |
21 | | |
22 | | #include <algorithm> |
23 | | #include <ostream> |
24 | | #include <utility> |
25 | | |
26 | | #include "common/cast_set.h" |
27 | | #include "common/logging.h" |
28 | | #include "core/data_type/data_type_array.h" |
29 | | #include "core/data_type/data_type_factory.hpp" |
30 | | #include "core/data_type/data_type_map.h" |
31 | | #include "core/data_type/data_type_struct.h" |
32 | | #include "core/data_type/define_primitive_type.h" |
33 | | #include "format/table/table_format_reader.h" |
34 | | #include "util/slice.h" |
35 | | #include "util/string_util.h" |
36 | | |
37 | | namespace doris { |
38 | | #include "common/compile_check_begin.h" |
39 | | |
40 | 4.74k | static bool is_group_node(const tparquet::SchemaElement& schema) { |
41 | 4.74k | return schema.num_children > 0; |
42 | 4.74k | } |
43 | | |
44 | 784 | static bool is_list_node(const tparquet::SchemaElement& schema) { |
45 | 784 | return schema.__isset.converted_type && schema.converted_type == tparquet::ConvertedType::LIST; |
46 | 784 | } |
47 | | |
48 | 1.05k | static bool is_map_node(const tparquet::SchemaElement& schema) { |
49 | 1.05k | return schema.__isset.converted_type && |
50 | 1.05k | (schema.converted_type == tparquet::ConvertedType::MAP || |
51 | 735 | schema.converted_type == tparquet::ConvertedType::MAP_KEY_VALUE); |
52 | 1.05k | } |
53 | | |
54 | 3.98k | static bool is_repeated_node(const tparquet::SchemaElement& schema) { |
55 | 3.98k | return schema.__isset.repetition_type && |
56 | 3.98k | schema.repetition_type == tparquet::FieldRepetitionType::REPEATED; |
57 | 3.98k | } |
58 | | |
59 | 267 | static bool is_required_node(const tparquet::SchemaElement& schema) { |
60 | 267 | return schema.__isset.repetition_type && |
61 | 267 | schema.repetition_type == tparquet::FieldRepetitionType::REQUIRED; |
62 | 267 | } |
63 | | |
64 | 4.19k | static bool is_optional_node(const tparquet::SchemaElement& schema) { |
65 | 4.19k | return schema.__isset.repetition_type && |
66 | 4.19k | schema.repetition_type == tparquet::FieldRepetitionType::OPTIONAL; |
67 | 4.19k | } |
68 | | |
69 | 468 | static int num_children_node(const tparquet::SchemaElement& schema) { |
70 | 468 | return schema.__isset.num_children ? schema.num_children : 0; |
71 | 468 | } |
72 | | |
73 | | /** |
74 | | * `repeated_parent_def_level` is the definition level of the first ancestor node whose repetition_type equals REPEATED. |
75 | | * Empty array/map values are not stored in doris columns, so have to use `repeated_parent_def_level` to skip the |
76 | | * empty or null values in ancestor node. |
77 | | * |
78 | | * For instance, considering an array of strings with 3 rows like the following: |
79 | | * null, [], [a, b, c] |
80 | | * We can store four elements in data column: null, a, b, c |
81 | | * and the offsets column is: 1, 1, 4 |
82 | | * and the null map is: 1, 0, 0 |
83 | | * For the i-th row in array column: range from `offsets[i - 1]` until `offsets[i]` represents the elements in this row, |
84 | | * so we can't store empty array/map values in doris data column. |
85 | | * As a comparison, spark does not require `repeated_parent_def_level`, |
86 | | * because the spark column stores empty array/map values , and use anther length column to indicate empty values. |
87 | | * Please reference: https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetColumnVector.java |
88 | | * |
89 | | * Furthermore, we can also avoid store null array/map values in doris data column. |
90 | | * The same three rows as above, We can only store three elements in data column: a, b, c |
91 | | * and the offsets column is: 0, 0, 3 |
92 | | * and the null map is: 1, 0, 0 |
93 | | * |
94 | | * Inherit the repetition and definition level from parent node, if the parent node is repeated, |
95 | | * we should set repeated_parent_def_level = definition_level, otherwise as repeated_parent_def_level. |
96 | | * @param parent parent node |
97 | | * @param repeated_parent_def_level the first ancestor node whose repetition_type equals REPEATED |
98 | | */ |
99 | 1.05k | static void set_child_node_level(FieldSchema* parent, int16_t repeated_parent_def_level) { |
100 | 1.85k | for (auto& child : parent->children) { |
101 | 1.85k | child.repetition_level = parent->repetition_level; |
102 | 1.85k | child.definition_level = parent->definition_level; |
103 | 1.85k | child.repeated_parent_def_level = repeated_parent_def_level; |
104 | 1.85k | } |
105 | 1.05k | } |
106 | | |
107 | 468 | static bool is_struct_list_node(const tparquet::SchemaElement& schema) { |
108 | 468 | const std::string& name = schema.name; |
109 | 468 | static const Slice array_slice("array", 5); |
110 | 468 | static const Slice tuple_slice("_tuple", 6); |
111 | 468 | Slice slice(name); |
112 | 468 | return slice == array_slice || slice.ends_with(tuple_slice); |
113 | 468 | } |
114 | | |
115 | 0 | std::string FieldSchema::debug_string() const { |
116 | 0 | std::stringstream ss; |
117 | 0 | ss << "FieldSchema(name=" << name << ", R=" << repetition_level << ", D=" << definition_level; |
118 | 0 | if (children.size() > 0) { |
119 | 0 | ss << ", type=" << data_type->get_name() << ", children=["; |
120 | 0 | for (int i = 0; i < children.size(); ++i) { |
121 | 0 | if (i != 0) { |
122 | 0 | ss << ", "; |
123 | 0 | } |
124 | 0 | ss << children[i].debug_string(); |
125 | 0 | } |
126 | 0 | ss << "]"; |
127 | 0 | } else { |
128 | 0 | ss << ", physical_type=" << physical_type; |
129 | 0 | ss << " , doris_type=" << data_type->get_name(); |
130 | 0 | } |
131 | 0 | ss << ")"; |
132 | 0 | return ss.str(); |
133 | 0 | } |
134 | | |
135 | 284 | Status FieldDescriptor::parse_from_thrift(const std::vector<tparquet::SchemaElement>& t_schemas) { |
136 | 284 | if (t_schemas.size() == 0 || !is_group_node(t_schemas[0])) { |
137 | 0 | return Status::InvalidArgument("Wrong parquet root schema element"); |
138 | 0 | } |
139 | 284 | const auto& root_schema = t_schemas[0]; |
140 | 284 | _fields.resize(root_schema.num_children); |
141 | 284 | _next_schema_pos = 1; |
142 | | |
143 | 2.62k | for (int i = 0; i < root_schema.num_children; ++i) { |
144 | 2.33k | RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, &_fields[i])); |
145 | 2.33k | if (_name_to_field.find(_fields[i].name) != _name_to_field.end()) { |
146 | 0 | return Status::InvalidArgument("Duplicated field name: {}", _fields[i].name); |
147 | 0 | } |
148 | 2.33k | _name_to_field.emplace(_fields[i].name, &_fields[i]); |
149 | 2.33k | } |
150 | | |
151 | 284 | if (_next_schema_pos != t_schemas.size()) { |
152 | 0 | return Status::InvalidArgument("Remaining {} unparsed schema elements", |
153 | 0 | t_schemas.size() - _next_schema_pos); |
154 | 0 | } |
155 | | |
156 | 284 | return Status::OK(); |
157 | 284 | } |
158 | | |
159 | | Status FieldDescriptor::parse_node_field(const std::vector<tparquet::SchemaElement>& t_schemas, |
160 | 4.19k | size_t curr_pos, FieldSchema* node_field) { |
161 | 4.19k | if (curr_pos >= t_schemas.size()) { |
162 | 0 | return Status::InvalidArgument("Out-of-bounds index of schema elements"); |
163 | 0 | } |
164 | 4.19k | auto& t_schema = t_schemas[curr_pos]; |
165 | 4.19k | if (is_group_node(t_schema)) { |
166 | | // nested structure or nullable list |
167 | 1.05k | return parse_group_field(t_schemas, curr_pos, node_field); |
168 | 1.05k | } |
169 | 3.13k | if (is_repeated_node(t_schema)) { |
170 | | // repeated <primitive-type> <name> (LIST) |
171 | | // produce required list<element> |
172 | 0 | node_field->repetition_level++; |
173 | 0 | node_field->definition_level++; |
174 | 0 | node_field->children.resize(1); |
175 | 0 | set_child_node_level(node_field, node_field->definition_level); |
176 | 0 | auto child = &node_field->children[0]; |
177 | 0 | parse_physical_field(t_schema, false, child); |
178 | |
|
179 | 0 | node_field->name = t_schema.name; |
180 | 0 | node_field->lower_case_name = to_lower(t_schema.name); |
181 | 0 | node_field->data_type = std::make_shared<DataTypeArray>(make_nullable(child->data_type)); |
182 | 0 | _next_schema_pos = curr_pos + 1; |
183 | 0 | node_field->field_id = t_schema.__isset.field_id ? t_schema.field_id : -1; |
184 | 3.13k | } else { |
185 | 3.13k | bool is_optional = is_optional_node(t_schema); |
186 | 3.13k | if (is_optional) { |
187 | 2.59k | node_field->definition_level++; |
188 | 2.59k | } |
189 | 3.13k | parse_physical_field(t_schema, is_optional, node_field); |
190 | 3.13k | _next_schema_pos = curr_pos + 1; |
191 | 3.13k | } |
192 | 3.13k | return Status::OK(); |
193 | 4.19k | } |
194 | | |
195 | | void FieldDescriptor::parse_physical_field(const tparquet::SchemaElement& physical_schema, |
196 | 3.13k | bool is_nullable, FieldSchema* physical_field) { |
197 | 3.13k | physical_field->name = physical_schema.name; |
198 | 3.13k | physical_field->lower_case_name = to_lower(physical_field->name); |
199 | 3.13k | physical_field->parquet_schema = physical_schema; |
200 | 3.13k | physical_field->physical_type = physical_schema.type; |
201 | 3.13k | physical_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id |
202 | 3.13k | _physical_fields.push_back(physical_field); |
203 | 3.13k | physical_field->physical_column_index = cast_set<int>(_physical_fields.size() - 1); |
204 | 3.13k | auto type = get_doris_type(physical_schema, is_nullable); |
205 | 3.13k | physical_field->data_type = type.first; |
206 | 3.13k | physical_field->is_type_compatibility = type.second; |
207 | 3.13k | physical_field->field_id = physical_schema.__isset.field_id ? physical_schema.field_id : -1; |
208 | 3.13k | } |
209 | | |
210 | | std::pair<DataTypePtr, bool> FieldDescriptor::get_doris_type( |
211 | 3.13k | const tparquet::SchemaElement& physical_schema, bool nullable) { |
212 | 3.13k | std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false}; |
213 | 3.13k | try { |
214 | 3.13k | if (physical_schema.__isset.logicalType) { |
215 | 1.39k | ans = convert_to_doris_type(physical_schema.logicalType, nullable); |
216 | 1.74k | } else if (physical_schema.__isset.converted_type) { |
217 | 439 | ans = convert_to_doris_type(physical_schema, nullable); |
218 | 439 | } |
219 | 3.13k | } catch (...) { |
220 | | // now the Not supported exception are ignored |
221 | | // so those byte_array maybe be treated as varbinary(now) : string(before) |
222 | 0 | } |
223 | 3.13k | if (ans.first->get_primitive_type() == PrimitiveType::INVALID_TYPE) { |
224 | 1.30k | switch (physical_schema.type) { |
225 | 147 | case tparquet::Type::BOOLEAN: |
226 | 147 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_BOOLEAN, nullable); |
227 | 147 | break; |
228 | 436 | case tparquet::Type::INT32: |
229 | 436 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable); |
230 | 436 | break; |
231 | 225 | case tparquet::Type::INT64: |
232 | 225 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable); |
233 | 225 | break; |
234 | 66 | case tparquet::Type::INT96: |
235 | 66 | if (_enable_mapping_timestamp_tz) { |
236 | | // treat INT96 as TIMESTAMPTZ |
237 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMESTAMPTZ, nullable, |
238 | 0 | 0, 6); |
239 | 66 | } else { |
240 | | // in most cases, it's a nano timestamp |
241 | 66 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable, |
242 | 66 | 0, 6); |
243 | 66 | } |
244 | 66 | break; |
245 | 128 | case tparquet::Type::FLOAT: |
246 | 128 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_FLOAT, nullable); |
247 | 128 | break; |
248 | 251 | case tparquet::Type::DOUBLE: |
249 | 251 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DOUBLE, nullable); |
250 | 251 | break; |
251 | 52 | case tparquet::Type::BYTE_ARRAY: |
252 | 52 | if (_enable_mapping_varbinary) { |
253 | | // if physical_schema not set logicalType and converted_type, |
254 | | // we treat BYTE_ARRAY as VARBINARY by default, so that we can read all data directly. |
255 | 22 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_VARBINARY, nullable); |
256 | 30 | } else { |
257 | 30 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
258 | 30 | } |
259 | 52 | break; |
260 | 0 | case tparquet::Type::FIXED_LEN_BYTE_ARRAY: |
261 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
262 | 0 | break; |
263 | 0 | default: |
264 | 0 | throw Exception(Status::InternalError("Not supported parquet logicalType{}", |
265 | 0 | physical_schema.type)); |
266 | 0 | break; |
267 | 1.30k | } |
268 | 1.30k | } |
269 | 3.13k | return ans; |
270 | 3.13k | } |
271 | | |
272 | | std::pair<DataTypePtr, bool> FieldDescriptor::convert_to_doris_type( |
273 | 1.39k | tparquet::LogicalType logicalType, bool nullable) { |
274 | 1.39k | std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false}; |
275 | 1.39k | bool& is_type_compatibility = ans.second; |
276 | 1.39k | if (logicalType.__isset.STRING) { |
277 | 927 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
278 | 927 | } else if (logicalType.__isset.DECIMAL) { |
279 | 152 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DECIMAL128I, nullable, |
280 | 152 | logicalType.DECIMAL.precision, |
281 | 152 | logicalType.DECIMAL.scale); |
282 | 316 | } else if (logicalType.__isset.DATE) { |
283 | 96 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATEV2, nullable); |
284 | 220 | } else if (logicalType.__isset.INTEGER) { |
285 | 122 | if (logicalType.INTEGER.isSigned) { |
286 | 122 | if (logicalType.INTEGER.bitWidth <= 8) { |
287 | 30 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_TINYINT, nullable); |
288 | 92 | } else if (logicalType.INTEGER.bitWidth <= 16) { |
289 | 92 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable); |
290 | 92 | } else if (logicalType.INTEGER.bitWidth <= 32) { |
291 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable); |
292 | 0 | } else { |
293 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable); |
294 | 0 | } |
295 | 122 | } else { |
296 | 0 | is_type_compatibility = true; |
297 | 0 | if (logicalType.INTEGER.bitWidth <= 8) { |
298 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable); |
299 | 0 | } else if (logicalType.INTEGER.bitWidth <= 16) { |
300 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable); |
301 | 0 | } else if (logicalType.INTEGER.bitWidth <= 32) { |
302 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable); |
303 | 0 | } else { |
304 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_LARGEINT, nullable); |
305 | 0 | } |
306 | 0 | } |
307 | 122 | } else if (logicalType.__isset.TIME) { |
308 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMEV2, nullable); |
309 | 98 | } else if (logicalType.__isset.TIMESTAMP) { |
310 | 94 | if (_enable_mapping_timestamp_tz) { |
311 | 0 | if (logicalType.TIMESTAMP.isAdjustedToUTC) { |
312 | | // treat TIMESTAMP with isAdjustedToUTC as TIMESTAMPTZ |
313 | 0 | ans.first = DataTypeFactory::instance().create_data_type( |
314 | 0 | TYPE_TIMESTAMPTZ, nullable, 0, |
315 | 0 | logicalType.TIMESTAMP.unit.__isset.MILLIS ? 3 : 6); |
316 | 0 | return ans; |
317 | 0 | } |
318 | 0 | } |
319 | 94 | ans.first = DataTypeFactory::instance().create_data_type( |
320 | 94 | TYPE_DATETIMEV2, nullable, 0, logicalType.TIMESTAMP.unit.__isset.MILLIS ? 3 : 6); |
321 | 94 | } else if (logicalType.__isset.JSON) { |
322 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
323 | 4 | } else if (logicalType.__isset.UUID) { |
324 | 4 | if (_enable_mapping_varbinary) { |
325 | 3 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_VARBINARY, nullable, -1, |
326 | 3 | -1, 16); |
327 | 3 | } else { |
328 | 1 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
329 | 1 | } |
330 | 4 | } else if (logicalType.__isset.FLOAT16) { |
331 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_FLOAT, nullable); |
332 | 0 | } else { |
333 | 0 | throw Exception(Status::InternalError("Not supported parquet logicalType")); |
334 | 0 | } |
335 | 1.39k | return ans; |
336 | 1.39k | } |
337 | | |
338 | | std::pair<DataTypePtr, bool> FieldDescriptor::convert_to_doris_type( |
339 | 439 | const tparquet::SchemaElement& physical_schema, bool nullable) { |
340 | 439 | std::pair<DataTypePtr, bool> ans = {std::make_shared<DataTypeNothing>(), false}; |
341 | 439 | bool& is_type_compatibility = ans.second; |
342 | 439 | switch (physical_schema.converted_type) { |
343 | 178 | case tparquet::ConvertedType::type::UTF8: |
344 | 178 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
345 | 178 | break; |
346 | 78 | case tparquet::ConvertedType::type::DECIMAL: |
347 | 78 | ans.first = DataTypeFactory::instance().create_data_type( |
348 | 78 | TYPE_DECIMAL128I, nullable, physical_schema.precision, physical_schema.scale); |
349 | 78 | break; |
350 | 72 | case tparquet::ConvertedType::type::DATE: |
351 | 72 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATEV2, nullable); |
352 | 72 | break; |
353 | 0 | case tparquet::ConvertedType::type::TIME_MILLIS: |
354 | 0 | [[fallthrough]]; |
355 | 0 | case tparquet::ConvertedType::type::TIME_MICROS: |
356 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_TIMEV2, nullable); |
357 | 0 | break; |
358 | 0 | case tparquet::ConvertedType::type::TIMESTAMP_MILLIS: |
359 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable, 0, 3); |
360 | 0 | break; |
361 | 24 | case tparquet::ConvertedType::type::TIMESTAMP_MICROS: |
362 | 24 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_DATETIMEV2, nullable, 0, 6); |
363 | 24 | break; |
364 | 42 | case tparquet::ConvertedType::type::INT_8: |
365 | 42 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_TINYINT, nullable); |
366 | 42 | break; |
367 | 0 | case tparquet::ConvertedType::type::UINT_8: |
368 | 0 | is_type_compatibility = true; |
369 | 0 | [[fallthrough]]; |
370 | 45 | case tparquet::ConvertedType::type::INT_16: |
371 | 45 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_SMALLINT, nullable); |
372 | 45 | break; |
373 | 0 | case tparquet::ConvertedType::type::UINT_16: |
374 | 0 | is_type_compatibility = true; |
375 | 0 | [[fallthrough]]; |
376 | 0 | case tparquet::ConvertedType::type::INT_32: |
377 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_INT, nullable); |
378 | 0 | break; |
379 | 0 | case tparquet::ConvertedType::type::UINT_32: |
380 | 0 | is_type_compatibility = true; |
381 | 0 | [[fallthrough]]; |
382 | 0 | case tparquet::ConvertedType::type::INT_64: |
383 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_BIGINT, nullable); |
384 | 0 | break; |
385 | 0 | case tparquet::ConvertedType::type::UINT_64: |
386 | 0 | is_type_compatibility = true; |
387 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_LARGEINT, nullable); |
388 | 0 | break; |
389 | 0 | case tparquet::ConvertedType::type::JSON: |
390 | 0 | ans.first = DataTypeFactory::instance().create_data_type(TYPE_STRING, nullable); |
391 | 0 | break; |
392 | 0 | default: |
393 | 0 | throw Exception(Status::InternalError("Not supported parquet ConvertedType: {}", |
394 | 0 | physical_schema.converted_type)); |
395 | 439 | } |
396 | 439 | return ans; |
397 | 439 | } |
398 | | |
399 | | Status FieldDescriptor::parse_group_field(const std::vector<tparquet::SchemaElement>& t_schemas, |
400 | 1.05k | size_t curr_pos, FieldSchema* group_field) { |
401 | 1.05k | auto& group_schema = t_schemas[curr_pos]; |
402 | 1.05k | if (is_map_node(group_schema)) { |
403 | | // the map definition: |
404 | | // optional group <name> (MAP) { |
405 | | // repeated group map (MAP_KEY_VALUE) { |
406 | | // required <type> key; |
407 | | // optional <type> value; |
408 | | // } |
409 | | // } |
410 | 267 | return parse_map_field(t_schemas, curr_pos, group_field); |
411 | 267 | } |
412 | 784 | if (is_list_node(group_schema)) { |
413 | | // the list definition: |
414 | | // optional group <name> (LIST) { |
415 | | // repeated group [bag | list] { // hive or spark |
416 | | // optional <type> [array_element | element]; // hive or spark |
417 | | // } |
418 | | // } |
419 | 468 | return parse_list_field(t_schemas, curr_pos, group_field); |
420 | 468 | } |
421 | | |
422 | 316 | if (is_repeated_node(group_schema)) { |
423 | 0 | group_field->repetition_level++; |
424 | 0 | group_field->definition_level++; |
425 | 0 | group_field->children.resize(1); |
426 | 0 | set_child_node_level(group_field, group_field->definition_level); |
427 | 0 | auto struct_field = &group_field->children[0]; |
428 | | // the list of struct: |
429 | | // repeated group <name> (LIST) { |
430 | | // optional/required <type> <name>; |
431 | | // ... |
432 | | // } |
433 | | // produce a non-null list<struct> |
434 | 0 | RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos, struct_field)); |
435 | | |
436 | 0 | group_field->name = group_schema.name; |
437 | 0 | group_field->lower_case_name = to_lower(group_field->name); |
438 | 0 | group_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id |
439 | 0 | group_field->data_type = |
440 | 0 | std::make_shared<DataTypeArray>(make_nullable(struct_field->data_type)); |
441 | 0 | group_field->field_id = group_schema.__isset.field_id ? group_schema.field_id : -1; |
442 | 316 | } else { |
443 | 316 | RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos, group_field)); |
444 | 316 | } |
445 | | |
446 | 316 | return Status::OK(); |
447 | 316 | } |
448 | | |
449 | | Status FieldDescriptor::parse_list_field(const std::vector<tparquet::SchemaElement>& t_schemas, |
450 | 468 | size_t curr_pos, FieldSchema* list_field) { |
451 | | // the list definition: |
452 | | // spark and hive have three level schemas but with different schema name |
453 | | // spark: <column-name> - "list" - "element" |
454 | | // hive: <column-name> - "bag" - "array_element" |
455 | | // parse three level schemas to two level primitive like: LIST<INT>, |
456 | | // or nested structure like: LIST<MAP<INT, INT>> |
457 | 468 | auto& first_level = t_schemas[curr_pos]; |
458 | 468 | if (first_level.num_children != 1) { |
459 | 0 | return Status::InvalidArgument("List element should have only one child"); |
460 | 0 | } |
461 | | |
462 | 468 | if (curr_pos + 1 >= t_schemas.size()) { |
463 | 0 | return Status::InvalidArgument("List element should have the second level schema"); |
464 | 0 | } |
465 | | |
466 | 468 | if (first_level.repetition_type == tparquet::FieldRepetitionType::REPEATED) { |
467 | 0 | return Status::InvalidArgument("List element can't be a repeated schema"); |
468 | 0 | } |
469 | | |
470 | | // the repeated schema element |
471 | 468 | auto& second_level = t_schemas[curr_pos + 1]; |
472 | 468 | if (second_level.repetition_type != tparquet::FieldRepetitionType::REPEATED) { |
473 | 0 | return Status::InvalidArgument("The second level of list element should be repeated"); |
474 | 0 | } |
475 | | |
476 | | // This indicates if this list is nullable. |
477 | 468 | bool is_optional = is_optional_node(first_level); |
478 | 468 | if (is_optional) { |
479 | 421 | list_field->definition_level++; |
480 | 421 | } |
481 | 468 | list_field->repetition_level++; |
482 | 468 | list_field->definition_level++; |
483 | 468 | list_field->children.resize(1); |
484 | 468 | FieldSchema* list_child = &list_field->children[0]; |
485 | | |
486 | 468 | size_t num_children = num_children_node(second_level); |
487 | 468 | if (num_children > 0) { |
488 | 468 | if (num_children == 1 && !is_struct_list_node(second_level)) { |
489 | | // optional field, and the third level element is the nested structure in list |
490 | | // produce nested structure like: LIST<INT>, LIST<MAP>, LIST<LIST<...>> |
491 | | // skip bag/list, it's a repeated element. |
492 | 468 | set_child_node_level(list_field, list_field->definition_level); |
493 | 468 | RETURN_IF_ERROR(parse_node_field(t_schemas, curr_pos + 2, list_child)); |
494 | 468 | } else { |
495 | | // required field, produce the list of struct |
496 | 0 | set_child_node_level(list_field, list_field->definition_level); |
497 | 0 | RETURN_IF_ERROR(parse_struct_field(t_schemas, curr_pos + 1, list_child)); |
498 | 0 | } |
499 | 468 | } else if (num_children == 0) { |
500 | | // required two level list, for compatibility reason. |
501 | 0 | set_child_node_level(list_field, list_field->definition_level); |
502 | 0 | parse_physical_field(second_level, false, list_child); |
503 | 0 | _next_schema_pos = curr_pos + 2; |
504 | 0 | } |
505 | | |
506 | 468 | list_field->name = first_level.name; |
507 | 468 | list_field->lower_case_name = to_lower(first_level.name); |
508 | 468 | list_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id |
509 | 468 | list_field->data_type = |
510 | 468 | std::make_shared<DataTypeArray>(make_nullable(list_field->children[0].data_type)); |
511 | 468 | if (is_optional) { |
512 | 421 | list_field->data_type = make_nullable(list_field->data_type); |
513 | 421 | } |
514 | 468 | list_field->field_id = first_level.__isset.field_id ? first_level.field_id : -1; |
515 | | |
516 | 468 | return Status::OK(); |
517 | 468 | } |
518 | | |
519 | | Status FieldDescriptor::parse_map_field(const std::vector<tparquet::SchemaElement>& t_schemas, |
520 | 267 | size_t curr_pos, FieldSchema* map_field) { |
521 | | // the map definition in parquet: |
522 | | // optional group <name> (MAP) { |
523 | | // repeated group map (MAP_KEY_VALUE) { |
524 | | // required <type> key; |
525 | | // optional <type> value; |
526 | | // } |
527 | | // } |
528 | | // Map value can be optional, the map without values is a SET |
529 | 267 | if (curr_pos + 2 >= t_schemas.size()) { |
530 | 0 | return Status::InvalidArgument("Map element should have at least three levels"); |
531 | 0 | } |
532 | 267 | auto& map_schema = t_schemas[curr_pos]; |
533 | 267 | if (map_schema.num_children != 1) { |
534 | 0 | return Status::InvalidArgument( |
535 | 0 | "Map element should have only one child(name='map', type='MAP_KEY_VALUE')"); |
536 | 0 | } |
537 | 267 | if (is_repeated_node(map_schema)) { |
538 | 0 | return Status::InvalidArgument("Map element can't be a repeated schema"); |
539 | 0 | } |
540 | 267 | auto& map_key_value = t_schemas[curr_pos + 1]; |
541 | 267 | if (!is_group_node(map_key_value) || !is_repeated_node(map_key_value)) { |
542 | 0 | return Status::InvalidArgument( |
543 | 0 | "the second level in map must be a repeated group(key and value)"); |
544 | 0 | } |
545 | 267 | auto& map_key = t_schemas[curr_pos + 2]; |
546 | 267 | if (!is_required_node(map_key)) { |
547 | 0 | LOG(WARNING) << "Filed " << map_schema.name << " is map type, but with nullable key column"; |
548 | 0 | } |
549 | | |
550 | 267 | if (map_key_value.num_children == 1) { |
551 | | // The map with three levels is a SET |
552 | 0 | return parse_list_field(t_schemas, curr_pos, map_field); |
553 | 0 | } |
554 | 267 | if (map_key_value.num_children != 2) { |
555 | | // A standard map should have four levels |
556 | 0 | return Status::InvalidArgument( |
557 | 0 | "the second level in map(MAP_KEY_VALUE) should have two children"); |
558 | 0 | } |
559 | | // standard map |
560 | 267 | bool is_optional = is_optional_node(map_schema); |
561 | 267 | if (is_optional) { |
562 | 239 | map_field->definition_level++; |
563 | 239 | } |
564 | 267 | map_field->repetition_level++; |
565 | 267 | map_field->definition_level++; |
566 | | |
567 | | // Directly create key and value children instead of intermediate key_value node |
568 | 267 | map_field->children.resize(2); |
569 | | // map is a repeated node, we should set the `repeated_parent_def_level` of its children as `definition_level` |
570 | 267 | set_child_node_level(map_field, map_field->definition_level); |
571 | | |
572 | 267 | auto key_field = &map_field->children[0]; |
573 | 267 | auto value_field = &map_field->children[1]; |
574 | | |
575 | | // Parse key and value fields directly from the key_value group's children |
576 | 267 | _next_schema_pos = curr_pos + 2; // Skip key_value group, go directly to key |
577 | 267 | RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, key_field)); |
578 | 267 | RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, value_field)); |
579 | | |
580 | 267 | map_field->name = map_schema.name; |
581 | 267 | map_field->lower_case_name = to_lower(map_field->name); |
582 | 267 | map_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id |
583 | 267 | map_field->data_type = std::make_shared<DataTypeMap>(make_nullable(key_field->data_type), |
584 | 267 | make_nullable(value_field->data_type)); |
585 | 267 | if (is_optional) { |
586 | 239 | map_field->data_type = make_nullable(map_field->data_type); |
587 | 239 | } |
588 | 267 | map_field->field_id = map_schema.__isset.field_id ? map_schema.field_id : -1; |
589 | | |
590 | 267 | return Status::OK(); |
591 | 267 | } |
592 | | |
593 | | Status FieldDescriptor::parse_struct_field(const std::vector<tparquet::SchemaElement>& t_schemas, |
594 | 316 | size_t curr_pos, FieldSchema* struct_field) { |
595 | | // the nested column in parquet, parse group to struct. |
596 | 316 | auto& struct_schema = t_schemas[curr_pos]; |
597 | 316 | bool is_optional = is_optional_node(struct_schema); |
598 | 316 | if (is_optional) { |
599 | 298 | struct_field->definition_level++; |
600 | 298 | } |
601 | 316 | auto num_children = struct_schema.num_children; |
602 | 316 | struct_field->children.resize(num_children); |
603 | 316 | set_child_node_level(struct_field, struct_field->repeated_parent_def_level); |
604 | 316 | _next_schema_pos = curr_pos + 1; |
605 | 1.16k | for (int i = 0; i < num_children; ++i) { |
606 | 852 | RETURN_IF_ERROR(parse_node_field(t_schemas, _next_schema_pos, &struct_field->children[i])); |
607 | 852 | } |
608 | 316 | struct_field->name = struct_schema.name; |
609 | 316 | struct_field->lower_case_name = to_lower(struct_field->name); |
610 | 316 | struct_field->column_id = UNASSIGNED_COLUMN_ID; // Initialize column_id |
611 | | |
612 | 316 | struct_field->field_id = struct_schema.__isset.field_id ? struct_schema.field_id : -1; |
613 | 316 | DataTypes res_data_types; |
614 | 316 | std::vector<String> names; |
615 | 1.16k | for (int i = 0; i < num_children; ++i) { |
616 | 852 | res_data_types.push_back(make_nullable(struct_field->children[i].data_type)); |
617 | 852 | names.push_back(struct_field->children[i].name); |
618 | 852 | } |
619 | 316 | struct_field->data_type = std::make_shared<DataTypeStruct>(res_data_types, names); |
620 | 316 | if (is_optional) { |
621 | 298 | struct_field->data_type = make_nullable(struct_field->data_type); |
622 | 298 | } |
623 | 316 | return Status::OK(); |
624 | 316 | } |
625 | | |
626 | 5 | int FieldDescriptor::get_column_index(const std::string& column) const { |
627 | 15 | for (int32_t i = 0; i < _fields.size(); i++) { |
628 | 15 | if (_fields[i].name == column) { |
629 | 5 | return i; |
630 | 5 | } |
631 | 15 | } |
632 | 0 | return -1; |
633 | 5 | } |
634 | | |
635 | 4.79k | FieldSchema* FieldDescriptor::get_column(const std::string& name) const { |
636 | 4.79k | auto it = _name_to_field.find(name); |
637 | 4.79k | if (it != _name_to_field.end()) { |
638 | 4.79k | return it->second; |
639 | 4.79k | } |
640 | 0 | throw Exception(Status::InternalError("Name {} not found in FieldDescriptor!", name)); |
641 | 0 | return nullptr; |
642 | 4.79k | } |
643 | | |
644 | 127 | void FieldDescriptor::get_column_names(std::unordered_set<std::string>* names) const { |
645 | 127 | names->clear(); |
646 | 1.24k | for (const FieldSchema& f : _fields) { |
647 | 1.24k | names->emplace(f.name); |
648 | 1.24k | } |
649 | 127 | } |
650 | | |
651 | 0 | std::string FieldDescriptor::debug_string() const { |
652 | 0 | std::stringstream ss; |
653 | 0 | ss << "fields=["; |
654 | 0 | for (int i = 0; i < _fields.size(); ++i) { |
655 | 0 | if (i != 0) { |
656 | 0 | ss << ", "; |
657 | 0 | } |
658 | 0 | ss << _fields[i].debug_string(); |
659 | 0 | } |
660 | 0 | ss << "]"; |
661 | 0 | return ss.str(); |
662 | 0 | } |
663 | | |
664 | 34 | void FieldDescriptor::assign_ids() { |
665 | 34 | uint64_t next_id = 1; |
666 | 360 | for (auto& field : _fields) { |
667 | 360 | field.assign_ids(next_id); |
668 | 360 | } |
669 | 34 | } |
670 | | |
671 | 0 | const FieldSchema* FieldDescriptor::find_column_by_id(uint64_t column_id) const { |
672 | 0 | for (const auto& field : _fields) { |
673 | 0 | if (auto result = field.find_column_by_id(column_id)) { |
674 | 0 | return result; |
675 | 0 | } |
676 | 0 | } |
677 | 0 | return nullptr; |
678 | 0 | } |
679 | | |
680 | 1.91k | void FieldSchema::assign_ids(uint64_t& next_id) { |
681 | 1.91k | column_id = next_id++; |
682 | | |
683 | 1.91k | for (auto& child : children) { |
684 | 1.55k | child.assign_ids(next_id); |
685 | 1.55k | } |
686 | | |
687 | 1.91k | max_column_id = next_id - 1; |
688 | 1.91k | } |
689 | | |
690 | 0 | const FieldSchema* FieldSchema::find_column_by_id(uint64_t target_id) const { |
691 | 0 | if (column_id == target_id) { |
692 | 0 | return this; |
693 | 0 | } |
694 | | |
695 | 0 | for (const auto& child : children) { |
696 | 0 | if (auto result = child.find_column_by_id(target_id)) { |
697 | 0 | return result; |
698 | 0 | } |
699 | 0 | } |
700 | | |
701 | 0 | return nullptr; |
702 | 0 | } |
703 | | |
704 | 373 | uint64_t FieldSchema::get_column_id() const { |
705 | 373 | return column_id; |
706 | 373 | } |
707 | | |
708 | 0 | void FieldSchema::set_column_id(uint64_t id) { |
709 | 0 | column_id = id; |
710 | 0 | } |
711 | | |
712 | 92 | uint64_t FieldSchema::get_max_column_id() const { |
713 | 92 | return max_column_id; |
714 | 92 | } |
715 | | |
716 | | #include "common/compile_check_end.h" |
717 | | |
718 | | } // namespace doris |