| 1 | #include "duckdb/execution/operator/persistent/base_csv_reader.hpp" |
| 2 | |
| 3 | #include "duckdb/catalog/catalog_entry/table_catalog_entry.hpp" |
| 4 | #include "duckdb/common/file_system.hpp" |
| 5 | #include "duckdb/common/string_util.hpp" |
| 6 | #include "duckdb/common/to_string.hpp" |
| 7 | #include "duckdb/common/types/cast_helpers.hpp" |
| 8 | #include "duckdb/common/operator/cast_operators.hpp" |
| 9 | #include "duckdb/common/operator/decimal_cast_operators.hpp" |
| 10 | #include "duckdb/common/vector_operations/unary_executor.hpp" |
| 11 | #include "duckdb/common/vector_operations/vector_operations.hpp" |
| 12 | #include "duckdb/function/scalar/strftime_format.hpp" |
| 13 | #include "duckdb/main/database.hpp" |
| 14 | #include "duckdb/parser/column_definition.hpp" |
| 15 | #include "duckdb/storage/data_table.hpp" |
| 16 | #include "utf8proc_wrapper.hpp" |
| 17 | #include "utf8proc.hpp" |
| 18 | #include "duckdb/parser/keyword_helper.hpp" |
| 19 | #include "duckdb/main/error_manager.hpp" |
| 20 | #include "duckdb/execution/operator/persistent/parallel_csv_reader.hpp" |
| 21 | |
| 22 | #include <algorithm> |
| 23 | #include <cctype> |
| 24 | #include <cstring> |
| 25 | #include <fstream> |
| 26 | |
| 27 | namespace duckdb { |
| 28 | |
| 29 | string BaseCSVReader::GetLineNumberStr(idx_t line_error, bool is_line_estimated, idx_t buffer_idx) { |
| 30 | // If an error happens during auto-detect it is an estimated line |
| 31 | string estimated = (is_line_estimated ? string(" (estimated)" ) : string("" )); |
| 32 | return to_string(val: GetLineError(line_error, buffer_idx)) + estimated; |
| 33 | } |
| 34 | |
| 35 | BaseCSVReader::BaseCSVReader(ClientContext &context_p, BufferedCSVReaderOptions options_p, |
| 36 | const vector<LogicalType> &requested_types) |
| 37 | : context(context_p), fs(FileSystem::GetFileSystem(context)), allocator(BufferAllocator::Get(context)), |
| 38 | options(std::move(options_p)) { |
| 39 | } |
| 40 | |
| 41 | BaseCSVReader::~BaseCSVReader() { |
| 42 | } |
| 43 | |
| 44 | unique_ptr<CSVFileHandle> BaseCSVReader::OpenCSV(const BufferedCSVReaderOptions &options_p) { |
| 45 | return CSVFileHandle::OpenFile(fs, allocator, path: options_p.file_path, compression: options_p.compression, enable_reset: true); |
| 46 | } |
| 47 | |
| 48 | void BaseCSVReader::InitParseChunk(idx_t num_cols) { |
| 49 | // adapt not null info |
| 50 | if (options.force_not_null.size() != num_cols) { |
| 51 | options.force_not_null.resize(new_size: num_cols, x: false); |
| 52 | } |
| 53 | if (num_cols == parse_chunk.ColumnCount()) { |
| 54 | parse_chunk.Reset(); |
| 55 | } else { |
| 56 | parse_chunk.Destroy(); |
| 57 | |
| 58 | // initialize the parse_chunk with a set of VARCHAR types |
| 59 | vector<LogicalType> varchar_types(num_cols, LogicalType::VARCHAR); |
| 60 | parse_chunk.Initialize(allocator, types: varchar_types); |
| 61 | } |
| 62 | } |
| 63 | |
| 64 | void BaseCSVReader::InitializeProjection() { |
| 65 | for (idx_t i = 0; i < GetTypes().size(); i++) { |
| 66 | reader_data.column_ids.push_back(x: i); |
| 67 | reader_data.column_mapping.push_back(x: i); |
| 68 | } |
| 69 | } |
| 70 | |
| 71 | void BaseCSVReader::SetDateFormat(const string &format_specifier, const LogicalTypeId &sql_type) { |
| 72 | options.has_format[sql_type] = true; |
| 73 | auto &date_format = options.date_format[sql_type]; |
| 74 | date_format.format_specifier = format_specifier; |
| 75 | StrTimeFormat::ParseFormatSpecifier(format_string: date_format.format_specifier, format&: date_format); |
| 76 | } |
| 77 | |
| 78 | struct TryCastDecimalOperator { |
| 79 | template <class OP, class T> |
| 80 | static bool Operation(string_t input, uint8_t width, uint8_t scale) { |
| 81 | T result; |
| 82 | string error_message; |
| 83 | return OP::Operation(input, result, &error_message, width, scale); |
| 84 | } |
| 85 | }; |
| 86 | |
| 87 | struct TryCastFloatingOperator { |
| 88 | template <class OP, class T> |
| 89 | static bool Operation(string_t input) { |
| 90 | T result; |
| 91 | string error_message; |
| 92 | return OP::Operation(input, result, &error_message); |
| 93 | } |
| 94 | }; |
| 95 | |
| 96 | bool TryCastDecimalValueCommaSeparated(const string_t &value_str, const LogicalType &sql_type) { |
| 97 | auto width = DecimalType::GetWidth(type: sql_type); |
| 98 | auto scale = DecimalType::GetScale(type: sql_type); |
| 99 | switch (sql_type.InternalType()) { |
| 100 | case PhysicalType::INT16: |
| 101 | return TryCastDecimalOperator::Operation<TryCastToDecimalCommaSeparated, int16_t>(input: value_str, width, scale); |
| 102 | case PhysicalType::INT32: |
| 103 | return TryCastDecimalOperator::Operation<TryCastToDecimalCommaSeparated, int32_t>(input: value_str, width, scale); |
| 104 | case PhysicalType::INT64: |
| 105 | return TryCastDecimalOperator::Operation<TryCastToDecimalCommaSeparated, int64_t>(input: value_str, width, scale); |
| 106 | case PhysicalType::INT128: |
| 107 | return TryCastDecimalOperator::Operation<TryCastToDecimalCommaSeparated, hugeint_t>(input: value_str, width, scale); |
| 108 | default: |
| 109 | throw InternalException("Unimplemented physical type for decimal" ); |
| 110 | } |
| 111 | } |
| 112 | |
| 113 | bool TryCastFloatingValueCommaSeparated(const string_t &value_str, const LogicalType &sql_type) { |
| 114 | switch (sql_type.InternalType()) { |
| 115 | case PhysicalType::DOUBLE: |
| 116 | return TryCastFloatingOperator::Operation<TryCastErrorMessageCommaSeparated, double>(input: value_str); |
| 117 | case PhysicalType::FLOAT: |
| 118 | return TryCastFloatingOperator::Operation<TryCastErrorMessageCommaSeparated, float>(input: value_str); |
| 119 | default: |
| 120 | throw InternalException("Unimplemented physical type for floating" ); |
| 121 | } |
| 122 | } |
| 123 | |
| 124 | bool BaseCSVReader::TryCastValue(const Value &value, const LogicalType &sql_type) { |
| 125 | if (value.IsNull()) { |
| 126 | return true; |
| 127 | } |
| 128 | if (options.has_format[LogicalTypeId::DATE] && sql_type.id() == LogicalTypeId::DATE) { |
| 129 | date_t result; |
| 130 | string error_message; |
| 131 | return options.date_format[LogicalTypeId::DATE].TryParseDate(str: string_t(StringValue::Get(value)), result, |
| 132 | error_message); |
| 133 | } else if (options.has_format[LogicalTypeId::TIMESTAMP] && sql_type.id() == LogicalTypeId::TIMESTAMP) { |
| 134 | timestamp_t result; |
| 135 | string error_message; |
| 136 | return options.date_format[LogicalTypeId::TIMESTAMP].TryParseTimestamp(str: string_t(StringValue::Get(value)), |
| 137 | result, error_message); |
| 138 | } else if (options.decimal_separator != "." && sql_type.id() == LogicalTypeId::DECIMAL) { |
| 139 | return TryCastDecimalValueCommaSeparated(value_str: string_t(StringValue::Get(value)), sql_type); |
| 140 | } else if (options.decimal_separator != "." && |
| 141 | ((sql_type.id() == LogicalTypeId::FLOAT) || (sql_type.id() == LogicalTypeId::DOUBLE))) { |
| 142 | return TryCastFloatingValueCommaSeparated(value_str: string_t(StringValue::Get(value)), sql_type); |
| 143 | } else { |
| 144 | Value new_value; |
| 145 | string error_message; |
| 146 | return value.TryCastAs(context, target_type: sql_type, new_value, error_message: &error_message, strict: true); |
| 147 | } |
| 148 | } |
| 149 | |
| 150 | struct TryCastDateOperator { |
| 151 | static bool Operation(BufferedCSVReaderOptions &options, string_t input, date_t &result, string &error_message) { |
| 152 | return options.date_format[LogicalTypeId::DATE].TryParseDate(str: input, result, error_message); |
| 153 | } |
| 154 | }; |
| 155 | |
| 156 | struct TryCastTimestampOperator { |
| 157 | static bool Operation(BufferedCSVReaderOptions &options, string_t input, timestamp_t &result, |
| 158 | string &error_message) { |
| 159 | return options.date_format[LogicalTypeId::TIMESTAMP].TryParseTimestamp(str: input, result, error_message); |
| 160 | } |
| 161 | }; |
| 162 | |
| 163 | template <class OP, class T> |
| 164 | static bool TemplatedTryCastDateVector(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, |
| 165 | idx_t count, string &error_message, idx_t &line_error) { |
| 166 | D_ASSERT(input_vector.GetType().id() == LogicalTypeId::VARCHAR); |
| 167 | bool all_converted = true; |
| 168 | idx_t cur_line = 0; |
| 169 | UnaryExecutor::Execute<string_t, T>(input_vector, result_vector, count, [&](string_t input) { |
| 170 | T result; |
| 171 | if (!OP::Operation(options, input, result, error_message)) { |
| 172 | line_error = cur_line; |
| 173 | all_converted = false; |
| 174 | } |
| 175 | cur_line++; |
| 176 | return result; |
| 177 | }); |
| 178 | return all_converted; |
| 179 | } |
| 180 | |
| 181 | bool TryCastDateVector(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, idx_t count, |
| 182 | string &error_message, idx_t &line_error) { |
| 183 | return TemplatedTryCastDateVector<TryCastDateOperator, date_t>(options, input_vector, result_vector, count, |
| 184 | error_message, line_error); |
| 185 | } |
| 186 | |
| 187 | bool TryCastTimestampVector(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, idx_t count, |
| 188 | string &error_message) { |
| 189 | idx_t line_error; |
| 190 | return TemplatedTryCastDateVector<TryCastTimestampOperator, timestamp_t>(options, input_vector, result_vector, |
| 191 | count, error_message, line_error); |
| 192 | } |
| 193 | |
| 194 | template <class OP, class T> |
| 195 | bool TemplatedTryCastFloatingVector(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, |
| 196 | idx_t count, string &error_message, idx_t &line_error) { |
| 197 | D_ASSERT(input_vector.GetType().id() == LogicalTypeId::VARCHAR); |
| 198 | bool all_converted = true; |
| 199 | idx_t row = 0; |
| 200 | UnaryExecutor::Execute<string_t, T>(input_vector, result_vector, count, [&](string_t input) { |
| 201 | T result; |
| 202 | if (!OP::Operation(input, result, &error_message)) { |
| 203 | line_error = row; |
| 204 | all_converted = false; |
| 205 | } else { |
| 206 | row++; |
| 207 | } |
| 208 | return result; |
| 209 | }); |
| 210 | return all_converted; |
| 211 | } |
| 212 | |
| 213 | template <class OP, class T> |
| 214 | bool TemplatedTryCastDecimalVector(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, |
| 215 | idx_t count, string &error_message, uint8_t width, uint8_t scale) { |
| 216 | D_ASSERT(input_vector.GetType().id() == LogicalTypeId::VARCHAR); |
| 217 | bool all_converted = true; |
| 218 | UnaryExecutor::Execute<string_t, T>(input_vector, result_vector, count, [&](string_t input) { |
| 219 | T result; |
| 220 | if (!OP::Operation(input, result, &error_message, width, scale)) { |
| 221 | all_converted = false; |
| 222 | } |
| 223 | return result; |
| 224 | }); |
| 225 | return all_converted; |
| 226 | } |
| 227 | |
| 228 | bool BaseCSVReader::TryCastVector(Vector &parse_chunk_col, idx_t size, const LogicalType &sql_type) { |
| 229 | // try vector-cast from string to sql_type |
| 230 | Vector dummy_result(sql_type); |
| 231 | if (options.has_format[LogicalTypeId::DATE] && sql_type == LogicalTypeId::DATE) { |
| 232 | // use the date format to cast the chunk |
| 233 | string error_message; |
| 234 | idx_t line_error; |
| 235 | return TryCastDateVector(options, input_vector&: parse_chunk_col, result_vector&: dummy_result, count: size, error_message, line_error); |
| 236 | } else if (options.has_format[LogicalTypeId::TIMESTAMP] && sql_type == LogicalTypeId::TIMESTAMP) { |
| 237 | // use the timestamp format to cast the chunk |
| 238 | string error_message; |
| 239 | return TryCastTimestampVector(options, input_vector&: parse_chunk_col, result_vector&: dummy_result, count: size, error_message); |
| 240 | } else { |
| 241 | // target type is not varchar: perform a cast |
| 242 | string error_message; |
| 243 | return VectorOperations::DefaultTryCast(source&: parse_chunk_col, result&: dummy_result, count: size, error_message: &error_message, strict: true); |
| 244 | } |
| 245 | } |
| 246 | |
| 247 | void BaseCSVReader::AddValue(string_t str_val, idx_t &column, vector<idx_t> &escape_positions, bool has_quotes, |
| 248 | idx_t buffer_idx) { |
| 249 | auto length = str_val.GetSize(); |
| 250 | if (length == 0 && column == 0) { |
| 251 | row_empty = true; |
| 252 | } else { |
| 253 | row_empty = false; |
| 254 | } |
| 255 | if (!return_types.empty() && column == return_types.size() && length == 0) { |
| 256 | // skip a single trailing delimiter in last column |
| 257 | return; |
| 258 | } |
| 259 | if (mode == ParserMode::SNIFFING_DIALECT) { |
| 260 | column++; |
| 261 | return; |
| 262 | } |
| 263 | if (column >= return_types.size()) { |
| 264 | if (options.ignore_errors) { |
| 265 | error_column_overflow = true; |
| 266 | return; |
| 267 | } else { |
| 268 | throw InvalidInputException( |
| 269 | "Error in file \"%s\", on line %s: expected %lld values per row, but got more. (%s)" , options.file_path, |
| 270 | GetLineNumberStr(line_error: linenr, is_line_estimated: linenr_estimated, buffer_idx).c_str(), return_types.size(), |
| 271 | options.ToString()); |
| 272 | } |
| 273 | } |
| 274 | |
| 275 | // insert the line number into the chunk |
| 276 | idx_t row_entry = parse_chunk.size(); |
| 277 | |
| 278 | // test against null string, but only if the value was not quoted |
| 279 | if ((!(has_quotes && !options.allow_quoted_nulls) || return_types[column].id() != LogicalTypeId::VARCHAR) && |
| 280 | !options.force_not_null[column] && Equals::Operation(left: str_val, right: string_t(options.null_str))) { |
| 281 | FlatVector::SetNull(vector&: parse_chunk.data[column], idx: row_entry, is_null: true); |
| 282 | } else { |
| 283 | auto &v = parse_chunk.data[column]; |
| 284 | auto parse_data = FlatVector::GetData<string_t>(vector&: v); |
| 285 | if (!escape_positions.empty()) { |
| 286 | // remove escape characters (if any) |
| 287 | string old_val = str_val.GetString(); |
| 288 | string new_val = "" ; |
| 289 | idx_t prev_pos = 0; |
| 290 | for (idx_t i = 0; i < escape_positions.size(); i++) { |
| 291 | idx_t next_pos = escape_positions[i]; |
| 292 | new_val += old_val.substr(pos: prev_pos, n: next_pos - prev_pos); |
| 293 | |
| 294 | if (options.escape.empty() || options.escape == options.quote) { |
| 295 | prev_pos = next_pos + options.quote.size(); |
| 296 | } else { |
| 297 | prev_pos = next_pos + options.escape.size(); |
| 298 | } |
| 299 | } |
| 300 | new_val += old_val.substr(pos: prev_pos, n: old_val.size() - prev_pos); |
| 301 | escape_positions.clear(); |
| 302 | parse_data[row_entry] = StringVector::AddStringOrBlob(vector&: v, data: string_t(new_val)); |
| 303 | } else { |
| 304 | parse_data[row_entry] = str_val; |
| 305 | } |
| 306 | } |
| 307 | |
| 308 | // move to the next column |
| 309 | column++; |
| 310 | } |
| 311 | |
| 312 | bool BaseCSVReader::AddRow(DataChunk &insert_chunk, idx_t &column, string &error_message, idx_t buffer_idx) { |
| 313 | linenr++; |
| 314 | |
| 315 | if (row_empty) { |
| 316 | row_empty = false; |
| 317 | if (return_types.size() != 1) { |
| 318 | if (mode == ParserMode::PARSING) { |
| 319 | FlatVector::SetNull(vector&: parse_chunk.data[0], idx: parse_chunk.size(), is_null: false); |
| 320 | } |
| 321 | column = 0; |
| 322 | return false; |
| 323 | } |
| 324 | } |
| 325 | |
| 326 | // Error forwarded by 'ignore_errors' - originally encountered in 'AddValue' |
| 327 | if (error_column_overflow) { |
| 328 | D_ASSERT(options.ignore_errors); |
| 329 | error_column_overflow = false; |
| 330 | column = 0; |
| 331 | return false; |
| 332 | } |
| 333 | |
| 334 | if (column < return_types.size() && mode != ParserMode::SNIFFING_DIALECT) { |
| 335 | if (options.null_padding) { |
| 336 | for (; column < return_types.size(); column++) { |
| 337 | FlatVector::SetNull(vector&: parse_chunk.data[column], idx: parse_chunk.size(), is_null: true); |
| 338 | } |
| 339 | } else if (options.ignore_errors) { |
| 340 | column = 0; |
| 341 | return false; |
| 342 | } else { |
| 343 | if (mode == ParserMode::SNIFFING_DATATYPES) { |
| 344 | error_message = "Error when adding line" ; |
| 345 | return false; |
| 346 | } else { |
| 347 | throw InvalidInputException( |
| 348 | "Error in file \"%s\" on line %s: expected %lld values per row, but got %d.\nParser options:\n%s" , |
| 349 | options.file_path, GetLineNumberStr(line_error: linenr, is_line_estimated: linenr_estimated, buffer_idx).c_str(), |
| 350 | return_types.size(), column, options.ToString()); |
| 351 | } |
| 352 | } |
| 353 | } |
| 354 | |
| 355 | if (mode == ParserMode::SNIFFING_DIALECT) { |
| 356 | sniffed_column_counts.push_back(x: column); |
| 357 | |
| 358 | if (sniffed_column_counts.size() == options.sample_chunk_size) { |
| 359 | return true; |
| 360 | } |
| 361 | } else { |
| 362 | parse_chunk.SetCardinality(parse_chunk.size() + 1); |
| 363 | } |
| 364 | |
| 365 | if (mode == ParserMode::PARSING_HEADER) { |
| 366 | return true; |
| 367 | } |
| 368 | |
| 369 | if (mode == ParserMode::SNIFFING_DATATYPES && parse_chunk.size() == options.sample_chunk_size) { |
| 370 | return true; |
| 371 | } |
| 372 | |
| 373 | if (mode == ParserMode::PARSING && parse_chunk.size() == STANDARD_VECTOR_SIZE) { |
| 374 | Flush(insert_chunk, buffer_idx); |
| 375 | return true; |
| 376 | } |
| 377 | |
| 378 | column = 0; |
| 379 | return false; |
| 380 | } |
| 381 | |
| 382 | void BaseCSVReader::VerifyUTF8(idx_t col_idx, idx_t row_idx, DataChunk &chunk, int64_t offset) { |
| 383 | D_ASSERT(col_idx < chunk.data.size()); |
| 384 | D_ASSERT(row_idx < chunk.size()); |
| 385 | auto &v = chunk.data[col_idx]; |
| 386 | if (FlatVector::IsNull(vector: v, idx: row_idx)) { |
| 387 | return; |
| 388 | } |
| 389 | |
| 390 | auto parse_data = FlatVector::GetData<string_t>(vector&: chunk.data[col_idx]); |
| 391 | auto s = parse_data[row_idx]; |
| 392 | auto utf_type = Utf8Proc::Analyze(s: s.GetData(), len: s.GetSize()); |
| 393 | if (utf_type == UnicodeType::INVALID) { |
| 394 | string col_name = to_string(val: col_idx); |
| 395 | if (col_idx < names.size()) { |
| 396 | col_name = "\"" + names[col_idx] + "\"" ; |
| 397 | } |
| 398 | int64_t error_line = linenr - (chunk.size() - row_idx) + 1 + offset; |
| 399 | D_ASSERT(error_line >= 0); |
| 400 | throw InvalidInputException("Error in file \"%s\" at line %llu in column \"%s\": " |
| 401 | "%s. Parser options:\n%s" , |
| 402 | options.file_path, error_line, col_name, |
| 403 | ErrorManager::InvalidUnicodeError(input: s.GetString(), context: "CSV file" ), options.ToString()); |
| 404 | } |
| 405 | } |
| 406 | |
| 407 | void BaseCSVReader::VerifyUTF8(idx_t col_idx) { |
| 408 | D_ASSERT(col_idx < parse_chunk.data.size()); |
| 409 | for (idx_t i = 0; i < parse_chunk.size(); i++) { |
| 410 | VerifyUTF8(col_idx, row_idx: i, chunk&: parse_chunk); |
| 411 | } |
| 412 | } |
| 413 | |
| 414 | bool TryCastDecimalVectorCommaSeparated(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, |
| 415 | idx_t count, string &error_message, const LogicalType &result_type) { |
| 416 | auto width = DecimalType::GetWidth(type: result_type); |
| 417 | auto scale = DecimalType::GetScale(type: result_type); |
| 418 | switch (result_type.InternalType()) { |
| 419 | case PhysicalType::INT16: |
| 420 | return TemplatedTryCastDecimalVector<TryCastToDecimalCommaSeparated, int16_t>( |
| 421 | options, input_vector, result_vector, count, error_message, width, scale); |
| 422 | case PhysicalType::INT32: |
| 423 | return TemplatedTryCastDecimalVector<TryCastToDecimalCommaSeparated, int32_t>( |
| 424 | options, input_vector, result_vector, count, error_message, width, scale); |
| 425 | case PhysicalType::INT64: |
| 426 | return TemplatedTryCastDecimalVector<TryCastToDecimalCommaSeparated, int64_t>( |
| 427 | options, input_vector, result_vector, count, error_message, width, scale); |
| 428 | case PhysicalType::INT128: |
| 429 | return TemplatedTryCastDecimalVector<TryCastToDecimalCommaSeparated, hugeint_t>( |
| 430 | options, input_vector, result_vector, count, error_message, width, scale); |
| 431 | default: |
| 432 | throw InternalException("Unimplemented physical type for decimal" ); |
| 433 | } |
| 434 | } |
| 435 | |
| 436 | bool TryCastFloatingVectorCommaSeparated(BufferedCSVReaderOptions &options, Vector &input_vector, Vector &result_vector, |
| 437 | idx_t count, string &error_message, const LogicalType &result_type, |
| 438 | idx_t &line_error) { |
| 439 | switch (result_type.InternalType()) { |
| 440 | case PhysicalType::DOUBLE: |
| 441 | return TemplatedTryCastFloatingVector<TryCastErrorMessageCommaSeparated, double>( |
| 442 | options, input_vector, result_vector, count, error_message, line_error); |
| 443 | case PhysicalType::FLOAT: |
| 444 | return TemplatedTryCastFloatingVector<TryCastErrorMessageCommaSeparated, float>( |
| 445 | options, input_vector, result_vector, count, error_message, line_error); |
| 446 | default: |
| 447 | throw InternalException("Unimplemented physical type for floating" ); |
| 448 | } |
| 449 | } |
| 450 | |
| 451 | bool BaseCSVReader::Flush(DataChunk &insert_chunk, idx_t buffer_idx, bool try_add_line) { |
| 452 | if (parse_chunk.size() == 0) { |
| 453 | return true; |
| 454 | } |
| 455 | |
| 456 | bool conversion_error_ignored = false; |
| 457 | |
| 458 | // convert the columns in the parsed chunk to the types of the table |
| 459 | insert_chunk.SetCardinality(parse_chunk); |
| 460 | if (reader_data.column_ids.empty() && !reader_data.empty_columns) { |
| 461 | throw InternalException("BaseCSVReader::Flush called on a CSV reader that was not correctly initialized. Call " |
| 462 | "MultiFileReader::InitializeReader or InitializeProjection" ); |
| 463 | } |
| 464 | D_ASSERT(reader_data.column_ids.size() == reader_data.column_mapping.size()); |
| 465 | for (idx_t c = 0; c < reader_data.column_ids.size(); c++) { |
| 466 | auto col_idx = reader_data.column_ids[c]; |
| 467 | auto result_idx = reader_data.column_mapping[c]; |
| 468 | auto &parse_vector = parse_chunk.data[col_idx]; |
| 469 | auto &result_vector = insert_chunk.data[result_idx]; |
| 470 | auto &type = result_vector.GetType(); |
| 471 | if (type.id() == LogicalTypeId::VARCHAR) { |
| 472 | // target type is varchar: no need to convert |
| 473 | // just test that all strings are valid utf-8 strings |
| 474 | VerifyUTF8(col_idx); |
| 475 | // reinterpret rather than reference so we can deal with user-defined types |
| 476 | result_vector.Reinterpret(other&: parse_vector); |
| 477 | } else { |
| 478 | string error_message; |
| 479 | bool success; |
| 480 | idx_t line_error = 0; |
| 481 | bool target_type_not_varchar = false; |
| 482 | if (options.has_format[LogicalTypeId::DATE] && type.id() == LogicalTypeId::DATE) { |
| 483 | // use the date format to cast the chunk |
| 484 | success = TryCastDateVector(options, input_vector&: parse_vector, result_vector, count: parse_chunk.size(), error_message, |
| 485 | line_error); |
| 486 | } else if (options.has_format[LogicalTypeId::TIMESTAMP] && type.id() == LogicalTypeId::TIMESTAMP) { |
| 487 | // use the date format to cast the chunk |
| 488 | success = |
| 489 | TryCastTimestampVector(options, input_vector&: parse_vector, result_vector, count: parse_chunk.size(), error_message); |
| 490 | } else if (options.decimal_separator != "." && |
| 491 | (type.id() == LogicalTypeId::FLOAT || type.id() == LogicalTypeId::DOUBLE)) { |
| 492 | success = TryCastFloatingVectorCommaSeparated(options, input_vector&: parse_vector, result_vector, count: parse_chunk.size(), |
| 493 | error_message, result_type: type, line_error); |
| 494 | } else if (options.decimal_separator != "." && type.id() == LogicalTypeId::DECIMAL) { |
| 495 | success = TryCastDecimalVectorCommaSeparated(options, input_vector&: parse_vector, result_vector, count: parse_chunk.size(), |
| 496 | error_message, result_type: type); |
| 497 | } else { |
| 498 | // target type is not varchar: perform a cast |
| 499 | target_type_not_varchar = true; |
| 500 | success = |
| 501 | VectorOperations::TryCast(context, source&: parse_vector, result&: result_vector, count: parse_chunk.size(), error_message: &error_message); |
| 502 | } |
| 503 | if (success) { |
| 504 | continue; |
| 505 | } |
| 506 | if (try_add_line) { |
| 507 | return false; |
| 508 | } |
| 509 | if (options.ignore_errors) { |
| 510 | conversion_error_ignored = true; |
| 511 | continue; |
| 512 | } |
| 513 | string col_name = to_string(val: col_idx); |
| 514 | if (col_idx < names.size()) { |
| 515 | col_name = "\"" + names[col_idx] + "\"" ; |
| 516 | } |
| 517 | |
| 518 | // figure out the exact line number |
| 519 | if (target_type_not_varchar) { |
| 520 | UnifiedVectorFormat inserted_column_data; |
| 521 | result_vector.ToUnifiedFormat(count: parse_chunk.size(), data&: inserted_column_data); |
| 522 | for (; line_error < parse_chunk.size(); line_error++) { |
| 523 | if (!inserted_column_data.validity.RowIsValid(row_idx: line_error) && |
| 524 | !FlatVector::IsNull(vector: parse_vector, idx: line_error)) { |
| 525 | break; |
| 526 | } |
| 527 | } |
| 528 | } |
| 529 | |
| 530 | idx_t error_line; |
| 531 | // The line_error must be summed with linenr (All lines emmited from this batch) |
| 532 | // But subtracted from the parse_chunk |
| 533 | D_ASSERT(line_error + linenr >= parse_chunk.size()); |
| 534 | line_error += linenr; |
| 535 | line_error -= parse_chunk.size(); |
| 536 | |
| 537 | error_line = GetLineError(line_error, buffer_idx); |
| 538 | |
| 539 | if (options.auto_detect) { |
| 540 | throw InvalidInputException("%s in column %s, at line %llu.\n\nParser " |
| 541 | "options:\n%s.\n\nConsider either increasing the sample size " |
| 542 | "(SAMPLE_SIZE=X [X rows] or SAMPLE_SIZE=-1 [all rows]), " |
| 543 | "or skipping column conversion (ALL_VARCHAR=1)" , |
| 544 | error_message, col_name, error_line, options.ToString()); |
| 545 | } else { |
| 546 | throw InvalidInputException("%s at line %llu in column %s. Parser options:\n%s " , error_message, |
| 547 | error_line, col_name, options.ToString()); |
| 548 | } |
| 549 | } |
| 550 | } |
| 551 | if (conversion_error_ignored) { |
| 552 | D_ASSERT(options.ignore_errors); |
| 553 | SelectionVector succesful_rows(parse_chunk.size()); |
| 554 | idx_t sel_size = 0; |
| 555 | |
| 556 | for (idx_t row_idx = 0; row_idx < parse_chunk.size(); row_idx++) { |
| 557 | bool failed = false; |
| 558 | for (idx_t c = 0; c < reader_data.column_ids.size(); c++) { |
| 559 | auto col_idx = reader_data.column_ids[c]; |
| 560 | auto result_idx = reader_data.column_mapping[c]; |
| 561 | |
| 562 | auto &parse_vector = parse_chunk.data[col_idx]; |
| 563 | auto &result_vector = insert_chunk.data[result_idx]; |
| 564 | |
| 565 | bool was_already_null = FlatVector::IsNull(vector: parse_vector, idx: row_idx); |
| 566 | if (!was_already_null && FlatVector::IsNull(vector: result_vector, idx: row_idx)) { |
| 567 | failed = true; |
| 568 | break; |
| 569 | } |
| 570 | } |
| 571 | if (!failed) { |
| 572 | succesful_rows.set_index(idx: sel_size++, loc: row_idx); |
| 573 | } |
| 574 | } |
| 575 | insert_chunk.Slice(sel_vector: succesful_rows, count: sel_size); |
| 576 | } |
| 577 | parse_chunk.Reset(); |
| 578 | return true; |
| 579 | } |
| 580 | |
| 581 | void BaseCSVReader::SetNewLineDelimiter(bool carry, bool carry_followed_by_nl) { |
| 582 | if ((mode == ParserMode::SNIFFING_DIALECT && !options.has_newline) || |
| 583 | options.new_line == NewLineIdentifier::NOT_SET) { |
| 584 | if (options.new_line == NewLineIdentifier::MIX) { |
| 585 | return; |
| 586 | } |
| 587 | NewLineIdentifier this_line_identifier; |
| 588 | if (carry) { |
| 589 | if (carry_followed_by_nl) { |
| 590 | this_line_identifier = NewLineIdentifier::CARRY_ON; |
| 591 | } else { |
| 592 | this_line_identifier = NewLineIdentifier::SINGLE; |
| 593 | } |
| 594 | } else { |
| 595 | this_line_identifier = NewLineIdentifier::SINGLE; |
| 596 | } |
| 597 | if (options.new_line == NewLineIdentifier::NOT_SET) { |
| 598 | options.new_line = this_line_identifier; |
| 599 | return; |
| 600 | } |
| 601 | if (options.new_line != this_line_identifier) { |
| 602 | options.new_line = NewLineIdentifier::MIX; |
| 603 | return; |
| 604 | } |
| 605 | options.new_line = this_line_identifier; |
| 606 | } |
| 607 | } |
| 608 | } // namespace duckdb |
| 609 | |