Flatten tuple columns: input a vector of columns, return a new vector with all tuples expanded All tuples are flattened recursively
| 381 | /// Flatten tuple columns: input a vector of columns, return a new vector with all tuples expanded |
| 382 | /// All tuples are flattened recursively |
| 383 | Columns flattenTupleColumnsRecursive(const Block & header, const Columns & columns) |
| 384 | { |
| 385 | if (header.columns() != columns.size()) |
| 386 | { |
| 387 | throw Exception( |
| 388 | ErrorCodes::LOGICAL_ERROR, |
| 389 | "Header columns count ({}) does not match columns count ({}) in flattenTupleColumns", |
| 390 | header.columns(), |
| 391 | columns.size()); |
| 392 | } |
| 393 | |
| 394 | Columns result; |
| 395 | result.reserve(columns.size()); /// Lower bound: every column flattens to at least one leaf. |
| 396 | |
| 397 | for (size_t i = 0; i < columns.size(); ++i) |
| 398 | { |
| 399 | const auto & header_col = header.getByPosition(i); |
| 400 | flattenTupleRecursiveImpl( |
| 401 | columns[i], header_col.type, |
| 402 | [&result](const ColumnPtr & col, const DataTypePtr &, const String &, const Strings &) |
| 403 | { |
| 404 | result.push_back(col); |
| 405 | }, |
| 406 | {}, {}); |
| 407 | } |
| 408 | |
| 409 | return result; |
| 410 | } |
| 411 | |
| 412 | static ColumnPtr reconstructTupleColumnImpl(const DataTypePtr & data_type, const Columns & flattened_columns, size_t & flattened_idx) |
| 413 | { |