polars.LazyFrame.fetch#
- LazyFrame.fetch(n_rows: int = 500, type_coercion: bool = True, predicate_pushdown: bool = True, projection_pushdown: bool = True, simplify_expression: bool = True, string_cache: bool = False, no_optimization: bool = False, slice_pushdown: bool = True, common_subplan_elimination: bool = True) DataFrame[source]#
Collect a small number of rows for debugging purposes.
Fetch is like a
collect()operation, but it overwrites the number of rows read by every scan operation. This is a utility that helps debug a query on a smaller number of rows.Note that the fetch does not guarantee the final number of rows in the DataFrame. Filter, join operations and a lower number of rows available in the scanned file influence the final number of rows.
- Parameters:
- n_rows
Collect n_rows from the data sources.
- type_coercion
Run type coercion optimization.
- predicate_pushdown
Run predicate pushdown optimization.
- projection_pushdown
Run projection pushdown optimization.
- simplify_expression
Run simplify expressions optimization.
- string_cache
This argument is deprecated. Please set the string cache globally. The argument will be ignored
- no_optimization
Turn off optimizations.
- slice_pushdown
Slice pushdown optimization
- common_subplan_elimination
Will try to cache branching subplans that occur on self-joins or unions.
- Returns:
- DataFrame