polars.LazyFrame.explain
-
Create a string representation of the query plan.
Different optimizations can be turned on or off.
- Parameters:
-
-
format{‘plain’, ‘tree’} -
The format to use for displaying the logical plan.
- optimized
-
Return an optimized query plan. Defaults to
True. If this is set toTruethe subsequent optimization flags control which optimizations run. - type_coercion
-
Do type coercion optimization.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - predicate_pushdown
-
Do predicate pushdown optimization.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - projection_pushdown
-
Do projection pushdown optimization.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - simplify_expression
-
Run simplify expressions optimization.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - slice_pushdown
-
Slice pushdown optimization.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - comm_subplan_elim
-
Will try to cache branching subplans that occur on self-joins or unions.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - comm_subexpr_elim
-
Common subexpressions will be cached and reused.
Deprecated since version 1.30.0: Use the
optimizationsparameters. - cluster_with_columns
-
Combine sequential independent calls to with_columns
Deprecated since version 1.30.0: Use the
optimizationsparameters. - collapse_joins
-
Collapse a join and filters into a faster join
Deprecated since version 1.30.0: Use the
optimizationsparameters. - streaming
-
Unused parameter, kept for backward compatibility.
Deprecated since version 1.30.0: Use the
engineparameter instead. - engine
-
Select the engine used to process the query (default
"auto"). AEngineinstance may also be passed. Supported engine names are:-
"auto": use the engine set byConfig.set_engine_affinityor thePOLARS_ENGINE_AFFINITYenvironment variable, falling back to"in-memory"if unset (this default may change in a future release). -
"in-memory": use the in-memory engine, this is the default engine. -
"streaming": use the streaming engine, which processes queries in batches, reducing memory pressure and often outperforming the in-memory engine. This will soon become the default engine of Polars. -
"gpu": use the CUDA GPU engine (requires an Nvidia GPU andcudf-polars). Pass aGPUEngineobject for fine-grained control (e.g. device selection on multi-GPU systems).
If the selected engine cannot run the query, Polars falls back to the in-memory engine.
Note
GPU mode is considered unstable. Not all queries will run successfully on the GPU, however, they should fall back transparently to the default engine if execution is not supported.
Running with
POLARS_VERBOSE=1will provide information if a query falls back (and why). -
- optimizations
-
The optimization passes done during query optimization.
Warning
This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.
- tree_format
-
Format the output as a tree.
Deprecated since version 0.20.30: Use
format="tree"instead.
-
Examples
>>> lf = pl.LazyFrame( ... { ... "a": ["a", "b", "a", "b", "b", "c"], ... "b": [1, 2, 3, 4, 5, 6], ... "c": [6, 5, 4, 3, 2, 1], ... } ... ) >>> lf.group_by("a", maintain_order=True).agg(pl.all().sum()).sort( ... "a" ... ).explain()
LazyFrame.explain(
*,
format: ExplainFormat = 'plain',
optimized: bool = True,
type_coercion: bool = True,
predicate_pushdown: bool = True,
projection_pushdown: bool = True,
simplify_expression: bool = True,
slice_pushdown: bool = True,
comm_subplan_elim: bool = True,
comm_subexpr_elim: bool = True,
cluster_with_columns: bool = True,
collapse_joins: bool = True,
streaming: bool = False,
engine: EngineType = 'auto',
tree_format: bool | None = None,
optimizations: QueryOptFlags = (,
), ) → str
© 2020 Ritchie Vink
© 2022 Polars contributors
Licensed under the MIT License.
https://docs.pola.rs/api/python/stable/reference/lazyframe/api/polars.LazyFrame.explain.html