polars.LazyFrame.show_graph
-
Show a plot of the query plan.
Note that Graphviz must be installed to render the visualization (if not already present, you can download it here: https://graphviz.org/download).
- Parameters:
-
- optimized
-
Optimize the query plan.
- show
-
Show the figure.
- output_path
-
Write the figure to disk.
- raw_output
-
Return dot syntax. This cannot be combined with
showand/oroutput_path. - figsize
-
Passed to matplotlib if
show == True. - 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. - 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). -
-
plan_stage{‘ir’, ‘physical’} -
Select the stage to display. Currently only the streaming engine has a separate physical stage, for the other engines both IR and physical are the same.
- optimizations
-
The set of the optimizations considered during query optimization.
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" ... ).show_graph(plan_stage="ir")
LazyFrame.show_graph(
*,
optimized: bool = True,
show: bool = True,
output_path: str | Path | None = None,
raw_output: bool = False,
figsize: tuple[float,
float] = (16.0,
12.0,
), type_coercion: bool = True, _type_check: 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, engine: EngineType = 'auto', plan_stage: PlanStage | None = None, _check_order: bool = True, optimizations: QueryOptFlags = (), ) → str | None
© 2020 Ritchie Vink
© 2022 Polars contributors
Licensed under the MIT License.
https://docs.pola.rs/api/python/stable/reference/lazyframe/api/polars.LazyFrame.show_graph.html