polars.LazyFrame.remote#

LazyFrame.remote( context: pc.ComputeContext | None = None, plan_type: pc._typing.PlanTypePreference = 'dot', ) → pc.LazyFrameExt[source]#

Run a query remotely on Polars Cloud.

This allows you to run Polars remotely on one or more workers via several strategies for distributed compute.

Read more in the Announcement post

Parameters:

context: Compute context in which queries are executed. If none given, it will take the default context.
plan_type: Whether to give a dot diagram of a plain text version of logical plan.

Examples

Run a query on a cloud instance.

>>> lf = pl.LazyFrame([1, 2, 3]).sum()
>>> in_progress = lf.remote().collect()  
>>> # do some other work
>>> in_progress.await_result()  
shape: (1, 1)
┌──────────┐
│ column_0 │
│ ---      │
│ i64      │
╞══════════╡
│ 6        │
└──────────┘

Run a query distributed.

>>> lf = (
...     pl.scan_parquet("s3://my_bucket/").group_by("key").agg(pl.sum("values"))
... )
>>> in_progress = lf.remote().distributed().collect()  
>>> in_progress.await_result()  
shape: (1, 1)
┌──────────┐
│ column_0 │
│ ---      │
│ i64      │
╞══════════╡
│ 6        │
└──────────┘