ray.data.Dataset.select_columns
ray.data.Dataset.select_columns#
- Dataset.select_columns(cols: List[str], *, compute: Optional[Union[str, ray.data._internal.compute.ComputeStrategy]] = None, **ray_remote_args) ray.data.dataset.Dataset [source]#
Select one or more columns from the dataset.
All input columns used to select need to be in the schema of the dataset.
Examples
>>> import ray >>> # Create a dataset with 3 columns >>> ds = ray.data.from_items([{"col1": i, "col2": i+1, "col3": i+2} ... for i in range(10)]) >>> # Select only "col1" and "col2" columns. >>> ds = ds.select_columns(cols=["col1", "col2"]) >>> ds MapBatches(<lambda>) +- Dataset( num_blocks=10, num_rows=10, schema={col1: int64, col2: int64, col3: int64} )
Time complexity: O(dataset size / parallelism)
- Parameters
cols – Names of the columns to select. If any name is not included in the dataset schema, an exception will be raised.
compute – The compute strategy, either “tasks” (default) to use Ray tasks,
ray.data.ActorPoolStrategy(size=n)
to use a fixed-size actor pool, orray.data.ActorPoolStrategy(min_size=m, max_size=n)
for an autoscaling actor pool.ray_remote_args – Additional resource requirements to request from ray (e.g., num_gpus=1 to request GPUs for the map tasks).