cuDFOnRayDataframePartitionManager#
This class is the specific implementation of GenericRayDataframePartitionManager
.
It serves as an intermediate level between cuDFOnRayDataframe
and cuDFOnRayDataframePartition
class.
This class is responsible for partition manipulation and applying a function to
block/row/column partitions.
Public API#
- class modin.core.execution.ray.implementations.cudf_on_ray.partitioning.cuDFOnRayDataframePartitionManager#
The class implements the interface in
GenericRayDataframePartitionManager
using cuDF on Ray.- classmethod from_pandas(df, return_dims=False)#
Create partitions from
pandas.DataFrame/pandas.Series
.- Parameters:
df (pandas.DataFrame/pandas.Series) – A
pandas.DataFrame
to add.return_dims (boolean, default: False) – Is return dimensions or not.
- Returns:
List of partitions in case return_dims == False, tuple (partitions, row lengths, col widths) in other case.
- Return type:
list or tuple
- classmethod lazy_map_partitions(partitions, map_func)#
Apply map_func to every partition lazily.
Compared to Modin-CPU, Modin-GPU lazy version represents:
A scheduled function in the Ray task graph.
A non-materialized key.
- Parameters:
partitions (np.ndarray) – NumPy array with partitions.
map_func (callable) – The function to apply.
- Returns:
A NumPy array of
cuDFOnRayDataframePartition
objects.- Return type:
np.ndarray