OmnisciOnNativeDataframePartitionManager#
Public API#
- class modin.experimental.core.execution.native.implementations.omnisci_on_native.partitioning.partition_manager.OmnisciOnNativeDataframePartitionManager#
Frame manager for
OmnisciOnNativeDataframe
.- This class handles several features of
OmnisciOnNativeDataframe
: frame always has a single partition
frame cannot process some data types
frame has to use mangling for index labels
frame uses OmniSci storage format for execution
- classmethod from_arrow(at, return_dims=False, unsupported_cols=None)#
Build frame from Arrow table.
- Parameters
at (pyarrow.Table) – Input table.
return_dims (bool, default: False) – True to include dimensions into returned tuple.
unsupported_cols (list of str, optional) – List of columns holding unsupported data. If None then check all columns to compute the list.
- Returns
Tuple holding array of partitions, list of columns with unsupported data and optionally partitions’ dimensions.
- Return type
tuple
- classmethod from_pandas(df, return_dims=False)#
Create
OmnisciOnNativeDataframe
frompandas.DataFrame
.- Parameters
df (pandas.DataFrame) – Source frame.
return_dims (bool, default: False) – Include resulting dimensions into the returned value.
- Returns
Tuple holding array of partitions, list of columns with unsupported data and optionally partitions’ dimensions.
- Return type
tuple
- classmethod run_exec_plan(plan, index_cols, dtypes, columns)#
Run execution plan in OmniSci storage format to materialize frame.
- Parameters
plan (DFAlgNode) – A root of an execution plan tree.
index_cols (list of str) – A list of index columns.
dtypes (pandas.Index) – Column data types.
columns (list of str) – A frame column names.
- Returns
Created frame’s partitions.
- Return type
np.array
- This class handles several features of