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Signed-off-by: Igoshev, Yaroslav <yaroslav.igoshev@intel.com>
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modin/core/dataframe/base/partitioning/axis_partition.py
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| # Licensed to Modin Development Team under one or more contributor license agreements. | ||
| # See the NOTICE file distributed with this work for additional information regarding | ||
| # copyright ownership. The Modin Development Team licenses this file to you under the | ||
| # Apache License, Version 2.0 (the "License"); you may not use this file except in | ||
| # compliance with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software distributed under | ||
| # the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF | ||
| # ANY KIND, either express or implied. See the License for the specific language | ||
| # governing permissions and limitations under the License. | ||
|
|
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| """Base class of an axis partition for a Modin Dataframe.""" | ||
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| from abc import ABC | ||
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| class BaseDataframeAxisPartition(ABC): # pragma: no cover | ||
| """ | ||
| An abstract class that represents the parent class for any axis partition class. | ||
| This class is intended to simplify the way that operations are performed. | ||
| """ | ||
|
|
||
| def apply( | ||
| self, | ||
| func, | ||
| num_splits=None, | ||
| other_axis_partition=None, | ||
| maintain_partitioning=True, | ||
| **kwargs, | ||
| ): | ||
| """ | ||
| Apply a function to this axis partition along full axis. | ||
| Parameters | ||
| ---------- | ||
| func : callable | ||
| The function to apply. This will be preprocessed according to | ||
| the corresponding `BaseDataframePartition` objects. | ||
| num_splits : int, default: None | ||
| The number of times to split the result object. | ||
| other_axis_partition : BaseDataframeAxisPartition, default: None | ||
| Another `BaseDataframeAxisPartition` object to be applied | ||
| to func. This is for operations that are between two data sets. | ||
| maintain_partitioning : bool, default: True | ||
| Whether to keep the partitioning in the same | ||
| orientation as it was previously or not. This is important because we may be | ||
| operating on an individual axis partition and not touching the rest. | ||
| In this case, we have to return the partitioning to its previous | ||
| orientation (the lengths will remain the same). This is ignored between | ||
| two axis partitions. | ||
| **kwargs : dict | ||
| Additional keywords arguments to be passed in `func`. | ||
| Returns | ||
| ------- | ||
| list | ||
| A list of `BaseDataframePartition` objects. | ||
| Notes | ||
| ----- | ||
| The procedures that invoke this method assume full axis | ||
| knowledge. Implement this method accordingly. | ||
| You must return a list of `BaseDataframePartition` objects from this method. | ||
| """ | ||
| pass | ||
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| def shuffle(self, func, lengths, **kwargs): | ||
| """ | ||
| Shuffle the order of the data in this axis partition based on the `lengths`. | ||
| Parameters | ||
| ---------- | ||
| func : callable | ||
| The function to apply before splitting. | ||
| lengths : list | ||
| The list of partition lengths to split the result into. | ||
| **kwargs : dict | ||
| Additional keywords arguments to be passed in `func`. | ||
| Returns | ||
| ------- | ||
| list | ||
| A list of `BaseDataframePartition` objects split by `lengths`. | ||
| """ | ||
| pass | ||
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| # Child classes must have these in order to correctly subclass. | ||
| instance_type = None | ||
| partition_type = None | ||
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| def _wrap_partitions(self, partitions): | ||
| """ | ||
| Wrap remote partition objects with `BaseDataframePartition` class. | ||
| Parameters | ||
| ---------- | ||
| partitions : list | ||
| List of remotes partition objects to be wrapped with `BaseDataframePartition` class. | ||
| Returns | ||
| ------- | ||
| list | ||
| List of wrapped remote partition objects. | ||
| """ | ||
| return [self.partition_type(obj) for obj in partitions] | ||
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| def force_materialization(self, get_ip=False): | ||
| """ | ||
| Materialize axis partitions into a single partition. | ||
| Parameters | ||
| ---------- | ||
| get_ip : bool, default: False | ||
| Whether to get node ip address to a single partition or not. | ||
| Returns | ||
| ------- | ||
| BaseDataframeAxisPartition | ||
| An axis partition containing only a single materialized partition. | ||
| """ | ||
| materialized = self.apply( | ||
| lambda x: x, num_splits=1, maintain_partitioning=False | ||
| ) | ||
| return type(self)(materialized, get_ip=get_ip) | ||
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| def unwrap(self, squeeze=False, get_ip=False): | ||
| """ | ||
| Unwrap partitions from this axis partition. | ||
| Parameters | ||
| ---------- | ||
| squeeze : bool, default: False | ||
| Flag used to unwrap only one partition. | ||
| get_ip : bool, default: False | ||
| Whether to get node ip address to each partition or not. | ||
| Returns | ||
| ------- | ||
| list | ||
| List of partitions from this axis partition. | ||
| Notes | ||
| ----- | ||
| If `get_ip=True`, a list of tuples of Ray.ObjectRef/Dask.Future to node ip addresses and | ||
| unwrapped partitions, respectively, is returned if Ray/Dask is used as an engine | ||
| (i.e. [(Ray.ObjectRef/Dask.Future, Ray.ObjectRef/Dask.Future), ...]). | ||
| """ | ||
| if squeeze and len(self.list_of_blocks) == 1: | ||
| if get_ip: | ||
| return self.list_of_ips[0], self.list_of_blocks[0] | ||
| else: | ||
| return self.list_of_blocks[0] | ||
| else: | ||
| if get_ip: | ||
| return list(zip(self.list_of_ips, self.list_of_blocks)) | ||
| else: | ||
| return self.list_of_blocks |
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