Skip to content

sync: main to datafusion-sql-planner #775

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
charlesbluca merged 1 commit into from
Sep 20, 2022
Merged

sync: main to datafusion-sql-planner #775

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 4 additions & 2 deletions .github/cluster-upstream.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,8 @@ services:
command: dask-scheduler
environment:
USE_MAMBA: "true"
EXTRA_CONDA_PACKAGES: "dask/label/dev::dask cloudpickle>=2.1.0"
# TODO: remove pandas constraint once Dask images are updated
EXTRA_CONDA_PACKAGES: "dask/label/dev::dask cloudpickle>=2.1.0 pandas>=1.5.0"
ports:
- "8786:8786"
dask-worker:
Expand All @@ -16,6 +17,7 @@ services:
command: dask-worker dask-scheduler:8786
environment:
USE_MAMBA: "true"
EXTRA_CONDA_PACKAGES: "dask/label/dev::dask cloudpickle>=2.1.0 pyarrow>=6.0.1 libstdcxx-ng>=12.1.0"
# TODO: remove pandas constraint once Dask images are updated
EXTRA_CONDA_PACKAGES: "dask/label/dev::dask cloudpickle>=2.1.0 pyarrow>=6.0.1 libstdcxx-ng>=12.1.0 pandas>=1.5.0"
volumes:
- /tmp:/tmp
3 changes: 2 additions & 1 deletion .github/cluster.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ services:
command: dask-worker dask-scheduler:8786
environment:
USE_MAMBA: "true"
EXTRA_CONDA_PACKAGES: "cloudpickle>=2.1.0 pyarrow>=6.0.1 libstdcxx-ng>=12.1.0"
# TODO: remove pandas constraint once Dask images are updated
EXTRA_CONDA_PACKAGES: "cloudpickle>=2.1.0 pyarrow>=6.0.1 libstdcxx-ng>=12.1.0 pandas>=1.5.0"
volumes:
- /tmp:/tmp
1 change: 1 addition & 0 deletions dask_sql/_compat.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@

FLOAT_NAN_IMPLEMENTED = _pandas_version >= parseVersion("1.2.0")
INT_NAN_IMPLEMENTED = _pandas_version >= parseVersion("1.0.0")
INDEXER_WINDOW_STEP_IMPLEMENTED = _pandas_version >= parseVersion("1.5.0")

# TODO: remove if prompt-toolkit min version gets bumped
PIPE_INPUT_CONTEXT_MANAGER = _prompt_toolkit_version >= parseVersion("3.0.29")
26 changes: 25 additions & 1 deletion dask_sql/physical/rel/logical/window.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
import pandas as pd
from pandas.api.indexers import BaseIndexer

from dask_sql._compat import INDEXER_WINDOW_STEP_IMPLEMENTED
from dask_sql.datacontainer import ColumnContainer, DataContainer
from dask_sql.java import org
from dask_sql.physical.rel.base import BaseRelPlugin
Expand Down Expand Up @@ -121,7 +122,7 @@ class Indexer(BaseIndexer):
def __init__(self, start: int, end: int):
super().__init__(self, start=start, end=end)

def get_window_bounds(
def _get_window_bounds(
self,
num_values: int = 0,
min_periods: Optional[int] = None,
Expand Down Expand Up @@ -150,6 +151,29 @@ def get_window_bounds(
)
return start, end

if INDEXER_WINDOW_STEP_IMPLEMENTED:

def get_window_bounds(
self,
num_values: int = 0,
min_periods: Optional[int] = None,
center: Optional[bool] = None,
closed: Optional[str] = None,
step: Optional[int] = None,
) -> Tuple[np.ndarray, np.ndarray]:
return self._get_window_bounds(num_values, min_periods, center, closed)

else:

def get_window_bounds(
self,
num_values: int = 0,
min_periods: Optional[int] = None,
center: Optional[bool] = None,
closed: Optional[str] = None,
) -> Tuple[np.ndarray, np.ndarray]:
return self._get_window_bounds(num_values, min_periods, center, closed)


def map_on_each_group(
partitioned_group: pd.DataFrame,
Expand Down