dchvn opened a new pull request #34737:
URL: https://github.com/apache/spark/pull/34737
### What changes were proposed in this pull request?
Skip check monotonic increasing for Series.asof with 'compute.eager_check'
### Why are the changes needed?
monotonic increasing checking is expensive, so we should use config
'compute.eager_check' to skip this one
### Does this PR introduce _any_ user-facing change?
Yes
Before this PR
```python
>>> s = ps.Series([1, 2, np.nan, 4], index=[10, 30, 20, 40])
>>> with ps.option_context("compute.eager_check", False):
... s.asof(20)
...
21/11/29 17:09:39 WARN WindowExec: No Partition Defined for Window
operation! Moving all data to a single partition, this can cause serious
performance degradation.
21/11/29 17:09:40 WARN WindowExec: No Partition Defined for Window
operation! Moving all data to a single partition, this can cause serious
performance degradation.
21/11/29 17:09:40 WARN WindowExec: No Partition Defined for Window
operation! Moving all data to a single partition, this can cause serious
performance degradation.
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
File "/u02/spark/python/pyspark/pandas/series.py", line 5220, in asof
raise ValueError("asof requires a sorted index")
ValueError: asof requires a sorted index
```
After this PR, when config 'compute.eager_check' is False, pandas-on-Spark
just proceeds and performs by ignoring the indeces's order
```python
>>> s = ps.Series([1, 2, np.nan, 4], index=[10, 30, 20, 40])
>>> with ps.option_context("compute.eager_check", False):
... s.asof(20)
...
1.0
```
### How was this patch tested?
Unit tests
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