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new 5d2d9155d24 [SPARK-45121][CONNECT][PS] Support `Series.empty` for
Spark Connect
5d2d9155d24 is described below
commit 5d2d9155d24ea9a466e1868969dccd4ae1ac7278
Author: Haejoon Lee <haejoon....@databricks.com>
AuthorDate: Tue Sep 12 14:37:52 2023 +0800
[SPARK-45121][CONNECT][PS] Support `Series.empty` for Spark Connect
### What changes were proposed in this pull request?
This PR proposes to support Series.empty for Spark Connect by removing JVM
dependency.
### Why are the changes needed?
Increase API coverage for Spark Connect.
### Does this PR introduce _any_ user-facing change?
`Series.empty` is available on Spark Connect.
### How was this patch tested?
Added UT.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #42877 from itholic/SPARK-45121.
Authored-by: Haejoon Lee <haejoon....@databricks.com>
Signed-off-by: Ruifeng Zheng <ruife...@apache.org>
---
python/pyspark/pandas/base.py | 2 +-
python/pyspark/pandas/tests/series/test_series.py | 2 ++
2 files changed, 3 insertions(+), 1 deletion(-)
diff --git a/python/pyspark/pandas/base.py b/python/pyspark/pandas/base.py
index 1cb17de89e8..ef0b51f757d 100644
--- a/python/pyspark/pandas/base.py
+++ b/python/pyspark/pandas/base.py
@@ -505,7 +505,7 @@ class IndexOpsMixin(object, metaclass=ABCMeta):
>>> ps.DataFrame({}, index=list('abc')).index.empty
False
"""
- return self._internal.resolved_copy.spark_frame.rdd.isEmpty()
+ return self._internal.resolved_copy.spark_frame.isEmpty()
@property
def hasnans(self) -> bool:
diff --git a/python/pyspark/pandas/tests/series/test_series.py
b/python/pyspark/pandas/tests/series/test_series.py
index 136d905eb49..aa147aa75cf 100644
--- a/python/pyspark/pandas/tests/series/test_series.py
+++ b/python/pyspark/pandas/tests/series/test_series.py
@@ -113,6 +113,8 @@ class SeriesTestsMixin:
self.assert_eq(ps.from_pandas(pser_a), pser_a)
self.assert_eq(ps.from_pandas(pser_b), pser_b)
+ self.assertTrue(pser_a.empty)
+
def test_all_null_series(self):
pser_a = pd.Series([None, None, None], dtype="float64")
pser_b = pd.Series([None, None, None], dtype="str")
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