zhengruifeng opened a new pull request, #42970:
URL: https://github.com/apache/spark/pull/42970
### What changes were proposed in this pull request?
Refactor `test_mode` to be compatible with Spark Connect
### Why are the changes needed?
for test parity
### Does this PR introduce _any_ user-facing change?
No, test-only
### How was this patch tested?
CI, and manually check:
```
In [5]: import pandas as pd
In [6]: def func(iterator):
...: for pdf in iterator:
...: if len(pdf) > 0:
...: if pdf["partition"][0] == 3:
...: yield pd.DataFrame({"num" : ["0", "1", "2",
"3", "4"] })
...: else:
...: yield pd.DataFrame({"num" : ["3", "3", "3",
"3", "4"]} )
...:
In [7]: df = spark.range(0, 4, 1,
4).select(sf.spark_partition_id().alias("partition"))
In [8]: df.mapInPandas(func, "num string").withColumn("p",
sf.spark_partition_id()).show()
/Users/ruifeng.zheng/Dev/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py:239:
FutureWarning: is_categorical_dtype is deprecated and will be removed in a
future version. Use isinstance(dtype, CategoricalDtype) instead
/Users/ruifeng.zheng/Dev/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py:239:
FutureWarning: is_categorical_dtype is deprecated and will be removed in a
future version. Use isinstance(dtype, CategoricalDtype) instead
/Users/ruifeng.zheng/Dev/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py:239:
FutureWarning: is_categorical_dtype is deprecated and will be removed in a
future version. Use isinstance(dtype, CategoricalDtype) instead
/Users/ruifeng.zheng/Dev/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py:239:
FutureWarning: is_categorical_dtype is deprecated and will be removed in a
future version. Use isinstance(dtype, CategoricalDtype) instead
+---+---+
|num| p|
+---+---+
| 3| 0|
| 3| 0|
| 3| 0|
| 3| 0|
| 4| 0|
| 3| 1|
| 3| 1|
| 3| 1|
| 3| 1|
| 4| 1|
| 3| 2|
| 3| 2|
| 3| 2|
| 3| 2|
| 4| 2|
| 0| 3|
| 1| 3|
| 2| 3|
| 3| 3|
| 4| 3|
+---+---+
```
### Was this patch authored or co-authored using generative AI tooling?
No
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