zhengruifeng opened a new pull request, #42743:
URL: https://github.com/apache/spark/pull/42743
### What changes were proposed in this pull request?
Add CalendarIntervalType to Python Client
### Why are the changes needed?
for feature parity
### Does this PR introduce _any_ user-facing change?
yes
before this PR:
```
In [1]: from pyspark.sql import functions as sf
In [2]: spark.range(1).select(sf.make_interval(sf.lit(1))).schema
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
Cell In[2], line 1
----> 1 spark.range(1).select(sf.make_interval(sf.lit(1))).schema
File ~/Dev/spark/python/pyspark/sql/connect/dataframe.py:1687, in
DataFrame.schema(self)
1685 if self._session is None:
1686 raise Exception("Cannot analyze without SparkSession.")
-> 1687 return self._session.client.schema(query)
1688 else:
1689 raise Exception("Empty plan.")
...
Exception: Unsupported data type calendar_interval
```
after this PR:
```
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 4.0.0.dev0
/_/
Using Python version 3.10.11 (main, May 17 2023 14:30:36)
Client connected to the Spark Connect server at localhost
SparkSession available as 'spark'.
In [1]: from pyspark.sql import functions as sf
In [2]: spark.range(1).select(sf.make_interval(sf.lit(1))).schema
Out[2]: StructType([StructField('make_interval(1, 0, 0, 0, 0, 0, 0)',
CalendarIntervalType(), True)])
```
### How was this patch tested?
added UT
### Was this patch authored or co-authored using generative AI tooling?
NO
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