HyukjinKwon commented on code in PR #43784:
URL: https://github.com/apache/spark/pull/43784#discussion_r1393562595
##########
python/pyspark/sql/tests/test_python_datasource.py:
##########
@@ -118,25 +118,26 @@ def reader(self, schema) -> "DataSourceReader":
self.spark.dataSource.register(JsonDataSource)
path1 = os.path.join(SPARK_HOME, "python/test_support/sql/people.json")
- path2 = os.path.join(SPARK_HOME,
"python/test_support/sql/people1.json")
+ # path2 = os.path.join(SPARK_HOME,
"python/test_support/sql/people1.json")
df1 = self.spark.read.format("my-json").load(path1)
self.assertEqual(df1.rdd.getNumPartitions(), 1)
assertDataFrameEqual(
df1,
[Row(name="Michael", age=None), Row(name="Andy", age=30),
Row(name="Justin", age=19)],
)
- df2 = self.spark.read.format("my-json").load([path1, path2])
- self.assertEqual(df2.rdd.getNumPartitions(), 2)
- assertDataFrameEqual(
- df2,
- [
- Row(name="Michael", age=None),
- Row(name="Andy", age=30),
- Row(name="Justin", age=19),
- Row(name="Jonathan", age=None),
- ],
- )
+ # Multiple paths are now allowed in DSv1, see SPARK-45597
Review Comment:
We can. the main problem is how to pass the multiple paths that are exposed
to the end users directly, e.g., should they be send in a json format? they
always have to be a string.
My past try: https://github.com/apache/spark/pull/16611
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