ueshin opened a new pull request, #50470:
URL: https://github.com/apache/spark/pull/50470
### What changes were proposed in this pull request?
Adds IN Subquery DataFrame API.
The existing `Column.isin` will take `Dataset`/`DataFrame` and use it as IN
subquery.
For example:
```py
>>> df = spark.createDataFrame([(2, "Alice"), (5, "Bob"), (8, "Mike")],
["age", "name"])
>>> df.createOrReplaceTempView('t')
>>> # SELECT * FROM t WHERE age IN (FROM range(6)) ORDER BY age
>>> df.where(df.age.isin(spark.range(6))).orderBy("age").show()
+---+-----+
|age| name|
+---+-----+
| 2|Alice|
| 5| Bob|
+---+-----+
```
For multiple values to be compared, `sf.struct` will be used to tuple them:
```py
>>> from pyspark.sql import functions as sf
>>> # SELECT * FROM t WHERE (age, name) IN (SELECT id, 'Bob' FROM range(6))
>>> df.where(sf.struct(df.age, df.name).isin(spark.range(6).select("id",
sf.lit("Bob")))).show()
+---+----+
|age|name|
+---+----+
| 5| Bob|
+---+----+
```
### Why are the changes needed?
The IN subquery was missing in DataFrame API.
### Does this PR introduce _any_ user-facing change?
Yes, `Column.isin` will take `Dataset`/`DataFrame` to use it as IN subquery.
### How was this patch tested?
Added the related tests.
### Was this patch authored or co-authored using generative AI tooling?
No.
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