[SPARK-31945][SQL][PYSPARK] Enable cache for the same Python function.

[ueshin]

What changes were proposed in this pull request?

This PR proposes to make PythonFunction holds Seq[Byte] instead of Array[Byte] to be able to compare if the byte array has the same values for the cache manager.

Why are the changes needed?

Currently the cache manager doesn't use the cache for udf if the udf is created again even if the functions is the same.

>>> func = lambda x: x

>>> df = spark.range(1)
>>> df.select(udf(func)("id")).cache()

>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
*(2) Project [pythonUDF0#14 AS <lambda>(id)#12]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#14]
 +- *(1) Range (0, 1, step=1, splits=12)

This is because PythonFunction holds Array[Byte], and equals method of array equals only when the both array is the same instance.

Does this PR introduce any user-facing change?

Yes, if the user reuse the Python function for the UDF, the cache manager will detect the same function and use the cache for it.

How was this patch tested?

I added a test case and manually.

>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
InMemoryTableScan [<lambda>(id)#12]
   +- InMemoryRelation [<lambda>(id)#12], StorageLevel(disk, memory, deserialized, 1 replicas)
         +- *(2) Project [pythonUDF0#5 AS <lambda>(id)#3]
            +- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#5]
               +- *(1) Range (0, 1, step=1, splits=12)

[HyukjinKwon]

LGTM

[SparkQA]

Test build #123714 has finished for PR 28774 at commit c2b6b86.

• This patch passes all tests.
• This patch merges cleanly.
• This patch adds no public classes.

[HyukjinKwon]

Merged to master.