### What changes were proposed in this pull request?
This PR proposes to expose `DataStreamReader.table` (SPARK-32885) and `DataStreamWriter.toTable` (SPARK-32896) to PySpark, which are the only way to read and write with table in Structured Streaming.
### Why are the changes needed?
Please refer SPARK-32885 and SPARK-32896 for rationalizations of these public APIs. This PR only exposes them to PySpark.
### Does this PR introduce _any_ user-facing change?
Yes, PySpark users will be able to read and write with table in Structured Streaming query.
### How was this patch tested?
Manually tested.
> v1 table
>> create table A and ingest to the table A
```
spark.sql("""
create table table_pyspark_parquet (
value long,
`timestamp` timestamp
) USING parquet
""")
df = spark.readStream.format('rate').option('rowsPerSecond', 100).load()
query = df.writeStream.toTable('table_pyspark_parquet', checkpointLocation='/tmp/checkpoint5')
query.lastProgress
query.stop()
```
>> read table A and ingest to the table B which doesn't exist
```
df2 = spark.readStream.table('table_pyspark_parquet')
query2 = df2.writeStream.toTable('table_pyspark_parquet_nonexist', format='parquet', checkpointLocation='/tmp/checkpoint2')
query2.lastProgress
query2.stop()
```
>> select tables
```
spark.sql("DESCRIBE TABLE table_pyspark_parquet").show()
spark.sql("SELECT * FROM table_pyspark_parquet").show()
spark.sql("DESCRIBE TABLE table_pyspark_parquet_nonexist").show()
spark.sql("SELECT * FROM table_pyspark_parquet_nonexist").show()
```
> v2 table (leveraging Apache Iceberg as it provides V2 table and custom catalog as well)
>> create table A and ingest to the table A
```
spark.sql("""
create table iceberg_catalog.default.table_pyspark_v2table (
value long,
`timestamp` timestamp
) USING iceberg
""")
df = spark.readStream.format('rate').option('rowsPerSecond', 100).load()
query = df.select('value', 'timestamp').writeStream.toTable('iceberg_catalog.default.table_pyspark_v2table', checkpointLocation='/tmp/checkpoint_v2table_1')
query.lastProgress
query.stop()
```
>> ingest to the non-exist table B
```
df2 = spark.readStream.format('rate').option('rowsPerSecond', 100).load()
query2 = df2.select('value', 'timestamp').writeStream.toTable('iceberg_catalog.default.table_pyspark_v2table_nonexist', checkpointLocation='/tmp/checkpoint_v2table_2')
query2.lastProgress
query2.stop()
```
>> ingest to the non-exist table C partitioned by `value % 10`
```
df3 = spark.readStream.format('rate').option('rowsPerSecond', 100).load()
df3a = df3.selectExpr('value', 'timestamp', 'value % 10 AS partition').repartition('partition')
query3 = df3a.writeStream.partitionBy('partition').toTable('iceberg_catalog.default.table_pyspark_v2table_nonexist_partitioned', checkpointLocation='/tmp/checkpoint_v2table_3')
query3.lastProgress
query3.stop()
```
>> select tables
```
spark.sql("DESCRIBE TABLE iceberg_catalog.default.table_pyspark_v2table").show()
spark.sql("SELECT * FROM iceberg_catalog.default.table_pyspark_v2table").show()
spark.sql("DESCRIBE TABLE iceberg_catalog.default.table_pyspark_v2table_nonexist").show()
spark.sql("SELECT * FROM iceberg_catalog.default.table_pyspark_v2table_nonexist").show()
spark.sql("DESCRIBE TABLE iceberg_catalog.default.table_pyspark_v2table_nonexist_partitioned").show()
spark.sql("SELECT * FROM iceberg_catalog.default.table_pyspark_v2table_nonexist_partitioned").show()
```
Closes#30835 from HeartSaVioR/SPARK-33836.
Lead-authored-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
Co-authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
8d4d433191