[SPARK-47852][PYTHON] Support DataFrameQueryContext for reverse operations

[itholic]

What changes were proposed in this pull request?

This PR proposes to support DataFrameQueryContext for reverse operations, such as rdiv, rsub and rmod.

Why are the changes needed?

To improve debuggability for reverse binary operations.

Does this PR introduce any user-facing change?

No API changes, but the user-facing error messages for reverse binary operations will be improved:

Example

The problematic rdiv is called from 4th line which raises DIVIDE_BY_ZERO:

  1 spark.conf.set("spark.sql.ansi.enabled", True)
  2 df = spark.createDataFrame([(0,), (1,), (2,)], ["id"])
  3
  4 a = 10 / df.id
  5 b = 0 / df.id
  6
  7 df.select(
  8     a,
  9     df.id + 4,
 10     b,
 11     df.id * 5
 12 ).collect()

Before

pyspark.errors.exceptions.captured.ArithmeticException: [DIVIDE_BY_ZERO] Division by zero. Use `try_divide` to tolerate divisor being 0 and return NULL instead. If necessary set "spark.sql.ansi.enabled" to "false" to bypass this error. SQLSTATE: 22012
== DataFrame ==
"divide" was called from
java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

After

pyspark.errors.exceptions.captured.ArithmeticException: [DIVIDE_BY_ZERO] Division by zero. Use `try_divide` to tolerate divisor being 0 and return NULL instead. If necessary set "spark.sql.ansi.enabled" to "false" to bypass this error. SQLSTATE: 22012
== DataFrame ==
"divide" was called from
test_error_context.py:4

How was this patch tested?

Was this patch authored or co-authored using generative AI tooling?

[itholic]

This can be covered by #46063