itholic opened a new pull request, #46053:
URL: https://github.com/apache/spark/pull/46053
### 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`:
```python
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**
```python
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**
```python
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?
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