ueshin opened a new pull request, #40538:
URL: https://github.com/apache/spark/pull/40538
### What changes were proposed in this pull request?
Introduces more basic exceptions.
- ArithmeticException
- ArrayIndexOutOfBoundsException
- DateTimeException
- NumberFormatException
- SparkRuntimeException
### Why are the changes needed?
There are more exceptions that Spark throws but PySpark doesn't capture.
We should introduce more basic exceptions; otherwise we still see
`Py4JJavaError` or `SparkConnectGrpcException`.
```py
>>> spark.conf.set("spark.sql.ansi.enabled", True)
>>> spark.sql("select 1/0")
DataFrame[(1 / 0): double]
>>> spark.sql("select 1/0").show()
Traceback (most recent call last):
...
py4j.protocol.Py4JJavaError: An error occurred while calling o44.showString.
: org.apache.spark.SparkArithmeticException: [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.
== SQL(line 1, position 8) ==
select 1/0
^^^
at
org.apache.spark.sql.errors.QueryExecutionErrors$.divideByZeroError(QueryExecutionErrors.scala:225)
... JVM's stacktrace
```
```py
>>> spark.sql("select 1/0").show()
Traceback (most recent call last):
...
pyspark.errors.exceptions.connect.SparkConnectGrpcException:
(org.apache.spark.SparkArithmeticException) [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.
== SQL(line 1, position 8) ==
select 1/0
^^^
```
### Does this PR introduce _any_ user-facing change?
The error message is more readable.
```py
>>> spark.sql("select 1/0").show()
Traceback (most recent call last):
...
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.
== SQL(line 1, position 8) ==
select 1/0
^^^
```
or
```py
>>> spark.sql("select 1/0").show()
Traceback (most recent call last):
...
pyspark.errors.exceptions.connect.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.
== SQL(line 1, position 8) ==
select 1/0
^^^
```
### How was this patch tested?
Added the related tests.
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