[jira] (SPARK-38615) Provide error context for runtime ANSI failures

["Gengliang Wang (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-38615 ]


    Gengliang Wang deleted comment on SPARK-38615:
    ----------------------------------------

was (Author: gengliang.wang):
[~maxgekk] I am targeting this one in 3.3 as well. Since it is an error message improvement, let's try to finish as much as we can in 3.3.

What do you think?

> Provide error context for runtime ANSI failures
> -----------------------------------------------
>
>                 Key: SPARK-38615
>                 URL: https://issues.apache.org/jira/browse/SPARK-38615
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.3.0
>            Reporter: Gengliang Wang
>            Priority: Major
>
> Currently,  there is not enough error context for runtime ANSI failures.
> In the following example, the error message only tells that there is a "divide by zero" error, without pointing out where the exact SQL statement is.
> {code:java}
> > SELECT
>   ss1.ca_county,
>   ss1.d_year,
>   ws2.web_sales / ws1.web_sales web_q1_q2_increase,
>   ss2.store_sales / ss1.store_sales store_q1_q2_increase,
>   ws3.web_sales / ws2.web_sales web_q2_q3_increase,
>   ss3.store_sales / ss2.store_sales store_q2_q3_increase
> FROM
>   ss ss1, ss ss2, ss ss3, ws ws1, ws ws2, ws ws3
> WHERE
>   ss1.d_qoy = 1
>     AND ss1.d_year = 2000
>     AND ss1.ca_county = ss2.ca_county
>     AND ss2.d_qoy = 2
>     AND ss2.d_year = 2000
>     AND ss2.ca_county = ss3.ca_county
>     AND ss3.d_qoy = 3
>     AND ss3.d_year = 2000
>     AND ss1.ca_county = ws1.ca_county
>     AND ws1.d_qoy = 1
>     AND ws1.d_year = 2000
>     AND ws1.ca_county = ws2.ca_county
>     AND ws2.d_qoy = 2
>     AND ws2.d_year = 2000
>     AND ws1.ca_county = ws3.ca_county
>     AND ws3.d_qoy = 3
>     AND ws3.d_year = 2000
>     AND CASE WHEN ws1.web_sales > 0
>     THEN ws2.web_sales / ws1.web_sales
>         ELSE NULL END
>     > CASE WHEN ss1.store_sales > 0
>     THEN ss2.store_sales / ss1.store_sales
>       ELSE NULL END
>     AND CASE WHEN ws2.web_sales > 0
>     THEN ws3.web_sales / ws2.web_sales
>         ELSE NULL END
>     > CASE WHEN ss2.store_sales > 0
>     THEN ss3.store_sales / ss2.store_sales
>       ELSE NULL END
> ORDER BY ss1.ca_county
>  {code}
> {code:java}
> org.apache.spark.SparkArithmeticException: divide by zero at org.apache.spark.sql.errors.QueryExecutionErrors$.divideByZeroError(QueryExecutionErrors.scala:140) at org.apache.spark.sql.catalyst.expressions.DivModLike.eval(arithmetic.scala:437) at org.apache.spark.sql.catalyst.expressions.DivModLike.eval$(arithmetic.scala:425) at org.apache.spark.sql.catalyst.expressions.Divide.eval(arithmetic.scala:534)
> {code}
>  
> I suggest that we provide details in the error message,  including:
>  * the problematic expression from the original SQL query, e.g. "ss3.store_sales / ss2.store_sales store_q2_q3_increase"
>  * the line number and starting char position of the problematic expression, in case of queries like "select a + b from t1 union select a + b from t2"



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