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

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

Gengliang Wang created SPARK-38615:
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             Summary: Provide error context for runtime ANSI failures
                 Key: SPARK-38615
                 URL: https://issues.apache.org/jira/browse/SPARK-38615
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.3.0
            Reporter: Gengliang Wang


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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