[GitHub] spark pull request #21647: [SPARK-21335] [DOC] doc changes for disallowed un...

[HyukjinKwon <gi...@git.apache.org>]

Github user HyukjinKwon commented on a diff in the pull request:

    https://github.com/apache/spark/pull/21647#discussion_r198364360
  
    --- Diff: docs/sql-programming-guide.md ---
    @@ -2017,6 +2017,7 @@ working with timestamps in `pandas_udf`s to get the best performance, see
         - Literal values used in SQL operations are converted to DECIMAL with the exact precision and scale needed by them.
         - The configuration `spark.sql.decimalOperations.allowPrecisionLoss` has been introduced. It defaults to `true`, which means the new behavior described here; if set to `false`, Spark uses previous rules, ie. it doesn't adjust the needed scale to represent the values and it returns NULL if an exact representation of the value is not possible.
       - In PySpark, `df.replace` does not allow to omit `value` when `to_replace` is not a dictionary. Previously, `value` could be omitted in the other cases and had `None` by default, which is counterintuitive and error-prone.
    +  - Un-aliased subquery is supported by Spark SQL for a long time. Its semantic was not well defined and had confusing behaviors. Since Spark 2.3, we invalid a weird use case: `SELECT v.i from (SELECT i FROM v)`. Now this query will throw analysis exception because users should not be able to use the qualifier inside a subquery. See [SPARK-20690](https://issues.apache.org/jira/browse/SPARK-20690) and [SPARK-21335](https://issues.apache.org/jira/browse/SPARK-21335) for details.
    --- End diff --
    
    Not a big deal but please consider:
    
    Un-aliased subquery is supported by Spark SQL for a long time. Its semantic was not well defined and had confusing behaviors. Since Spark 2.3, we invalid a weird use case: `SELECT v.i from (SELECT i FROM v)`
    
    >
    
    Un-aliased subquery's semantic has not been well defined with confusing behaviors. Since Spark 2.3, we invalidate such confusing cases, for example, `SELECT v.i from (SELECT i FROM v)`.
    



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