You might be able to leverage the prepareQuery option, that is at
https://spark.apache.org/docs/3.5.1/sql-data-sources-jdbc.html#data-source-option
... this was introduced in Spark 3.4.0 to handle temp table query and CTE
query against MSSQL server since what you send in is not actually what
-03-30| 2|
| 4|2014-03-31| 3|
| 5|2015-03-07| 7|
| 6|2015-03-08| 1|
| 7|2015-03-30| 2|
| 8|2015-03-31| 3|
+---+--++
From: Appel, Kevin
Sent: Friday, February 11, 2022 2:35 PM
To: user@spark.apache.org; 'Sean Owen
Previously in Spark2 we could use the spark function date_format with the "W"
flag and it will provide back the week of month of that date. In Spark3 when
trying this there is an error back:
* org.apache.spark.SparkUpgradeException: You may get a different
result due to the upgrading
