German Schiavon Matteo created SPARK-30828:
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Summary: Improve insertInto behaviour
Key: SPARK-30828
URL: https://issues.apache.org/jira/browse/SPARK-30828
Project: Spark
Issue Type: Improvement
Components: Spark Core, SQL
Affects Versions: 3.0.0
Reporter: German Schiavon Matteo
Actually ****when you call _*insertInto*_ to add a dataFrame into an existing
table the only safety check is that the number of columns match, but the order
doesn't matter, and the message in case that the number of columns doesn't
match is not very helpful, specially when you have a lot of columns:
```org.apache.spark.sql.AnalysisException: `default`.`table` requires that the
data to be inserted have the same number of columns as the target table: target
table has 2 column(s) but the inserted data has 1 column(s), including 0
partition column(s) having constant value(s).; ```
I think a standard column check would be very helpful, just in almost other
cases with Spark:
``` cannot resolve 'p2' given input columns: [id, p1];" ```
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