Improve insertInto behaviour

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 like in almost other cases with Spark:

"cannot resolve 'p2' given input columns: [id, p1];"