Can you pastebin the full error with all column types ?
There should be a difference between some column(s).
Cheers
> On Feb 11, 2016, at 2:12 AM, Zsolt Tóth <toth.zsolt....@gmail.com> wrote:
>
> Hi,
>
> I'd like to append a column of a dataframe to another DF (using Spark 1.5.2):
>
> DataFrame outputDF = unlabelledDF.withColumn("predicted_label",
> predictedDF.col("predicted"));
>
> I get the following exception:
>
> java.lang.IllegalArgumentException: requirement failed: DataFrame must have
> the same schema as the relation to which is inserted.
> DataFrame schema: StructType(StructField(predicted_label,DoubleType,true),
> ...<other 700 numerical (ByteType/ShortType) columns>
> Relation schema: StructType(StructField(predicted_label,DoubleType,true),
> ...<the same 700 columns>
>
> The interesting part is that the two schemas in the exception are exactly the
> same.
> The same code with other input data (with fewer, both numerical and
> non-numerical column) succeeds.
> Any idea why this happens?
>
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