Spark Machine Learning pipeline works fine in Spark 1 6 but it gives error when executed on Spark 2 x

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I have written a code in Spark1.6 which was working fine. However when I converted it to Saprk 2.0. I am getting an error as following:

 <console>:56: error: type mismatch;
found   : Array[org.apache.spark.ml.feature.QuantileDiscretizer]
required: Array[org.apache.spark.ml.PipelineStage with org.apache.spark.ml.para                                                                                                                         m.shared.HasOutputCol with org.apache.spark.ml.util.DefaultParamsWritable{def co                                                                                                                       py(extra: org.apache.spark.ml.param.ParamMap): org.apache.spark.ml.PipelineStage                                                                                                                      with org.apache.spark.ml.param.shared.HasOutputCol with org.apache.spark.ml.uti                                                                                                                     l.DefaultParamsWritable{def copy(extra: org.apache.spark.ml.param.ParamMap): org                                                                                                                     .apache.spark.ml.PipelineStage with org.apache.spark.ml.param.shared.HasOutputCo                                                                                                                     l with org.apache.spark.ml.util.DefaultParamsWritable}}]
Note: org.apache.spark.ml.feature.QuantileDiscretizer <: org.apache.spark.ml.Pip                                                                                                                     elineStage with org.apache.spark.ml.param.shared.HasOutputCol with org.apache.sp                                                                                                                     ark.ml.util.DefaultParamsWritable{def copy(extra: org.apache.spark.ml.param.Para                                                                                                                     mMap): org.apache.spark.ml.PipelineStage with org.apache.spark.ml.param.shared.H                                                                                                                     asOutputCol with org.apache.spark.ml.util.DefaultParamsWritable{def copy(extra:                                                                                                                      org.apache.spark.ml.param.ParamMap): org.apache.spark.ml.PipelineStage with org.                                                                                                                     apache.spark.ml.param.shared.HasOutputCol with org.apache.spark.ml.util.DefaultP                                                                                                                     aramsWritable}}, but class Array is invariant in type T.   
 You may wish to investigate a wildcard type such as `_ <: org.apache.spark.ml.Pi                                                                                                                     pelineStage with org.apache.spark.ml.param.shared.HasOutputCol with org.apache.s                                                                                                                     park.ml.util.DefaultParamsWritable{def copy(extra: org.apache.spark.ml.param.Par                                                                                                                     amMap): org.apache.spark.ml.PipelineStage with org.apache.spark.ml.param.shared.                                                                                                                     HasOutputCol with org.apache.spark.ml.util.DefaultParamsWritable{def copy(extra:                                                                                                                      org.apache.spark.ml.param.ParamMap): org.apache.spark.ml.PipelineStage with org                                                                                                                     .apache.spark.ml.param.shared.HasOutputCol with org.apache.spark.ml.util.Default                                                                                                                     ParamsWritable}}`. (SLS 3.2.10)
May 31, 2018 in Apache Spark by hack236
 • 1,540 views

1 answer to this question.

0 votes

You need to change the following:

val pipeline = new Pipeline().setStages(discretizers ++ Array(assembler, selector))

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answered May 31, 2018 by Shubham
 • 13,490 points

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