I am using Spark's MultilayerPerceptronClassifier. This generates a column 'predicted' in 'predictions'. When I try to show it I get the error:
SparkException: Failed to execute user defined function($anonfun$1: (vector) => double) ...
Caused by: java.lang.IllegalArgumentException: requirement failed: A & B Dimension mismatch!
Other columns, for example, vector display OK. Part of predictions schema:
|-- vector: vector (nullable = true)
|-- prediction: double (nullable = true)
My code is:
//racist is boolean, needs to be string:
val train2 = train.withColumn("racist", 'racist.cast("String"))
val test2 = test.withColumn("racist", 'racist.cast("String"))
val indexer = new StringIndexer().setInputCol("racist").setOutputCol("indexracist")
val word2Vec = new Word2Vec().setInputCol("lemma").setOutputCol("vector") //.setVectorSize(3).setMinCount(0)
val layers = Array[Int](4,5, 2)
val mpc = new MultilayerPerceptronClassifier().setLayers(layers).setBlockSize(128).setSeed(1234L).setMaxIter(100).setFeaturesCol("vector").setLabelCol("indexracist")
val pipeline = new Pipeline().setStages(Array(indexer, word2Vec, mpc))
val model = pipeline.fit(train2)
val predictions = model.transform(test2)
predictions.select("prediction").show()
EDIT the proposed similar question's problem was
val layers = Array[Int](0, 0, 0, 0)
which is not the case here, nor is it the same error.
EDIT AGAIN: part0 of train and test are saved in PARQUET format here.