mleap

问题 PMML, Mleap, PFA currently only support row based transformations. None of them support frame based transformations like aggregates or groupby or join. What is the recommended way to export a spark pipeline consisting of these operations. 回答1: I see 2 options wrt Mleap: 1) implement dataframe based transformers and the SQLTransformer -Mleap equivalent. This solution seems to be conceptually the best (since you can always encapsule such transformations in a pipeline element) but also alot of

问题 PMML, Mleap, PFA currently only support row based transformations. None of them support frame based transformations like aggregates or groupby or join. What is the recommended way to export a spark pipeline consisting of these operations. 回答1: I see 2 options wrt Mleap: 1) implement dataframe based transformers and the SQLTransformer -Mleap equivalent. This solution seems to be conceptually the best (since you can always encapsule such transformations in a pipeline element) but also alot of

问题 PMML, Mleap, PFA currently only support row based transformations. None of them support frame based transformations like aggregates or groupby or join. What is the recommended way to export a spark pipeline consisting of these operations. 回答1: I see 2 options wrt Mleap: 1) implement dataframe based transformers and the SQLTransformer -Mleap equivalent. This solution seems to be conceptually the best (since you can always encapsule such transformations in a pipeline element) but also alot of

问题 java.lang.AssertionError: assertion failed: This op only supports binary logistic regression I am trying to serialize a spark pipeline in mleap. I am using Tokenizer, HashingTF and LogisticRegression in my pipeline. When I am trying to serialize my pipeline I get the above error. Here is the code I am using to serialize the pipeline - val pipeline = Pipeline(pipelineConfig) val model = pipeline.fit(data) (for(bf <- managed(BundleFile("jar:file:/tmp/abc.model.twitter.zip"))) yield { model