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User16826992666
by • Valued Contributor
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Resolved! What's the difference between SparkML and Spark MLlib?

I have heard people talk about SparkML but when reading documentation it talks about MLlib. I don't understand the difference, could anyone help me understand this?

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sean_owen
Databricks Employee
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They're not really different. Before DataFrames in Spark, older implementations of ML algorithms build on the RDD API. This is generally called "Spark MLlib". After DataFrames, some newer implementations were added as wrappers on top of the old ones ...

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Joseph_B
by • Databricks Employee
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When doing hyperparameter tuning with Hyperopt, when should I use SparkTrials? Does it work with both single-machine ML (like sklearn) and distributed ML (like Apache Spark ML)?

I want to know how to use Hyperopt in different situations:Tuning a single-machine algorithm from scikit-learn or single-node TensorFlowTuning a distributed algorithm from Spark ML or distributed TensorFlow / Horovod

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Joseph_B
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The right question to ask is indeed: Is the algorithm you want to tune single-machine or distributed?If it's a single-machine algorithm like any from scikit-learn, then you can use SparkTrials with Hyperopt to distribute hyperparameter tuning.If it's...

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z160896
by • New Contributor II
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why spark very slow with large number of dataframe columns

scala Spark App: I have a dataset of 130x14000. I read from a parquet file with SparkSession. Then used for Spark ML Random Forest model (using pipeline). It takes 7 hours to complete! for reading the parquet file takes about 1 minute. If I implemen...

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EliasHaydar
New Contributor II
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I've already answered a similar question on StackOverflow so I'll repeat what a I said there. The following may not solve your problem completely but it should give you some pointer to start. The first problem that you are facing is the disproportio...

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