Re: Does Random Forest in spark ML supports multi label classification in scala

Yes, see https://dzone.com/articles/predictive-analytics-with-spark-ml Although the example uses two labels, the same approach supports multiple labels. Sent from my iPad > On Nov 7, 2017, at 6:30 AM, HARSH TAKKAR wrote: > > Hi > > Does Random Forest in spark Ml

Re: spark-avro aliases incompatible

In the doc you refer: // The Avro records get converted to Spark types, filtered, and// then written back out as Avro recordsval df = spark.read.avro("/tmp/episodes.avro")df.filter("doctor > 5").write.avro("/tmp/output") Alternatively you can specify the format to use instead: [image: Copy to

Stopping a Spark Streaming Context gracefully

Hello. I am running Spark 2.1, Scala 2.11. We're running several Spark streaming jobs. In some cases we restart these jobs on an occasional basis. We have code that looks like the following: logger.info("Starting the streaming context!") ssc.start() logger.info("Waiting for termination!")

Spark REST API

Is there a way to flush the API? I execute http://localhost:18080/api/v1/applications?status=runningning In the results I will get a list of applications but not all are still running. This is causing an issue with monitoring what is actually running. To compound the problem these are

How to branch a Stream / have multiple Sinks / do multiple Queries on one Stream

Hi, I’m obviously new to Spark Structured Streaming, and I want to 1.) Open one (a single) Connection to a Mqtt broker / topic spewing JSON Objects 2.) Transform JSON to Wide Table 3.) Do several different queries on wide Table What I do: val lines = session.readStream

Does Random Forest in spark ML supports multi label classification in scala

Hi Does Random Forest in spark Ml supports multi label classification in scala ? I found out, sklearn provides sklearn.ensemble.RandomForestClassifier in python, do we have the similar functionality in scala ?

Re: Programmatically get status of job (WAITING/RUNNING)

Hello Behroz, you can use a SparkListener to get updates from the underlying process (c.f. https://spark.apache.org/docs/2.2.0/api/java/org/apache/spark/scheduler/SparkListener.html ) You need first to create your own SparkAppListener class that extends it: -

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Re: Programmatically get status of job (WAITING/RUNNING)

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