Hi all, I'm writing here after some intensive usage on pyspark and SparkSQL. I would like to use a well known function in the R world: coxph() from the survival package. >From what I understood, I can't parallelize a function like coxph() because it isn't provided with the SparkR package. In other words, I should implement a SparkR compatible algorithm instead of using coxph(). I have no chance to make coxph() parallelizable, right? More generally, I think this is true for any non-spark function which only accept data.frame format as the data input.
Do you plan to implement the coxph() counterpart in Spark? The most useful version of this model is the Cox Regression Model for Time-Dependent Covariates, which is missing from ANY ML framework as far as I know. Thank you Pietro -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-R-guidelines-for-non-spark-functions-and-coxph-Cox-Regression-for-Time-Dependent-Covariates-tp28077.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
