spark-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From rok <rokros...@gmail.com>
Subject ensuring RDD indices remain immutable
Date Mon, 01 Dec 2014 14:36:38 GMT
I have an RDD that serves as a feature look-up table downstream in my
analysis. I create it using the zipWithIndex() and because I suppose that
the elements of the RDD could end up in a different order if it is
regenerated at any point, I cache it to try and ensure that the (feature -->
index) mapping remains fixed. 

However, I'm having trouble verifying that this is actually robust -- can
someone comment whether using such a mapping should be stable or is there
another preferred method? zipWithUniqueID() isn't optimal since max ID
generated this way is always greater than the number of features so I'm
trying to avoid it. 






--
View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/ensuring-RDD-indices-remain-immutable-tp20094.html
Sent from the Apache Spark User List mailing list archive at Nabble.com.

---------------------------------------------------------------------
To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
For additional commands, e-mail: user-help@spark.apache.org


Mime
View raw message