I have seen a talk by Brian Clapper in NE-SCALA 2016 - RDDs, DataFrames and
Datasets @ Apache Spark - NE Scala 2016
At 15:00 there is a slide to show a comparison of aggregating 10 Million
integer pairs using RDD , DataFrame with different language bindings like
Scala , Python , R
As per
Hi ,
I would prefer Scala if you are starting afresh , this is considering both ease
of usage , features , performance and support.
You will find numerous examples & support with Scala which might not be true
for any other language.
I had personally developed the first version of my App using
You could check following link.
http://stackoverflow.com/questions/35154267/how-to-compute-cumulative-sum-using-spark
From: Jon Barksdale [mailto:jon.barksd...@gmail.com]
Sent: 09 August 2016 08:21
To: ayan guha
Cc: user
Subject: Re: Cumulative Sum function using Dataset API
I don't think that
in scala and it turned out much simpler to
develop in scala due to some of its powerful functions like lambda , map ,
filter etc… which were not available to me in Java 7.
Regards,
Santosh Akhilesh
From: Sonal Goyal [mailto:sonalgoy...@gmail.com]
Sent: 01 June 2016 00:56
To: Santoshakhilesh
Cc: Kumar
From: Kumar, Abhishek (US - Bengaluru) [mailto:abhishekkuma...@deloitte.com]
Sent: 30 May 2016 13:24
To: Santoshakhilesh; user@spark.apache.org
Cc: Golatkar, Jayesh (US - Bengaluru); Soni, Akhil Dharamprakash (US -
Bengaluru); Matta, Rishul (US - Bengaluru); Aich, Risha (US - Bengaluru);
Kumar
GraphX APis are available only in Scala. If you need to use GraphX you need to
switch to Scala.
From: Kumar, Abhishek (US - Bengaluru) [mailto:abhishekkuma...@deloitte.com]
Sent: 27 May 2016 19:59
To: user@spark.apache.org
Subject: GraphX Java API
Hi,
We are trying to consume the Java API for
Hi,
I have following scenario in my project;
1.I will continue to get a stream of data from a source
2.I need to calculate mean and variance for a key every minute
3.After minute is over I should restart fresh computing the values for new
minute
Example:
10:00:00 computation and
