Take a look at RDD.pipe().
You could also accomplish the same thing using RDD.mapPartitions, which
you pass a function that processes the iterator for each partition
rather than processing each element individually. This lets you only
start up as many processes as there are partitions, pipe the
Those pages include
instructions for running locally:
"Note that all of the sample programs take a
parameter specifying the cluster URL
to connect to. This can be a URL
for a distributed cluster,
or local to run locally with one thread, or local[N]
to run locally with N threads. You should st
Code in a transformation
(i.e. inside the function passed to RDD.map() or RDD.filter()) will run
on workers, not the driver. They will run in parallel. In Spark, the
driver actually doesn't do much -- it just builds up a description of
the computation to be performed and then sends it off to th
mputation transformations. May be this is
due to my ignorance of how Scala works, but when I see the code, I see
that the function is applied to the elements of RDD when I call distinct
- or is it not applied immediately? How does the returned RDD 'keep
track of the operation'?
You should probably be
asking the opposite question: why do you think it *should* be applied
immediately? Since the driver program hasn't requested any data back
(distinct generates a new RDD, it doesn't return any data), there's no
need to actually compute anything yet.
As the documentation d
You need to convert it to
the format you want yourself. The output you're seeing is just the
automatic conversion of your data by unicode().
-Ewen
Chengi Liu
February 26, 2014
at 9:43 AM
Hi,
How do we save data to hdfs using pyspark in "right" format.I
use:counts = cou
You must be parsing each
line of the file at some point anyway, so adding a step to filter out
the header should work fine. It'll get executed at the same time as your
parsing/conversion to ints, so there's no significant overhead aside
from the check itself.
For standalone programs, there's a
Or use RDD.filterWith to create whatever you need out of serializable
parts so you only run it once per partition.
Andrew Ash
February 24, 2014
at 7:17 PM
This is because
Joda's DateTimeFormatter is not serializable (doesn't implement the
empty Serializable interface) ht
