How to join two RDDs with mutually exclusive keys
Say I have two RDDs with the following values x = [(1, 3), (2, 4)] and y = [(3, 5), (4, 7)] and I want to have z = [(1, 3), (2, 4), (3, 5), (4, 7)] How can I achieve this. I know you can use outerJoin followed by map to achieve this, but is there a more direct way for this.
Is there a way to create key based on counts in Spark
As it is difficult to explain this, I would show what I want. Lets us say, I have an RDD A with the following value A = [word1, word2, word3] I want to have an RDD with the following value B = [(1, word1), (2, word2), (3, word3)] That is, it gives a unique number to each entry as a key value. Can we do such thing with Python or Scala?
How can I apply such an inner join in Spark Scala/Python
So let us say I have RDDs A and B with the following values. A = [ (1, 2), (2, 4), (3, 6) ] B = [ (1, 3), (2, 5), (3, 6), (4, 5), (5, 6) ] I want to apply an inner join, such that I get the following as a result. C = [ (1, (2, 3)), (2, (4, 5)), (3, (6,6)) ] That is, those keys which are not present in A should disappear after the left inner join. How can I achieve that? I can see outerJoin functions but no innerJoin functions in the Spark RDD class.
Which function in spark is used to combine two RDDs by keys
Let us say I have the following two RDDs, with the following key-pair values. rdd1 = [ (key1, [value1, value2]), (key2, [value3, value4]) ] and rdd2 = [ (key1, [value5, value6]), (key2, [value7]) ] Now, I want to join them by key values, so for example I want to return the following ret = [ (key1, [value1, value2, value5, value6]), (key2, [value3, value4, value7]) ] How I can I do this, in spark using python or scala? One way is to use join, but join would create a tuple inside the tuple. But I want to only have one tuple per key value pair.
How to change the default limiter for textFile function
I am a newbie to spark, and I program in Python. I use textFile function to make an RDD from a file. I notice that the default limiter is newline. However I want to change this default limiter to something else. After searching the web, I came to know about textinputformat.record.delimiter property, but doesn't seem to have any effect, when I use it with SparkConf. So my question is, how do I change the default limiter in python?
Does spark works on multicore systems?
I am a Spark newbie and I use python (pyspark). I am trying to run a program on a 64 core system, but no matter what I do, it always uses 1 core. It doesn't matter if I run it using spark-submit --master local[64] run.sh or I call x.repartition(64) in my code with an RDD, the spark program always uses one core. Has anyone experience of running spark programs on multicore processors with success? Can someone provide me a very simple example that does properly run on all cores of a multicore system?
