Spark Joins SparkSQL and Spark DataFrames join(): inner outer left outer right outer semijoin Spark PairRDD: x.join(y): returns key-value pairs [(k,(v₁,v₂).....]where: k is a common key between x and y (v₁,v₂) are values in x and y leftOuterJoin() rightOuterJoin() fullOuterJoin() x = sc.parallelize([('a',2), ('b',3)]) y = sc.parallelize([('a',3), ('a',2), ('a',5)]) x.join(y).collect() [(‘a’, (2, 3)), (‘a’, (2,…

Apache Spark RDD: pyspark.SparkContext: sc.parallelize(data, num) sc.textFile(file, num) dir(sc) from pyspark import SparkContext sc = SparkContext() # xrange() is more efficient than range() because it’s generator data = range(1,11) rdd = sc.parallelize(data,2) type(sc) pyspark.context.SparkContext sc.version ’1.4.0′ type(rdd) pyspark.rdd.PipelinedRDD print(‘The id of rdd is {0}’.format(rdd.id())) The id of rdd is 1 rdd.setName(‘My first RDD’) My first…

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