What is the difference between HashingTF and CountVectorizer in Spark?
As per the Spark 2.1.0 documentation, Both HashingTF and CountVectorizer can be used to generate the term frequency vectors. HashingTF HashingTF is a Transformer which takes sets of terms and converts those sets into fixed-length feature vectors. In text processing, a “set of terms” might be a bag of words. HashingTF utilizes the hashing trick. A raw feature is mapped into an index (term) by apply
How do I iterate RDD's in apache spark (scala)
You call various methods on the RDD that accept functions as parameters. // set up an example -- an RDD of arrays val sparkConf = new SparkConf().setMaster("local").setAppName("Example") val sc = new SparkContext(sparkConf) val testData = Array(Array(1,2,3), Array(4,5,6,7,8)) val testRDD = sc.parallelize(testData, 2) // Print the RDD of arrays. testRDD.collect().foreach(a => println(a.size)) // Us
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Applying a Window function to calculate differences in pySpark
