[ad_1] You can foldLeft over the input string, with a state of List[(Char, Int)]. Note that if you use Map[Char, Int], all occurrences of each character would be added up, weather they’re beside each other or not. s.foldLeft(List.empty[(Char, Int)]) { case (Nil, newChar) => (newChar, 1) :: Nil case (list@(headChar, headCount) :: tail, newChar) => … Read more
[ad_1] IIUC, you need to change the key before the reduce, and then map your values back in the desired format. You should be able to do the following: new_rdd = rdd.map(lambda row: ((row[0], row[1][0]), row[1][1]))\ .reduceByKey(sum). .map(lambda row: (row[0][0], (row[0][1], row[1]))) 0 [ad_2] solved python : reduce by key with if condition statement?
[ad_1] Perhaps this is helpful – Load the test data df2.show(false) df2.printSchema() /** * +—–+—–+ * |class|score| * +—–+—–+ * |A |null | * |A |46 | * |A |null | * |A |null | * |A |35 | * |A |null | * |A |null | * |A |null | * |A |46 | … Read more
[ad_1] How to perform self join with same row of previous group(month) to bring in additional columns with different expressions in Pyspark [ad_2] solved How to perform self join with same row of previous group(month) to bring in additional columns with different expressions in Pyspark
[ad_1] replace null_df.show() with : for i,j in null_df.first().asDict().items(): print(i,j) [ad_2] solved How to get a list view of columns and % of nans/nulls in Pyspark?
[ad_1] If this two column are same data type , you can just union a = predictons_lr.select(‘prediction’) b = predictions_nb.select(‘prediction’) new_df = a.union(b) 4 [ad_2] solved How to create a dataframe from two others dataframe?
[ad_1] I solved it. The problem was that I was trying to split a list. This is the new line rdd=rdd.filter(lambda line: len(line[0].split(” “))<5).collect() [ad_2] solved number of lines with number of words less than 5