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) => if … Read more
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 solved python : reduce by key with if condition statement?
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
How to perform self join with same row of previous group(month) to bring in additional columns with different expressions in Pyspark solved How to perform self join with same row of previous group(month) to bring in additional columns with different expressions in Pyspark
replace null_df.show() with : for i,j in null_df.first().asDict().items(): print(i,j) solved How to get a list view of columns and % of nans/nulls in Pyspark?
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 solved How to create a dataframe from two others dataframe?
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() solved number of lines with number of words less than 5