Counting occurences over String columns

I have say 10 String columns. These columns can contain the same or different values. I want to find the value(s) that occurs the most over these 10 columns. If there are multiple values with same occurence, return all of them.

I can do that with a rather complex workflow including Column Aggreagation, cell splitting and a Java Snippet. My question is if there is a node I don't know about that could easily achieve this?

It sounds like a good case for unpivot followed by a groupby.  Can you post an example workflow?


This would be for ranking passed on occurence.

See attachment. This works but look overly complicated.

I have a solution using unpivot into R snippet, but I there doesn't appear to be an elegant way to handle ties.  

After completely unpivoting the table, an R snippet with the following code will give you the most frequent entry for each row.  Unfortunately, "which.max" returns only the first entry in a tie. Alternatively, "" from the nnet package will return a random winner, but if you need all 3, I think your current method is best. 


myFun <- function(x){
    tbl <- table(x$ColumnValues)
    x$freq <- rep(names(tbl)[which.max(tbl)],nrow(x))

knime.out = ddply(,.(RowIDs),.fun=myFun)




Hi collegues, in particular @beginner_

I know it's an old thread but I have take a look to the example workflow, in particular the Java Snipped node in which you rank the occurrences.


int highestCount = -1;

for (String occurence : c_Uniqueconcatenatewithcount_SplitResultList) {
 	final Matcher matcher = pattern.matcher(occurence);
 	if (matcher.matches()) {
		final String compound =;
		final int count = Integer.parseInt(;
		if (count > highestCount) {		
			out_MostCommon = compound;
			highestCount = count;
		} else if(count == highestCount) {
			out_MostCommon += ", " + compound;

My question is:

and if I want to get as result the top 5 highest unique occurrences instead of the highest one? How the Java code should be structured in this example?

Thanks in advice.