Compare two maps and find differences using Groovy or Java

Question

I would like to find difference in two maps and create a new csv file with the difference (and put the difference between **) like below:

Map 1

  [
    [         


        

Answer 1

In the following I'm assuming that the list of maps is sorted appropriately so that the comparison is fair, and that both lists are of the same length:

First, create an Iterator to traverse both lists simultaneously:

@groovy.transform.TupleConstructor
class DualIterator implements Iterator<List> {
    Iterator iter1
    Iterator iter2

    boolean hasNext() {
        iter1.hasNext() && iter2.hasNext()
    }

    List next() {
        [iter1.next(), iter2.next()]
    }

    void remove() {
        throw new UnsupportedOperationException()
    }
}

Next, process the lists to get rows for the CSV file:

def rows = new DualIterator(list1.iterator(), list2.iterator())
    .findAll { it[0] != it[1] } // Grab the non-matching lines.
    .collect { // Mark the non-matching values.
        (m1, m2) = it
        m1.keySet().each { key ->
            if(m1[key] != m2[key]) {
                m1[key] = "*${m1[key]}*"
                m2[key] = "*${m2[key]}*"
            }          
        }

        [m1, m2]
    }.collect { // Merge the map values into a List of String arrays
        [it[0].values(), it[1].values()].flatten() as String[]
    }

Finally, write the header and rows out in CSV format. NOTE: I'm using a proper CSV; your example is actually invalid because the number of columns are inconsistent:

def writer = new CSVWriter(new FileWriter('blah.csv'))
writer.writeNext(['name1', 'cuInfo1', 'service1', 'startDate1', 'appId1', 'name2', 'cuInfo2', 'service2', 'startDate2', 'appId2'] as String[])
writer.writeAll(rows)
writer.close()

The output looks like this:

"name1","cuInfo1","service1","startDate1","appId1","name2","cuInfo2","service2","startDate2","appId2"
"Apple","T12","3","*14-02-16 10:00*","*G12351*","Apple","T12","3","*14-01-16 13:22*","*G12355*"
"Apple","T13","3","*14-01-16 13:00*","*G12352*","Apple","T13","3","*12-02-16 13:00*","*G12356*"
"Google","T14","9","10-01-16 11:20","*G12301*","Google","T14","9","10-01-16 11:20","*G12300*"