private static JavaRDD genDataset()

in cassandra-analytics-core-example/src/main/java/org/apache/cassandra/spark/example/SampleCassandraJob.java [234:269]
36 lines of code
6 McCabe index (conditional complexity)

    private static JavaRDD<Row> genDataset(JavaSparkContext sc, long records, Integer parallelism,
                                           boolean addTTLColumn, boolean addTimestampColumn)
    {
        long recordsPerPartition = records / parallelism;
        long remainder = records - (recordsPerPartition * parallelism);
        List<Integer> seq = IntStream.range(0, parallelism).boxed().collect(Collectors.toList());
        int ttl = 120; // data will not be queryable in two minutes
        long timeStamp = System.currentTimeMillis() * 1000;
        JavaRDD<Row> dataset = sc.parallelize(seq, parallelism).mapPartitionsWithIndex(
        (Function2<Integer, Iterator<Integer>, Iterator<Row>>) (index, integerIterator) -> {
            long firstRecordNumber = index * recordsPerPartition;
            long recordsToGenerate = index.equals(parallelism) ? remainder : recordsPerPartition;
            java.util.Iterator<Row> rows = LongStream.range(0, recordsToGenerate).mapToObj(offset -> {
                long recordNumber = firstRecordNumber + offset;
                String courseNameString = String.valueOf(recordNumber);
                Integer courseNameStringLen = courseNameString.length();
                Integer courseNameMultiplier = 1000 / courseNameStringLen;
                byte[] courseName = dupStringAsBytes(courseNameString, courseNameMultiplier);
                if (addTTLColumn && addTimestampColumn)
                {
                    return RowFactory.create(recordNumber, courseName, recordNumber, ttl, timeStamp);
                }
                if (addTTLColumn)
                {
                    return RowFactory.create(recordNumber, courseName, recordNumber, ttl);
                }
                if (addTimestampColumn)
                {
                    return RowFactory.create(recordNumber, courseName, recordNumber, timeStamp);
                }
                return RowFactory.create(recordNumber, courseName, recordNumber);
            }).iterator();
            return rows;
        }, false);
        return dataset;
    }