CassandraJavaRDD<CassandraRow> cassandraRowsRDD = CassandraJavaUtil.javaFunctions(sc).cassandraTable(KEYSPACE, TABLE).select("date", "type");

JavaPairRDD<String, Integer> batchRDD = cassandraRowsRDD.mapToPair(new PairFunction<CassandraRow, String, Integer>() {
    @Override
    public Tuple2<String, Integer> call(CassandraRow row) {
        return new Tuple2<String, Integer>(row.getString("date"), 1);
    }
}).reduceByKey(new Function2<Integer, Integer, Integer>() {
    @Override
    public Integer call(Integer count1, Integer count2) {
        return count1 + count2;
    }
});

save(batchRDD) // Assume this saves the batch RDD somewhere

...

// Assume we read a chunk of logs from the Kafka stream every x seconds.
JavaPairReceiverInputDStream<String, String> kafkaStream =  KafkaUtils.createStream(...);
JavaPairDStream<String, Integer> streamRDD = kafkaStream.flatMapToPair(new PairFunction<Tuple2<String, String>, String, Integer>() {
    @Override
    public Iterator<Tuple2<String, Integer> call(Tuple2<String, String> data) {
        String jsonString = data._2;
        JSON jsonObj = JSON.parse(jsonString);
        Date eventDate = ... // get date from json object
        // Assume startTime is broadcast variable that is set to the time when the job started.
        if (eventDate.after(startTime.value())) {
            ArrayList<Tuple2<Integer>> pairs = new ArrayList<Tuple2<String, Integer>>();
            pairs.add(new Tuple2<String, Integer>(jsonObj.get("date"), 1));
            return pairs;
        } else {
            return new ArrayList<Tuple2<String, Integer>>(0); // Return empty list when we ignore some logs
        }
    }
}).reduceByKey(new Function2<Integer, Integer, Integer>() {
    @Override
    public Integer call(Integer count1, Integer count2) {
        return count1 + count2;
    }
}).updateStateByKey(new Function2<List<Integer>, Optional<List<Integer>>, Optional<Integer>>() {
    @Override
    public Optional<Integer> call(List<Integer> counts, Optional<Integer> state) {
        Integer previousValue = state.or(0l);
        Integer currentValue = ... // Sum of counts
        return Optional.of(previousValue + currentValue);
    }
});
save(streamRDD); // Assume this saves the stream RDD somewhere

sc.start();
sc.awaitTermination();

("2014-10-15", 1000000)
("2014-10-16", 2000000)

|------------------------|-------------|--------------|--------->
tBatchStart             tStreamStart   streamBatch1  streamBatch2

("2014-10-19", 1000)

("2014-10-19", 2001000)

("2014-10-19", 4000)

("2014-10-19", 2005000)