Commit Offsets to Kafka on Spark Executors

Question

I am getting events from Kafka, enriching/filtering/transforming them on Spark and then storing them in ES. I am committing back the offsets to Kafka

I have two questions/problems:

(1) My current Spark job is VERY slow

I have 50 partitions for a topic and 20 executors. Each executor has 2 cores and 4g of memory each. My driver has 8g of memory. I am consuming 1000 events/partition/second and my batch interval is 10 seconds. This means, I am consuming 500000 events in 10 seconds

My ES cluster is as follows:

20 shards / index

3 master instances c5.xlarge.elasticsearch

12 instances m4.xlarge.elasticsearch

disk / node = 1024 GB so 12 TB in total

And I am getting huge scheduling and processing delays

(2) How can I commit offsets on executors?

Currently, I enrich/transform/filter my events on executors and then send everything to ES using BulkRequest . It's a synchronous process. If I get positive feedback, I send the offset list to driver. If not, I send back an empty list. On the driver, I commit offsets to Kafka. I believe, there should be a way, where I can commit offsets on executors but I don't know how to pass kafka Stream to executors:

((CanCommitOffsets) kafkaStream.inputDStream()).commitAsync(offsetRanges, this::onComplete);

This is the code for committing offsets to Kafka which requires Kafka Stream

Here is my overall code:

 kafkaStream.foreachRDD( // kafka topic
                rdd -> { // runs on driver
                    rdd.cache();
                    String batchIdentifier =
                            Long.toHexString(Double.doubleToLongBits(Math.random()));

                    LOGGER.info("@@ [" + batchIdentifier + "] Starting batch ...");

                    Instant batchStart = Instant.now();

                    List<OffsetRange> offsetsToCommit =
                            rdd.mapPartitionsWithIndex( // kafka partition
                                    (index, eventsIterator) -> { // runs on worker

                                        OffsetRange[] offsetRanges = ((HasOffsetRanges) rdd.rdd()).offsetRanges();

                                        LOGGER.info(
                                                "@@ Consuming " + offsetRanges[index].count() + " events" + " partition: " + index
                                        );

                                        if (!eventsIterator.hasNext()) {
                                            return Collections.emptyIterator();
                                        }

                                        // get single ES documents
                                        List<SingleEventBaseDocument> eventList = getSingleEventBaseDocuments(eventsIterator);

                                        // build request wrappers
                                        List<InsertRequestWrapper> requestWrapperList = getRequestsToInsert(eventList, offsetRanges[index]);

                                        LOGGER.info(
                                                "@@ Processed " + offsetRanges[index].count() + " events" + " partition: " + index + " list size: " + eventList.size()
                                        );

                                        BulkResponse bulkItemResponses = elasticSearchRepository.addElasticSearchDocumentsSync(requestWrapperList);

                                        if (!bulkItemResponses.hasFailures()) {
                                            return Arrays.asList(offsetRanges).iterator();
                                        }

                                        elasticSearchRepository.close();
                                        return Collections.emptyIterator();
                                    },
                                    true
                            ).collect();

                    LOGGER.info(
                            "@@ [" + batchIdentifier + "] Collected all offsets in " + (Instant.now().toEpochMilli() - batchStart.toEpochMilli()) + "ms"
                    );

                    OffsetRange[] offsets = new OffsetRange[offsetsToCommit.size()];

                    for (int i = 0; i < offsets.length ; i++) {
                        offsets[i] = offsetsToCommit.get(i);
                    }

                    try {
                        offsetManagementMapper.commit(offsets);
                    } catch (Exception e) {
                        // ignore
                    }

                    LOGGER.info(
                            "@@ [" + batchIdentifier + "] Finished batch of " + offsetsToCommit.size() + " messages " +
                                    "in " + (Instant.now().toEpochMilli() - batchStart.toEpochMilli()) + "ms"
                    );
                    rdd.unpersist();
                });

Answer 1

You can move the offset logic above the rdd loop... I am using below template for better offset handling and performance

JavaInputDStream<ConsumerRecord<String, String>> kafkaStream = KafkaUtils.createDirectStream(jssc,
                LocationStrategies.PreferConsistent(),
                ConsumerStrategies.<String, String>Subscribe(topics, kafkaParams));



        kafkaStream.foreachRDD( kafkaStreamRDD -> {
            //fetch kafka offsets for manually commiting it later
            OffsetRange[] offsetRanges = ((HasOffsetRanges) kafkaStreamRDD.rdd()).offsetRanges();

            //filter unwanted data
            kafkaStreamRDD.filter(
                    new Function<ConsumerRecord<String, String>, Boolean>() {
                @Override
                public Boolean call(ConsumerRecord<String, String> kafkaRecord) throws Exception {
                    if(kafkaRecord!=null) {
                        if(!StringUtils.isAnyBlank(kafkaRecord.key() , kafkaRecord.value())) {
                            return Boolean.TRUE;
                        }
                    }
                    return Boolean.FALSE;
                }
            }).foreachPartition( kafkaRecords -> {

                // init connections here

                while(kafkaRecords.hasNext()) {
                    ConsumerRecord<String, String> kafkaConsumerRecord = kafkaRecords.next();
                    // work here
                }

            });
            //commit offsets
            ((CanCommitOffsets) kafkaStream.inputDStream()).commitAsync(offsetRanges);
        });