CCDAK Free Questions Good Demo For Confluent CCDAK Exam Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well 1. A producer is sending messages with null key to a topic with 6 partitions using the DefaultPartitioner. Where will the messages be stored? A. Partition 5 B. Any of the topic partitions C. The partition for the null key D. Partition 0 Answer: A Explanation: Message with no keys will be stored with round-robin strategy among partitions. 2. Suppose you have 6 brokers and you decide to create a topic with 10 partitions and a replication factor of 3. The brokers 0 and 1 are on rack A, the brokers 2 and 3 are on rack B, and the brokers 4 and 5 are on rack C. If the leader for partition 0 is on broker 4, and the first replica is on broker 2, which broker can host the last replica? (select two) A. 6 B. 1 C. 2 D. 5 E. 0 F. 3 Answer: B,E Explanation: When you create a new topic, partitions replicas are spreads across racks to maintain availability. Hence, the Rack A, which currently does not hold the topic partition, will be selected for the last replica 3. Which of the following is not an Avro primitive type? A. string B. long C. int D. date E. null Answer: D Explanation: date is a logical type 4. There are 3 brokers in the cluster. You want to create a topic with a single partition that is resilient to one broker failure and one broker maintenance . What is the replication factor will you specify while creating the topic? Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well A. 6 B. 3 C. 2 D. 1 Answer: B Explanation: 1 is not possible as it doesn't provide resilience to failure, 2 is not enough as if we take a broker down for maintenance, we cannot tolerate a broker failure, and 6 is impossible as we only have 3 brokers (RF cannot be greater than the number of brokers). Here the correct answer is 3 5. StreamsBuilder builder = new StreamsBuilder(); KStream<String, String> textLines = builder.stream("word-count-input"); KTable<String, Long> wordCounts = textLines .mapValues(textLine -> textLine.toLowerCase()) .flatMapValues(textLine -> Arrays.asList(textLine.split("\W+"))) .selectKey((key, word) -> word) .groupByKey() .count(Materialized.as("Counts")); wordCounts.toStream().to("word-count-output", Produced.with(Serdes.String(), Serdes.Long())); builder.build(); What is an adequate topic configuration for the topic word-count-output? A. max.message.bytes=10000000 B. cleanup.policy=delete C. compression.type=lz4 D. cleanup.policy=compact Answer: D Explanation: Result is aggregated into a table with key as the unique word and value its frequency. We have to enable log compaction for this topic to align the topic's cleanup policy with KTable semantics. 6. You are using JDBC source connector to copy data from a table to Kafka topic. There is one connector created with max.tasks equal to 2 deployed on a cluster of 3 workers . How many tasks are launched? A. 3 B. 2 C. 1 D. 6 Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well Answer: C Explanation: JDBC connector allows one task per table. 7. You are using JDBC source connector to copy data from 2 tables to two Kafka topics. There is one connector created with max.tasks equal to 2 deployed on a cluster of 3 workers . How many tasks are launched? A. 6 B. 1 C. 2 D. 3 Answer: C Explanation: we have two tables, so the max number of tasks is 2 8. To import data from external databases, I should use A. Confluent REST Proxy B. Kafka Connect Sink C. Kafka Streams D. Kafka Connect Source Answer: D Explanation: Kafka Connect Sink is used to export data from Kafka to external databases and Kafka Connect Source is used to import from external databases into Kafka. 9. What is a generic unique id that I can use for messages I receive from a consumer? A. topic + partition + timestamp B. topic + partition + offset C. topic + timestamp Answer: B Explanation: (Topic,Partition,Offset) uniquely identifies a message in Kafka 10. Which of the following setting increases the chance of batching for a Kafka Producer? A. Increase batch.size B. Increase message.max.bytes Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well C. Increase the number of producer threads D. Increase linger.ms Answer: D Explanation: linger.ms forces the producer to wait to send messages, hence increasing the chance of creating batches 11. A client connects to a broker in the cluster and sends a fetch request for a partition in a topic. It gets an exception Not Leader For Partition Exception in the response . How does client handle this situation? A. Get the Broker id from Zookeeper that is hosting the leader replica and send request to it B. Send metadata request to the same broker for the topic and select the broker hosting the leader replica C. Send metadata request to Zookeeper for the topic and select the broker hosting the leader replica D. Send fetch request to each Broker in the cluster Answer: B Explanation: In case the consumer has the wrong leader of a partition, it will issue a metadata request. The Metadata request can be handled by any node, so clients know afterwards which broker are the designated leader for the topic partitions. Produce and consume requests can only be sent to the node hosting partition leader. 12. You are running a Kafka Streams application in a Docker container managed by Kubernetes, and upon application restart, it takes a long time for the docker container to replicate the state and get back to processing the data . How can you improve dramatically the application restart? A. Mount a persistent volume for your RocksDB B. Increase the number of partitions in your inputs topic C. Reduce the Streams caching property D. Increase the number of Streams threads Answer: A Explanation: Although any Kafka Streams application is stateless as the state is stored in Kafka, it can take a while and lots of resources to recover the state from Kafka. In order to speed up recovery, it is advised to store the Kafka Streams state on a persistent volume, so that only the missing part of the state needs to be recovered. Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well 13. To enhance compression, I can increase the chances of batching by using A. acks=all B. linger.ms=20 C. batch.size=65536 D. max.message.size=10MB Answer: B Explanation: linger.ms forces the producer to wait before sending messages, hence increasing the chance of creating batches that can be heavily compressed. 14. In Avro, removing or adding a field that has a default is a __ schema evolution A. full B. backward C. breaking D. forward Answer: A Explanation: Clients with new schema will be able to read records saved with old schema and clients with old schema will be able to read records saved with new schema. 15. Compaction is enabled for a topic in Kafka by setting log.cleanup.policy=compact What is true about log compaction? A. After cleanup, only one message per key is retained with the first value B. Each message stored in the topic is compressed C. Kafka automatically de-duplicates incoming messages based on key hashes D. After cleanup, only one message per key is retained with the latest value Compaction changes the offset of messages Answer: D Explanation: Log compaction retains at least the last known value for each record key for a single topic partition. All compacted log offsets remain valid, even if record at offset has been compacted away as a consumer will get the next highest offset. 16. is KSQL ANSI SQL compliant? A. Yes B. No Answer: B Valid Confluent CCDAK Exam Questions [2022] Prepare CCDAK Exam Well Explanation: KSQL is not ANSI SQL compliant, for now there are no defined standards on streaming SQL languages 17. What is true about partitions? (select two) A. A broker can have a partition and its replica on its disk B. You cannot have more partitions than the number of brokers in your cluster C. A broker can have different partitions numbers for the same topic on its disk D. Only out of sync replicas are replicas, the remaining partitions that are in sync are also leader E. A partition has one replica that is a leader, while the other replicas are followers Answer: C,E Explanation: Only one of the replicas is elected as partition leader. And a broker can definitely hold many partitions from the same topic on its disk, try creating a topic with 12 partitions on one broker! 18. What isn't a feature of the Confluent schema registry? A. Store avro data B. Enforce compatibility rules C. Store schemas Answer: A Explanation: Data is stored on brokers. 19. If I supply the setting compression.type=snappy to my producer, what will happen? (select two) A. The Kafka brokers have to de-compress the data B. The Kafka brokers have to compress the data C. The Consumers have to de-compress the data D. The Consumers have to compress the data E. The Producers have to compress the data Answer: C Explanation: Kafka transfers data with zero copy and no transformation. Any transformation (including compression) is the responsibility of clients. 20.1.Where are the dynamic configurations for a topic stored? A. In Zookeeper B. In an internal Kafka topic __topic_configuratins C. In server.properties D. On the Kafka broker file system Answer: A Explanation: Dynamic topic configurations are maintained in Zookeeper. 21. A topic "sales" is being produced to in the Americas region. You are mirroring this topic using Mirror Maker to the European region. From there, you are only reading the topic for analytics purposes . What kind of mirroring is this? A. Passive-Passive B. Active-Active C. Active-Passive Answer: C Explanation: This is active-passing as the replicated topic is used for read-only purposes only Go To CCDAK Exam Questions Full Version