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Confluent CCDAK認定は、包括的な知識、実践的な経験、およびKafkaアプリケーションを設計、開発、およびテストするために必要な実証済みのスキルを提供することにより、Kafkaベースのシステムを構築および管理する候補者の能力を検証します。認定試験は、プロデューサーおよびコンシューマーAPI、Kafka Connect、Kafka Streams、Avro、およびスキーマ管理を含むKafkaエコシステムコンポーネントの構成、展開、および管理方法に精通していることを認めます。
質問 # 65
If I supply the setting compression.type=snappy to my producer, what will happen? (select two)
- A. The Consumers have to de-compress the data
- B. The Kafka brokers have to compress the data
- C. The Producers have to compress the data
- D. The Consumers have to compress the data
- E. The Kafka brokers have to de-compress the data
正解：A
解説：
Kafka transfers data with zero copy and no transformation. Any transformation (including compression) is the responsibility of clients.
質問 # 66
Which of the following statements are true regarding the number of partitions of a topic?
- A. We can remove partitions in a topic by removing a broker
- B. The number of partitions in a topic cannot be altered
- C. We can add partitions in a topic by adding a broker to the cluster
- D. We can add partitions in a topic using the kafka-topics.sh command
- E. We can remove partitions in a topic using the kafka-topics.sh command
正解：D
解説：
We can only add partitions to an existing topic, and it must be done using the kafka-topics.sh command
質問 # 67
Producing with a key allows to...
- A. Influence partitioning of the producer messages
- B. Allow a Kafka Consumer to subscribe to a (topic,key) pair and only receive that data
- C. Add more information to my message
- D. Ensure per-record level security
正解：A
解説：
Keys are necessary if you require strong ordering or grouping for messages that share the same key. If you require that messages with the same key are always seen in the correct order, attaching a key to messages will ensure messages with the same key always go to the same partition in a topic. Kafka guarantees order within a partition, but not across partitions in a topic, so alternatively not providing a key - which will result in round-robin distribution across partitions - will not maintain such order.
質問 # 68
A consumer wants to read messages from partitions 0 and 1 of a topic topic1. Code snippet is shown below.
consumer.subscribe(Arrays.asList("topic1"));
List<TopicPartition> pc = new ArrayList<>();
pc.add(new PartitionTopic("topic1", 0));
pc.add(new PartitionTopic("topic1", 1));
consumer.assign(pc);
- A. Throws IllegalStateException
- B. This works fine. subscribe() will subscribe to the topic and assign() will assign partitions to the consumer.
正解：A
解説：
subscribe() and assign() cannot be called by the same consumer, subscribe() is used to leverage the consumer group mechanism, while assign() is used to manually control partition assignment and reads assignment
質問 # 69
Which of the following Kafka Streams operators are stateful? (select all that apply)
- A. count
- B. joining
- C. aggregate
- D. flatmap
- E. reduce
- F. peek
正解：A、B、C、E
解説：
Seehttps://kafka.apache.org/20/documentation/streams/developer-guide/dsl-api.html#stateful-transformations
質問 # 70
What's a Kafka partition made of?
- A. One file and two indexes
- B. One file and two indexes per segment
- C. One file
- D. One file and one index
正解：B
解説：
Kafka partitions are made of segments (usually each segment is 1GB), and each segment has two corresponding indexes (offset index and time index)
質問 # 71
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?
- A. Message order not preserved
- B. Less resilient
- C. At least once delivery is not guaranteed
- D. Reduce throughput
正解：A
解説：
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.
idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira
/browse/KAFKA-5494
質問 # 72
Which function does ZooKeeper offer in Kafka?
- A. Partition assignment
- B. Controller re-election
- C. Consumer group rebalancing
- D. Authentication
正解：B
質問 # 73
ksqIDB Lambda functions must be used inside what type of designated functions?
- A. Deployment
- B. Stafcc
- C. Invocation
- D. Application
正解：B
質問 # 74
You use Kafka Connect with the JDBC source connector to extract data from a large database and push it into Kafka.
The database contains tens of tables, and the current connector is unable to process the data fast enough.
You add more Kafka Connect workers, but throughput doesn't improve.
What should you do next?
- A. Increase the number of Kafka partitions for the topics.
- B. Increase the value of the connector's property tasks.max.
- C. Modify the database schemas to enable horizontal sharding.
- D. Add more Kafka brokers to the cluster.
正解：B
解説：
Increasingtasks.maxallows the connector to createmultiple tasks, each responsible for processing different tables or table partitions. If onlyone taskis used,adding more workers has no effect.
FromKafka Connect JDBC Connector Docs:
"Use tasks.max to configure how many tasks are created for the connector. Each task can process a subset of the data."
* A and C help only if the bottleneck is in Kafka, not Connect.
* D is a large architectural change, not the first step.
Reference:Kafka Connect JDBC Connector Configuration
質問 # 75
Once sent to a topic, a message can be modified
- A. No
- B. Yes
正解：A
解説：
Kafka logs are append-only and the data is immutable
質問 # 76
You create a producer that writes messages about bank account transactions from tens of thousands of different customers into a topic.
* Your consumers must process these messages with low latency and minimize consumer lag
* Processing takes ~6x longer than producing
* Transactions for each bank account must be processedin orderWhich strategy should you use?
- A. Use a combination of the bank account number and the transaction timestamp as the message key.
- B. Use a unique identifier such as a universally unique identifier (UUID) as the message key.
- C. Use the bank account number found in the message as the message key.
- D. Use the timestamp of the message's arrival as its key.
正解：C
解説：
To maintainmessage ordering per bank account, themessage key must be the account number. Kafka guaranteesordering per partition, and the partition is selected based on thehash of the key.
FromKafka Producer Docs:
"All records with the same key will be sent to the same partition, and Kafka preserves the order of records in a partition." Using account number ensures:
* All messages for the same account go to the same partition
* Order is maintained
* Workload is evenly distributed if account keys are varied
Other options break ordering or introduce unnecessary randomness.
Reference:Kafka Producer Concepts > Partitions and Keys
質問 # 77
You have a topic t1 in a Kafka cluster. A producer running on host A can successfully write messages to t1.
Then, you move that producer code to run on host B, but it fails writing messages to t1.
What is a likely reason for that failure?
- A. Another producer started writing to t1.
- B. The producer is connecting to a different broker in the same cluster.
- C. Topic T1 no longer exists in the same environment as host B.
- D. Kafka ACLs are not configured to allow host B's IP address.
正解：D
質問 # 78
Your Kafka cluster has five brokers. The topic t1 on the cluster has:
* Two partitions
* Replication factor = 4
* min.insync.replicas = 3You need strong durability guarantees for messages written to topic t1.You configure a producer acks=all and all the replicas for t1 are in-sync.How many brokers need to acknowledge a message before it is considered committed?
- A. 0
- B. 1
- C. 2
- D. 3
正解：D
解説：
With acks=all, the leader waits formin.insync.replicasto acknowledge the message. Since min.insync.
replicas=3, Kafka will only commit the messageonce 3 brokers (leader + 2 followers)confirm they have the message.
FromKafka Documentation > Acks and Durability:
"If acks=all is specified, the producer will wait until the full set of in-sync replicas has acknowledged the record. The minimum number of in-sync replicas is controlled by min.insync.replicas." Even though the replication factor is 4, only3 acknowledgments are needed, as defined by min.insync.
replicas.
Reference:Apache Kafka Producer Configs > acks, min.insync.replicas
質問 # 79
A stream processing application is tracking the user activity of online shopping carts. The application tracks items added to the cart, items removed from the cart, and items ordered from the cart throughout the day for each user.
You need to capture the data to identify possible periods of user inactivity.
Which type of Kafka Streams window should you use?
- A. Tumbling
- B. Sliding
- C. Hopping
- D. Session
正解：D
質問 # 80
A producer is configured with the default partitioner. It is sending records to a topic that is configured with five partitions. The record does not contain any key.
What is the result of this?
- A. Records will be sent to the least used partition.
- B. Records will be dispatched among the available partitions.
- C. An error will be raised and no record will be sent.
- D. Records will be sent to partition 0.
正解：B
解説：
If a key isnot specified, thedefault Kafka partitioner uses round-robinlogic to assign partitions. This leads toeven distributionof messages across all partitions.
FromKafka Producer Design:
"If the key is null, the producer will assign the partition in a round-robin fashion to achieve load balancing." There isno error, and partition 0 isnot alwayschosen in this case.
Reference:Kafka Producer Partitioner Behavior - Official Docs
質問 # 81
We would like to be in an at-most once consuming scenario. Which offset commit strategy would you recommend?
- A. Do not commit any offsets and read from beginning
- B. Commit the offsets in Kafka, after processing the data
- C. Commit the offsets on disk, after processing the data
- D. Commit the offsets in Kafka, before processing the data
正解：D
解説：
Here, we must commit the offsets right after receiving a batch from a call to .poll()
質問 # 82
In Avro, adding an element to an enum without a default is a __ schema evolution
- A. full
- B. backward
- C. forward
- D. breaking
正解：D
解説：
Since Confluent 5.4.0, Avro 1.9.1 is used. Since default value was added to enum complex type , the schema resolution changed from:
(<1.9.1) if both are enums:** if the writer's symbol is not present in the reader's enum, then an error is signalled. **(>=1.9.1) if both are enums:
if the writer's symbol is not present in the reader's enum and the reader has a default value, then that value is used, otherwise an error is signalled.
質問 # 83
A stream processing application is consuming from a topic with five partitions. You run three instances of the application. Each instance has num.stream.threads=5.
You need to identify the number of stream tasks that will be created and how many will actively consume messages from the input topic.
- A. 15 created, 15 actively consuming
- B. 5 created, 5 actively consuming
- C. 5 created, 1 actively consuming
- D. 15 created, 5 actively consuming
正解：A
解説：
In Kafka Streams,the number of stream tasks = number of input partitions × num.stream.threads × number of instances,but only as many as the number of partitions can actively consume at once.
However, in this case,Kafka Streams assigns one task per partition, and because there are 5 partitions and
15 threads (3 instances × 5 threads),15 tasks are created, andall 15 can be activedepending on processing topology.
FromKafka Streams Developer Guide:
"Kafka Streams creates one task per input partition. If you increase the number of stream threads, it runs multiple tasks in parallel within a single instance." So,15 stream tasks will be created and 15 will be actively consuming.
Reference:Apache Kafka Streams Documentation > Concepts > Tasks and Threads
質問 # 84
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