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The CCDAK Certification examination is an industry-recognized validation of one's knowledge and experience with the Kafka platform. It is designed to assess one's understanding of Kafka architecture, design principles, and implementation details. Confluent Certified Developer for Apache Kafka Certification Examination certification is highly respected in the industry and is recognized by leading organizations worldwide. To prepare for the exam, candidates must have a solid understanding of Kafka's architecture, design principles, and implementation details, as well as experience working with Kafka in a production environment.

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q125-Q130):

NEW QUESTION # 125
Which of the following is true regarding thread safety in the Java Kafka Clients?

A. One Producer can be safely used in multiple threads
B. One Consumer can be safely used in multiple threads
C. One Consumer needs to run in one thread
D. One Producer needs to be run in one thread

Answer: A,C

Explanation:
KafkaConsumer is not thread-safe, KafkaProducer is thread safe.

NEW QUESTION # 126
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. cleanup.policy=compact
B. compression.type=lz4
C. cleanup.policy=delete
D. max.message.bytes=10000000

Answer: A

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.

NEW QUESTION # 127
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?

A. 0
B. 1
C. 2
D. 3

Answer: C

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

NEW QUESTION # 128
Compaction is enabled for a topic in Kafka by setting log.cleanup.policy=compact. What is true about log compaction?

A. Each message stored in the topic is compressed
B. After cleanup, only one message per key is retained with the latest value Compaction changes the offset of messages
C. Kafka automatically de-duplicates incoming messages based on key hashes
D. After cleanup, only one message per key is retained with the first value

Answer: B

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.

NEW QUESTION # 129
How will you read all the messages from a topic in your KSQL query?

A. KSQL reads from the beginning of a topic, by default.
B. KSQL reads from the end of a topic. This cannot be changed.
C. Use KSQL CLI to set auto.offset.reset property to earliest

Answer: C

Explanation:
Consumers can set auto.offset.reset property to earliest to start consuming from beginning. For KSQL, SET 'auto.offset.reset'='earliest';

NEW QUESTION # 130
......

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