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Achieving the CCDAK Certification demonstrates that an individual has a deep understanding of Kafka technology and is capable of developing Kafka-based applications. Confluent Certified Developer for Apache Kafka Certification Examination certification is a valuable asset for developers who work with Kafka and want to advance their careers. It is also a valuable asset for organizations that use Kafka technology, as it ensures that their developers have the necessary skills to develop and maintain Kafka-based applications.

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Confluent CCDAK Practice Braindumps | CCDAK Questions Answers

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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Examination is designed for developers who wish to demonstrate their expertise in developing Apache Kafka-based applications using Confluent's platform. Confluent is a leading provider of Apache Kafka-based solutions, and the CCDAK Certification confirms that developers have the necessary skills to design, develop, and troubleshoot Kafka-based applications using Confluent's platform.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q53-Q58):

NEW QUESTION # 53
Which of the following is a push query?

A. SELECT windowstart, windowend, item_id, SUM(quantity)
FROM orders
WINDOW TUMBLING (SIZE 20 SECONDS)
GROUP BY item_id
EMIT CHANGES;
B. CREATE STREAM STUDENTS (ID STRING KEY, SCORE INT)
WITH (kafka_topic='students_topic', value_format='JSON', partitions=4);
C. CREATE TABLE LEFT_TABLE (ID BIGINT PRIMARY KEY, NAME varchar, VALUE bigint) WITH (kafka_topic='left_topic', value_format='JSON', partitions=4);
D. SELECT *
FROM NUMBER_OF_TESTS
WHERE ID='10';

Answer: A

NEW QUESTION # 54
You have a topic t1 with six partitions. You use Kafka Connect to send data from topic t1 in your Kafka cluster to Amazon S3. Kafka Connect is configured for two tasks.
How many partitions will each task process?

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

Answer: B

Explanation:
When using Kafka Connect with sink connectors (like S3 Sink),each task is assigned one or more topic partitions. Thetotal number of partitions (6)isevenly distributedacross the available tasks (2). Thus, each task will handle3 partitions.
FromKafka Connect Documentation:
"Kafka Connect divides the topic partitions among available tasks. For example, a topic with six partitions and two tasks results in each task handling three partitions." Reference:Kafka Connect Concepts > Tasks and Partitions

NEW QUESTION # 55
Which KSQL queries write to Kafka?

A. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic>
B. SHOW STREAMS and EXPLAIN <query> statements
C. CREATE STREAM AS SELECT and CREATE TABLE AS SELECT
D. COUNT and JOIN

Answer: A,C

Explanation:
SHOW STREAMS and EXPLAIN <query> statements run against the KSQL server that the KSQL client is connected to. They don't communicate directly with Kafka. CREATE STREAM WITH <topic> and CREATE TABLE WITH <topic> write metadata to the KSQL command topic. Persistent queries based on CREATE STREAM AS SELECT and CREATE TABLE AS SELECT read and write to Kafka topics.
Non-persistent queries based on SELECT that are stateless only read from Kafka topics, for example:
SELECT A FROM foo WHERE A;
Non-persistent queries that are stateful read and write to Kafka, for example, COUNT and JOIN. The data in Kafka is deleted automatically when you terminate the query with CTRL-C.

NEW QUESTION # 56
In Kafka Streams, by what value are internal topics prefixed by?

A. tasks-<number>
B. application.id
C. group.id
D. kafka-streams-

Answer: B

Explanation:
In Kafka Streams, the application.id is also the underlying group.id for your consumers, and the prefix for all internal topics (repartition and state)

NEW QUESTION # 57
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. Add more Kafka brokers to the cluster.
B. Increase the value of the connector's property tasks.max.
C. Modify the database schemas to enable horizontal sharding.
D. Increase the number of Kafka partitions for the topics.

Answer: B

Explanation:
Increasing tasks.max allows the connector to create multiple tasks, each responsible for processing different tables or table partitions. If only one task is used, adding more workers has no effect.
From Kafka 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

NEW QUESTION # 58
......

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