Certified CCDAK Questions & CCDAK Valid Study Plan

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The CCDAK Certification Exam is a hands-on exam that requires developers to demonstrate their skills in a real-world scenario. CCDAK exam consists of a set of tasks that must be completed within a set time frame. The tasks are designed to test a developer's ability to work with Kafka and Confluent's tools to build and manage Kafka-based applications. CCDAK exam is graded based on the number of tasks completed and the quality of the solutions provided.

The CCDAK certification is a valuable asset for developers who want to advance their careers in the field of big data and data engineering. Confluent Certified Developer for Apache Kafka Certification Examination certification demonstrates a developer's proficiency in Apache Kafka and makes them stand out in the job market. Companies that use Apache Kafka value the CCDAK Certification as it indicates that the developer has the skills and knowledge necessary to build and manage Kafka-based applications.

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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Examination is a rigorous and comprehensive certification exam designed to test the skills and knowledge of developers working with Apache Kafka. Confluent, the company behind Apache Kafka, offers this certification to help organizations identify and hire qualified developers who can build and maintain Kafka-based applications.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q91-Q96):

NEW QUESTION # 91
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?

Answer: A

Explanation:
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


NEW QUESTION # 92
You need to set alerts on key broker metrics to trigger notifications when the cluster is unhealthy.
Which are three minimum broker metrics to monitor?
(Select three.)

Answer: A,B,D

Explanation:
These three metrics are critical for cluster health:
OfflinePartitionsCount: Indicates partitions without active leaders - a sign of broker failure.
ActiveControllerCount: There should be exactly one active controller. A count # 1 signals controller failure.
UncleanLeaderElectionsPerSec: Tracks leader elections where out-of-sync replicas were selected - risky for data loss.
From Kafka Monitoring Documentation:
"Offline partitions and unclean leader elections should trigger alerts. Also, ensure a single active controller is running." A is about topics pending deletion - not critical.
E is a per-topic record metric, not broker-level.
Reference: Kafka Monitoring > Key JMX Metrics


NEW QUESTION # 93
An ecommerce website maintains two topics - a high volume "purchase" topic with 5 partitions and low volume "customer" topic with 3 partitions. You would like to do a stream-table join of these topics. How should you proceed?

Answer: D

Explanation:
In case of KStream-KStream join, both need to be co-partitioned. This restriction is not applicable in case of join with GlobalKTable, which is the most efficient here.


NEW QUESTION # 94
Match the testing tool with the type of test it is typically used to perform.

Answer:

Explanation:

Explanation:
Unit Testing # MockProducer
Integration Testing # Testcontainers
Performance Testing # Trogdor
Mock Data Generation # Connect Datagen
MockProducer: Simulates a Kafka producer in unit tests (no real broker interaction).
Testcontainers: Spawns Kafka in Docker for real environment testing.
Trogdor: Kafka's built-in performance load testing framework.
Connect Datagen: Creates sample source records for test and demo purposes.
From Kafka Developer Tools Guide:
"Kafka developers commonly use MockProducer for unit tests, Testcontainers for integration, and Trogdor for performance tests." Reference: Kafka Testing and Tools Overview


NEW QUESTION # 95
(Which configuration is valid for deploying a JDBC Source Connector to read all rows from the orders table and write them to the dbl-orders topic?)

Answer: C

Explanation:
According to the official Apache Kafka Connect and Confluent JDBC Source Connector documentation, the correct connector class for a JDBC source connector is io.confluent.connect.jdbc.JdbcSourceConnector. This connector is used to read data from relational databases and publish each table as a Kafka topic.
To read all rows from a specific table, the configuration must include table.whitelist (or table.include.list in newer versions) with the table name, and a topic.prefix to determine the Kafka topic name. In this case, using topic.prefix=dbl- with table.whitelist=orders results in records being written to the dbl-orders topic, which matches the requirement.
Options A, B, and C are invalid because they reference a non-existent connector class (DdbcSourceConnector), contain unsupported properties such as topic.whitelist for a source connector, or include malformed/incorrect JDBC parameters. Additionally, blacklisting tables does not ensure that only the orders table is read.
Therefore, option D is the only configuration that is syntactically correct, uses the proper connector class, and aligns with the official Kafka Connect JDBC Source Connector documentation.


NEW QUESTION # 96
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