A. The maximum number of tasks to run for this connector
B. The maximum number of Kafka brokers to connect
C. The maximum size of each message sent
D. The maximum number of topics to read from
Solution
Step 1: Understand the tasks.max parameter
In Kafka Connect, tasks.max sets how many tasks a connector can run in parallel.
Step 2: Apply to given config
Here, tasks.max is 2, so the connector can run up to 2 tasks to increase throughput.
Final Answer:
The maximum number of tasks to run for this connector -> Option A
Quick Check:
tasks.max = max tasks per connector [OK]
Hint: tasks.max limits parallel tasks for connector [OK]
Common Mistakes:
Confusing tasks.max with broker count
Thinking it limits message size
Assuming it controls topic count
4. You have a distributed Kafka Connect cluster but notice that connectors are not starting tasks as expected. Which of the following is the most likely cause?
medium
A. The connector configuration file is missing the tasks.max property
B. Kafka brokers are offline
C. The worker.properties file is empty
D. The connector class name is misspelled in the configuration
Solution
Step 1: Analyze why tasks don't start
If connectors don't start tasks, a common cause is an invalid connector class name.
Step 2: Check other options
Missing tasks.max defaults to 1 task, so not likely cause. Brokers offline cause other errors. Empty worker.properties would prevent worker start. Misspelled connector class prevents task creation.
Final Answer:
The connector class name is misspelled in the configuration -> Option D
Quick Check:
Misspelled connector class blocks tasks [OK]
Hint: Check connector class spelling if tasks don't start [OK]
Common Mistakes:
Assuming missing tasks.max stops tasks
Ignoring connector class name correctness
Not verifying worker config completeness
5. You want to build a fault-tolerant data pipeline using Kafka Connect that can scale horizontally and recover from worker failures. Which Kafka Connect mode should you choose and why?
hard
A. Standalone mode, because it is simpler and easier to configure
B. Distributed mode, because it requires no configuration files
C. Distributed mode, because it supports multiple workers and fault tolerance
D. Standalone mode, because it automatically balances tasks across workers
Solution
Step 1: Understand Kafka Connect modes
Standalone mode runs a single worker, no fault tolerance or scaling. Distributed mode runs multiple workers, supports scaling and fault tolerance.
Step 2: Match requirements to mode
For fault tolerance and horizontal scaling, distributed mode is required.
Final Answer:
Distributed mode, because it supports multiple workers and fault tolerance -> Option C
Quick Check:
Fault tolerance needs distributed mode [OK]
Hint: Use distributed mode for scaling and fault tolerance [OK]
Common Mistakes:
Choosing standalone for fault tolerance
Thinking standalone balances tasks
Believing distributed mode needs no config
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