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| Section | Weight | Objectives |
|---|---|---|
| Security | 5-10% | - Authentication (SASL, SSL/TLS) - Encryption in Transit - Securing Schema Registry - Authorization (ACLs) |
| Installing and Configuring Kafka | 5-10% | - Broker Configuration Parameters - Topic Creation and Configuration - Partition Assignment Strategies - ZooKeeper vs KRaft Mode |
| Monitoring and Operations | 5-10% | - Log Compaction - Consumer Lag and Health Checks - Cross-region Replication - Disaster Recovery - Kafka Metrics and Monitoring |
| Schema Management | 5-10% | - Schema Evolution and Compatibility - Avro Schemas - Schema Registry Architecture - Schema Registration and Retrieval - Protobuf and JSON Schemas |
| Kafka Fundamentals | 10-15% | - Brokers and Clusters - Replication Factor and ISR - Log Segments and Retention - Topics, Partitions, and Offsets - Producer and Consumer Basics |
| Kafka Streams | 20-25% | - Streams Architecture and Topology - State Stores and Processors - Transformation Operations (map, filter, join, aggregate) - Exactly-Once Processing - Interactive Queries - Windowed Operations (Tumbling, Hopping, Session) - Testing Kafka Streams Applications |
| Kafka Connect | 10-15% | - Converters and Transforms - Connector Configuration - Source and Sink Connectors - Offset Management in Connect - Connect Architecture (Workers, Connectors, Tasks) - Single Message Transformations (SMT) |
| Developing with Kafka Producers | 15-20% | - Serialization (JSON, Avro, Protobuf) - Exactly-Once Semantics - Error Handling and Retry Logic - Idempotent Producers - Producer Interceptors - Partitioning Strategies - Producer Configuration and Tuning |
| Developing with Kafka Consumers | 15-20% | - Consumer Interceptors - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Commit Strategies (Auto, Manual, Cooperative) - Multi-threaded Consumers - Offset Management - Deserialization |
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NEW QUESTION # 90
What is the default maximum size of a message the Apache Kafka broker can accept?
Answer: C
Explanation:
The default maximum message size that a Kafka broker accepts is1MB (1,048,576 bytes), controlled by the config propertymessage.max.bytes.
FromKafka Broker Configuration Docs:
"The default maximum message size is 1MB. To accept larger messages, configure message.max.bytes and the producer's max.request.size." Producers also have a matching limit via max.request.size, and consumers via fetch.message.max.bytes.
Reference:Kafka Broker Configuration > message.max.bytes
NEW QUESTION # 91
You are doing complex calculations using a machine learning framework on records fetched from a Kafka topic. It takes more about 6 minutes to process a record batch, and the consumer enters rebalances even though it's still running. How can you improve this scenario?
Answer: D
Explanation:
Here, we need to change the setting max.poll.interval.ms (default 300000) to its double in order to tell Kafka a consumer should be considered dead if the consumer only if it hasn't called the .poll() method in 10 minutes instead of 5.
NEW QUESTION # 92
Which function does ZooKeeper offer in Kafka?
Answer: B
NEW QUESTION # 93
In Kafka Streams, by what value are internal topics prefixed by?
Answer: D
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 # 94
Match the topic configuration setting with the reason the setting affects topic durability.
(You are given settings like unclean.leader.election.enable=false, replication.factor, min.insync.replicas=2)
Answer:
Explanation:
Explanation:
unclean.leader.election.enable=false # Prevents data loss by only considering in-sync replicas when rebalancing.
replication.factor # Specifies how many redundant copies of partitions are distributed across brokers.
min.insync.replicas=2 # Sets the standard for the number of partition instances that must keep up with the latest committed message.
unclean.leader.election.enable=false ensures that only in-sync replicas can be elected as leaders. If disabled, an out-of-sync replica may become leader, potentially leading to data loss.
replication.factor defines how many brokers will maintain copies of each partition, directly impacting durability and availability.
min.insync.replicas determines how many replicas must acknowledge a write when acks=all is used, enforcing write durability.
Reference: Apache Kafka Topic Configuration Documentation
NEW QUESTION # 95
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