Producing with a key allows to...
A kafka topic has a replication factor of 3 and min.insync.replicas setting of 1. What is the maximum number of brokers that can be down so that a producer with acks=all can still produce to the topic?
Which Kafka CLI should you use to consume from a topic?
How will you find out all the partitions where one or more of the replicas for the partition are not in-sync with the leader?
How does a consumer commit offsets in Kafka?
You want to sink data from a Kafka topic to S3 using Kafka Connect. There are 10 brokers in the cluster, the topic has 2 partitions with replication factor of 3. How many tasks will you configure for the S3 connector?
Which actions will trigger partition rebalance for a consumer group? (select three)
There are 3 producers writing to a topic with 5 partitions. There are 5 consumers consuming from the topic. How many Controllers will be present in the cluster?
You are receiving orders from different customer in an "orders" topic with multiple partitions. Each message has the customer name as the key. There is a special customer named ABC that generates a lot of orders and you would like to reserve a partition exclusively for ABC. The rest of the message should be distributed among other partitions. How can this be achieved?
Once sent to a topic, a message can be modified
What is a generic unique id that I can use for messages I receive from a consumer?
We have a store selling shoes. What dataset is a great candidate to be modeled as a KTable in Kafka Streams?
A topic has three replicas and you set min.insync.replicas to 2. If two out of three replicas are not available, what happens when a consume request is sent to broker?
If I want to send binary data through the REST proxy to topic "test_binary", it needs to be base64 encoded. A consumer connecting directly into the Kafka topic A. "test_binary" will receive
B. binary data
C. avro data
D. json data
E. base64 encoded data, it will need to decode it
while (true) {
ConsumerRecords
try {
consumer.commitSync();
} catch (CommitFailedException e) {
log.error("commit failed", e)
}
for (ConsumerRecord
{
System.out.printf("topic = %s, partition = %s, offset =
%d, customer = %s, country = %s
",
record.topic(), record.partition(),
record.offset(), record.key(), record.value());
}
}
What kind of delivery guarantee this consumer offers?
What happens when broker.rack configuration is provided in broker configuration in Kafka cluster?
You are building a consumer application that processes events from a Kafka topic. What is the most important metric to monitor to ensure real-time processing?
If I produce to a topic that does not exist, and the broker setting auto.create.topic.enable=true, what will happen?
There are 3 producers writing to a topic with 5 partitions. There are 10 consumers consuming from the topic as part of the same group. How many consumers will remain idle?
Your streams application is reading from an input topic that has 5 partitions. You run 5 instances of your application, each with num.streams.threads set to 5. How many stream tasks will be created and how many will be active?
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?
A topic receives all the orders for the products that are available on a commerce site. Two applications want to process all the messages independently - order fulfilment and monitoring. The topic has 4 partitions, how would you organise the consumers for optimal performance and resource usage?