Can multiple consumers read from same partition in Kafka?
So the rule in Kafka is only one consumer in a consumer group can be assigned to consume messages from a partition in a topic and hence multiple Kafka consumers from a consumer group can not read the same message from a partition.
Can two consumers in the same consumer group listen to the same message 2 points?
Two consumers in two groups (Consumer 1 from Group 1, Consumer 1 from Group 2) CAN consume the same message from partition (Partition 0).
Can one Kafka topic have multiple consumers?
You can’t have multiple consumers that belong to the same group in one thread and you can’t have multiple threads safely use the same consumer. One consumer per thread is the rule. To run multiple consumers in the same group in one application, you will need to run each in its own thread.
Can you have more consumers than partitions in Kafka?
Note however that there cannot be more consumer instances than partitions. Kafka only provides a total order over messages within a partition, not between different partitions in a topic.
Can 2 consumers consume from same partition?
While Kafka allows only one consumer per topic partition, there may be multiple consumer groups reading from the same partition. Multiple consumers may subscribe to a Topic under a common Consumer Group ID, although in this case, Kafka switches from sub/pub mode to a queue messaging approach.
Can Kafka consume from another Kafka?
4 Answers. If you want to replicate data from one cluster to another then there is one kafka tool called MirrorMaker . Kafka comes with a tool for mirroring data between Kafka clusters. The tool reads from a source cluster and writes to a destination cluster.
How many partitions do consumers have?
For most implementations you want to follow the rule of thumb of 10 partitions per topic, and 10,000 partitions per Kafka cluster. Going beyond that amount can require additional monitoring and optimization. (You can learn more about Kafka monitoring here.)
How many partitions can a Kafka topic have?
How many consumers can Kafka have?
one consumer
Kafka can at max assign one partition to one consumer. If there are more number of consumers than the partitions, Kafka would fall short of the partitions to assign to the consumers. Not all the consumers of the group would get assigned to a partition and hence some of the consumers of the group would be idle.
How many partitions can Kafka handle?
How many partitions does a Kafka broker have?
As a rule of thumb, we recommend each broker to have up to 4,000 partitions and each cluster to have up to 200,000 partitions.
Do Kafka partitions have the same data?
Kafka sends all messages from a particular producer to the same partition, storing each message in the order it arrives. As Kafka adds each record to a partition, it assigns a unique sequential ID called an offset.
What are partitions in Kafka?
Partitions in Kafka. In Kafka, partitions serve as another layer of abstraction – a Partition. Here is a quickie. Topic is divided into one (default, can be increased) or more partitions. A partition is like a log. Publishers append data (end of log) and each entry is identified by a unique number called the offset.
What is consumer group in Kafka?
Kafka Consumer Groups. You group consumers into a consumer group by use case or function of the group. One consumer group might be responsible for delivering records to high-speed, in-memory microservices while another consumer group is streaming those same records to Hadoop. Consumer groups have names to identify them from other consumer groups.
Can Kafka Process multiple files?
Kafka is a message broker so it only receives files/events from publishers and makes them available for consumption by consumers. It does not do any processing. Spark streaming would dictate how files/events are read. Since Spark Streaming does micro-batching it will read several files/events from Kafka and process them together in a micro-batch.
What is a Kafka topic?
Recall that a Kafka topic is a named stream of records. Kafka stores topics in logs. A topic log is broken up into partitions. Kafka spreads log’s partitions across multiple servers or disks.