Learn what producers are and how they interact with Kafka.
- [Narrator] When it comes to producers,…there are the things again that generate the data…and send it to your cluster.…Now when they publish this data,…they use something called a partitioner.…And the partitioner's job is to figure out…which partition for the topic that the producer…is writing to is the current lead,…and, where that data is then going to be written to,…which broker that is.…Now after the data gets written,…and the partitioner has sent that back,…it will need to know whether or not…the message was received, and whether or not the data…has been written successfully.…
You see, what happens typically is,…the response back is only done after the data…has been replicated.…That way, if any issues arise,…during the process of writing the new data,…it will already have been replicated,…and you won't lose anything.…Now, the real challenge here,…is to focus on throughput,…because the bigger throughput you can have,…and there's lots of way to tune that we'll look at,…the bigger amounts of data that you can handle.…
- Understanding the Kafka log
- Creating topics
- Partitioning topics across brokers
- Installing and testing Kafka locally
- Sending and receiving messages
- Setting up a multibroker cluster
- Testing fault tolerance
Skill Level Intermediate
Transitioning from Data Warehousing to Big Datawith Alan Simon1h 50m Intermediate
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
1. Why Use Kafka?
2. Core Concepts
4. Installing and Testing Kafka Locally
5. Real-World Examples
6. Distributions and Packaging
Next steps1m 4s
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