Cheatography
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Kafka is a distributed publish-subscribe messaging system used for collecting and delivering high volumes of data with low latency
This is a draft cheat sheet. It is a work in progress and is not finished yet.
Basics
What is Kafka Used For? |
1. Building real-time streaming pipelines that move data between different applications.
2. Building real-time streaming applications that are capable of processing streams of data.
3. Building a fault tolerant storage system that stores streams of records. |
Topic |
A Kafka topic is a category or feed name under which messages are stored. A Kafka producer publishes messages to a topic, which may be subscribed by zero or more consumers. |
Partitions |
A topic partition is a structured commit log to which the records are continually appended. For each topic, Kafka keeps a minimum of one partition. Each record in the partition is assigned a sequential id called as the offset, which uniquely identifies each of them within the partition. The partitions enable the topic to scale beyond a single server and act as the unit of parallelism. |
Benefits of Kafka
Reliability |
Kafka's distributed design, topic partitioning, and data replication over servers make it reliable. |
Scalability |
Kafka system exists as a cluster of brokers. The number of brokers can grow over time when more data comes. Any failure of an individual broker in a cluster is handled by the system providing uninterrupted service. |
Durability |
Disk-based data retention makes Kafka durable. Messages remain on the disk based on the retention rule configured on a per-topic basis. Even if a consumer falls backs due to any reason, the data continue to reside in the Broker till the retention period and is not lost. |
High-Performance |
All the above features make Kafka a High-Performance messaging system. |
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