12/7/2023 0 Comments Snappy compression command lineThe table below compares the characteristics of each compression type: zstd compression is only available from Kafka version 2.1 onward. "None" means no compression is applied and is the default compression type in Kafka. Kafka supports the following options as compression types: To understand the different compression considerations, let’s compare all of the compression algorithms that Kafka supports. Why choose gzip as a compression algorithm?īecause gzip provides the highest level of compression (with a few tradeoffs). However, it's important to note that compression can also increase CPU usage and message dispatch latency, so you need to use it with care. This can be especially helpful when you're working with data that contains a lot of duplicated content, like server logs or XML and JSON files. One way to reduce the amount of storage and network bandwidth you need is by using compression. Why Is compression important when working with Kafka?Īs mentioned in the introduction, Kafka needs lots of storage space-especially when you use its replication functionality. Just be aware that it’s not intended for absolute beginners. This tutorial is simple enough to follow along, and we’ll briefly explain these technologies. You’ve heard of Apache Kafka and know roughly what it’s for.īut don't worry if you don’t meet these criteria.This article is intended for data scientists and engineers, so we’re assuming the following things about you: How to consume the compressed messages.Īnd you’ll learn how to do all of this in Python.How to fine-tune the producer compression settings for even better compression.How to enable compression in different ways, at the topic level and in a Kafka producer, and the pros and cons of each.Why gzip is a popular choice and how you can use it to compress messages.The different types of message compression supported by Kafka.What you’ll learnīy the end of this tutorial, you’ll understand: That’s why it’s important to think about message compression early on-and it’s why we’ve created this tutorial that focuses on compression. However, the downside is that Kafka’s storage requirements can be immense (depending on the volume of data you’re pumping through it). It stores all published messages for a configurable amount of time, which means that it can serve as a log of all the data that has passed through the system. One of the great things about Apache Kafka is its durability.
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