By Neha Narkhede
Methods to take complete benefit of Apache Kafka, the disbursed, publish-subscribe queue for dealing with real-time info feeds. With this finished e-book, you are going to know how Kafka works and the way it really is designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino make it easier to set up creation Kafka clusters; safe, track, and computer screen them; write rock-solid functions that use Kafka; and construct scalable stream-processing purposes.
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Extra resources for Kafka: The Definitive Guide: Real-time data and stream processing at scale
It is preferable to reduce the size of the page cache rather than swap. Why Not Set Swappiness to Zero? swappiness was always to set it to 0. This value used to have the meaning “do not swap unless there is an out of memory condi‐ tion”. 32-303. This changed the meaning of the value 0 to “never swap under any circumstances”. It is for this reason that a value of 1 is now recommended. There is also a benefit to adjusting how the kernel handles dirty pages that must be flushed to disk. Kafka relies on disk I/O performance to provide a good response time to producers.
Dirty_background_ratio+ value lower than the default of 10. The value is a per‐ centage of the total amount of system memory, and setting this value to 5 is appropri‐ ate in many situations. This setting should not be set to zero, however, as that would cause the kernel to continually flush pages, which would eliminate the ability for the kernel to buffer disk writes against temporary spikes in the underlying device perfor‐ mance. dirty_ratio, increasing it above the default of 20 (also a percentage of total sys‐ tem memory).
CPU Processing power is a lesser concern when compared to disk and memory, but it will affect overall performance of the broker to some extent. Ideally, clients should com‐ press message to optimize network and disk usage. This does require that the Kafka broker decompress every message batch in order to assign offsets, and then recom‐ press the message batch to store it on disk. This is where the majority of Kafka’s requirement for processing power comes from. This should not be the primary factor in selecting hardware, however.