Hi,
The number of partitions drives the parailism of consumers. In general, the 
more partitions, the more parallel consumer can be added , the more throughput 
can be provided. In other words, if you have 10 partitions, the most number of 
consumer is 10.  So you need to assume the  throughput a consumer can provide 
is C, and the target throughput is T. Then the minimum number of partitions, 
that is, the number of consumers,  is T/C.



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From: shalom sagges
Date: 2019-03-21 06:43
To: users
Subject: Partition Count Dilemma
Hi All,
 
I'm really new to Kafka and wanted to know if anyone can help me better
understand partition count in relation to the Kafka cluster (apologies in
advance for noob questions).
 
I was requested to increase a topic's partition count from 30 to 100 in
order to increase workers' parallelism (there are already other topics in
this cluster with 100-200 partition counts per topic).
The cluster is built of 4 physical servers. Each server has 132 GB RAM, 40
CPU cores, 6 SAS disks 1.1 TB each.
 
Is PartitionCount:100 considered a high number of partitions per topic in
relation to the cluster?
Is there a good way for me to predetermine what an optimal partition count
might be?
 
Thanks a lot!

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