Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Extend tuning docs #1110

Merged
merged 2 commits into from
Nov 16, 2023
Merged

Extend tuning docs #1110

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
7c09581
Extend tuning docs
erikvanoosten Nov 16, 2023
e063775
Extend tuning docs (2)
erikvanoosten Nov 16, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 6 additions & 2 deletions docs/consumer-tuning.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,8 +41,12 @@ val highThroughputSettings = ConsumerSettings(bootstrapServers).tuneForHighThrou
val lowLatencySettings = ConsumerSettings(bootstrapServers).tuneForLowLatency
```

Kafka’s performance is not very sensitive to record size. However, when records become very small (< 100 bytes) or very
large (> 100Kb), increasing or decreasing `max.poll.records` and `partitionPreFetchBufferLimit` can be considered.
## Small and large records

Kafka’s performance is not very sensitive to record size. However, when records become very small (< 100 bytes) it
might be beneficial to increase `max.poll.records` and `partitionPreFetchBufferLimit`. Similarly, when records are
very large (> 100Kb), `max.poll.records` can be decreased. Also, pre-fetching can be limited by decreasing
`partitionPreFetchBufferLimit` or even disabled by using `ConsumerSettngs.withoutPartitionPreFetching`.

## High number of partitions

Expand Down