Partitioning best practices
Use the following best practices when defining custom partitioning strategies for your data stored in InfluxDB Cloud Dedicated.
- Partition by tags that you commonly query for a specific value
- Only partition by tags that always have a value
- Avoid over-partitioning
Partition by tags that you commonly query for a specific value
Custom partitioning primarily benefits queries that look for a specific tag
value in the WHERE
clause. For example, if you often query data related to a
specific ID, partitioning by the tag that stores the ID helps the InfluxDB
query engine to more quickly identify what partitions contain the relevant data.
Use tag buckets for high-cardinality tags
Partitioning using distinct values of tags with many (10K+) unique values can actually hurt query performance as partitions are created for each unique tag value. Instead, use tag buckets to partition by high-cardinality tags. This method of partitioning groups tag values into “buckets” and partitions by bucket.
Only partition by tags that always have a value
You should only partition by tags that always have a value. If points don’t have a value for the tag, InfluxDB can’t store them in the correct partitions and, at query time, must read all the partitions.
Avoid over-partitioning
As you plan your partitioning strategy, keep in mind that data can be “over-partitioned”–meaning partitions are so granular that queries end up having to retrieve and read many partitions from the object store, which hurts query performance.
- Balance the partition time interval with the actual amount of data written during each interval. If a single interval doesn’t contain a lot of data, it is better to partition by larger time intervals.
- Don’t partition by tags that you typically don’t use in your query workload.
- Don’t partition by distinct values of high-cardinality tags. Instead, use tag buckets to partition by these tags.
Was this page helpful?
Thank you for your feedback!
Support and feedback
Thank you for being part of our community! We welcome and encourage your feedback and bug reports for InfluxDB and this documentation. To find support, use the following resources:
Customers with an annual or support contract can contact InfluxData Support.