What would be the basic optimization techniques/parameters for a time series table in this example?

[proddata]

• Typically one should aim for a single shard size of about 10-50 GiB
• Partitions can be deleted/dropped like a table. i.e. if you want to delete old data quickly, you should partition by e.g. month
• typically having less shards is more performant, than having too many

@jayeff wrote a basic guide for time series data

Sharding and partitioning guide for time-series data

The goal of this guide is to support you with building a sharding and partitioning strategy for your time series data. Let’s start with your time series data which you want to store in a table in CrateDB. You need to consider how to partition your data, how many shards to configure, and how many replicas to use. Partitioning Typically you want to partition your time series data based on a time axis. You can achieve this in CrateDB by using the date_trunc function on a timestamp. An example …

also some core information on sharding:

Sharding guide