Lesnik & Voltina
Voltina
Lesnik, I’m building a lightweight logging micro‑service to track every millisecond of a rare pine’s growth rate. Need a concise, reliable schema for the data you’ve collected—let me know how you structure it.
Lesnik
id, timestamp, growth_rate, event_type, notes, sensor_id, batch_id, unit, accuracy, source, status, comments, file_path, data_hash, created_at, updated_at
Voltina
Here’s a lean table layout for you.
`id` int PK auto‑increment, `timestamp` bigint or datetime, `growth_rate` float, `event_type` varchar(50), `notes` text, `sensor_id` int FK, `batch_id` int FK, `unit` varchar(10), `accuracy` float, `source` varchar(100), `status` varchar(20), `comments` text, `file_path` varchar(255), `data_hash` char(64) unique, `created_at` datetime default now, `updated_at` datetime default now on update. That covers the basics, no fluff.
Lesnik
Sounds solid, but keep an eye on the `data_hash` – a 64‑char field is fine if you’re hashing with SHA‑256, just remember to update it whenever you alter the source data. Also, if your sensors ever drift, a separate `calibration` table might help track corrections without cluttering the main log. Keep the schema lean, but be ready to add a tiny audit trail if you ever need to trace a weird spike.
Voltina
Got it, I’ll add a `calibration` table linked by `sensor_id` and a tiny `audit_log` that just records `id`, `changed_at`, `changed_by`, `old_value`, `new_value`—nothing else. Data_hash will be auto‑generated whenever `data_hash` or any of the raw fields change, so you won’t have to remember to update it manually.
Lesnik
nice approach, keeps the main log clean; just make sure the audit_log writes fast enough so you don’t miss a rapid growth spike. the auto hash is handy, but double‑check that your hashing routine handles nulls and timestamps consistently so the same data never ends up with two different hashes. keep it simple and the pine will talk.