When I try and enable compression on my TimeScale DB hypertable using this query: I get the following error: All I can say is that AssetId is a valid column in the Session table. I’m not sure what else to try. Is anybody familiar with this error and could offer a solution please? Thank you Answer Sometimes Postgresql requires the
Tag: timescaledb
How do I join a string and an int in PostgreSQL?
I have a procedure with an int parameter. The syntax for the add_retention_policy function is add_retention_policy(‘hypertable’, INTERVAL ‘x days’, true). I want to prefix the hypertable with the schema which is always ‘schema_’ and then followed by the id parameter, how do I do that? Answer You just need to rewrite the INTERVAL part in your function call as days
TimescaleDB – how get timestamp differences between rows?
Say you need to know how long something was ‘active’ in a time range – (with timestamp in minutes, as an example) – For a 0-15min bucket, the answer would be 6.8-3.5 + 15-9.3 = 9.0mins. (ie the first active state lasts 6.8-3.5mins, the next one goes from 9.3mins to the 15min barrier). How would you do something like this
Ruby on Rails converting Timescale SQL rate code to Ruby
I’m trying to use the Rate function from timescale to generate graph data. Right now I have a database view that does this using the concepts from the SQL code below from TimescaleDocs: Is there a way to convert this directly to ruby code in a timeseries model to improve runtime? Answer It’s possible, but I bet building the same
Calculating average with biginteger time intervals using TimescaleDB
I have a schema with the following fields: Name of row | Type ————————–+——– name | string value1 | numeric …
Postgres query nested JSONB
I have a JSONB column containing list of objects.> Here’s the table schema: column Name | Datatype ——————— timestamp | timestamp data | JSONB Sample Data 1. timestamp : …
How to use timebucket_gapfill when rows can have null values?
I have a time series table where measurements are recorded into “wide” rows. Rows may contain all measurements or only some. The other columns are then set to NULL. I would like to use timebucket_gapfill() to “clean” this table and make sure that every row in the output has data in all columns, even if the underlying dataset has some