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This repository has been archived by the owner on Aug 4, 2021. It is now read-only.
I am not 100% sure that what I will write is completely true, but we are using the pg_prometheus with normalized storage for some time now. Today we wanted to create some basic continuous aggregates view so that our dashboards are more responsive when looking to the long-term data.
Unfortunately we constantly fail to do so. Even the most simply aggregate like:
prometheus=# CREATE VIEW basic
prometheus-# WITH (timescaledb.continuous)
prometheus-# AS
prometheus-# SELECT
prometheus-# time_bucket('1 day', time),
prometheus-# sum(value) AS "total"
prometheus-# FROM metrics
prometheus-# GROUP BY time_bucket('1 day', time);
ERROR: invalid SELECT query for continuous aggregate
fails with the invalid select query error message. The select query itself works without any problem of course.
As I understand this, the creation most likely fails as the metric is not a table, but a view. If this is the case, how can we perform continuous aggregates with the normalized storage? Would I need to go directly to the metrics_labels and metrics_values tables?
Any suggestions would be great here.
The text was updated successfully, but these errors were encountered:
I am not 100% sure that what I will write is completely true, but we are using the pg_prometheus with normalized storage for some time now. Today we wanted to create some basic continuous aggregates view so that our dashboards are more responsive when looking to the long-term data.
Unfortunately we constantly fail to do so. Even the most simply aggregate like:
fails with the invalid select query error message. The select query itself works without any problem of course.
As I understand this, the creation most likely fails as the
metric
is not a table, but a view. If this is the case, how can we perform continuous aggregates with the normalized storage? Would I need to go directly to themetrics_labels
andmetrics_values
tables?Any suggestions would be great here.
The text was updated successfully, but these errors were encountered: