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Following #286:
During query execution, we should first analyze all label matches and group them into "attribute-only", "resource-only" or "both".
To do it fast, there should be a materialized view or additional table that holds this information.
So, before:
SELECT name, timestamp, mapping, value, flags, attributes, resource FROM `metrics_points` WHERE true AND toUnixTimestamp64Nano(timestamp) >= 1704546540000000000 AND toUnixTimestamp64Nano(timestamp) <= 1704549765000000000 AND ( JSONExtractString(attributes, 'instance') = 'host-0' OR JSONExtractString(resource, 'instance') = 'host-0' ) AND ( JSONExtractString(attributes, 'job') = 'node_exporter' OR JSONExtractString(resource, 'job') = 'node_exporter' ) AND ( JSONExtractString(attributes, 'mode') = 'user' OR JSONExtractString(resource, 'mode') = 'user' ) AND ( name = 'node_cpu_seconds_total' ) ORDER BY timestamp;
After:
SELECT name, timestamp, mapping, value, flags, attributes, resource FROM `metrics_points` WHERE true AND toUnixTimestamp64Nano(timestamp) >= 1704546540000000000 AND toUnixTimestamp64Nano(timestamp) <= 1704549765000000000 AND JSONExtractString(resource, 'instance') = 'host-0' AND JSONExtractString(resource, 'job') = 'node_exporter' AND JSONExtractString(attributes, 'mode') = 'user' AND name = 'node_cpu_seconds_total' ORDER BY timestamp;
The text was updated successfully, but these errors were encountered:
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Following #286:
During query execution, we should first analyze all label matches and group them into "attribute-only", "resource-only" or "both".
To do it fast, there should be a materialized view or additional table that holds this information.
So, before:
After:
The text was updated successfully, but these errors were encountered: