Cardinality
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wikipedia:Cardinality is generally defined as the number of elements in a set.
Calculating the exact cardinality of a multiset requires an amount of memory proportional to the cardinality, which is impractical for very large data sets. The HyperLogLog algorithm is able to estimate cardinalities of > 109 with a typical accuracy (standard error) of 2%, using 1.5 kB of memory.
You can have lower cardinality (1:5 label-value ratio), standard cardinality (1:80 label-value ratio), or high cardinality (1:10,000 label-value ratio). [1]
FROM Metric SELECT cardinality(metric.name) SINCE today RAW
Activities
- Read about cardinality aggregation in Elasticsearch https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-cardinality-aggregation.html
- Read https://docs.newrelic.com/docs/data-apis/ingest-apis/metric-api/NRQL-high-cardinality-metrics/ to understand "What metric is contributing the most cardinality?" and "What impact does a given attribute(s) have to that total cardinality?".
- Prometheus https://www.robustperception.io/cardinality-is-key/
- Read https://valyala.medium.com/high-cardinality-tsdb-benchmarks-victoriametrics-vs-timescaledb-vs-influxdb-13e6ee64dd6b
Related
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