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The cardinality aggregation is a metric aggregation that allows to compute approximate unique counts based on the HyperLogLog++ algorithm which has the nice properties of both being close to accurate on low cardinalities and having fixed memory usage so that estimating high cardinalities doesn't blow up memory.
This aggregation computes unique term counts using the hyperloglog++ algorithm
which uses linear counting to estimate low cardinalities and hyperloglog on
higher cardinalities.
Since this algorithm works on hashes, it is useful for high-cardinality fields
to store the hash of values directly in the index, which is the purpose of
the new `murmur3` field type. This is less necessary on low-cardinality
string fields because the aggregator is smart enough to only compute the hash
once per unique value per segment thanks to ordinals, or on numeric fields
since hashing them is very fast.
Close#5426
The cardinality aggregation is a metric aggregation that allows to compute approximate unique counts based on the HyperLogLog++ algorithm which has the nice properties of both being close to accurate on low cardinalities and having fixed memory usage so that estimating high cardinalities doesn't blow up memory.
Example:
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