[Docs] clarification about cardinality accuracy (#34616)

Adds a bit more clarification about how accuracy is dependent
on the dataset in question.

Closes #18231
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Zachary Tong 2018-10-22 13:15:45 -04:00 committed by GitHub
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@ -150,10 +150,18 @@ public static void main(String[] args) {
image:images/cardinality_error.png[]
For all 3 thresholds, counts have been accurate up to the configured threshold
(although not guaranteed, this is likely to be the case). Please also note that
even with a threshold as low as 100, the error remains very low, even when
counting millions of items.
For all 3 thresholds, counts have been accurate up to the configured threshold.
Although not guaranteed, this is likely to be the case. Accuracy in practice depends
on the dataset in question. In general, most datasets show consistently good
accuracy. Also note that even with a threshold as low as 100, the error
remains very low (1-6% as seen in the above graph) even when counting millions of items.
The HyperLogLog++ algorithm depends on the leading zeros of hashed
values, the exact distributions of hashes in a dataset can affect the
accuracy of the cardinality.
Please also note that even with a threshold as low as 100, the error remains
very low, even when counting millions of items.
==== Pre-computed hashes