hll() (aggregation function)

Calculates the Intermediate results of dcount across the group. only in context of aggregation inside summarize.

Read about the underlying algorithm (HyperLogLog) and the estimation accuracy.

Note

This function is used in conjunction with the summarize operator.

Syntax

hll (Expr [, Accuracy])

Arguments

Name	Type	Required	Description
Expr	string	✓	Expression used for the aggregation calculation.
Accuracy			Controls the balance between speed and accuracy.

Returns

Returns the intermediate results of distinct count of Expr across the group.

Tip

• You may use the aggregation function hll_merge to merge more than one hll intermediate results (it works on hll output only).
• You may use the function dcount_hll, which will calculate the dcount from hll / hll_merge aggregation functions.

Examples

This example returns the hll results of property damage based on the start time.

[Click to run query]

StormEvents
| summarize hll(DamageProperty) by bin(StartTime,10m)

The results table shown includes only the first 10 rows.

StartTime	hll_DamageProperty
2007-01-01T00:20:00Z	[[1024,14],["3803688792395291579"],[]]
2007-01-01T01:00:00Z	[[1024,14],["7755241107725382121","-5665157283053373866","3803688792395291579","-1003235211361077779"],[]]
2007-01-01T02:00:00Z	[[1024,14],["-1003235211361077779","-5665157283053373866","7755241107725382121"],[]]
2007-01-01T02:20:00Z	[[1024,14],["7755241107725382121"],[]]
2007-01-01T03:30:00Z	[[1024,14],["3803688792395291579"],[]]
2007-01-01T03:40:00Z	[[1024,14],["-5665157283053373866"],[]]
2007-01-01T04:30:00Z	[[1024,14],["3803688792395291579"],[]]
2007-01-01T05:30:00Z	[[1024,14],["3803688792395291579"],[]]
2007-01-01T06:30:00Z	[[1024,14],["1589522558235929902"],[]]

Estimation accuracy

This function uses a variant of the HyperLogLog (HLL) algorithm, which does a stochastic estimation of set cardinality. The algorithm provides a "knob" that can be used to balance accuracy and execution time per memory size:

Accuracy	Error (%)	Entry count
0	1.6	212
1	0.8	214
2	0.4	216
3	0.28	217
4	0.2	218

Note

The "entry count" column is the number of 1-byte counters in the HLL implementation.

The algorithm includes conditions for doing a perfect count (zero error), if the set cardinality is small enough:

• When the accuracy level is 1, 1000 values are returned
• When the accuracy level is 2, 8000 values are returned

The error bound is probabilistic, not a theoretical bound. The value is the standard deviation of error distribution (the sigma), and 99.7% of the estimations will have a relative error of under 3 x sigma.

The following image shows the probability distribution function of the relative estimation error, in percentages, for all supported accuracy settings: