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1st June 2018 at 10:36am


HyperLogLog is an algorithm that can solve Count Distinct problem. A Count Distinct problem is something like getting number 5 for a data set like [1, 3, 2, 1, 5, 2, 4], for it has [1, 2, 3, 4, 5] 5 elements.

HyperLogLog can provide estimated count on a very large data stream.

  • Advantage
    • Fast (O(1)).
    • Memory efficient.
    • Can be distributed and paralleled.
  • Disadvantage
    • Only provides estimated count.


  • Hash each item.
  • Place each item into 32 buckets based on first 5-bits of the hash.
  • Update value for each item in 32 buckets based on last 27-bits of the hash.
  • Apply to some fancy mathematical formulas to get the number based on the 32 buckets data.




HyperLogLogPlusPlus is an enhancement of HyperLogLog.

  • Uses 64-bit integers rather than 32-bit
  • Sparse data structure rather than one huge array
  • Better bias correction algorithm at lower cardinalities.



Commands PFADD, PFCOUNT, and PFMERGE are the main interfaces for manipulating HyperLogLog data structure in Redis.

redis> PFADD hll a b c d e f g
(integer) 1
redis> PFCOUNT hll
(integer) 7

redis> PFADD hll1 foo bar zap a
(integer) 1
redis> PFADD hll2 a b c foo
(integer) 1
redis> PFMERGE hll3 hll1 hll2
redis> PFCOUNT hll3
(integer) 6



Source code of the script test.py:

from datasketch import HyperLogLog

data = [1, 2, 3, 5, 2, 4, 1, 6, 7]

hll = HyperLogLog()
for element in data:

print(f'estimate: {hll.count()}')
print(f'real: {len(set(data))}')

Run the script:

$ mkdir testdatasketch
$ python3 -mvenv venv
$ source venv/bin/activate
(venv) $ pip install datasketch
(venv) $ python test.py
estimate: 7.097484291802821
real: 7



Logswan can find unique IP addresses in very large log files but only consumes 4MB memory.

$ logswan access.log



Short-term Bucket & Long-term Merge

  • Keep HyperLogLog data for every 10 minutes for the past 24 hours.
  • Merge HyperLogLog data into hourly HLL after 24 hours.
  • Merge HyperLogLog data into daily HLL after 60 days.
  • ...

Example redis usage: PFADD users:<date>:<hour>:<MM> <UID>, MM=[00, 10, 20, 30, 40, 50]