mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-05 15:21:43 +00:00
9963e2f160
* Changing size() return type from UInt32 to UInt64 to prevent overflow (this shouldn't break back compatibility). * Removing "big cardinalities fix" for cardinalities >2^32/30 as it was very inaccurate and for estimates >2^32 it was trying to do 'log' of negative number which is NaN and it was casted to 0. * Adding python script to show that intHash32 is not a good choice for HyperLogLog algorithm when it's used for linear counting branch of it. * Adding bash script to test uniq, uniqHLL12, uniqCombined on different set cardinalities. * Altering documentation of uniq* aggregate functions with recommendations to use uniq instead of uniqHLL12 or uniqCombined.
57 lines
1.5 KiB
Python
Executable File
57 lines
1.5 KiB
Python
Executable File
#!/usr/bin/python3
|
|
import sys
|
|
import math
|
|
import statistics as stat
|
|
|
|
start = int(sys.argv[1])
|
|
end = int(sys.argv[2])
|
|
|
|
#Copied from dbms/src/Common/HashTable/Hash.h
|
|
def intHash32(key, salt = 0):
|
|
key ^= salt;
|
|
|
|
key = (~key) + (key << 18);
|
|
key = key ^ ((key >> 31) | (key << 33));
|
|
key = key * 21;
|
|
key = key ^ ((key >> 11) | (key << 53));
|
|
key = key + (key << 6);
|
|
key = key ^ ((key >> 22) | (key << 42));
|
|
|
|
return key & 0xffffffff
|
|
|
|
#Number of buckets for precision p = 12, m = 2^p
|
|
m = 4096
|
|
n = start
|
|
c = 0
|
|
m1 = {}
|
|
m2 = {}
|
|
l1 = []
|
|
l2 = []
|
|
while n <= end:
|
|
c += 1
|
|
|
|
h = intHash32(n)
|
|
#Extract left most 12 bits
|
|
x1 = (h >> 20) & 0xfff
|
|
m1[x1] = 1
|
|
z1 = m - len(m1)
|
|
#Linear counting formula
|
|
u1 = int(m * math.log(float(m) / float(z1)))
|
|
e1 = abs(100*float(u1 - c)/float(c))
|
|
l1.append(e1)
|
|
print("%d %d %d %f" % (n, c, u1, e1))
|
|
|
|
#Extract right most 12 bits
|
|
x2 = h & 0xfff
|
|
m2[x2] = 1
|
|
z2 = m - len(m2)
|
|
u2 = int(m * math.log(float(m) / float(z2)))
|
|
e2 = abs(100*float(u2 - c)/float(c))
|
|
l2.append(e2)
|
|
print("%d %d %d %f" % (n, c, u2, e2))
|
|
|
|
n += 1
|
|
|
|
print("Left 12 bits error: min=%f max=%f avg=%f median=%f median_low=%f median_high=%f" % (min(l1), max(l1), stat.mean(l1), stat.median(l1), stat.median_low(l1), stat.median_high(l1)))
|
|
print("Right 12 bits error: min=%f max=%f avg=%f median=%f median_low=%f median_high=%f" % (min(l2), max(l2), stat.mean(l2), stat.median(l2), stat.median_low(l2), stat.median_high(l2)))
|