the value 'j' is equal to <w_0, w_1 .
the value 'j' is equal to <w_0, w_1 ... w_(bits-1)> TODO: We could read in a byte at a time.
We are computing j and \rho(w) from the paper, sorry for the name, but it allows someone to compare to the paper extremely low probability rhow (position of the leftmost one bit) is > 127, so we use a Byte to store it Given a hash <w_0, w_1, w_2 .
We are computing j and \rho(w) from the paper, sorry for the name, but it allows someone to compare to the paper extremely low probability rhow (position of the leftmost one bit) is > 127, so we use a Byte to store it Given a hash <w_0, w_1, w_2 ... w_n> the value 'j' is equal to <w_0, w_1 ... w_(bits-1)> and the value 'w' is equal to <w_bits ... w_n>. The function rho counts the number of leading zeroes in 'w'. We can calculate rho(w) at once with the method rhoW.
The value 'w' is equal to <w_bits .
The value 'w' is equal to <w_bits ... w_n>. The function rho counts the number of leading zeroes in 'w'. We can calculate rho(w) at once with the method rhoW.
Implementation of the HyperLogLog approximate counting as a Monoid