Skip to content

small typo fix in readme #49

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.markdown
Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ Our motivation for augmenting the original HLL algorithm went something like thi

The first addition to the original HLL algorithm came from realizing that 1,280 bytes is the size of 160 64-bit integers. So, if we wanted more accuracy at low cardinalities, we could just keep an explicit set of the inputs as a sorted list of 64-bit integers until we hit the 161st distinct value. This would give us the true representation of the distinct values in the stream while requiring the same amount of memory. (This is the `EXPLICIT` algorithm.)

The second came from the realization that we didn't need to store registers whose value was zero. We could simply represent the set of registers that had non-zero values as a map from index to values. This is map is stored as a list of index-value pairs that are bit-packed "short words" of length `log2m + regwidth`. (This is the `SPARSE` algorithm.)
The second came from the realization that we didn't need to store registers whose value was zero. We could simply represent the set of registers that had non-zero values as a map from index to values. This map is stored as a list of index-value pairs that are bit-packed "short words" of length `log2m + regwidth`. (This is the `SPARSE` algorithm.)

Combining these two augmentations, we get a "promotion hierarchy" that allows the algorithm to be tuned for better accuracy, memory, or performance.

Expand Down