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turbonss/README.md

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Turbo NSS
---------
glibc nss library for passwd and group.
Checking out and building
-------------------------
```
$ git clone --recursive https://git.sr.ht/~motiejus/turbonss
```
Alternatively, if you forgot `--recursive`:
```
$ git submodule update --init
```
And run tests:
```
$ zig build test
```
... the other commands will be documented as they are implemented.
This project uses [git subtrac][git-subtrac] for managing dependencies.
Steps
-----
A known implementation runs id(1) at ~250 rps sequentially. Our goal is 10k
ID/s.
id(1) works as follows:
- lookup user by name.
- get all additional gids (an array attached to a member).
- for each additional gid, return the group name.
Assuming a member is in ~100 groups on average, that's 1M group lookups per
second. We need to convert gid to a group index quickly.
Data structures
---------------
Basic data structures that allow efficient storage:
```lang=c
// reminder:
typedef uid_t uint32;
typedef gid_t uint32;
// 6*32b = 6*4B = 24B/user
typedef struct {
uid_t uid;
gid_t gid;
name_offset uint32; // offset into *usernames
gecos_offset uint32; // offset into *gecos
shell_offset uint32; // offset into *shells
additional_groups_offset uint32; // offset into additional_groups
} user;
const char* usernames; // all concatenated usernames, fsst-compressed
const char* gecoss; // all concatenated gecos, fsst-compressed
const char* shells; // all concatenated home directories, fsst-compressed
const uint8_t additional_groups; // all additional_groups, turbo compressed
typedef struct {
gid_t gid;
name_offset uint32; // offset into *groupnames
members_offset uint32; // offset into members
}
const char* groupnames; // all concatenated group names, fsst-compressed
const uint8_8 members; // all concatenated members, turbo compressed
```
"turbo compression" encodes a list of uids/gids with this algorithm:
1. sort ascending.
2. extract deltas and subtract 1: `awk '{diff=$0-prev; prev=$0; print
diff-1}'`.
3. varint-encode these deltas into an uint32, like protobuf or utf8.
With typical group memberships (as of writing) this requires ~1.3-1.5 byte per
entry.
Indexes
-------
The following operations need to be fast, in order of importance:
1. lookup gid -> group (this is on hot path in id).
2. lookup uid -> user.
3. lookup username -> user.
4. lookup groupname -> group.
5. (optional) iterate users using a defined order (`getent passwd`).
6. (optional) iterate groups using a defined order (`getent group`).
Preliminary results of playing with [cmph][cmph]:
BDZ: tried b=3, b=7 (default), and b=10.
* BDZ algorithm stores 1M values in (900KB, 338KB, 306KB) respectively.
* Latency for 1M keys: (170ms, 180ms, 230ms).
* Packed vs non-packed latency differences are not meaningful.
CHM retains order, however, 1M keys weigh 8MB. 10k keys are ~20x larger with
CHM than with BDZ, eliminating the benefit of preserved ordering.
[git-subtrac]: https://github.com/apenwarr/git-subtrac/
[cmph]: http://cmph.sourceforge.net/