https://github.com/evanxg852000/gorilla
Gorilla 🦍 is a port of the Facebook gorilla time-series data compression algorithm to Zig
https://github.com/evanxg852000/gorilla
compression-algorithm time-series
Last synced: 3 months ago
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Gorilla 🦍 is a port of the Facebook gorilla time-series data compression algorithm to Zig
- Host: GitHub
- URL: https://github.com/evanxg852000/gorilla
- Owner: evanxg852000
- License: mit
- Created: 2024-01-13T08:45:25.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-13T18:41:18.000Z (over 1 year ago)
- Last Synced: 2025-01-17T04:32:32.108Z (5 months ago)
- Topics: compression-algorithm, time-series
- Language: Zig
- Homepage:
- Size: 17.6 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Gorilla 🦍
A port of the Facebook gorilla time-series data compression algorithm to Zig.
ℹ️ This was done as part of my time at [Recurse Center](https://www.recurse.com/).
⚠️ Please, do not rely on this library for production work. It still needs to be thoroughly tested. You are also welcome to help.
## How to use?
```zig
const std = @import("std");
const gorilla = @import("gorilla");
const GorillaEncoder = gorilla.GorillaEncoder;
const GorillaDecoder = gorilla.GorillaDecoder;
const DataPoint = gorilla.DataPoint;
pub fn main() !void {
var gpa = std.heap.GeneralPurposeAllocator(.{}){};
defer _ = gpa.deinit();
const allocator = gpa.allocator();
const dataset = [_]DataPoint{
.{ .timestamp = 1482892270, .value = 1.76},
.{ .timestamp = 1482892280, .value = 7.78},
.{ .timestamp = 1482892288, .value = 7.95},
.{ .timestamp = 1482892292, .value = 5.53},
.{ .timestamp = 1482892310, .value = 4.41},
.{ .timestamp = 1482892323, .value = 5.30},
.{ .timestamp = 1482892334, .value = 5.30},
.{ .timestamp = 1482892341, .value = 2.92},
.{ .timestamp = 1482892350, .value = 0.73},
.{ .timestamp = 1482892360, .value = -1.33},
.{ .timestamp = 1482892390, .value = -12.45},
.{ .timestamp = 1482892390, .value = -12.45},
.{ .timestamp = 1482892401, .value = -34.76},
.{ .timestamp = 1482892490, .value = 78.9},
.{ .timestamp = 1482892500, .value = 335.67},
.{ .timestamp = 1482892800, .value = 12908.12},
};
var encoder = try GorillaEncoder.init(allocator, 1482892270);
defer encoder.deinit();
for(dataset)|point| {
try encoder.encode(point);
}
const data = try encoder.finish();
var decoder = try GorillaDecoder.init(data[0], data[1]);
var actual_points = [_]DataPoint{ DataPoint{ .timestamp = 0, .value = 0 } } ** 16;
for(&actual_points) |*dp| {
dp.* = (try decoder.next()).?;
}
const testing = @import("std").testing;
try testing.expectEqual(@as(?DataPoint, null), (try decoder.next()));
try testing.expectEqualSlices(DataPoint, dataset[0..], actual_points[0..]);
}
```
## Credits to the following resources.
- [The Facebook gorilla paper](https://www.vldb.org/pvldb/vol8/p1816-teller.pdf)
- [The reference implementation](https://github.com/facebookarchive/beringei)
- [A golang implementation](https://github.com/keisku/gorilla)
- [A rust implementation](https://github.com/jeromefroe/tsz-rs)