Monkey

Introduction

Monkey is a lossless compression algorithm for floating-point, including 32-bit and 64-bit.

Comparation with Gorilla

Monkey has better compression ratio than Gorilla.

Monkey algorithm is inspired by "Gorilla: A Fast, Scalable, In-Memory Time Series Database". Gorilla has been wildly used in TimeSeries DBMS such as InfluxDB and Apache IoTDB.

Table: 64-bit floating-point compression comparison

File Name	Monkey Size	Grilla Size	Monkey/Gorilla
Beach_Water_Quality_-_Automated_Sensors.csv	787352	878544	0.896200987087727
stream-gages-1.csv	6452072	7672992	0.8408808454381289
stream-gages.csv	3973608	4243320	0.9364384491388819
Beach_Weather_Stations_-_Automated_Sensors.csv	4266648	5142088	0.829750093736241

Test data is from https://data.cityofchicago.org/.

The Java base implementation is inspired by gorilla-tsc.

Test your data:

1. Make a csv file, one float/double per line;
2. Put the csv file in folder src/test/resources/data;
3. Run test: SizeBenchmark.java

It's very thankful for Test Data Set sharing.

Use Monkey

1 import in pom.xml

<dependency>
    <groupId>io.github.youbenshan</groupId>
    <artifactId>monkey</artifactId>
    <version>1.0</version>
</dependency>

2 double batch compression

byte[] bytes = DoubleCompressor.compress(ds);

3 double stream compression

DoubleCompressor compressor = new DoubleCompressor();
for (double value : values) {
    compressor.compressOne(value);
}
return compressor.finish();

4 double decompression

double[] doubles = DoubleCompressor.decompress(bytes);

4 float compression and decompression use FloatCompressor.java