gorilla4j

Implementation of time series compression method based on the Facebook Gorilla paper

Лицензия

Лицензия

Группа

Группа

com.jarslab.ts
Идентификатор

Идентификатор

gorilla4j
Последняя версия

Последняя версия

0.4
Дата

Дата

Тип

Тип

jar
Описание

Описание

gorilla4j
Implementation of time series compression method based on the Facebook Gorilla paper
Ссылка на сайт

Ссылка на сайт

https://github.com/milpol/gorilla4j
Система контроля версий

Система контроля версий

https://github.com/milpol/gorilla4j

Скачать gorilla4j

Как подключить последнюю версию

<!-- https://jarcasting.com/artifacts/com.jarslab.ts/gorilla4j/ -->
<dependency>
    <groupId>com.jarslab.ts</groupId>
    <artifactId>gorilla4j</artifactId>
    <version>0.4</version>
</dependency>
// https://jarcasting.com/artifacts/com.jarslab.ts/gorilla4j/
implementation 'com.jarslab.ts:gorilla4j:0.4'
// https://jarcasting.com/artifacts/com.jarslab.ts/gorilla4j/
implementation ("com.jarslab.ts:gorilla4j:0.4")
'com.jarslab.ts:gorilla4j:jar:0.4'
<dependency org="com.jarslab.ts" name="gorilla4j" rev="0.4">
  <artifact name="gorilla4j" type="jar" />
</dependency>
@Grapes(
@Grab(group='com.jarslab.ts', module='gorilla4j', version='0.4')
)
libraryDependencies += "com.jarslab.ts" % "gorilla4j" % "0.4"
[com.jarslab.ts/gorilla4j "0.4"]

Зависимости

test (2)

Идентификатор библиотеки Тип Версия
junit : junit jar 4.13.1
org.assertj : assertj-core jar 3.18.1

Модули Проекта

Данный проект не имеет модулей.

Travis CI Maven Central

What is all about

It is all about storing data in a efficient way.

Stop! two things. First: it is not about any data, but a very special kind: time series. Sounds scary but all in all it is just a value (numerical) in time (epoch). Second: but they said that storage is cheap! Well, so the bubble gum, it is just a buck. Million packs do the million bucks though. Also, what they don't say that we store enormous load of data which we write once and read once never.

Give me the numbers

As mentioned, we are considering here a time series data (value in time). Let's say we want to store stock price valuation of single company, single day, sampled every 10 second. 8 hours gives 2880 samples, sample is a time (Java long, 8 bytes) and a value (Java double, 8 bytes). Math is simple:

8 * 60 * 6 * 16 = 46080B = 45KB Phew. That's nothing you'll say. Sure, the bubble gum is just a buck, blah, blah... How about Gorilla format, can it do any better?

From ad-hoc test:

~8465B ~= 8,3KB (We could compare that to JSON format... but it would not make any sense.) Just to be clear: we are talking about exact same data, no rounding or data losses, but... Well, in wise algorithms there is almost always but, the one here is how the data is distributed.

But how?

All answers and technical guts can be found in great paper from the Facebook engineers Gorilla: A Fast, Scalable, In-Memory Time Series Database

Usage

Maven coords

<dependency>
  <groupId>com.jarslab.ts</groupId>
  <artifactId>gorilla4j</artifactId>
  <version>0.4</version>
</dependency>

Examples

Building basic Gorilla block

TSG tsg = new TSG(1546300800, new OutBitSet());
tsg.put(1546300800, 4.0);
tsg.put(1546300860, 4.1);
tsg.put(1546300920, 4.2);
tsg.close(); // at this point no more points are accepted

Dump block and re-create

TSG tsg = new TSG(1546300800, new OutBitSet());
tsg.put(1546300800, 4.2);
byte[] tsgBytes = tsg.toBytes();
TSG recreatedTsg = TSG.fromBytes(tsgBytes); // block is still open and can accept points

Extract iterator from block

TSG tsg = new TSG(1546300800, new OutBitSet());
tsg.put(1546300800, 4.2);
Iterator<DataPoint> tsgIterator = tsg.toIterator(); // iterator works on copied bytes, tsg accepts points

Open block in iterator

TSG tsg = new TSG(1546300800, new OutBitSet());
tsg.put(1546300800, 4.2);
tsg.close();
byte[] tsgBytes = tsg.getDataBytes();
Iterator<DataPoint> tsgIterator = new TSGIterator(new InBitSet(tsgBytes));

Other Java implementation?

Please check excellent Michael Burman implementation: gorilla-tsc.

Changelog

0.4

  • Bump test libs

0.2

  • Use long for time values (start and current).
  • Move DataPoint to abstraction
  • Add JavaDocs

Версии библиотеки

Версия
0.4
0.2
0.1