Clojure data frame with parallel computing on larger-than-memory datasets
Unlimited size
Theoretically speaking, it supports dataset larger than memory, even to infinity!
Fast
Faster than Dask in most operations, and the larger the dataframe is, the bigger the advantage
All native types
All the datatypes used to store data is native Clojure (or Java) types!
From file to file
Integrate IO inside the dataframe. No need to write your own read-in and output functions!
Parallel
Most operations could be executed into multiple threads or even machines. See the principle in Onyx.
Lazy operations
Most operations will not be executed immediately. Dataframe will intelligently pipeline the operations altogether in computation.
Available on Clojars.
Insert this line into your project.clj
if using Leiningen.
[com.github.clojure-finance/clojask "1.1.0"]
Insert this line into your deps.edn
if using CLI.
com.github.clojure-finance/clojask {:mvn/version "1.1.0"}
The detailed doc for every API can be found here.
A separate repository for some typical usage of Clojask can be found here.
If your question is not answered in existing issues. Feel free to create a new one.
Can you improve this documentation? These fine people already did:
Yuchen Liu, awoo424, c-sungho, Angel Woo & clojure-financeEdit on GitHub
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