commit | d000364e972c6ab2816e0a4990c7ab9c736042c8 | [log] [tgz] |
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author | Olga <ovcharenko.folga@gmail.com> | Wed Aug 26 14:44:04 2020 +0200 |
committer | baunsgaard <baunsgaard@tugraz.at> | Sat Nov 14 21:05:26 2020 +0100 |
tree | 54d61cd7a440c7e597f5437b388661ff9c7146d8 | |
parent | d61c3bffc677443c28d0fca27364267c1ca41111 [diff] |
[SYSTEMDS-2727-9] Federated CM, Var, qsort & qpick This commit adds more primitive federated instructions for statistics calculations. - Correlation - Variance, - Quantile sort and - Quantile pick. closes #1103 closes #1102
Overview: SystemDS is a versatile system for the end-to-end data science lifecycle from data integration, cleaning, and feature engineering, over efficient, local and distributed ML model training, to deployment and serving. To this end, we aim to provide a stack of declarative languages with R-like syntax for (1) the different tasks of the data-science lifecycle, and (2) users with different expertise. These high-level scripts are compiled into hybrid execution plans of local, in-memory CPU and GPU operations, as well as distributed operations on Apache Spark. In contrast to existing systems - that either provide homogeneous tensors or 2D Datasets - and in order to serve the entire data science lifecycle, the underlying data model are DataTensors, i.e., tensors (multi-dimensional arrays) whose first dimension may have a heterogeneous and nested schema.
Quick Start Install, Quick Start and Hello World
Documentation: SystemDS Documentation
Python Documentation Python SystemDS Documentation
Issue Tracker Jira Dashboard
Status and Build: SystemDS is renamed from SystemML which is an Apache Top Level Project. To build from source visit SystemDS Install from source