commit | 18f86d4eb0f4efa24eb7a616016c85e66ee73bf9 | [log] [tgz] |
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author | Olga <ovcharenko.folga@gmail.com> | Mon Jan 11 23:52:53 2021 +0100 |
committer | Shafaq Siddiqi <shafaq.siddiqi@tugraz.at> | Mon Jan 11 23:52:53 2021 +0100 |
tree | ed62adb1ecaa9f72f5385431e17f4fe6335b7ea1 | |
parent | 6bb9a0d082fe89451e1f90ba85dc1a8796bd19bc [diff] |
[SYSTEMDS-2782] MDedup Builtin for finding duplicate rows DIA project WS2020/21. Closes #1139. Date: Mon Jan 11 23:50:57 2021 +0100
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