commit | 1fa2ebc7bad9e6bb8006f70c8ae01a00cde74d5d | [log] [tgz] |
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author | Sebastian Baunsgaard <baunsgaard@apache.org> | Fri Apr 05 17:01:47 2024 +0200 |
committer | Sebastian Baunsgaard <baunsgaard@apache.org> | Fri Apr 05 17:53:00 2024 +0200 |
tree | 020e1d973869c6d00ff03d8cf8b95568fabb5a71 | |
parent | 6b23ea4227127dd8bb9f071453de59ddf518b226 [diff] |
[MINOR] Frame Shallow Update This commit make minor modifications to the shallow handling of Frames. One instance is fast abort of isShallowSerialize. Closes #2013
Overview: SystemDS is an open source ML 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.
Resource | Links |
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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