| commit | e910c718d9dd520cbbc510b8228336d6fad893ed | [log] [tgz] |
|---|---|---|
| author | Matthias Boehm <mboehm7@gmail.com> | Wed Apr 03 19:48:47 2024 +0200 |
| committer | Matthias Boehm <mboehm7@gmail.com> | Wed Apr 03 19:48:47 2024 +0200 |
| tree | 98f63e5e07f338c1de664a63b3fd7e6a2cd365ba | |
| parent | 505f8711229b954198c0cee1f1f727d42b767632 [diff] |
[SYSTEMDS-3329] Generalized parameters pageRank built-in function This patch makes some of the pageRank parameter optional, in order to allow simple calls that just pass a given graph.
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 |
|---|---|
| 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
