| commit | 6b23ea4227127dd8bb9f071453de59ddf518b226 | [log] [tgz] |
|---|---|---|
| author | Sebastian Baunsgaard <baunsgaard@apache.org> | Fri Apr 05 17:07:54 2024 +0200 |
| committer | Sebastian Baunsgaard <baunsgaard@apache.org> | Fri Apr 05 17:07:57 2024 +0200 |
| tree | 4901b702dcdaefdf6f77bb83a6377a763a91549f | |
| parent | 3e6e462854b1818893e86443aae858ae1cfc1088 [diff] |
[MINOR] Fix compression statistic logging for frames Logging of frames statistics for compression is misleading when samples are used to estimate the number of elements. Therefore this commit change the logging message to reflect the approximate nature of distinct counts
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
