commit | 029b68a3c4f8da36efe074d1a677c354b58864ee | [log] [tgz] |
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author | baunsgaard <baunsgaard@tu-berlin.de> | Wed May 31 21:50:41 2023 +0200 |
committer | baunsgaard <baunsgaard@tu-berlin.de> | Thu Jun 08 10:03:02 2023 +0200 |
tree | 8906b53593eb472aa90df90170bafc6f04c04483 | |
parent | 04e1e61a3ad2d6dd48e92c04fb44fe3b0eb107ad [diff] |
[SYSTEMDS-3575] Column Group get Compression Info This commit allows one to extract the compression info, from a column group. The implementation is basic and does not consider if the user want to get information about different potential compression plans for the individual column groups. A follow up task is to extract more information to enable morphing [SYSTEMDS-3578]
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.
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