[SYSTEMDS-3135] Reader Generation for Custom Text Formats This commit contains the the updated implementation of GIO, a system for generating efficient matrix and frame readers for custom data formats by example. Our GIO paper was published in SIGMOD 2023. The main improvements and extensions over the previous implementation are 1. Support for both frame and matrix reader generation 2. Support for projection over the selected fields 3. Improved code generation that adapts to single/multi-threaded configuration 4. Support for single/multi-line record representations Closes #1865
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
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Status and Build: SystemDS is renamed from SystemML which is an Apache Top Level Project. To build from source visit SystemDS Install from source
