[SYSTEMDS-2632] Fix dynamic recompilation in singlenode exec mode

Our default execution mode is hybrid, but our bin/systemds startup
script uses singlenode to ensure local operations without the need for
proper spark configuration. Since the latter entry point is used
increasingly often, we need to ensure that all default compilation
techniques nicely work in this context too.

This patch fixes an issue where recompilation of recompile-once
functions (enabled by IPA) disabled the recompilation of individual
blocks despite unknown dimensions because the execution type was already
set to CP (due to the forced singlenode execution).
2 files changed
tree: 06d045eadb441255432c04ba0b1b467319a4cb4f
  1. .github/
  2. bin/
  3. conf/
  4. dev/
  5. docker/
  6. docs/
  7. notebooks/
  8. scripts/
  9. src/
  10. .gitattributes
  11. .gitignore
  12. CONTRIBUTING.md
  13. LICENSE
  14. NOTICE
  15. pom.xml
  16. README.md
README.md

Apache SystemDS

Overview: SystemDS is a versatile 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 still in pre-alpha status. The original code base was forked from Apache SystemML 1.2 in September 2018. We will continue to support linear algebra programs over matrices, while replacing the underlying data model and compiler, as well as substantially extending the supported functionalities. Until the first release, you can build your own snapshot via Apache Maven: mvn clean package -P distribution.

Build Documentation Component Test Application Test Function Test Python Test Federated Python Test