Apache SystemDS
A machine learning system for the end-to-end data science lifecycle, encompassing data integration, cleaning, feature engineering, efficient model training, and deployment.
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| + | Algorithm Customizability | Allows customization via R-like and Python-like languages |
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| + | Hybrid Execution Plans | Combines local, in-memory CPU and GPU operations with distributed operations on Apache Spark. |
| + | Multiple Execution Modes | Includes Spark MLContext, Spark Batch, Hadoop Batch, Standalone, and JMLC for varied operational needs. |
| + | Automatic Optimization | Optimizes based on data and cluster characteristics for efficiency and scalability. |
| + | Declarative Languages | Provides R-like syntax for various data science tasks |
| + | Compressed Linear Algebra | Enhances large scale machine learning |
| + | Principal Component Analysis | Provides scripts for statistical analysis |
| + | Compatibility | Compatibility with popular programming languages (Support for Java 11 and Python 3.5+) for broader use. |
| + | Integration | Works with Hadoop 3.3.x and Spark 3.5.x for big data processing. |
| + | Nvidia CUDA and Intel MKL Support | Utilizes Nvidia CUDA 10.2 and Intel MKL (<=2019.x) for enhanced performance. |
| - | Limited Monitoring | Lacks a comprehensive set of monitoring and management tools, making it difficult to diagnose and troubleshoot issues |
| - | Performance Impact of Message Tweaking | Modifying messages can significantly decrease performance, limiting flexibility. |
| - | No Wildcard Topic Selection | Only supports matching exact topic names, which can be restrictive for complex messaging needs |
| - | Potential Performance Reduction | Data compression and decompression by brokers and consumers can negatively impact throughput. |
| - | Clumsy Behavior with higher number of Queues | As the number of queues in the Kafka Cluster increases, SystemDS may become unstable. |
| - | Missing Message Paradigms | Doesn’t support certain message paradigms like point-to-point queues, hindering its use in specific scenarios |
System Requirements
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Ratings
4.005
| G2CROWD | 4.05 based on 1 reviews |
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Developer
Written in
Java, R, Python, Scala
Initial Release
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Repository
License
Categories
Alternatives
Machine Learning
Deep Learning
Deep Learning
Notes
- Apache Spark is a prerequisite for installing Apache SystemDS. Hence, platforms for which Apache Spark is available are considered for Apache SystemDS.
- Apache SystemML is now Apache SystemDS.