graph processing framework

Angel is a distributed machine learning framework and graph computation engine designed to train predictive models and execute algorithms across a cluster of servers. It functions as a distributed parameter server that synchronizes model weights and gradients across multiple machines to handle massive datasets. The system provides a production environment for model inference deployment to provide real-time predictions for end users. It integrates with Spark to run machine learning workflows and data processing pipelines through a compatible interface. The framework covers distributed graph c

Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation graphs. It functions as a distributed machine learning framework, a graph processing system, a real-time stream processor, and a SQL analytics engine. The system enables the execution of distributed SQL querying, large-scale graph analysis, and real-time stream analytics across clusters of machines. It also provides a scalable environment for implementing machine learning algorithms and predictive model development on massive datasets. The engine incorporates relational query e