How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Mirror of Apache Hadoop MapReduce
The main features of apache/hadoop-mapreduce are: Data Analysis Visualization.
Projects with overlapping indexed features include: avelino/mining — Business Intelligence (BI) in Python, OLAP. cloudera/impala — Real-time Query for Hadoop; mirror of Apache Impala. continuumio/bokeh — Interactive Data Visualization in the browser, from Python. dcjones/gadfly.jl — Crafty statistical graphics for Julia. iainnz/graphlayout.jl — Graph layout algorithms in pure Julia. apache/spark — Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation…
Interactive Data Visualization in the browser, from Python
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
