sparkling-graph/sparkling-graph
SparklingGraph provides easy to use set of features that will give you ability to proces large scala graphs using Spark and GraphX.
This tool helps data engineers and scientists analyze extremely large graph datasets efficiently. You input graph data in formats like CSV or GraphML, and it provides various analytical measures and community detection results. It's designed for professionals working with big data infrastructure who need to uncover patterns and relationships within massive networks.
153 stars. No commits in the last 6 months.
Use this if you need to process and analyze graphs containing millions or billions of nodes and edges, and you are already using or familiar with Apache Spark.
Not ideal if you are working with small to medium-sized graphs or if you don't have access to or expertise in distributed computing environments like Apache Spark.
Stars
153
Forks
34
Language
Scala
License
BSD-2-Clause
Category
Last pushed
Jul 31, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sparkling-graph/sparkling-graph"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lensacom/sparkit-learn
PySpark + Scikit-learn = Sparkit-learn
Angel-ML/angel
A Flexible and Powerful Parameter Server for large-scale machine learning
flink-extended/dl-on-flink
Deep Learning on Flink aims to integrate Flink and deep learning frameworks (e.g. TensorFlow,...
MingChen0919/learning-apache-spark
Notes on Apache Spark (pyspark)
mahmoudparsian/data-algorithms-book
MapReduce, Spark, Java, and Scala for Data Algorithms Book