Analysis of Blockchain transaction captured in a project that uses Jupyter notebook with GraphFrames and NetworkX, spark-notebook with GrapX. Notebooks attaches to a Spark cluster deployed in a standalone mode, everything containerized and running in Kubernetes or OpenShift.
I will show the Blockchain analysis in Jupyter interactive notebook using the external Spark cluster running in Kubernetes, everything dockerized.
The talk will briefly describe how Blockchain transactions work, but most of the time would be the demo. In the demo I will show how we can run various queries on the publicly available Blockchain data, graph algorithms such as PageRank for identifying significant BTC addresses and more.
Intended audience: intermediate, analysts, Bitcoin/Altcoin enthusiasts
In this presentation I showed a simple way of leveraging Spark's GraphX and GraphFrames for analyzing the transaction graph of Bitcoin transactions. Real data was used.
In this presentation I showed a simple way of leveraging Spark's GraphX and GraphFrames for analyzing the transaction graph of Bitcoin transactions. Real data was used.