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
Let's go together through the cloud native landscape and explore all the goodies that may help you to develop scalable and reliable distributed systems. Hopefully, you will leave this talk with basic understanding of Kubernetes and motivated to use it in production.
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.
I will show how you can leverage the containers and run the Spark cluster in PaaS, namely OpenShift and Kubernetes. For demonstration purposes, I'll be demoing the Blockchain analysis in Jupyter notebook using the Spark cluster running in OpenShift, everything dockerized. I am out of buzzwords.
Have you ever wondered how to implement your own operator pattern for you service X in Kubernetes? You can learn this in this session and see an example of open-source project that does spawn Apache Spark clusters on Kubernetes and OpenShift following the pattern. You will leave this talk with a better understanding of how spark-on-k8s native scheduling mechanism can be leveraged and how you can wrap your own service into operator pattern not only in Go lang but also in Java. Let's make the data science more scalable in a cloud native fashion.
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.
The Reactive Extensions (Rx) is a tool for composing asynchronous and event-based programs using observable sequences. It's very powerful technique to avoid callback hell and it can be used both on the server side as well as for designing the user interfaces. It leverages the concepts from functional programming such as composable monadic functors, immutable state, etc. There are libraries for Rx to almost all modern languages (Java, .Net, JavaScript, C++, Scala, Android sdk, etc.) and the presentation will show the examples in multiple languages.
Have you ever wanted to write your own programming language? Why not to start with much simpler task - writing some domain specific language. Since the Scala programming language is a great fit for creating internal DSL, we will utilize its functional nature and implicit conversions, and together we will create a fluent API in form of a DSL.
Scala noob? No worries! No previous Scala experience is needed, all the techniques will be explained during the workshop. It’ll be piece of cake if you know any modern programming language.