A Smooth Sea Never Made a Skillful Sailor

Today, we're going to explore CockroachDB from the Data Science perspective again. We will continue to use Jupyter notebook but instead of Python, we're going to use the R language. I was inspired to write this post based on an article written by my colleague. I will build on that article by introducing Jupyter Notebook to the mix.

Today, we're going to explore CockroachDB from the Data Science perspective, using a popular exploratory web tool called Jupyter Notebook. I was inspired to write this post based on this article . The article goes over using Jupyter with Oracle, MySql and Postgresql, we're going to do the same with Cockroach! One caveat here is the heavy reliance on ipython-sql library. We're going to use Pandas library as the ipython-sql magic functions are not compatible with Cockroach today. Hopefully you will find it useful.

Today we're going to take a slight detour from docker compose and evaluate ingestion of data from Hadoop into Cockroach. One word of caution, this is being tested on an unsecured cluster with very small volume of data. Always test your own set up before taking public articles for face value! CockroachDB can natively import data from HTTP endpoints, object storage with respective APIs and local/NFS mounts. The full list of supported schemes can be found here . It does not support HDFS file scheme and we're left to our wild imagination to find alternatives. As previously discussed, Hadoop community is working on Hadoop Ozone, a native scalable object store with S3 API compatibility. For reference, here's my article demonstrating CockroachDB and Ozone integration. The limitation here is that you need to run Hadoop 3 to get access to it. What if you're on Hadoop 2? There are several choices I can think of off the top of my head. One approach is to ...

Today, we're going to evaluate Hadoop Ozone object store for CockroachDB object store sink viability. A bit of caution, this article only explores the art of possible, please use the ideas in this article at your own risk! Firstly, Hadoop Ozone is a new object store Hadoop Community is working on. It exposes an S3 API backed by HDFS and can scale to billions of files on prem! This article only scratches the surface, for everything there is to learn about Hadoop and Ozone , navigate to their respective websites.

Today, we’re going to explore CDC capability in CockroachDB Enterprise Edition using Minio object store as sink. To achieve this, we’re going to reuse the compose file from the first two tutorials and finally bring this to a close. Without further ado

This is my second post on creating a multi-service architecture with docker-compose. This is meant to be a learning exercise and typically docker-compose is used to set up a local development environment rather than a production-ready set up. I regularly, find myself building these environments to reproduce customer bugs. For a production-specific application, refer to your platform vendor documentation. At some later time, I will cover Kubernetes deployments that can be used as a stepping stone for a real-world application. Until then, let's focus on the task at hand. We're building a microservice architecture with CockroachDB writing changes in real-time to an S3 bucket in JSON format. S3 bucket is served by a service called Minio. It can act like an S3 appliance on premise or serve as a local gateway to your cloud storage. Let's dig in:

Over the next few weeks, I will be publishing a series of tutorials on CockroachDB and various third-party tools to demonstrate how easy it is to integrate CockroachDB into your daily work. Today, we're covering docker-compose and single-node Cockroach cluster as that will be a foundation for the next blog post.