Practical data visualization in Hadoop
Hadoop has a rich ecosystem of data sources and applications that help us build rich visualizations. In the coming sections, we will understand two such applications:
- Apache Druid
- Apache Superset
We will also learn how to use Apache Superset with data in RDBMSes such as MySQL.
Apache Druid
Apache Druid is a distributed, high-performance columnar store. Its official website is https://druid.io.
Druid allows us to store both real-time and historical data that is time series in nature. It also provides fast data aggregation and flexible data exploration. The architecture supports storing trillions of data points on petabyte sizes.
In order to understand more about the Druid architecture, please refer to this white paper at http://static.druid.io/docs/druid.pdf.
Druid components
Let's take a quick look at the different components of the Druid cluster:
Component | Description |
Druid Broker | These are the nodes that are aware of where the data lies in the cluster. These nodes... |