Unbelievable! We have completed the study of Spark and Elasticsearch for real-time analytics via ES-Hadoop. We started with the basic concepts of Apache Hadoop. We learned how to configure ES-Hadoop for Apache Spark support. We read the data from Elasticsearch, processed it, and then wrote it back to Elasticsearch. We learned about the find_anomalies() function, which is a real-time anomaly detection routine based on the k-means model, which was created from past data using the Spark MLlib. This can tell you whether the input data is an anomaly.
The next chapter is the final chapter of this book. We will use Spring Boot to build a RESTful API to provide search and analytics backed by Elasticsearch. We will revisit what we have learned before and glue it together to make a real-world use case project. Finally, we will visualize the results produced by the project by using...
