For those of you that are still following along, let's recap what we've accomplished since the last post, Solr Document Processing with Apache Camel - Part II. We started by deploying SolrCloud with the sample gettingstarted collection and then developed a very simple standalone Camel application to index products from a handful of stub JSON files.
In this post, we will continue to work against the SolrCloud cluster we set up previously. If you haven't done this, refer to the Apache Solr Setup in README.md. We will also start out with a new Maven project available in GitHub called camel-dp-part3. This project will be similar to the last version; but with the following changes:
- We will be using a real data source. Specifically, Best Buy's movie product line.
- We will introduce property placeholders. This will allow us to specify environment-specific configurations within a Java properties file.
In my last post, Solr Document Processing with Apache Camel - Part 1, I made the case for using Apache Camel as a document processing platform. In this article, our objective is to create a simple Apache Camel standalone application for ingesting products into Solr. While this example may seem a bit contrived, it is intended to provide a foundation for future articles in the series.
Our roadmap for today is as follows:
- Set up Solr
- Create a Camel Application
- Index sample products into Solr via Camel
When I first started working as a search engineer in 2008, I had the pleasure of working with Microsoft FAST ESP. It truly was a full stack enterprise search platform that included among other things, a powerful document processing pipeline engine. The Document Processing engine sits between your data sources and the indexer and is largely responsible for... Read More