Urania Humboldtsaal

You've indexed your data and people are searching it. But how do you know if they are happy with the results? How do you know if they are finding what they need?

So you have downloaded Solr, configured it, indexed your data and are now ready to integrate it with the rest of your enterprise Java application. For most situations, this process will begin with Solr's Java client library SolrJ, but how do you configure SolrJ? What are best practices for using it? And how can you use it to build a robust search service tailored to your applications needs? In this presentation we'll show how to configure SolrJ in a Spring application and walkthrough a powerful design for incorporating Solr/Lucene and SolrJ in your application.

Obviously, there’s a huge amount of interest and use around Hadoop for processing large amounts of data given its scalability and cost/performance. Its great for a lot of Big Data needs but it was never designed to replace RDBMS systems. Hadoop is batch oriented, it doesn’t supports queries and its environment can best be described as “ideal” for programmers but abysmal for business users.

"Most NoSQL stores focus on throughput and resilience to failure. The trade-off in achieving those goals has been a substantial decrease in the sophistication of data models compared to RDBMS systems, and a corresponding increase in processing frameworks to deal with large volumes of unconnected data.