Scaling Big Data Search with Solr and HBase

HBase can easily store terabytes of data, but how do you scale your search mechanism to sift through these mountains of bits and retrieve large result sets in a matter of milliseconds? We used a combination of Solr sharding, careful index creation, and result pruning to meet these strict requirements in our production environment. Come see how we handle millions of rapid fire queries from dozens of parallel search clients against many terabytes of data while addressing high availability through load balancing and replication.