How Bloomberg Scales Apache Solr in a Multi-tenant Environment
Case study of a hosted communications archive and search solution, with over 2.5 billion documents in a 45TB Solr index.
As we countdown to the annual Lucene/Solr Revolution conference in Austin this October, we’re highlighting talks and sessions from past conferences. Today, we’re highlighting Bloomberg engineer Harry Hight’s session on scaling Solr in a multi-tenant environment.
Bloomberg Vault is a hosted communications archive and search solution, with over 2.5 billion documents in a 45TB Solr index. This talk will cover some of the challenges we encountered during the development of our Solr search backend, and the steps we took to overcome them, with emphasis on security and scalability. Basic security always starts with different users having access to subsets of the documents, but gets more interesting when users only have access to a subset of the data within a given document, and their search results must reflect that restriction to avoid revealing information. Scaling Solr to such extreme sizes presents some interesting challenges. We will cover some of the techniques we used to reduce hardware requirements while still maintaining fast responses times.
Harry Hight is a software engineer for Bloomberg Vault. He has been working with Solr/Lucene for the last 3 years building, extending, and maintaining a communications archive/e-discovery search back-end.
Join us at Lucene/Solr Revolution 2015, the biggest open source conference dedicated to Apache Lucene/Solr on October 13-16, 2015 in Austin, Texas. Come meet and network with the thought leaders building and deploying Lucene/Solr open source search technology. Full details and registration…
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