Spanner is a globally-distributed data management system that backs hundreds of mission-critical services at Google. Spanner is built on ideas from both the systems and database communities. The first Spanner paper published at OSDI'12 focused on the systems aspects such as scalability, automatic sharding, fault tolerance, consistent replication, external consistency, and wide-area distribution. This paper highlights the database DNA of Spanner. We describe distributed query execution in the presence of resharding, query restarts upon transient failures, range extraction that drives query routing and index seeks, and the improved blockwise-columnar storage format. We touch upon migrating Spanner to the common SQL dialect shared with other systems at Google.

We address two open problems involving algebraic execution of full-text search queries. First, we show how to correctly apply traditional database rewrite optimizations to full-text algebra plans with integrated scoring, and explain why existing techniques fail. Second, we show how our techniques are applied in a generic scoring framework that supports a wide class of scoring algorithms, including algorithms seen in the literature and user-defined scoring.