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.

Achieving predictable performance in shared cloud storage services is hard. Tenants want reservations in terms of system-wide application-level throughput, but the provider must ultimately deal with low-level IO resources at each storage node where contention arises. Such a guarantee has thus proven elusive, due to the complexities inherent to modern storage stacks: non-uniform IO amplification, unpredictable IO interference, and non-linear IO performance.

Datacenter networks should support high network utilization. Yet today's routing is typically load agnostic, so large flows can starve other flows if routed through overutilized links. Even recent proposals like centralized scheduling or end-host multi-pathing give suboptimal throughput, and they suffer from poor scalability and other limitations.