Summary of Data at Scale 7

00:00:00 - 00:30:00

This video discusses how to manage data at scale efficiently. It covers topics such as the use of followers to scale out reads, the use of a shard management service to manage replication and roles, and how to perform periodic evaluations to keep the data in an optimal state.

• 00:00:00 The PDB is a distributed key value store that came about as a result of Facebook's need for a replication library for its various data applications. The library is reliable, scalable, and has a variety of consistency options.
• 00:05:00 The presenter discusses how Facebook built a data-at-scale system using Rocks TV, USPA, and the pre-existing shard management service. The system allows for quick adaptation to constantly changing requirements, while also supporting basic operations like getting a key, putting a key in a value, deleting a key, and prefixing a scan with a snapshot handle. Additionally, the system provides custom read and write operators, as well as a queue service.
• 00:10:00 The data shuttle system manages replication for multiple shards and is powered by PackSauce. Data at scale is discussed, with particular emphasis on the replication aspect of the system. The replication process is described, with particular emphasis on the use of rights to establish a global ordering of data.
• 00:15:00 Data at Scale 7 discusses the use of followers to scale out reads and maintain availability. The video also covers the use of a shard management service to manage replication and roles.
• 00:20:00 The PDB (Data at Scale) is a scalable, distributed database that was developed at Facebook. It accepts a variety of pluggable stores, and provides a very simplistic API for clients. The pdb handles replication, failover, and throttling, among other tasks.
• 00:25:00 The video discusses how the lock service, which is built on top of Z PDB, replicates and persists data to ensure consistency. It also describes how the lock service can be used to lock users for specific periods of time, and how load balancing is done to ensure that the service is available to as many users as possible.
• 00:30:00 This video discusses how data at scale can be managed efficiently. The logic behind the load balancing process is explained, and periodic evaluations are performed to keep the data in an optimal state.