‘unicode_loose_md5’, ‘-80’) 46 VITESS.IO Materializ ed Views Use Cases Real- Time Rollups Reshardi ng Backfilling of Lookup vindexes Schema deploym ent Data Migratio n Change Notificatio n

shards with overlapping key ranges. For example, the source shard of a split may serve c0-d0 while its destination shards serve c0-c8 and c8-d0 respectively. Since these shards need to exist simultaneously MySQL instance within a shard has the same data (excepting some replication lag). The slaves can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis tools YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

shards with overlapping key ranges. For example, the source shard of a split may serve c0-d0 while its destination shards serve c0-c8 and c8-d0 respectively. Since these shards need to exist simultaneously MySQL instance within a shard has the same data (excepting some replication lag). The slaves can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis tools YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

shards with overlapping key ranges. For example, the source shard of a split may serve c0-d0 while its destination shards serve c0-c8 and c8-d0 respectively. Since these shards need to exist simultaneously MySQL instance within a shard has the same data (excepting some replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis tools YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

MySQL instance within a shard has identical data (if we ignore any replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis queries complete. Fortu- nately, due to how PRS works, that code path is not used. We instead use the “dont_serve” code path. But this needs to be fixed for future-proofing. Many approaches were discussed in #6645 YouTube has scaled its user base by a factor of more than 50, greatly 94 increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

MySQL instance within a shard has identical data (if we ignore any replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis queries complete. Fortunately, due to how PRS works, that code path is not used. We instead use the “dont_serve” code path. But this needs to be fixed for future-proofing. Many approaches were discussed in #6645 YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

MySQL instance within a shard has the same data (excepting some replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis tools complete. Fortu- nately, due to how PRS works, that code path is not used. We instead use the “dont_serve” code path. But this needs to be fixed for future-proofing. Many approaches were discussed in #6645 YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

MySQL instance within a shard has identical data (if we ignore any replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis queries complete. Fortu- nately, due to how PRS works, that code path is not used. We instead use the “dont_serve” code path. But this needs to be fixed for future-proofing. Many approaches were discussed in #6645 YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues

MySQL instance within a shard has the same data (excepting some replication lag). The replicas can serve read-only traffic (with eventual consistency guarantees), execute long-running data analysis tools YouTube has scaled its user base by a factor of more than 50, greatly increasing its capacity to serve pages, process newly uploaded videos, and more. Even more importantly, Vitess is a platform that continues in a database with masters in Europe is easy to do. Replicas can exist in every cell anyway, and serve the replica traffic quickly. • Replica serving cells are a good compromise to reduce user-visible