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Shard a Live Database Without Downtime, stage 8 of 9: change it

Queries that cross shards

Rows for different workspaces now live in different databases.

System so far· 7 parts
12345678CLIENTUsersSERVICEApplicationserversDATABASEMonolithPostgresLOG / STREAMWrite audit logWORKERBackfilland catch-upSERVICEConnectionpoolersDATABASEShard hosts

Select a component to see what it is responsible for and which state it owns.

  1. 1Users → Application servers: Requests
  2. 2Application servers → Monolith Postgres: Reads and writes until cutover
  3. 3Application servers → Write audit log: Log every write
  4. 4Backfill and catch-up → Monolith Postgres: Copy existing rows
  5. 5Backfill and catch-up → Write audit log: Replay logged writes
  6. 6Backfill and catch-up → Shard hosts: Write rows by shard
  7. 7Application servers → Connection poolers: Queries by shard
  8. 8Connection poolers → Shard hosts: Schema on host
  • Request / response
  • Asynchronous

What you need to know

0 of 2 checks done

  1. Sharding makes every operation inside the shard key cheaper and every operation across keys harder:

    • Queries across shards become scatter-gathers, or need an index maintained on write.
    • Uniqueness across shards needs one place that owns it.
    • Transactions across shards become multi-step workflows.

  2. Check

    Users are sharded by workspace. Each shard has a unique index on email. Are emails globally unique?