James Mulholland

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Adding keys as indexed keys vs STORING

Last updated: 2022-02-01

Regular indexed keys and the STORING clause serve very similar purposes in Google Cloud Spanner.

For example, let's consider this table which describes completable tasks.

CREATE TABLE tasks
  created_by_user_id STRING(36) NOT NULL,
  # e.g. "Buy milk"
  content STRING(MAX),
  # "HIGH" | "LOW"
  priority STRING(MAX),
  completed_at TIMESTAMP,

Let's imagine we want to show the current user all their tasks for a given priority. One way we can speed up this query is by creating the following index.

CREATE INDEX
  active_tasks_by_priority_idx
ON
  user (
    created_by_user_id,
    completed_at,
    priority
  )

Alternatively, we could have priority in a STORING clause instead of in the index keys.

CREATE INDEX
  active_tasks_by_priority_idx
ON
  user (
    created_by_user_id,
    completed_at
  ) STORING (
    priority
  )

The advantage of adding STORING over an index with just the other two keys is that it removes the need to join on the base tasks table which makes the query cheaper as priority is colocated with the index. If we did not store priority, Spanner would have to look at the values in our index then go to the base tasks table to look up the priority value.

But adding priority to the indexed keys would also avoid having to look up the value in the base table. Let's imagine our app limits the user to three active (compelted_at IS NOT NULL) HIGH priority tasks and five active MEDIUM priority tasks (focus is important). This means that when we create a new task, we need to first do a read inside a read-write transaction to avoid a task being created which exceeds the task limit, then do our write to create the task. What is the difference between using indexed keys and STORING if we create one HIGH priority task then one MEDIUM priority task?

If STORING is used and we create a new HIGH priority task, the transaction will lock all rows matching the specified created_by_user_id and completed_at values. i.e. All user task creation will be locked, regardless of priority. This means that the subsequent MEDIUM priority task creation will be blocked.

If priority is an indexed key, on the other hand, the transaction will only lock rows which match the queried priority. Consequently, the MEDIUM priority task creation will not be blocked.

This is a trivial example where the blocking is minimal. However, with larger amounts of data, this difference can cause serious performance issues.

Also note that read-only transactions do not acquire locks so this difference only applies to read-write transactions.

Open Questions

  • STORING comes at the cost of extra storage space vs not using STORING. However, this is also true of additional index keys. What is the difference in cost here?
  • How can we illustrate this with the query planner?
  • Why don't we always use indexed keys if they come with reduced locking costs?
  • How does INTERLEAVE fit in here? Like STORING, it is an approach to reduce join costs.