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Database / Google Spanner Database Interview questions

Explain the execution flow of a partitioned DML statement in Spanner?

Partitioned DML is designed for bulk updates or deletes that would be impractical, or impossible, inside a single transaction, so instead of one atomic operation it decomposes the statement into many independent pieces.

flowchart TD A[Client issues partitioned DML statement] --> B[Spanner computes key range partitions] B --> C[Each partition run as its own transaction] C --> D[Partition 1 commits independently] C --> E[Partition 2 commits independently] C --> F[Partition N commits independently] D --> G[Progress/row-count aggregated and reported] E --> G F --> G

Spanner first analyzes the statement's key range and splits it into partitions roughly aligned with existing table splits. Each partition is then executed as its own small, independent read-write transaction that commits on its own, rather than all partitions committing together atomically. This means a partitioned DML statement is not all-or-nothing: if it's interrupted partway through, some partitions will have committed and others won't, so it's designed to be idempotent and safely re-runnable rather than treated like a single ACID operation. The trade-off is deliberate - by giving up whole-statement atomicity, Spanner can update or delete rows across an entire large table without a single long-running transaction holding excessive locks or exceeding transaction size limits.

Is a partitioned DML statement all-or-nothing across its whole scope?
Why should partitioned DML statements be designed to be idempotent?

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