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Database / Google Spanner Database Interview questions

Describe primary keys in Google Spanner schema design?

Every Spanner table requires a primary key, and unlike most relational databases, that key also decides how rows are physically distributed across storage splits. Rows are stored in primary-key order, so the key you choose directly controls which machine handles which rows.

This makes primary key choice a performance decision, not just a uniqueness rule. A key that increases monotonically, like an auto-incrementing integer or a timestamp, sends all new writes to the same split, creating a hotspot. Common fixes include prefixing the key with a hashed or shuffled value, using a UUID, or bit-reversing a sequential ID so consecutive values land on different splits. Composite keys are also used to support interleaved parent-child relationships.

What do Spanner primary keys control beyond uniqueness?
Which key pattern risks creating a write hotspot?

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What is Google Cloud Spanner? What are the main features of Google Spanner? What is the purpose of TrueTime in Spanner? Define interleaved tables in Google Spanner? What is a Spanner instance? What are processing units in Google Spanner? Describe primary keys in Google Spanner schema design? What are the supported database dialects in Spanner? List the data types supported by Google Spanner? How do you create a database in Google Spanner? What is a secondary index in Spanner? Explain the purpose of splits in Spanner? What are mutations in Google Spanner? How do you apply schema changes in Spanner? What is the Spanner emulator? Why does Spanner use TrueTime for consistency? How does Spanner achieve external consistency? What is the difference between read-write and read-only transactions in Spanner? When should you use interleaved tables versus foreign keys? What happens when a hotspot occurs in Spanner? How is data partitioned across nodes in Spanner? Why should you avoid monotonically increasing primary keys? What is the difference between Spanner and Cloud SQL? How does Spanner handle schema changes without downtime? When would you choose bounded staleness over strong reads? How can you optimize query performance in Spanner? What is the difference between Data Boost and standard reads? Why do we use commit timestamps in Spanner tables? How does Spanner's query optimizer choose an execution plan? What is the difference between batch DML and partitioned DML? When should you use change streams in Spanner? How is fine-grained access control implemented in Spanner? Why doesn't Spanner support auto-incrementing primary keys? What is the difference between GoogleSQL and PostgreSQL dialects in Spanner? How do you troubleshoot high latency in Spanner queries? Explain the internal working of Paxos in Spanner replication? Explain the execution flow of a read-write transaction in Spanner? Explain the lifecycle of a split in Spanner? How does Spanner guarantee external consistency across regions? What happens internally when Spanner commits a distributed transaction? How can you optimize a multi-region Spanner configuration for latency? Which is better and why: multi-region or regional Spanner configuration for a global app? How does directed reads improve read latency in multi-region Spanner? Why is clock skew uncertainty critical to Spanner's TrueTime API? How do you troubleshoot transaction aborts in Spanner? Explain the internal working of the Spanner query execution engine? What happens when a leader region becomes unavailable in Spanner? How does Spanner implement point-in-time recovery internally? Explain the execution flow of a partitioned DML statement in Spanner? How can you optimize schema design to avoid hotspotting at scale?
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