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Database deadlocks and how engines resolve them
Define a deadlock as mutual waiting on locks, name detection plus victim rollback, and prevention by consistent lock ordering.
The lost update anomaly explained
Both transactions read the same value, each adds one, the second overwrite erases the first.
The ACID properties of transactions
Define Atomicity, Consistency, Isolation, Durability and why each matters.
Shard key impact on uniqueness and cross-shard lookups
Uniqueness and FKs hold only within a shard; non-shard-key lookups need scatter-gather or a secondary index.
Relational versus wide-column for a news feed
Relational gives flexible joins but read-time fan-out; Cassandra precomputes per-user feed rows for fast writes-side fan-out.
Polymorphic associations and referential integrity
A single column can't FK two tables, so integrity is unenforced; alternatives use exclusive arcs or per-type tables.
3NF versus BCNF and the overlapping-key gap
BCNF requires every determinant be a superkey; 3NF allows exceptions for prime attributes.
Adjacency List versus Nested Set for hierarchies
Adjacency list is simple writes but recursive reads; nested set is fast subtree reads but costly writes.
Modeling one-to-many versus many-to-many relationships
One-to-many uses a foreign key on the many side; many-to-many needs a junction table with two foreign keys.
Normalizing a flat orders table to 3NF
Split repeating data, remove partial dependencies, remove transitive dependencies, define keys.
When to intentionally denormalize a schema
Identify read-heavy join cost, duplicate or precompute data, and own the consistency burden.
Diagnosing and fixing the N+1 query problem
Define the 1 parent plus N child queries, fix via JOIN or batched IN, and ORM eager loading.
Read Committed versus Serializable isolation levels
Name the four levels, map each anomaly (dirty read, non-repeatable read, phantom) to the level that blocks it.
Materialization and Pipelining
Two query-execution strategies: materialization writes each operator's full output to disk before the next reads it, while pipelining streams tuples operator-to-operator without intermediate storage.
Demographic Parity versus Equalized Odds in hiring
Demographic parity equalizes selection rates regardless of qualification; equalized odds equalizes true and false positive rates across groups, conditioning on the true label.
Explain an interaction effect to a non-statistician
Define interaction as it depends on, show separate slope lines per age group, give the business takeaway on targeting.
Present a small but significant A/B test lift
Hypothesis, design and validity checks, result with effect size and interval, business impact of 0.5%, then a clear recommendation.
Interactive versus static plots for EDA
Interactive libraries win for exploring dense, high-cardinality, or multi-dimensional data via zoom, hover, and filtering; static plots win for reproducible, publication output.
Parquet versus CSV for analytical data lakes
Parquet stores by column enabling projection pushdown, compression, and predicate skipping; CSV is row-based, untyped, and slow to scan.
Audit an ML pipeline for GDPR compliance
Inventory data and check minimization, verify processing matches stated purpose, build lineage to trace any prediction's inputs.