Analytics Infrastructure and Query Performance Questions
Designing analytics data infrastructure and optimizing query performance for analytics workloads. Includes data modeling for analytics, columnar versus row storage trade offs, clustering and partitioning strategies, indexing and materialized views, caching and result reuse, profiling and tuning slow queries, cost and latency trade offs for large scale analytics, and considerations for ingest pipelines and analytical storage choices.
HardTechnical
20 practiced
Propose a strategy to detect and fix data skew that causes long-running partitions during a distributed aggregation by user_id. Include detection signals, mitigation techniques (e.g., salting, splitting heavy keys), and how to integrate fixes into the ETL pipeline.
HardTechnical
24 practiced
Describe how to implement join strategies in a distributed analytics engine: broadcast (replicated) join, shuffle hash join, and sort-merge join. For each strategy, state when it performs best, its network and memory characteristics, and how you would choose among them automatically.
MediumTechnical
18 practiced
You are evaluating analytical storage options for a new product: managed cloud data warehouse, open-source data lake with query engine (e.g., Presto/Trino), and a purpose-built OLAP datastore (e.g., ClickHouse). Build a decision matrix comparing them across: cost at scale, query latency for aggregations, ease of ad-hoc analysis, maintenance overhead, and ecosystem integrations.
EasyTechnical
21 practiced
Given a large fact table with 1 billion rows partitioned by event_date (daily), describe how you would implement partitioning and clustering to speed up queries that filter by event_date and often group by user_id. Specify partitioning scheme, clustering keys, and how to handle skew.
MediumTechnical
19 practiced
Describe the trade-offs between push-based and pull-based data freshness for analytics dashboards. For a use case requiring 1-minute freshness, which approach would you pick for the pipeline from event producers to analytical store, and why?
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