BigData / Apache Parquet Interview Questions
How does AWS Athena query Parquet files in S3?
AWS Athena is a serverless interactive query service that uses Presto/Trino under the hood. It reads Parquet files directly from S3 using the Parquet columnar reader.
Steps to query Parquet in Athena:
- Define a Glue Data Catalog table pointing to the S3 prefix:
CREATE EXTERNAL TABLE events ( user_id BIGINT, event_type STRING, revenue DOUBLE, event_date DATE ) STORED AS PARQUET LOCATION 's3://my-bucket/events/' TBLPROPERTIES ("parquet.compress"="SNAPPY");
- Query as normal SQL — Athena applies column pruning and predicate pushdown automatically.
Cost optimisation: Athena charges per byte scanned. Parquet compression + columnar reads can reduce costs by 90%+ compared to querying CSV for the same logical data.
Partition projection or partition-filtered queries (WHERE event_date BETWEEN ...) reduce both scan size and latency.
What query engine powers AWS Athena under the hood?
Why does querying Parquet in Athena cost significantly less than querying CSV for the same data?
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