Engineering Logs
Articles & Studies
> Field notes from real systems. SQL performance, Python pipelines, database internals, and the architectural decisions behind them.
All Articles
5 ENTRIES[ PYTHON ]SEQ. 0142025-03-12· 8 min
Constructing Dataframes from Raw Postgres Outputs
How to pull large query results into pandas efficiently, avoid memory blowups, and chunk reads from production Postgres.
[ SQL ]SEQ. 0222025-02-28· 10 min
Window Functions for Time-Series Interpolation
Use OVER and PARTITION BY to compute rolling averages, fill gaps, and rank events without collapsing rows.
[ SYSTEM ]SEQ. 0382025-02-04· 12 min
Indexing Strategies for Large-Scale Joins
B-tree vs hash vs BRIN — when each index type pays off, and how to read EXPLAIN ANALYZE to prove it.
[ SQL ]SEQ. 0412025-01-18· 6 min
Subquery vs CTE — Which Should You Reach For?
Both express the same logic, but readability, reusability, and the optimizer's behavior differ. A practical comparison.
[ PYTHON ]SEQ. 0442025-01-02· 11 min
Async DB Pools in Python with asyncpg
Building a high-throughput data ingestion service with connection pooling, batching, and back-pressure.