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Fix an N+1 Query Problem
Optimize a hidden loop that is crushing your database.
Implement Redis Caching
Speed up a slow 3rd-party API response using an in-memory cache.
Profile and Fix a Memory Leak
Stop a Node.js server from continuously crashing out of memory.
Backend Performance Optimization & SQL Query Tuning
High-traffic software applications demand optimized database queries and backend execution. Employers look for developers who can analyze query execution plans (EXPLAIN ANALYZE), eliminate N+1 query problems, configure database indexes (B-Tree/GIN), and implement Redis caching layers.
1. Database Query Bottleneck Audit Report
Performance report diagnosing slow SQL queries, missing indexes, and un-indexed foreign key joins using EXPLAIN ANALYZE.
2. Optimized SQL & Index Migration Script
DDL migration script adding targeted B-Tree/GIN indexes and refactoring inefficient JOIN queries.
3. Post-Optimization Benchmark & Load Test Log
Load test report documenting response time latency reductions and database CPU utilization improvements.
Frequently Asked Questions (Backend Performance Optimization)
What is the N+1 query problem and how do you resolve it?
N+1 occurs when an application executes 1 query to fetch parent records, followed by N separate queries to fetch related child records. Resolve it using JOIN fetching or eager batch loading (e.g. Prisma include or SQL JOIN).
When should you add a database index?
Add indexes to columns frequently queried in WHERE clauses, JOIN conditions, and ORDER BY statements. Avoid indexing low-cardinality columns or tables with high write/insert volumes.
How does Redis cache invalidation work?
Cache invalidation clears or updates cached Redis keys when underlying database data changes, preventing stale data reads.
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