Our team is migrating to a serverless architecture on AWS, and I need to improve my ability to query Athena and RDS efficiently. I'm thinking of initiating a team-wide 7-Day SQL Challenge to get everyone up to speed. Has anyone tried a similar sprint for cloud-native SQL? What are the biggest hurdles when querying distributed data stores compared to local ones?
3 answers
Moving to cloud-native SQL requires a shift in how you think about partitioning and scan costs. During your 7-Day SQL Challenge, I highly recommend dedicating day three specifically to "Query Optimization for Cost." In tools like Athena, a poorly written join can be expensive. Teach your team to use partitions effectively and to limit data scans. We did a similar internal sprint last year, and it reduced our monthly cloud bill by nearly 15% because developers stopped running SELECT * on massive tables. It's a vital skill for any modern cloud engineer or architect today.
Are you worried about the latency differences when running these queries across distributed regions, or is cost management your primary concern?
I found that focusing on 'EXPLAIN' plans for every query helped our team understand what was happening under the hood.
William is spot on. Using EXPLAIN is the only way to truly visualize the execution path and identify bottlenecks in a cloud environment.
Hi David, cost is definitely the priority for us right now. Latency is manageable, but seeing those unexpected spikes in our AWS bill because of unoptimized queries is what we are trying to solve. That’s why I want the team to focus on the performance tuning aspect of the challenge this week.