At 9:00:00 AM, a surge of traffic hit. Every user, in every time zone, suddenly demanded the same piece of data: the flash sale metadata for item ID #42.
In the bustling data center of the e-commerce platform, there lived a tired but loyal piece of infrastructure: a PostgreSQL database named KQR (Key-Query-Resolver). kqr row cache contention check gets
CACHE GETS (total): 10,000 CACHE HITS: 0 CACHE MISSES: 10,000 MISSES WHILE LOCK HELD: 10,000 CONTENTION RATIO: 1.00 TOP CONTENDED ROW: item:42 WAITING THREADS: 9,999 LOCK HOLD TIME (avg): 487ms This was a contention storm . The first thread to acquire the cache lock went to the database (487ms). The other 9,999 threads didn’t just wait — they spun, retried, and choked the CPU. At 9:00:00 AM, a surge of traffic hit
She hot-patched KQR’s logic to use :
KQR> ROW CACHE CONTENTION CHECK GETS It printed: CACHE GETS (total): 10,000 CACHE HITS: 0 CACHE