We have a table with 5 billion rows and we need to perform lightning-fast point lookups on a specific UUID. Is the Search Optimization Service worth the extra credit cost compared to just using a well-defined cluster key? Does it work well with VARCHAR columns in Snowflake?
3 answers
Search Optimization (SOS) is specifically designed for exactly your use case: needle-in-a-haystack queries. Unlike clustering, which is better for range scans (like dates), SOS creates a persistent search access path that makes point lookups on UUIDs or names incredibly fast. It does support VARCHAR, but be prepared for the background maintenance cost. If your table is updated constantly, the service will consume credits to keep the search index in sync. For a 5 billion row table, I would test it on a subset first to estimate the credit burn.
Have you analyzed the "Overlap" ratio of your table lately to see if your current clustering is already providing enough pruning for these UUID lookups?
It’s a great feature but keep an eye on the SYSTEM$ESTIMATE_SEARCH_OPTIMIZATION_COSTS function before you commit. It will save you from a nasty billing surprise.
Definitely check the estimate, Nancy. For a table that size, the initial build could take a significant chunk of credits depending on the number of unique values.
Kevin, the overlap is actually quite high because the UUIDs are random and not correlated with the ingestion time. This is why our pruning is so poor right now. If we enable SOS, is there a way to limit it to only that specific UUID column so we don't pay to index the entire row? We have about 50 columns in that table but only two are used for these direct lookups.