60Parse a JSON-lines file of LLM logs and aggregate tokens generated per request.▼easyOpenAIAnthropicGlean1 replies◆ premiumReal LLM logs are JSONL, not JSON, and real log files have a malformed line halfway through. The warm-up that screens whether you can stream a file and aggregate without one bad record nuking the whole run.Open full answer →
34Write SQL for click-through rate by ad in October, then monthly average star ratings per Marketplace product.▼easySnowflake1 replies◆ premiumThe two reported Snowflake SQL-screen warmups. Both look trivial; both have a silent-failure trap, integer division and divide-by-zero in one, the EXTRACT(MONTH) year-collision in the other.Open full answer →
46Find the customers whose return rate exceeded 30% last quarter.▼mediumNewPalantirDatabricksScale2 replies◆ premiumEveryone writes the join and the ratio. Then the result comes back dominated by people who bought one thing and sent it back, and the list is useless to the person who asked for it.Open full answer →
63Forty deployments, and the platform median looks fine while three customers are having their worst week. Design the metrics pipeline.▼hardDatabricksSnowflakeNVIDIA◆ premiumAggregate metrics hide exactly the customer who is about to churn. Adding a tenant label to everything is the obvious fix and it is also how you get a cardinality explosion that takes down the monitoring before it takes down the platform.Open full answer →