A company's daily Snowflake workload consists of a huge number of concurrent queries triggered between 9pm and 11pm. At the individual level, these queries are smaller statements that get completed wi

Question

Options

• AEnable a multi-clustered virtual warehouse in maximized mode during the workload duration.
• BSet the MAX_CONCURRENCY_LEVEL to a higher value than its default value of 8 at the virtual
• CIncrease the size of the virtual warehouse to size X-Large.
• DReduce the amount of data that is being processed through this workload.
• ESet the connection timeout to a higher value than its default.

• A
  77% (49)
• C
  6% (4)
• D
  3% (2)
• E
  14% (9)

Explanation

The workload is defined by high concurrency (many simultaneous short queries), not by query complexity. A multi-cluster warehouse in maximized mode (A) automatically spins up additional compute clusters to serve concurrent queued queries in parallel - each cluster handles a separate queue of queries, directly addressing the concurrency bottleneck. Increasing MAX_CONCURRENCY_LEVEL (B) above its default of 8 allows more queries to run simultaneously within a single cluster before being queued, which helps absorb the burst of concurrent small statements. Increasing warehouse size to X-Large (C) adds more compute per cluster, which helps large complex queries but provides minimal benefit for many small concurrent ones. Reducing data processed (D) is an operational change, not an architectural configuration. Connection timeout (E) is unrelated to query throughput.

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