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Cloud Efficiency Hub

Suboptimal Use of Search Optimization Service

Explanation

Search Optimization can enable significant cost savings when selectively applied to workloads that heavily rely on point-lookup queries. By improving lookup efficiency, it allows smaller warehouses to satisfy performance SLAs, reducing credit consumption.

However, inefficiencies arise when:

  • Search Optimization is not enabled on critical lookup-heavy tables, forcing oversized warehouses.
  • It is enabled unnecessarily on infrequently queried data, adding avoidable costs.
  • Warehouse sizing is not adjusted after Search Optimization is implemented, missing the primary cost-saving opportunity.

Regular review of query patterns and warehouse sizing is essential to maximize the intended benefit of Search Optimization.

Relevant Billing Model

Detection

  • Identify tables where Search Optimization is enabled and assess actual query usage patterns on optimized columns.
  • Detect cases where Search Optimization is enabled but query volume against the indexed columns is low.
  • Identify workloads that experience point-lookup query latency but operate on oversized warehouses without Search Optimization.
  • Evaluate if warehouses supporting lookup-heavy workloads remain oversized despite Search Optimization being available.

Remediation

  • Enable Search Optimization selectively on columns supporting frequent, high-value point-lookup queries
  • After enabling Search Optimization, reassess and right-size warehouses where feasible.
  • Remove Search Optimization from tables or columns with low query activity to eliminate unnecessary storage and maintenance costs.
  • Periodically audit Search Optimization configurations against evolving workload patterns and business needs.

Relevant Documentation