soql-optimization

Optimize SOQL queries by interpreting query plans to identify selective filters, applying LIMIT clauses, and avoiding leading wildcards. This reduces relativeCost and sobjectCardinality to prevent governor-limit exhaustion during Salesforce data access.

The Salesforce Query Plan tool reveals the leadingOperationType, cardinality, relativeCost, and sobjectCardinality of your SOQL. Interpreting these plan fields guides indexing decisions and highlights inefficient filters causing bulk query bottlenecks.

Improve SOQL selectivity by analyzing query plan fields like cardinality and relativeCost. High relativeCost indicates non-selective filters; optimize them by designing appropriate indexing strategies for common filters to lower the leading operation cost.

Leading wildcards cause performance issues because they bypass database indexes, forcing a full table scan. This increases the query plan's relativeCost and triggers governor-limit pressure during Salesforce data retrieval.

Yes, you can optimize bulk SOQL queries for large Salesforce data loads by validating selective filters across object types and applying LIMIT usage. Interpreting the query plan ensures your incremental query tuning stays within governor limits.

Create custom indexes for SOQL queries when the query plan shows a high relativeCost and a TableScan as the leadingOperationType. Indexing common filters improves selectivity and is required to optimize complex joins across related objects.