Shinya Kato lays out four approaches:
PostgreSQL’s query planner relies on table statistics to estimate the number of rows (estimated rows) each operation will process, and then selects an optimal execution plan based on these estimates. When the estimated rows diverge significantly from the actual rows, the planner can choose a suboptimal plan, leading to severe query performance degradation.
This article walks through four approaches I used to reduce row count estimation errors, ordered from least to most invasive. Due to confidentiality constraints, I cannot share actual SQL or execution plans, so the focus is on the diagnostic thought process and the techniques applied.
Click through for those thought processes.