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FULL AI ANALYSIS

JDBC prepared statements on application server suddenly select a generic plan causing a 15× slowdown for partitioned table queries

Generated Oct 3, 2026, 12:35:03 AM

Analysis summary

This is the known interaction where server-side prepared statements can produce a generic plan if the planner cannot rely on parameter values at plan time — leading to partition pruning not firing and index scans being skipped. The JDBC driver and connection pool by default use server-side prepared statements after a threshold; setting driver parameters that force simple query mode or a zero prepare threshold causes the planner to see constants and produce custom plans. Recent growth in partition count and parameterized usage amplifies the effect. Disabling server-side prepares fixes the symptom but removes benefits of prepared statement reuse.

Possible causes

JDBC driver / connection pool switching to server-side prepared statements so the server produces generic plans that prevent effective partition pruning.

95%

Large number of partitions increases cost of a generic plan; planner defaults to sequential scan over partitions when parameter values are unknown.

90%

Parameter binding with varying data types (setObject vs strongly-typed setters) causing planner to generalize and choose a generic plan.

55%

Application-level statement caching reuses prepared statements across different query shapes leading to suboptimal generic plans.

30%

Suggested fixes

1

Diagnostic step 1

In a staging environment, set the JDBC URL parameter prepareThreshold=0 (or equivalent for your driver) to force simple query mode and validate latency improvement; this is reversible by changing the JDBC config and restarting app pool.

2

Diagnostic step 2

If you want server-side prepares mostly enabled, lower the driver's server-side prepare threshold (e.g., increase prepare threshold to a higher number) and selectively use prepared statements only for queries that benefit from them.

3

Diagnostic step 3

Audit application code to use strongly-typed setter methods (setTimestamp, setInt) instead of setObject to reduce type ambiguity at the server planner.

4

Diagnostic step 4

Consider using explicit SQL with CASTed literals for hot queries or use EXECUTE with dynamic SQL where appropriate, or add custom prepared-statement invalidation when partition boundaries change.

5

Diagnostic step 5

As a longer-term fix, evaluate using prepared statement stabilization techniques: pg_hint_plan for targeted queries, increasing statistics on partition key columns, or PostgreSQL parameters like plan_cache_mode (if available) — test these in staging. If unsure, escalate to DBA for targeted query rewriting and plan inspection.

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