Oracle to PostgreSQL Migration Series – NoValidate and Parallel Constraints in PostgreSQL

Can you implement NoValidate and Parallel Constraints in PostgreSQL? Oracle to PostgreSQL Migration Blog series



PostgreSQL does not have a direct equivalent to Oracle’s NOVALIDATE option for constraints. However, there are some strategies to achieve similar functionality and improve performance when adding constraints to large tables. Additionally, PostgreSQL offers powerful parallel query capabilities that can enhance constraint validation and overall query performance.

NOVALIDATE-like Functionality in PostgreSQL

While PostgreSQL doesn’t have a NOVALIDATE option, you can achieve similar results using the following approaches:

1. Partial Unique Indexes

For unique constraints, you can create a partial unique index that excludes existing data:

CREATE UNIQUE INDEX idx_unique_constraint 
ON table_name (column1, column2) 
WHERE some_condition;

2. Deferred Constraints

For foreign key constraints, you can use deferred constraints:

ALTER TABLE child_table 
ADD CONSTRAINT fk_constraint 
FOREIGN KEY (column_name) 
REFERENCES parent_table (column_name) 
DEFERRABLE INITIALLY DEFERRED;

3. CHECK Constraints with Exclusions

For CHECK constraints, you can create a constraint that excludes existing data:

ALTER TABLE table_name 
ADD CONSTRAINT check_constraint 
CHECK (column_name > 0 OR created_at < '2025-01-10');

Parallel Query Implementation in PostgreSQL

PostgreSQL offers robust parallel query capabilities that can significantly improve performance, including constraint validation on large tables.

Enabling Parallel Queries

To enable parallel queries:

  • Set max_parallel_workers_per_gather to a value greater than 0:
SET max_parallel_workers_per_gather = 4;
  • Ensure parallel_setup_cost and parallel_tuple_cost are set appropriately:
SET parallel_setup_cost = 1000;
SET parallel_tuple_cost = 0.1;

Example of Parallel Query Execution

Consider a large table with millions of rows:

CREATE TABLE large_table (
    id SERIAL PRIMARY KEY,
    value INTEGER,
    created_at TIMESTAMP
);

INSERT INTO large_table (value, created_at)
SELECT random() * 1000000, 
       now() - interval '1 day' * random() * 365
FROM generate_series(1, 10000000);

Now, let’s add a CHECK constraint using parallel query execution:

EXPLAIN ANALYZE 
ALTER TABLE large_table 
ADD CONSTRAINT check_value 
CHECK (value >= 0 AND value <= 1000000);

The query plan might show parallel workers being used to validate the constraint:

Gather  (cost=1000.00..1234567.89 rows=10000000 width=6)
  Workers Planned: 4
  ->  Parallel Seq Scan on large_table
        (cost=0.00..1234567.89 rows=2500000 width=6)
        Filter: ((value >= 0) AND (value <= 1000000))

This parallel execution can significantly reduce the time required to validate constraints on large tables.

Best Practices

  • Use partial indexes or exclusion conditions when adding constraints to large tables with existing data.
  • Consider using deferred constraints for foreign keys in bulk operations.
  • Enable parallel query execution for constraint validation on large tables.
  • Monitor query plans using EXPLAIN ANALYZE to ensure parallel execution is being utilized effectively.
  • Adjust parallel query settings based on your specific hardware and workload characteristics.

By leveraging these strategies, you can achieve better performance when working with constraints on large tables in PostgreSQL, even without a direct NOVALIDATE equivalent.

How to Implement a unique constraint in PostgreSQL when NULL conflicts with everything

Unlocking Efficiency: Enhancing INSERT Performance in InnoDB – Practical Examples and Execution Plans

Preventing Broken Foreign Keys in PostgreSQL: Causes and Solutions

Step-by-Step Guide for Optimizing PostgreSQL Queries with Partial Indexes

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