Parallel Query Execution in PostgreSQL

1. Introduction

Parallel Query Execution in PostgreSQL allows the database to utilize multiple CPU cores to execute a single query simultaneously. This can significantly improve performance, particularly for large datasets or complex queries.

2. Key Concepts

• **Parallelism**: The process of dividing a task into smaller sub-tasks that can be executed concurrently.
• **Workers**: Additional processes that assist in executing a query in parallel.
• **Gather Node**: A node in the execution plan that collects results from multiple parallel workers.

3. How It Works

The PostgreSQL planner determines whether a query can benefit from parallel execution based on its cost and the system's configuration. If it can, it creates a plan that includes parallel workers and a Gather node.

graph TD;
    A[Start] --> B{Is query parallelizable?};
    B -- Yes --> C[Create parallel plan];
    B -- No --> D[Execute sequentially];
    C --> E[Assign workers];
    E --> F[Execute tasks];
    F --> G[Gather results];
    G --> H[Return results];
            

4. Configuration

To enable parallel query execution, certain configuration parameters need to be set in the postgresql.conf file:

# Enable parallel query execution
max_parallel_workers = 8
max_parallel_workers_per_gather = 4
        

These settings dictate how many parallel workers can be used across all queries and for each individual query, respectively.

5. Best Practices

• Analyze your queries to identify those that could benefit from parallel execution.
• Monitor system resources to ensure parallel execution does not overwhelm the server.
• Test performance impact: Always benchmark query performance before and after enabling parallel execution.
• Consider the workload: Parallel execution is not always beneficial for small datasets.

6. FAQ