Query Optimization with HypoPG

Query optimization is a critical aspect of database performance tuning. While YugabyteDB’s YSQL API provides powerful tools for analyzing query performance through EXPLAIN plans, sometimes we need to experiment with different indexing strategies without the overhead of actually creating the indexes. This is where HypoPG comes in handy.

Understanding HypoPG

HypoPG is a PostgreSQL extension that allows you to create hypothetical indexes and see how they would affect your query plans without actually creating the indexes. This is particularly useful when:

• You want to test multiple indexing strategies quickly
• You need to evaluate the potential impact of indexes on large tables
• You’re working in a production environment where creating test indexes isn’t feasible

A Practical Example

Let’s walk through a practical example of using HypoPG to optimize a query. First, we’ll create a sample table:

-- create the table
CREATE TABLE orders (
    order_id SERIAL PRIMARY KEY,
    customer_id INTEGER NOT NULL,
    order_date TIMESTAMP NOT NULL
);

Now, let’s say we frequently run queries to list orders for specific customers:

EXPLAIN SELECT order_id, customer_id FROM orders WHERE customer_id=557;

The initial EXPLAIN plan shows a sequential scan due to the filtering on customer_id.

QUERY PLAN
--------------------
 Seq Scan on orders  (cost=0.00..102.50 rows=1000 width=8)
   Storage Filter: (customer_id = 557)
(2 rows)

Set up the extension:

-- install the extension if not already installed
create extension if not exists hypopg;

Let’s use HypoPG to test if a composite index would help:

-- create a hypothetical index to test
SELECT hypopg_create_index('CREATE INDEX idx_orders_1 ON orders(customer_id)');

-- check the query plan with the first hypothetical index
EXPLAIN SELECT order_id FROM orders WHERE customer_id=557;

The explain plan shows an index scan, good!

-- explain plan
QUERY PLAN
-------------------
 Index Scan using <13258>lsm_orders_customer_id on orders  (cost=0.00..4.01 rows=1000 width=4)
   Index Cond: (customer_id = 557)
(2 rows)

Now let’s create a covering index to see if there would be improvement:

-- create a better, covering hypothetical index to test
SELECT hypopg_create_index('CREATE INDEX idx_orders_2 ON orders(customer_id) include (order_id)');

-- check the query plan with the second hypothetical index
EXPLAIN SELECT order_id FROM orders WHERE customer_id=557;

The explain plan shows an Index Only Scan, even better!

QUERY PLAN
-------------------
 Index Only Scan using <13259>lsm_orders_customer_id_order_id on orders  (cost=0.00..4.01 rows=1000 width=4)
   Index Cond: (customer_id = 557)
(2 rows)

Analyzing the Results

If the hypothetical index shows significant improvement in the query plan, you can create the actual index. In YugabyteDB, you have the option to create the index concurrently to minimize impact on ongoing operations.

The CONCURRENTLY option is particularly valuable in distributed systems like YugabyteDB, as it allows index creation without blocking writes to the table.

-- create the index for real
CREATE INDEX CONCURRENTLY idx_orders_customerid_orderid
ON orders(customer_id) include (order_id);

-- remove the hypothetical indexes
SELECT hypopg_reset();

-- run the explain plan again to confirm the index only scan is being used
EXPLAIN SELECT order_id FROM orders WHERE customer_id=557;

Success!

QUERY PLAN
-----------------------
 Index Only Scan using idx_orders_customerid_orderid on orders  (cost=0.00..5.12 rows=10 width=4)
   Index Cond: (customer_id = 557)
(2 rows)

Session Management

Remember that hypothetical indexes are session-specific. They disappear when your session ends or when you explicitly reset them. This makes HypoPG perfect for testing without affecting other users.

Summary

HypoPG is a powerful tool for query optimization in YugabyteDB, allowing you to:

• Test index strategies without the overhead of actual index creation
• Compare multiple indexing approaches quickly
• Make data-driven decisions about index implementation
• Optimize queries in a safe, isolated environment

When combined with YugabyteDB’s distributed architecture and YSQL compatibility, HypoPG helps database engineers make informed decisions about index creation and query optimization while maintaining system performance and availability.