Insert data in 3 tables at a time using Postgres

sql

transactional-integrity

concurrent-writes

temporary-tables

byAlex Kataev·Nov 2, 2024

Leverage CTE in PostgreSQL to insert data into multiple tables with interdependencies. The following example shows how to sequentially perform inserts into table1, table2, and table3. The RETURNING clause captures each new id from table1 and table2 for use as a foreign key in the subsequent inserts.

-- Fasten your seatbelt, we're about to go data-driving! 🚀
WITH insert1 AS (
  INSERT INTO table1 (col1) VALUES ('val1') RETURNING id -- Super secret spy id returns from the mission 🕵️‍♂️ 
),
insert2 AS (
  INSERT INTO table2 (table1_id, col2) 
  SELECT id, 'val2' FROM insert1 RETURNING id -- id comes back with a new friend
)
INSERT INTO table3 (table2_id, col3)
SELECT id, 'val3' FROM insert2; -- id's final tour 🏁

Run this SQL command where col1, col2, and col3 are your columns and val1, val2, val3 are the values you'd like to insert. The newly generated id in each table is passed on to the next insert operation.

Ensuring Data Consistency and Handling Duplicates

In multi-table insertion, ensuring data consistency comes first. Make certain to use explicit foreign key constraints to maintain the integrity of your interdependent table links.

While duplicates might be great in your CD collection, they're band practice in data. Appearances of UNIQUE constraints in key columns get you ready for this concert. For a successful audience response, use the ON CONFLICT clause, enabling you to manage conflicts gracefully during inserts:

-- Say NO to clones! 🚫👥
INSERT INTO table1 (col1)
VALUES ('unique_value')
ON CONFLICT (col1) DO NOTHING; -- Takes a step back when a doppelganger appears

The above ensures a successful encore (i.e., insert) only when the crowd (i.e., table1) doesn't already know the tune (i.e., unique_value). When a potential crowd surfer (i.e., conflict) is sighted, security (i.e., DO NOTHING) steps in.

Upkeep of Transactional Integrity and Reusable SQL Patterns

Transactional integrity ensures that your data isn’t left hanging in an inconsistent state. Encase the total insertion procedure within BEGIN...COMMIT commands. This makes sure all your inserts succeed or fail as a team. No band member left behind!

Furthermore, consider embodying recurring SQL patterns within stored procedures or functions. These provide you with a repeatable, alterable chunk of SQL that lets you manage complex multi-table inserts.

Dealing with Concurrent Writes

Concurrent writes can be as problematic as a device running out of battery in the middle of a binge-watch session. To make sure you continue to enjoy uninterrupted, PostgreSQL provides locking mechanisms and transaction isolation levels. These tackle concurrency and handle conflicts as well as your device handles multiple app installations:

-- One operation at a time, keeps the data in line.
BEGIN;
LOCK TABLE table1 IN SHARE ROW EXCLUSIVE MODE; -- Place a reserved sign on table1 📛
WITH insert1 AS (
  INSERT INTO table1 (col1) VALUES ('val1') RETURNING id
)
-- conduct the rest of the inserts...
COMMIT;

Maximizing Values using Temporary Tables and CTEs

When dealing with complex insert operations, temporary tables or CTEs can be leveraged as docking stations for your data. This strategy shines especially when handling large data sets or when complex manipulation is required before the data is ready for insertion:

BEGIN;
CREATE TEMPORARY TABLE tmp_data AS
SELECT data_col1, data_col2 FROM source_table WHERE condition; -- Oh look, a wild temporary table has appeared!

-- Insert from the new temporary table into the destination tables
-- ...

DROP TABLE tmp_data; -- Just like Thanos, it disappears once the mission is complete
COMMIT;