Understand MERGE matches

TutorialApplies to: Unified engine deployments

Match existing and incoming customers, then update an existing customer and insert a new one. The target is the stored table being changed. The source is the incoming set of rows. ON decides which source and target rows match. The WHEN clauses choose what happens to those rows. An upsert combines an update for an existing key with an insert for a new key.

Before you start

You need a writable Iceberg catalog with namespace creation, table creation, and MERGE support. These examples create format-v2 tables in a private namespace. They use inline data and do not need an external sample dataset. Choose an unused namespace. The examples use learn_merge_01. Replace it everywhere if it already exists. In Workbench, select your writable catalog before running any SQL. Keep that catalog selected throughout the lesson. Opening an example does not execute it.

Set up the namespace

Run this setup once:

SET spark.sql.caseSensitive = true;
CREATE NAMESPACE learn_merge_01;

Each example creates a separate table. Run an example’s setup once. To start it again, remove only that example’s table first, using the cleanup section. Scripts execute as separate operations; they are not a multi-statement transaction.

1. Update an existing customer and insert a new one

Start with these target rows:

id	name	balance	version	is_deleted
1	Ada	100	1	false
2	Ben	200	2	false
3	Cyd	300	1	false

CREATE TABLE learn_merge_01.first_upsert (id BIGINT, name STRING, balance BIGINT, version BIGINT, is_deleted BOOLEAN)
USING iceberg TBLPROPERTIES ('format-version' = '2');
INSERT INTO learn_merge_01.first_upsert VALUES (1, 'Ada', 100, 1, false), (2, 'Ben', 200, 2, false), (3, 'Cyd', 300, 1, false);

Apply the incoming source below:

MERGE INTO learn_merge_01.first_upsert AS t
USING (SELECT 2 AS id, 'Ben' AS name, 250 AS balance, 3 AS version, false AS is_deleted UNION ALL SELECT 4, 'Dan', 400, 1, false) AS s
ON t.id = s.id
WHEN MATCHED THEN UPDATE SET name = s.name, balance = s.balance, version = s.version
WHEN NOT MATCHED THEN INSERT (id,name,balance,version,is_deleted) VALUES (s.id,s.name,s.balance,s.version,s.is_deleted);

Check all rows:

SELECT id, name, balance, version, is_deleted FROM learn_merge_01.first_upsert;

Expect these exact rows, in any display order:

id	name	balance	version	is_deleted
1	Ada	100	1	false
2	Ben	250	3	false
3	Cyd	300	1	false
4	Dan	400	1	false

Change one thing

Start the relevant example again from its original target rows. Drop only that example table, rerun its CREATE TABLE and INSERT statements, then apply the changed MERGE. Keep the lesson namespace. Change customer 4 to customer 5 in the source. The final table should contain keys 1, 2, 3, and 5. Customer 2 should still have balance 250.

Check the result

Compare every row and field with the expected tables, including unchanged customers and the number of copies of each key. A Succeeded status alone is not the result check. Wait for confirmed publication before reading the target.

Clean up

Remove only the private tables created by this lesson:

DROP TABLE IF EXISTS learn_merge_01.first_upsert;
DROP NAMESPACE learn_merge_01;

Continue

Choose which rows MERGE updates or review the MERGE SQL reference.

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Understand MERGE matches

Before you start

Set up the namespace

1. Update an existing customer and insert a new one

Change one thing

Check the result

Clean up

Continue

​Before you start

​Set up the namespace

​1. Update an existing customer and insert a new one

​Change one thing

​Check the result

​Clean up

​Continue

Before you start

Set up the namespace

1. Update an existing customer and insert a new one

Change one thing

Check the result

Clean up

Continue