postgresqlinsert-updateupsertsql-merge

How to UPSERT (MERGE, INSERT ... ON DUPLICATE UPDATE) in PostgreSQL?


A very frequently asked question here is how to do an upsert, which is what MySQL calls INSERT ... ON DUPLICATE UPDATE and the standard supports as part of the MERGE operation.

Given that PostgreSQL doesn't support it directly (before pg 9.5), how do you do this? Consider the following:

CREATE TABLE testtable (
    id integer PRIMARY KEY,
    somedata text NOT NULL
);

INSERT INTO testtable (id, somedata) VALUES
(1, 'fred'),
(2, 'bob');

Now imagine that you want to "upsert" the tuples (2, 'Joe'), (3, 'Alan'), so the new table contents would be:

(1, 'fred'),
(2, 'Joe'),    -- Changed value of existing tuple
(3, 'Alan')    -- Added new tuple

That's what people are talking about when discussing an upsert. Crucially, any approach must be safe in the presence of multiple transactions working on the same table - either by using explicit locking, or otherwise defending against the resulting race conditions.

This topic is discussed extensively at Insert, on duplicate update in PostgreSQL?, but that's about alternatives to the MySQL syntax, and it's grown a fair bit of unrelated detail over time. I'm working on definitive answers.

These techniques are also useful for "insert if not exists, otherwise do nothing", i.e. "insert ... on duplicate key ignore".


Solution

  • 9.5 and newer:

    PostgreSQL 9.5 and newer support INSERT ... ON CONFLICT (key) DO UPDATE (and ON CONFLICT (key) DO NOTHING), i.e. upsert.

    Comparison with ON DUPLICATE KEY UPDATE.

    Quick explanation.

    For usage see the manual - specifically the conflict_action clause in the syntax diagram, and the explanatory text.

    Unlike the solutions for 9.4 and older that are given below, this feature works with multiple conflicting rows and it doesn't require exclusive locking or a retry loop.

    The commit adding the feature is here and the discussion around its development is here.


    If you're on 9.5 and don't need to be backward-compatible you can stop reading now.


    9.4 and older:

    PostgreSQL doesn't have any built-in UPSERT (or MERGE) facility, and doing it efficiently in the face of concurrent use is very difficult.

    This article discusses the problem in useful detail.

    In general you must choose between two options:

    Individual row retry loop

    Using individual row upserts in a retry loop is the reasonable option if you want many connections concurrently trying to perform inserts.

    The PostgreSQL documentation contains a useful procedure that'll let you do this in a loop inside the database. It guards against lost updates and insert races, unlike most naive solutions. It will only work in READ COMMITTED mode and is only safe if it's the only thing you do in the transaction, though. The function won't work correctly if triggers or secondary unique keys cause unique violations.

    This strategy is very inefficient. Whenever practical you should queue up work and do a bulk upsert as described below instead.

    Many attempted solutions to this problem fail to consider rollbacks, so they result in incomplete updates. Two transactions race with each other; one of them successfully INSERTs; the other gets a duplicate key error and does an UPDATE instead. The UPDATE blocks waiting for the INSERT to rollback or commit. When it rolls back, the UPDATE condition re-check matches zero rows, so even though the UPDATE commits it hasn't actually done the upsert you expected. You have to check the result row counts and re-try where necessary.

    Some attempted solutions also fail to consider SELECT races. If you try the obvious and simple:

    -- THIS IS WRONG. DO NOT COPY IT. It's an EXAMPLE.
    
    BEGIN;
    
    UPDATE testtable
    SET somedata = 'blah'
    WHERE id = 2;
    
    -- Remember, this is WRONG. Do NOT COPY IT.
    
    INSERT INTO testtable (id, somedata)
    SELECT 2, 'blah'
    WHERE NOT EXISTS (SELECT 1 FROM testtable WHERE testtable.id = 2);
    
    COMMIT;
    

    then when two run at once there are several failure modes. One is the already discussed issue with an update re-check. Another is where both UPDATE at the same time, matching zero rows and continuing. Then they both do the EXISTS test, which happens before the INSERT. Both get zero rows, so both do the INSERT. One fails with a duplicate key error.

    This is why you need a re-try loop. You might think that you can prevent duplicate key errors or lost updates with clever SQL, but you can't. You need to check row counts or handle duplicate key errors (depending on the chosen approach) and re-try.

    Please don't roll your own solution for this. Like with message queuing, it's probably wrong.

    Bulk upsert with lock

    Sometimes you want to do a bulk upsert, where you have a new data set that you want to merge into an older existing data set. This is vastly more efficient than individual row upserts and should be preferred whenever practical.

    In this case, you typically follow the following process:

    For example, for the example given in the question, using multi-valued INSERT to populate the temp table:

    BEGIN;
    
    CREATE TEMPORARY TABLE newvals(id integer, somedata text);
    
    INSERT INTO newvals(id, somedata) VALUES (2, 'Joe'), (3, 'Alan');
    
    LOCK TABLE testtable IN EXCLUSIVE MODE;
    
    UPDATE testtable
    SET somedata = newvals.somedata
    FROM newvals
    WHERE newvals.id = testtable.id;
    
    INSERT INTO testtable
    SELECT newvals.id, newvals.somedata
    FROM newvals
    LEFT OUTER JOIN testtable ON (testtable.id = newvals.id)
    WHERE testtable.id IS NULL;
    
    COMMIT;
    

    Related reading

    What about MERGE?

    SQL-standard MERGE actually has poorly defined concurrency semantics and is not suitable for upserting without locking a table first.

    It's a really useful OLAP statement for data merging, but it's not actually a useful solution for concurrency-safe upsert. There's lots of advice to people using other DBMSes to use MERGE for upserts, but it's actually wrong.

    Other DBs: