- #POSTGRESQL INSERT CONFLICT UPDATE#
- #POSTGRESQL INSERT CONFLICT FULL#
- #POSTGRESQL INSERT CONFLICT CODE#
In PostgreSQL, when a row is updated, the actual process is to mark the original row deleted (old value) and then insert a new row (new value). On the other hand, in the case of INSERT.ON CONFLICT DO NOTHING, because of the pre-check, no dead tuples are generated, and the count(*) completes much faster, as expected for just one row in the table.
#POSTGRESQL INSERT CONFLICT FULL#
To count the actual visible rows, the entire table has to be scanned, and when it’s full of dead tuples, it takes considerably longer. The difference in time is because of the 1 million dead tuples generated in the first case by the regular duplicate inserts.
This change eliminates the overhead of performing the insert, finding out that it is a duplicate, and marking it as a dead tuple.įor example, the following is a simple select query on a table that attempted 1 million regular inserts that were duplicates: Other sessions can wait for the speculative insertion to be confirmed, turning it into a regular tuple, or canceled, as if it never existed and therefore never made visible. HEAP_INSERT_IS_SPECULATIVE is used on so-called speculative insertions, which can be backed out afterwards without canceling the whole transaction.
#POSTGRESQL INSERT CONFLICT CODE#
Back in version 9.5, this code was modified (along with a lot of other code) to incorporate speculative inserts. The heap_insert () function is used to insert a tuple into a heap.
This pre-check avoids the overhead of inserting a tuple into the heap to later delete it in case it turns out to be a duplicate. If the insertion succeeds without detecting a conflict, the tuple is deemed inserted.”
#POSTGRESQL INSERT CONFLICT UPDATE#
If the pre-check finds a matching tuple the alternative DO NOTHING or DO UPDATE action is taken. If a violating tuple was inserted concurrently, the speculatively inserted tuple is deleted and a new attempt is made. It is an optimistic variant of regular insertion that first does a pre-check for existing tuples and then attempts an insert. “This is implemented using a new infrastructure called ‘speculative insertion’. The following excerpt of the commit message adding the INSERT.ON CONFLICT clause describes the improvement: In the following sections, we examine the performance impact, bloat considerations, transaction ID acceleration and autovacuum impact, and finally storage impact of a regular INSERT vs. Although the end results appear identical (no rows inserted), there are important differences when you use the ON CONFLICT DO NOTHING clause.
The INSERT 0 0 indicates that while nothing was inserted in the table, the query didn’t error out. Let’s look at simple examples of each type of insert, starting with a regular INSERT: The following table outlines the advantages of the ON CONFLICT DO NOTHING clause. Let’s compare the case of attempting to insert a duplicate value with and without the ON CONFLICT DO NOTHING clause. The usage and requirements for all these types differ, and they all have a different impact on the performance of the database. In PostgreSQL, an insert statement can contain several clauses, such as simple insert with the values to be put into a table, an insert with the ON CONFLICT DO NOTHING clause, or an insert with the ON CONFLICT DO UPDATE SET clause. Understanding the differences between INSERT and INSERT.ON CONFLICT This information applies to PostgreSQL whether self-managed or hosted in Amazon Relational Database Service (Amazon RDS) for PostgreSQL or Amazon Aurora PostgreSQL-Compatible Edition. In this post, we examine the performance impact, storage impact, and autovacuum considerations for both the normal INSERT and INSERT.ON CONFLICT clauses. This seems like an intuitive approach, but relying on this optimistic insert can quickly have a negative performance impact on your database. The “duplicate key violates unique constraint” error notifies the caller that a retry is needed. A common coding strategy is to have multiple application servers attempt to insert the same data into the same table at the same time and rely on the database unique constraint to prevent duplication.
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