9/3/2023 0 Comments Mysql batch update![]() ![]() Session.scalars() is used to allowĬhanged in version 2.0: The ORM Session now interprets RETURNINGĮven Delete constructs in an ORM context, meaning a mixture UpdateBase.returning() method, passing the full User entityĪs what we’d like to return. With the exception of MySQL (MariaDB is included).Īs an example, we can run the same statement as before, adding use of the With RETURNING this feature is available with all Supports SQL RETURNING syntax as well as support for executemany INSERT.RETURNING requires the use of a backend that The bulk ORM insert feature supports INSERT.RETURNING for selectedīackends, which can return a Result object that may yield individualĬolumns back as well as fully constructed ORM objects corresponding Core-style functionality is available by passing In a Core-centric way, using column names for value keys ORM attribute This is a behavior changeĬompared to the 1.x series where the Insert would be interpreted Makes use of the same functionality as the legacy Session.execute() method now invokes a “bulk insert”, which A list of parameterĭictionaries sent to the parameter, separateįrom the Insert object itself, will invoke bulk INSERT modeįor the statement, which essentially means the operation will optimizeĬhanged in version 2.0: Passing an Insert construct to the ORM UPDATE and DELETE with Custom WHERE CriteriaĪ insert() construct can be constructed in terms of an ORM classĪnd passed to the Session.execute() method. ORM Bulk Insert with Per Row SQL Expressions The following table summarizes the calling forms that are discussed in this Make use of UPDATE for rows that already exist. There is also dialect-specific supportįor ORM-enabled “upserts”, which are INSERT statements that automatically In various ways which are each used to INSERT, UPDATE, or DELETE Select objects, can also accommodate ORM-enabled The Session.execute() method, in addition to handling ORM-enabled Mappings shown in the section Mapping Class Inheritance Hierarchies. SQLAlchemy Unified Tutorial, shown in the sectionĭeclaring Mapped Classes, as well as inheritance This section makes use of ORM mappings first illustrated in the ORM-Enabled INSERT, UPDATE, and DELETE statements.Previous: Writing SELECT statements for Inheritance Mappings.UPDATE/DELETE with Custom WHERE Criteria for Joined Table Inheritance.Using RETURNING with UPDATE/DELETE and Custom WHERE Criteria.ORM UPDATE and DELETE with Custom WHERE Criteria.Bulk UPDATE by Primary Key for Joined Table Inheritance.Disabling Bulk ORM Update by Primary Key for an UPDATE statement with multiple parameter sets.ORM Bulk Insert with Per Row SQL Expressions.Bulk INSERT for Joined Table Inheritance.Using Heterogenous Parameter Dictionaries.Correlating RETURNING records with input data order.ORM-Enabled INSERT, UPDATE, and DELETE statements ¶.Writing SELECT statements for Inheritance Mappings.Writing SELECT statements for ORM Mapped Classes. ![]() Insert into foo_tmp (id, category, animal) values changes to make animal a bit more specific. Insert into foo (id, category, animal) values Would love to have a DBA's thoughts on whether this is as efficient as the recommended "why don't we do it in a trans?" approach. Usually, when I've had to do this, I've created a temporary table, inserted my changes into that, and then done an update with the join as shown below. `b` bigint(20) unsigned NOT NULL DEFAULT '0', `a` bigint(20) unsigned NOT NULL DEFAULT '0', `id` int(10) unsigned NOT NULL AUTO_INCREMENT, I've removed column names due to them being irrelevant. If there really isn't a way that's faster than ON DUPLICATE KEY, would it be worth it to switch to PostgreSQL and use its UPDATE FROM syntax?Īny other suggestions are also greatly appreciated!Įdit: here's one of the tables that gets updated frequently. It baffles me that, as far as I can tell, there's no idiomatic, efficient way to do this in MySQL. Would either of these be faster than my current method? (which would be hard to generate due to the way I'm building the queries, and I'm not sure about the performance of CASE for hundreds/thousands of keys), and simply multiple concatenated updates. Other approaches I've seen are to update using SET value = CASE WHEN. I don't ever actually need to insert rows. VALUES (.), (.) ON DUPLICATE KEY UPDATE, which works to batch all of the values into one query, but executes excruciatingly slowly on large tables. I'm writing an application that needs to flush out a large number of updates to the database for an extended period of time, and I've gotten stuck at how to optimize the query. ![]()
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