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Category: Triggers

Using Triggers for Change Tracking

Chad Callihan shows how you can roll your own change tracking with triggers:

Have you ever come across triggers being used to audit table changes? In this post, we’ll look at a few examples of DML triggers in action.

Click through for examples around tracking updates and last edit times, as well as creating audit tables for operations.

If you do go this route, Chad has an important warning. In addition, I appreciate that the statements in this example support multi-row updates. That’s something people often forget when writing triggers.

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Inserted and Deleted Scans

Hugo Kornelis has a two-parter for us. First up is the inserted scan operator:

The Inserted Scan operator is only found in execution plans for code in triggers. It is used for queries that read data from the inserted pseudo-table. Its counterpart, Deleted Scan, reads from the deleted pseudo-table.

This pseudo-table contains a copy of all the rows that were inserted in AFTER INSERT triggers, or the new content of the data in all affected rows in AFTER UPDATE triggers. In INSTEAD OF INSERT or INSTEAD OF UPDATE triggers, the data in the inserted pseudo-table is the data that would have been inserted, or the data as it would have been after the update. In AFTER DELETE and INSTEAD OF DELETE triggers, using the inserted pseudo-table is allowed but returns no data.

Then, the deleted scan:

This pseudo-table contains a copy of all rows that has just been deleted in AFTER DELETE triggers, or the original data of all affected rows in AFTER UPDATE triggers. In INSTEAD OF DELETE or INSTEAD OF UPDATE triggers, the data in the deleted pseudo-table is the current data in the rows that would have been deleted or updated. In AFTER INSERT and INSTEAD OF INSERT triggers, using the deleted pseudo-table is allowed but returns no data.

Click through to see how they work.

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Capturing Extended Properties when a Table is Dropped

Thomas Rushton attempts to preserve extended property history:

Custom extended properties can be a useful tool when creating a self-documenting database. However, in an environment where tables are routinely dropped and recreated by software/systems not within your control, it may be desirable to have these stored so they can be repopulated when the table is recreated.

Read on to learn about the results of each test. Also read on for a use of the term “faff” in its appropriate context.

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Improving Triggers

Ed Pollack tries to improve our usage of triggers:

SQL Server triggers are a subject of both functionality and controversy on any database platform. They can provide immense utility at a low cost, but are often misused by developers, DBAs, and architects alike, resulting in performance bottlenecks or maintainability challenges.

This article briefly reviews DML (data manipulation language) triggers and delves into a discussion about how triggers can be efficiently and effectively used as well as when triggers can dig developers into holes that are hard to escape.

Read the whole thing. Triggers are rather useful tools when used correctly, but it’s easy to misuse them on accident.

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Triggers Should Handle Multi-Row Scenarios

Kenneth Fisher has a public service announcement:

While I was helping him with part of it I noticed that the trigger was only set up to handle single row updates. When I told him it needed to be able to handle multiple row updates he asked me in all seriousness, “Why? Since only one value can be changed at a time why should I worry about multiple rows being changed at once?”

Read on for Kenneth’s response, which approximates to Au contraire mon frère. Unhandled assumptions often become bugs.

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Triggers and Isolation Levels

Louis Davidson walks us through a tricky problem:

Writing data integrity code in TRIGGER objects is generally is pretty simple. Typically you write a query to see “is there a row in inserted/deleted that is not set up as desired for the current transaction?” and no bad data is found, keep moving. And because MOST of the time, you would only use a TRIGGER object where transactions are quick coupled with the reality that a lot of the issues like I will describe would have to occur within milliseconds… concurrency issues seem to rarely occur. But…anything that isn’t impossible, is possible. Because of the rarity of the issue, if your code isn’t running a life of death system, when the anomalies happen, they are brushed off as “just something weird occurred”. 

This blog will cover one such weird occurrence that can happen when your trigger validation code queries another table in the default isolation level. You expect that your data is protected until your transaction ends, but it may not be.

Do read the whole thing.

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Accelerated Database Recovery and tempdb Usage

Jason Hall takes a look at how much tempdb space Accelerated Database Recovery might use:

You might have heard me talk about tempdb parasites in the past, or maybe you’ve read my blog post on the same topic, “Be Mindful of SQL Server Tempdb Use (aka Tempdb Parasites!).” I know that at least one person did, because they recently asked a great question.

In that blog post, I reviewed how triggers use the version store in tempdb for access to the “special” trigger tables we can use from within the trigger code to access the previous and new versions of data being modified. One person on Twitter was wondering if that is still the case for triggers on databases using Accelerated Database Recovery (ADR) in SQL Server 2019. I really wasn’t sure, so I decided to find out.

Click through for the answer.

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Reducing Trigger Executions

Jared Poche writes up a fun scenario he discovered:

I’ve never been a fan of triggers. I don’t like the idea of them adding an additional tax on every operation. It’s easy to forget they are even there, consuming your cycles. I’ve even seen a few nasty death-by-a-thousand-cuts scenarios with them. But I found something out this week that makes me like them even less.

I was tuning a procedure that runs 284 million times a day.

Over a number of servers and databases, but yes, that number is correct. It takes 2.5ms to run on average, with 1.0ms of CPU time. I’ll spare you the math, but that means over 3 cores of SQL Server are doing nothing but running this procedure 24/7/365. Anything we can do to improve this will be significant, even if we just shave off half a millisecond.

The best stories start with “I was tuning a procedure [which] runs 284 million times a day.”

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Creating Triggers with Cosmos DB

Hasan Savran shows how you can create a trigger in Cosmos DB:

You have options if you need to use any type of triggers in Cosmos DB. There are two types of triggers in Cosmos DB. First one which I will cover here is the regular triggers which can be executed before (Pre-Triggers) or after (Post-Triggers) an operation. This type of triggers is written in JavaScript and you need to register them to a collection just like stored procedures. Second type of triggers can be created by Azure Functions and you can find more information about them in my older posts.

     Pre-Triggers and Post-Triggers do not take any input parameters. Since Cosmos DB needs to work more work to execute triggers, you will end up with higher Request Units for your queries. They might name triggers, but both do not get executed automatically with every operation. You need to call them programmatically if you want to run them.  If trigger throws any error for any reason, transaction will roll back and data will not be saved to the database.

Naturally, triggers are going to have a performance impact on your system regardless of the choice of data platform.

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