Joining on NULLs

Published on: 2019-03-26

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It’s important to be aware of columns that allow NULL values since SQL Server may handle NULLs differently than you might expect.

Today I want to look at what things to consider when joining on columns containing NULL values.

Natural, Composite, NULLable keys

Let’s pretend we have an Account table containing the accounts of various users and an AccountType table describing the different types of accounts:

Account and AccountType tables

These tables have the unfortunate design characteristics of:

  1. They use a natural, composite key of YearOpened and AccountType
  2. NULL is the valid default for AccountType

Not that either of the above attributes are outright bad, just that we need to handle them appropriately. For example, if we want to bring back a description of each user’s account, we might write a query with an inner join like this:

SELECT
    a.UserId,
    at.YearOpened,
    at.AccountType,
    at.Description
FROM
    dbo.Account a
    INNER JOIN dbo.AccountType at
        ON a.YearOpened = at.YearOpened
        AND a.AccountType = at.AccountType

Only to discover the rows with NULLs are not present:

Inner join with no NULLs

Joining on NULLs

Since it’s not possible to join on NULL values in SQL Server like you might expect, we need to be creative to achieve the results we want.

One option is to make our AccountType column NOT NULL and set some other default value. Another option is to create a new column that will act as a surrogate key to join on instead.

Both of the above options would fix the problem at the source, but what about if we can only make changes to our queries?

One common approach is to convert the NULLs to some other non-NULL value using a function like COALESCE or ISNULL:

SELECT
    a.UserId,
    at.YearOpened,
    at.AccountType,
    at.Description
FROM
    dbo.Account a
    INNER JOIN dbo.AccountType at
        ON a.YearOpened = at.YearOpened
        AND ISNULL(a.AccountType,'`') = ISNULL(at.AccountType,'`')
Correct results with ISNULL

While this returns the results we want, there are two major issues with this approach:

  1. In the above example we converted NULLs to the ` character. If we had a valid ` character in our data, we would get logically incorrect joins.
  2. Our query can no longer perform index seeks.

The first issue isn’t a huge deal if you can guarantee the character you are replacing NULLs with will never appear in the column of data.

The second issue is more important since ISNULL prevents your query from being SARGable and will cause poor performance on large tables of data.

SARG Killer

Those Compute Scalar operators are forcing SQL Server to Scan the indexes and compute a value for every row.

A More Efficient Solution

If using a function like ISNULL hurts the performance of our queries, what can we do instead?

SELECT
    a.UserId,
    at.YearOpened,
    at.AccountType,
    at.Description
FROM
    dbo.Account a
    INNER JOIN dbo.AccountType at
        ON a.YearOpened = at.YearOpened
        AND (a.AccountType = at.AccountType OR (a.AccountType IS NULL AND at.AccountType IS NULL))
Correct results with efficiency

This produces the same exact results while allowing SQL Server to Seek when possible and avoid costly row by row computations:

There are no seeks here since I don’t have any additional filters, but the lack of Compute Scalar operators should be enough to prove the point.

While there are a few more variations that can achieve the same results using different execution plans (writing a query that joins non-nulls and unioning it with a query that selects only the nulls, using a computed column to convert the NULLs to non-null values, etc…) the key to good performance is to choose a solution that will not force SQL Server to compute values for every single row.

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One SSMS Trick That Will Make You a Faster Query Builder

Published on: 2017-07-25

SQL in 60 Seconds #3

17/365: i could be your magician” by Jin is licensed under CC BY 2.0

Here’s the scenario: you copy and paste some code into a query you are building. A few minutes later you need that same snippet again, but you’ve already copied and pasted something else onto the clipboard.

The next five minutes of your life are spent searching across the twenty query editor tabs you have open looking for that original piece of code.

Sound familiar?

THERE’S A BETTER WAY!

Copying and pasting is a feature that’s available in nearly every text editor (“nearly” — anyone remember the days before iOS had a clipboard?).

However, SQL Server Management Studio goes above and beyond the regular copy and paste feature set — it has a clipboard ring.

What’s a clipboard ring you ask?

The clipboard ring let’s you cycle through the last 20 things you copied onto your clipboard when you go to paste in SSMS. It can be accessed in the Edit menu (like in the screenshot above) or by using the keyboard shortcut CTRL + SHIFT + V.

Let’s say you have the following queries:

----------------- Query 1 --------------------------
SELECT FruitId FROM dbo.Fruits WHERE Name = 'Apple'
----------------- Query 2 --------------------------
SELECT FruitId FROM dbo.Fruits WHERE Name = 'Banana'
----------------- Query 3 --------------------------
SELECT FruitId FROM dbo.Fruits WHERE Name = 'Orange'

And let’s pretend you want to copy all of the fruit names into the IN statement of this query:

SELECT FruitId FROM dbo.Fruit WHERE Name IN ()

Instead of copying and pasting each fruit separately, you can batch your copies together and then paste them from the clipboard ring into your IN statement at the same time:

Use this trick the next time you need to find that snippet of code you used right before heading off to lunch and I guarantee you will be saving yourself tons of time.

 

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How to Use SQL Temporal Tables For Easy Point-In-Time Analysis

Published on: 2017-07-19

Bordeaux, The Grand Theatre” by Stefano Montagner is licensed under CC BY-NC-ND 2.0

Have you ever needed to look at what data in a table used to look like?

If you have, it probably took a knuckle-cracking filled session of writing group-by statements, nested sub-queries, and window functions to write your time-travelling query.

Sorry for your lost day of productivity — I’ve been there too.

Fortunately for us, SQL Server 2016 introduces a new feature to make our point-in-time analysis queries easy to write: temporal tables.

Temporal Tables? Are Those The Same As Temporary Tables?

Don’t let the similar sounding name fool you: “temporal” <> “temporary”.

Temporal tables consist of two parts:

  1. The temporal table — this is the table that contains the current values of your data.
  2. The historical table — this table holds all of the previous values that at some point existed in your temporal table.

You might have created a similar setup yourself in previous versions of SQL using triggers. However, using a temporal table is different from this because:

  1. You don’t need to write any triggers/stored procedures! All of the history tracking is done automatically by SQL Server.
  2. Retrieving the data uses a simple WHERE clause — no complex querying required.

I want to make my life easier by using temporal tables! Take my money and show me how!

I’m flattered by your offer, but since we are good friends I’ll let you in on these secrets for free.

First let’s create a temporal table. I’m thinking about starting up a car rental business, so let’s model it after that:

IF OBJECT_ID('dbo.CarInventory', 'U') IS NOT NULL 
BEGIN
 -- When deleting a temporal table, we need to first turn versioning off
 ALTER TABLE [dbo].[CarInventory] SET ( SYSTEM_VERSIONING = OFF  ) 
 DROP TABLE dbo.CarInventory
 DROP TABLE dbo.CarInventoryHistory
END
CREATE TABLE CarInventory   
(    
 CarId INT IDENTITY PRIMARY KEY,
 Year INT,
 Make VARCHAR(40),
 Model VARCHAR(40),
 Color varchar(10),
 Mileage INT,
 InLot BIT NOT NULL DEFAULT 1,
 SysStartTime datetime2 GENERATED ALWAYS AS ROW START NOT NULL,
 SysEndTime datetime2 GENERATED ALWAYS AS ROW END NOT NULL,
 PERIOD FOR SYSTEM_TIME (SysStartTime, SysEndTime)     
)   
WITH 
( 
 SYSTEM_VERSIONING = ON (HISTORY_TABLE = dbo.CarInventoryHistory)   
)

The key things to note with our new table above are that

  1. it contains a PRIMARY KEY.
  2. it contains two datetime2 fields, marked with GENERATED ALWAYS AS ROW START/END.
  3. It contains the PERIOD FOR SYSTEM_TIME statement.
  4. It contains the SYSTEM_VERSIONING = ON property with the (optional) historical table name (dbo.CarInventoryHistory).

If we query our newly created tables, you’ll notice our column layouts are identical:

SELECT * FROM dbo.CarInventory
SELECT * FROM dbo.CarInventoryHistory

Let’s fill it with the choice car of car rental agencies all across the U.S. — the Chevy Malibu:

INSERT INTO dbo.CarInventory (Year,Make,Model,Color,Mileage) VALUES(2017,'Chevy','Malibu','Black',0)
INSERT INTO dbo.CarInventory (Year,Make,Model,Color,Mileage) VALUES(2017,'Chevy','Malibu','Silver',0)
Although we got some unassuming car models, at least we can express our individuality with two different paint colors!

In all of the remaining screen shots, the top result is our temporal table dbo.CarInventory and the bottom result is our historical table dbo.CarInventoryHistory.

You’ll notice that since we’ve only inserted one row for each our cars, there’s no row history yet and therefore our historical table is empty.

Let’s change that by getting some customers and renting out our cars!

UPDATE dbo.CarInventory SET InLot = 0 WHERE CarId = 1
UPDATE dbo.CarInventory SET InLot = 0 WHERE CarId = 2

Now we see our temporal table at work: we updated the rows in dbo.CarInventory and our historical table was automatically updated with our original values as well as timestamps for how long those rows existed in our table.

After a while, our customers return their rental cars:

UPDATE dbo.CarInventory SET InLot = 1, Mileage = 73  WHERE CarId = 1
UPDATE dbo.CarInventory SET InLot = 1, Mileage = 488 WHERE CarId = 2
It’s totally possible for someone to have driven 73 or 488 miles in a Chevy Malibu in under 4 minutes…ever hear the phrase “drive it like a rental”?

Our temporal table show the current state of our rental cars: the customers have returned the cars back to our lot and each car has accumulated some mileage.

Our historical table meanwhile got a copy of the rows from our temporal table right before our last UPDATE statement. It’s automatically keeping track of all of this history for us!

Continuing on, business is going well at the car rental agency. We get another customer to rent our silver Malibu:

UPDATE dbo.CarInventory SET InLot = 0 WHERE CarId = 2

Unfortunately, our second customer gets into a crash and destroys our car:

DELETE FROM dbo.CarInventory WHERE CarId = 2
The customer walked away from the crash unscathed; the same can not be said for our profits.

With the deletion of our silver Malibu, our test data is complete.

Now that we have all of this great historically tracked data, how can we query it?

If we want to reminisce about better times when both cars were damage free and we were making money, we can write a query using SYSTEM_TIME AS OFto show us what our table looked like at that point in the past:

SELECT
 *
FROM 
 dbo.CarInventory
FOR SYSTEM_TIME AS OF '2017-05-18 23:49:50'
The good old days.

And if we want to do some more detailed analysis, like what rows have been deleted, we can query both temporal and historical tables normally as well:

-- Find the CarIds of cars that have been wrecked and deleted
SELECT DISTINCT
 h.CarId AS DeletedCarId
FROM
 dbo.CarInventory t
 RIGHT JOIN dbo.CarInventoryHistory h
  ON t.CarId = h.CarId 
WHERE 
 t.CarId IS NULL

C̶o̶l̶l̶i̶s̶i̶o̶n̶ Conclusion

Even with my car rental business not working out, at least we were able to see how SQL Server’s temporal tables helped us keep track of our car inventory data.

I hope you got as excited as I did the first time I saw temporal tables in action, especially when it comes to querying with FOR SYSTEM_TIME AS OF. Long gone are the days of needing complicated queries to rebuild data for a certain point in time.

 

Thanks for reading. You might also enjoy following me on Twitter.

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