Using FULL JOINs to Compare Datasets

Question

Using FULL JOINs to Compare Datasets

markoos1

SSChasing Mays

Points: 653
More actions
September 25, 2010 at 1:16 pm

#238779

Comments posted to this topic are about the item Using FULL JOINs to Compare Datasets

Viewing 15 posts - 1 through 15 (of 23 total)

You must be logged in to reply to this topic. Login to reply

jensgc Mr or Mrs. 500 Points: 554 More actions · Answer 1

The FULL OUTER JOIN method shown in the article has one major flaw compared to the EXCEPT method - identical rows are not excluded from the result set. With the example data provided it doesn't make a difference since the update ensures that there are differences in all rows - but in a real world example there will often be many identical rows and only a rather small number of differences to check (the last statement filtering out differences under a given tolerance only helps if it is possible to provide such a tolerance value - and it doesn't address the issue where a difference can occur in any number of fields.

The OUTER JOIN is still a good method to be able to compare source and destination tables - but I would combine it with the EXCEPT statement in order to only look at rows with actual differences.

Hugo Kornelis SSC Guru Points: 64790 More actions · Answer 2

But you can of course add a WHERE clause to exclude the identical rows (like the final example, where small differences were excluded - change the requirement to an exact match, and you get all differences, but no matching rows..

Hugo Kornelis, SQL Server/Data Platform MVP (2006-2016)
Visit my SQL Server blog: https://sqlserverfast.com/blog/
SQL Server Execution Plan Reference: https://sqlserverfast.com/epr/

jensgc Mr or Mrs. 500 Points: 554 More actions · Answer 3

Agreed - however if the tables have a lot of fields instead, the where clause will be long and tedious to maintain.

markoos1 SSChasing Mays Points: 653 More actions · Answer 4

It's not so bad to maintain. You just have to extend the WHERE clause:

WHERE ABS(RandomNumberDiff) > @Tolerance

to the following:

WHERE (

ABS(RandomNumberDiff) > @Tolerance

OR ABS(RandomNumberDiff2) > @Tolerance

OR ABS(RandomNumberDiff3) > @Tolerance

...

)

to get the desired result. If you had 50 columns to compare, then it would make sense to generate this code using a query off INFORMATION_SCHEMA.COLUMNS.

This is definitely a real-world technique. We're using it at my company to compare 10's of thousands of rows across over 20 columns to reconcile datasets from disparate systems.

In the next chapter of this article I'll explain why it's useful to have the exact differences like this, and not just the identification of rows that are different from source to destination.

TheSQLGuru SSC Guru Points: 134017 More actions · Answer 5

Nicely written and detailed article. I like the mechanism too.

Best,
Kevin G. Boles
SQL Server Consultant
SQL MVP 2007-2012
TheSQLGuru on googles mail service

sjsubscribe SSCrazy Points: 2080 More actions · Answer 6

Nice solution that has great utility if extended to other data types with tolerances for dates, times, text, and binary values as well.

Trey Staker SSCarpal Tunnel Points: 4796 More actions · Answer 7

Thanks for the article!

---------------------------------------------------------------------
Use Full Links:
KB Article from Microsoft on how to ask a question on a Forum

shannonjk SSCarpal Tunnel Points: 4286 More actions · Answer 8

Good article though the Except part at the beginning seems superfluous and unnecessary. If you wanted to compare data sets to see variation then I don't know why an Except query would even come to mind.

This seems like the next intuitive step to compare a data set after you have done an Except query and have determined there are records in your data set that do not match.

My nitpickyness (is that a word?) aside, this is a great article 😀

Link to my blog http://notyelf.com/

markoos1 SSChasing Mays Points: 653 More actions · Answer 9

ShannonJk,

Thanks for the positive feedback, much appreciated!

I was just reviewing the EXCEPT query syntax at the top as it's the classic way to test for dataset deviations. I needed to set the context for situations where EXCEPT is appropriate before discussing where it's not.

In practice, if I were to run an EXCEPT query in some of the situations that I use the FULL JOIN, it would return many thousands of rows, with miniscule deviations. I can safely assume that the two datasets in these situations will never match exactly, which is why I go directly to the FULL JOIN technique to find the exact deviations.

-Mark

rchantler SSCrazy Points: 2128 More actions · Answer 10

Good article, but are you actually creating random numbers in your example, using NewID()? Random and pseudo-random numbers have properties that this technique may not create.

markoos1 SSChasing Mays Points: 653 More actions · Answer 11

I'm just using the NEWID() function as a way to create unique random numbers for each row. When you use RAND() in a query like this, it generates the same number for each row.

This is just for illustration in this example. In real situations, the numeric measures come from the source and destination queries, and aren't random numbers.

le_billy Old Hand Points: 312 More actions · Answer 12

Thank you for the great article, I am seeing some work cut out for me to improve my previously written query 😀

Billy

Hardy21 SSCrazy Eights Points: 9708 More actions · Answer 13

Hardy21

SSCrazy Eights

Points: 9708

September 27, 2010 at 10:37 pm

#1228141

Nice article and good examples. Thanks

Thanks

Misha_SQL SSCertifiable Points: 5407 More actions · Answer 14

I love the articles with examples which work "out of the box". This is one of those. These very helpful techniques are going into my tool box. Thank you!