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RE: Using FULL JOINs to Compare Datasets

lunds007 — Wed, 01 May 2013 15:48:08 GMT

EXCEPT Shouldn't really be used when comparing tables with lots of columns. Investigating which fields are actually different will take more time than using the FULL OUTER JOIN with Where clause to filter on only non matched records. If your compare query has an added column to tell you which column(s) are not matching, then you won't spend time investigating which fields are different.

RE: Using FULL JOINs to Compare Datasets

Carla Wilson-484785 — Wed, 24 Apr 2013 07:16:57 GMT

[quote][b]tom.w.brannon (4/23/2013)[/b][hr]The calculation of the column ISNULL(S.RandomNumber, 0) - ISNULL(D.RandomNumber, 0) AS RandomNumberDiffrequires some attention. It is important to choose a numeric value that is far from your threshold number or it will yeild incorrect results. For example if the RandomNumber value in one set is 0 and the key is missing in the other then the difference will calculate as 0, even though they actually are not equal. If no good dummy value is apparent then logic like the following is needed:SELECT COALESCE(S.ID, D.ID) AS ID, S.RandomNumber AS SrcRandomNumber, D.RandomNumber AS DestRandomNumber, S.RandomNumber - D.RandomNumber AS RandomNumberDiff FROM SRC S FULL JOIN DEST D ON S.ID = D.ID WHERE ABS(S.RandomNumber - D.RandomNumber) > @Tolerance or (S.RandomNumber is null and D.RandomNumber is not null) or (S.RandomNumber is not null and D.RandomNumber is null);[/quote]+1 I actually prefer retaining the nulls, and testing for those conditions as well.

RE: Using FULL JOINs to Compare Datasets

tom.w.brannon — Tue, 23 Apr 2013 11:11:24 GMT

The calculation of the column ISNULL(S.RandomNumber, 0) - ISNULL(D.RandomNumber, 0) AS RandomNumberDiffrequires some attention. It is important to choose a numeric value that is far from your threshold number or it will yeild incorrect results. For example if the RandomNumber value in one set is 0 and the key is missing in the other then the difference will calculate as 0, even though they actually are not equal. If no good dummy value is apparent then logic like the following is needed:SELECT COALESCE(S.ID, D.ID) AS ID, S.RandomNumber AS SrcRandomNumber, D.RandomNumber AS DestRandomNumber, S.RandomNumber - D.RandomNumber AS RandomNumberDiff FROM SRC S FULL JOIN DEST D ON S.ID = D.ID WHERE ABS(S.RandomNumber - D.RandomNumber) > @Tolerance or (S.RandomNumber is null and D.RandomNumber is not null) or (S.RandomNumber is not null and D.RandomNumber is null);

RE: Using FULL JOINs to Compare Datasets

53280comma1 — Tue, 23 Apr 2013 03:14:29 GMT

The other option of course is to build the tolerance into the cte that is then compared with intersect or except, as in the following pseudo code (i'm using a phone here, forgive me for not using the posted example tables)With a as (Select id , cast( randomnum as numeric(3,2) from table1), b as (Select id , cast( randomnum as numeric(3,2) from table2)Select * from aExceptSelect * from b;

RE: Using FULL JOINs to Compare Datasets

astmart — Thu, 23 Dec 2010 06:59:51 GMT

Great Article..and well laid out..

RE: Using FULL JOINs to Compare Datasets

markoos1 — Sun, 28 Nov 2010 09:24:23 GMT

Coalesce is needed because you don't know in advance if the value will be on the source side, the destination side, or both. If you only refer to one of the join keys, you will get nulls for the records that don't exist for that side. Coalesce solves this problem by using the first non-null value it finds. Does this make sense? As an aside, you don't need coalesce for the a left join...only for a full join.

RE: Using FULL JOINs to Compare Datasets

ashishtiwarivds — Fri, 26 Nov 2010 21:08:47 GMT

Nice article. Thanks for your efforts for putting this together.Just wondering, what will happen if we don't use COALESCE() function? Generally when I am using LEFT JOIN to find delta at source I don't use this? Can you please elaborate?Thanks again and appriciate your work.Cheers!!

RE: Using FULL JOINs to Compare Datasets

markoos1 — Wed, 29 Sep 2010 07:59:37 GMT

GPatterson -- that's a very good point. I've run into that exact problem before. I was going to address that in part 2....but as a preview let me just say that the ISNULL() has to resolve to an impossible value, or else the full join will over-join. I had an ISNULL(<field>,0) once where the field had a possible value of 0, and this caused a problem.Thanks for your input.

RE: Using FULL JOINs to Compare Datasets

gpatterson-825050 — Wed, 29 Sep 2010 07:41:24 GMT

Thanks for the time and effort to produce this informative article. One small thing I noticed is that this solution requires an assumption that a "missing" row in either destination or source implies a 0. Because of the way you are using ISNULL(), a particular ID that exists with a value of 0 on one side and does not exist at all on the other side will never be identified as a difference.This is probably fine in many cases (e.g. daily sales data), but it might be conceivable to create a circumstance where it would matter. For example, if we are comparing a normalized (to z scores) data set, 0 would have a very different meaning and not be a logical default assumption.Admittedly, my example is a poor and far fetched one. But I think this assumption is worth pointing out for those who may use this snippet of code.Geoff

RE: Using FULL JOINs to Compare Datasets

mishaluba — Tue, 28 Sep 2010 07:17:01 GMT

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!

RE: Using FULL JOINs to Compare Datasets

Hardy21 — Mon, 27 Sep 2010 22:37:15 GMT

Nice article and good examples. Thanks

RE: Using FULL JOINs to Compare Datasets

le_billy — Mon, 27 Sep 2010 18:19:57 GMT

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

RE: Using FULL JOINs to Compare Datasets

markoos1 — Mon, 27 Sep 2010 14:06:41 GMT

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.

RE: Using FULL JOINs to Compare Datasets

rchantler — Mon, 27 Sep 2010 13:25:43 GMT

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.

RE: Using FULL JOINs to Compare Datasets

markoos1 — Mon, 27 Sep 2010 11:55:05 GMT

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

RE: Using FULL JOINs to Compare Datasets

shannonjk — Mon, 27 Sep 2010 11:44:31 GMT

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 :-D

RE: Using FULL JOINs to Compare Datasets

Trey Staker — Mon, 27 Sep 2010 09:45:07 GMT

Thanks for the article!

RE: Using FULL JOINs to Compare Datasets

sjsubscribe — Mon, 27 Sep 2010 09:05:34 GMT

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

RE: Using FULL JOINs to Compare Datasets

TheSQLGuru — Mon, 27 Sep 2010 07:48:50 GMT

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

RE: Using FULL JOINs to Compare Datasets

markoos1 — Mon, 27 Sep 2010 06:40:08 GMT

It's not so bad to maintain. You just have to extend the WHERE clause:WHERE ABS(RandomNumberDiff) > @Toleranceto the following:WHERE ( ABS(RandomNumberDiff) > @ToleranceOR ABS(RandomNumberDiff2) > @ToleranceOR 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.

RE: Using FULL JOINs to Compare Datasets

jensgc — Mon, 27 Sep 2010 06:30:05 GMT

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

RE: Using FULL JOINs to Compare Datasets

Hugo Kornelis — Mon, 27 Sep 2010 03:23:29 GMT

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..

RE: Using FULL JOINs to Compare Datasets

jensgc — Mon, 27 Sep 2010 00:58:17 GMT

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.

Using FULL JOINs to Compare Datasets

markoos1 — Sat, 25 Sep 2010 13:16:20 GMT

Comments posted to this topic are about the item [B]Using FULL JOINs to Compare Datasets[/B]