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on 03-03-201612:37 PM - edited on 05-21-201901:43 PM by SydneyF
It's not uncommon to have a situation where you need to conditionally join one dataset to another. Perhaps the most common is when you want to join one file to another where a date from the first file is between, greater than or less than a date(s) on a second file. The default tools found in the Join section of the tool palette don't provide a simple way of doing this (it can be done, but you need to string several tools together to make it work. There is a better way! Read on...).
There is great macro available in the public Alteryx gallery called Advanced Join (find it here, but spoiler alert... you can download the attached workflow which includes this macro so you don't have to go to the gallery to get it). The Advanced Join gives you greater latitude than the Join tool. Most notably, you can select records from file A that are unique to A AND intersect with file B. Now you may be thinking, “I can do that by unioning the records from an inner join with records from a left join,” and you would be correct. But it takes two tools to do what one Advance Join does. More importantly, the Advanced Join allows you to put a conditional statement on your join which is something you can't do with the Join tool. And it’s this feature - the ability to use conditional statements in a join - which we will focus on for our purpose here.
Let's get into some examples. I have a file, 'Fruit List’, which contains data about various fruits. This file contains a Column Id, a Fruit Name, a Start DateTime and an End DateTime:
I have a second file, 'Greek Alphabet’, which contains a Column Id, a Greek letter and a Datetime.
I want to join the two files on ColumnId where the Datetime from Greek Alphabet (file B) is BETWEEN Start Datetime and End Datetime from Fruit List (file A). Here's the workflow and a screenshot of how to configure the Advanced Join:
And here are what my results look like:
Only one record from Greek Alphabet matched one from Fruit List on ColumnId where Greek Alphabet's Datetime was between Fruit List's Start Datetime and End Datetime.
In the next example, I have the same Fruit List file and want to join it another file, Greek Alphabet that contains just one datetime filed:
The first thing to note is both files have a field called 'DateTime.' We'll want to give these unique names to avoid ambiguity when we write our conditional state in the Advance Join configuration.
I want to join both files on ColumnId but only when DateTime from Fruit List is LESS THAN DateTime from Greek Alphabet:
And the results...:
Let's look at one last example. This time, I'm going to use the Fruit List and Greek Alphabet files used in the first example (Fruit List has a Start DateTime and an End DateTime). I'm interested in matching records where DateTime from Greek Alphabet is BETWEEN Start Datetime and End DateTime from Fruit List. I'm not matching on ColumnId this time.
For the Advanced Join configuration, I'm going to cross join my files. (CAUTION: the resulting join could contain as many rows as the product of the number of rows of the incoming datasets - a.k.a. Cartesian join - depending on how restrictive your conditional is. This means if you're joining 2 datasets that contain a million records each, the resulting dataset could contain as many as one trillion records! ). If I had wanted to match on ColumnId, I would have had to do that separately using a Join tool. The cross join option only allows you to apply a conditional statement:
Results from our 3rd example:
Notice how 10 records from Greek Alphabet were joined to just one record from Fruit List.
The Advanced Join tool can save you time and a lot of headaches when you want to join files using a conditional statement. It has some limitations - you can only join two datasets and include one conditional statement per tool, cross join limitation mentioned above - but Advanced Join provides greater capability and flexibility than the standard Join tool.