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Sometimes you just want a summary of a particular dataset. Many NoSQL databases, including CouchDB, allow you to define a reduce function to do this on the server side. Let's navigate to the restaurant database. If you're not already at the All Documents view, go there. I've already loaded in several documents that we're going to apply a Map and a Reduce function to. These documents each represent an item that's going to be on the menu for the restaurant.
Each document has the name of the menu item as well as the category that that menu item belongs to. What I'd like to do with this data is create a reduce function to tell me how many items are in each category. Let's do this by going to the Temporary View. If you already have a function defined here for Map Function, you can just paste over it.
Now I am going to paste in the function and click Run. This Map Function is detecting whether or not the category property is set on the document. We're not going to get the other documents that are pages in the system, we just want the menu items that have the category property. Next, we emit the category as the key, and the document as the value. You'll notice that we have three documents that each have the key entree. This is important because the reduce function is going to be called once for entree, once for dessert, once for beverages, and once for side dish even though entree is listed three times. The reduce function is going to receive all three of these documents in an array.
Now let's paste in a reduce function that will allow us to count the items in each category. Paste the function in. There's a small quirk in the Futon interface that doesn't allow me to run the reduce function until I have both the map function and the reduce function before I hit run. So, click the Refresh button, and then paste in that reduce function and click Run. Now, click Refresh again, and then click Run again.
Now, you'll notice a Reduce check box. Click the check box and the reduce function runs. So the reduce function takes three arguments: key, values, and rereduce. The reduce function gets called once for each key that the map function supplies. So even though three documents had the key of entree, the reduce function was called only once for entree. The values argument is an array that contains all the values that match up to that key.
So, in this case, the values array had three documents for the key entree. Finally, we are returning the value that we want for each key. In this case, we're just returning the length of the array. You can use whatever logic you want here to return sums or other statistics on your values, but at the end, you just want to return one value. Also, whenever you return more than one value, the reduce function is called recursively and rereduce is set to true.
This can help you reduce complex nested datasets. Reduce functions work together with map functions. The map function first retrieves a keyed set of data. Then, the reduce function takes the values mapped to each key, and transforms them into a single value. Using this combination allows you to retrieve summaries directly from the database, saving time and bandwidth.
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