Writing and Querying MapReduce Views in CouchDB by Bradley Holt

By Bradley Holt

That allows you to use CouchDB to help real-world purposes, you'll have to create MapReduce perspectives that allow you to question this document-oriented database for significant facts. With this brief and concise publication, you'll how one can create a number of MapReduce perspectives that can assist you question and mixture information in CouchDB’s huge, allotted datasets.

You'll get step by step directions and many pattern code to create and discover numerous MapReduce perspectives during the process the publication, utilizing an instance database you build. To paintings with those varied perspectives, you’ll easy methods to use the Futon net management console and the cURL command line device that include CouchDB.

* learn the way the Map and decrease steps paintings independently and jointly to index your info
* Use the instance database to create numerous transitority perspectives according to various standards
* realize the makes use of of Map and decrease JavaScript services
* Convert your transitority perspectives to everlasting perspectives inside a layout rfile
* examine a number of thoughts for querying the information inside of your perspectives
* restrict the variety of effects back, pass a few effects, or opposite the order of the output
* crew your effects by way of designated keys or by way of elements of keys

Bradley Holt, co-founder of the inventive companies company came upon Line, is an internet developer and entrepreneur ten years of Hypertext Preprocessor and MySQL event. He all started utilizing CouchDB prior to the discharge of model 1.0. Bradley is an energetic member of the personal home page community.

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Grouping is controlled by parameters passed to your view, not by the Reduce function itself. CouchDB has three built-in Reduce functions: _count, _sum, and _stats (shown in Table 2-5). In most situations, you will want to use one of these built-in Reduce functions. You can write your own custom Reduce functions, but you should rarely need to. Both the _sum and _stats built-in Reduce functions will only reduce sets of numbers. The _count function will count arbitrary values, including null values.

We will call this the releases view and add it to our _design/default design document. In this new view, we will map book documents to key/value pairs of release dates and number of pages. Instead of a string, the release date will be a JSON array containing the date’s year, month, and day. We will do this by using the split method of JavaScript’s String object on each book document’s released field. , ["2007","05","08"]. Group levels require JSON arrays to group on, and they work best when the array elements are ordered from least specific to most specific.

Table 4-8. Rows from the formats view, limited to five and filtered by start key and document ID key id value "Safari Books Online" "978-0-596-15589-6" 272 "Safari Books Online" "978-0-596-52926-0" 448 Reversing Output Let’s reverse the output of our book titles view: curl -X GET http://localhost:5984/books/_design/default/_view/titles -G \ -d reduce=false \ -d descending=true The response: { "total_rows":3, "offset":0, "rows":[ { "id":"978-0-596-52926-0", "key":"RESTful Web Services", "value":448 }, { "id":"978-1-565-92580-9", "key":"DocBook: The Definitive Guide", Limiting, Skipping, and Reversing Results | 49 }, { } "value":648 "id":"978-0-596-15589-6", "key":"CouchDB: The Definitive Guide", "value":272 ] } See Table 4-9 for the rows in tabular format.

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Writing and Querying MapReduce Views in CouchDB by Bradley Holt
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