MapReduce Views

how-to

You can use MapReduce views to create queryable indexes in Couchbase Data Platform.

Although still maintained and supported for legacy use, Views date from the earliest days of Couchbase Server development, and as such are rarely the best choice over, say, our Query service if you are starting a fresh application. See our discussion document on the best service for you to use.

Note, if you are provisioning Views on Couchbase Server for a legacy application, they must run on a couchstore bucket.

The normal CRUD methods allow you to look up a document by its ID. A MapReduce (view query) allows you to lookup one or more documents based on various criteria. MapReduce views are comprised of a map function that is executed once per document (this is done incrementally, so this is not run each time you query the view) and an optional reduce function that performs aggregation on the results of the map function. The map and reduce functions are stored on the server and written in JavaScript.

MapReduce queries can be further customized during query time to allow only a subset (or range) of the data to be returned.

See the Incremental MapReduce Views and Querying Data with Views sections of the general documentation to learn more about views and their architecture.

Querying Views

Once you have a view defined, it can be queried from the Python SDK by using the view_query method on a Bucket instance.

The following example is the definition of a by_country view in a landmarks-by-country design document. This view checks whether a document is a landmark and has a country. If it does, it emits the landmark’s country into the index. This view allows landmarks to be queried for by country. For example, it’s now possible to ask the question "What countries start with U?"

result = bucket.view_query("landmarks-by-country",
                           "by_country",
                           ViewOptions(startkey="U",
                                       limit=10,
                                       namespace=DesignDocumentNamespace.DEVELOPMENT,
                                       scan_consistency=ViewScanConsistency.REQUEST_PLUS))

The following example is the definition of a by_name view in a landmarks-by-name design document in the travel-sample sample dataset. This view checks whether a document is a landmark and has a name. If it does, it emits the landmark’s name into the index. This view allows landmarks to be queried for by its name field.

result = bucket.view_query("landmarks-by-name",
                           "by_name",
                           ViewOptions(key="Circle Bar",
                                       namespace=DesignDocumentNamespace.PRODUCTION))

Once a view result is obtained then it can be iterated over and the ID, keys and values extracted.

for row in result.rows():
    print("Landmark named {} has documentID: {}".format(row.key, row.id))