We can perform most SQL operations in views also. We only need to change the way we visualize data extraction from the database using SQL and think in terms of the map and reduce functions. Here, we will see how to incorporate SQL queries into the MapReduce format.
Any fields or attributes selection for a document from a bucket can be performed by adding it to the emitted key or the value of the map function, which can be used for selection of attributes in the result set or for performing aggregation in the reduce function. The key generated by the map() function determines the ability of the view to query the bucket. Whenever you want to select documents based on some attributes of a document, you need to mention all those attributes that need to be part of the conditions as part of the key emitted by the map function.
Wherever conditions enable filtering of result set is required, it can be in cooperated using parameters such as key...
