mongodb mapreduce scope example

1. MongoDB MapReduce is equivalent to Mysql's groupby, so it is easy to use MapReduce for parallel statistics on MongoDB. MapReduce is used to implement two functions: Map function and Reduce function. Map function calls emit (key, value), traverses

MongoDB MapReduce MapReduce is a computational model that simply executes a large amount of work (data) decomposition (MAP) and then merges the results into the final result (REDUCE). The advantage of this is that after the task is decomposed, it

about MongoDB's MapReduceCategory: MongoDB2012-12-06 21:378676 People read Comments (2) favorite reports MongoDB Mapreducemapreduce is a computational model that simply executes a large amount of work (data) decomposition (MAP) and then merges

The small partners who have played Hadoop should be no stranger to MapReduce, MapReduce is powerful and flexible, it can divide a big problem into a number of small problems, the small problems sent to different machines to process, all the machines

Topics on MongoDB data aggregation Http://blog.nosqlfan.com/html/3548.html MapreduceMapreduce is a computing model. Simply put, it is to execute a large number of jobs (data) into maps, and then merge the results into the final result (reduce ).

It's been a long time. Here, life is at a new beginning. This blog content long ago wanted to update up, but has not found the right time point (haha, in fact, lazy), the main content focused on the use of MongoDB when some of the hidden MapReduce

MapReduce can be used in MongoDB for complex aggregate queries. Map and Reduce functions can be implemented using JavaScript. You can use db. runCommand or mapReduce command to execute a MapReduce operation: Db. runCommand (

The example below is a test in small data. I tried to test tens of millions of data records on a single machine. I haven't finished the test for a long time...   Data has a table: crawler. Videos. The table structure is: _ id, playurl,

An interesting trend have been developing in the IT landscape over the past few years.  Many new technologies develop and immediately latch onto the "Big Data" buzzword. And as older technologies add "Big Data" features in an attempt to keep up with

Used MySQL database, the whole day is to write a large heap of SQL statements, to remember that these SQL keywords are going to take a few days, write the eggs are exploded, when the contact to MongoDB, found not to write SQL, instantly feel tall on,