jmapreduce
v0.1.1
Published
map reduce for nodejs
Downloads
4
Maintainers
Readme
jmapreduce
a map reduce for nodejs
install
$ npm install --save jmapreduce
test
$ npm test
usage
var JMapReduce = require('jmapreduce');
example
general usage
var JMapReduce = require('jmapreduce');
var input = "A MapReduce program is composed of a Map() procedure (method) that\n" +
" performs filtering and sorting\n" +
"(such as sorting students by first name into queues,\n" +
" one queue for each name) and a Reduce() method that \n" +
"performs a summary operation (such as counting the number\n" +
" of students in each queue, yielding name frequencies).\n\n" +
" The 'MapReduce System' (also called 'infrastructure' or 'framework')\n" +
" orchestrates the processing by marshalling\n\n\n" +
" the distributed servers, running the various tasks in parallel,\n" +
" managing all communications and data transfers\n" +
" between the various parts of the system, and providing for redundancy\n" +
" and fault tolerance.\n" +
" The model is inspired by the map and reduce functions commonly\n" +
" used in functional programming, although their \n" +
"purpose in the MapReduce framework is not the same as in their\n" +
" original forms. The key contributions of \n" +
"the MapReduce framework are not the actual map and reduce functions,\n" +
" but the scalability and fault-tolerance\n" +
" achieved for a variety of applications by optimizing\n" +
" the execution engine once. As such, a single-threaded\n" +
" implementation of MapReduce will usually not be faster than\n" +
" a traditional (non-MapReduce) implementation,\n" +
" any gains are usually only seen with multi-threaded implementations.\n" +
" The use of this model is beneficial\n" +
" only when the optimized distributed shuffle operation (which reduces\n" +
" network communication cost) and fault tolerance\n" +
" features of the MapReduce framework come into play. Optimizing the communication\n" +
" cost is essential to a good MapReduce algorithm.";
var jmapReduce = new JMapReduce();
jmapReduce.textData(input)
.flatMap(function(data){
return data.match(/[^\s]+|\s+[^\s+]$/g);
})
.map(function(x){
return {key: x, value: 1};
})
.groupByKey()
.reduce(0, function(a,b){
return a + b;
})
.sort(function(a, b){
return b.value - a.value;
});
// print ten first elements
console.log("%s", JSON.stringify(jmapReduce.toArray().slice(0, 10), null, 2));
// from console
[
{
"key": "the",
"value": 16
},
{
"key": "and",
"value": 9
},
{
"key": "of",
"value": 8
},
{
"key": "a",
"value": 7
},
{
"key": "MapReduce",
"value": 6
},
{
"key": "is",
"value": 5
},
{
"key": "in",
"value": 5
},
{
"key": "by",
"value": 4
},
{
"key": "The",
"value": 4
},
{
"key": "for",
"value": 3
}
]
#textData(data) data: a string or an array of strings
var jmapReduce = new JMapReduce();
jmapReduce.textData('text data sample');
jmapReduce.textData(['this is ', 'an example', ' for reading data']);