npm install map-reduceIncremental map-reduces and real-time results.
An "incremental map reduce" means when you update one key,
only a relevant protion of the data needs to be recalculated.
"real-time results" means that you can listen to the database,
and recieve change notifications on the fly! a la
level-live-stream
If you just want something very simple, like mapping the date a blog post
is created to the blog, then level-index
may be enough.
`` js
var LevelUp = require('levelup')
var SubLevel = require('level-sublevel')
var MapReduce = require('map-reduce')
var db = SubLevel(LevelUp(file))
var mapDb =
MapReduce(
db, //the parent db
'example', //name.
function (key, value, emit) {
//perform some mapping.
var obj = JSON.parse(value)
//emit(key, value)
//key may be an array of strings.
//value must be a string or buffer.
emit(['all', obj.group], ''+obj.lines.length)
},
function (acc, value, key) {
//reduce little into big
//must return a string or buffer.
return ''+(Number(acc) + Number(value))
},
//pass in the initial value for the reduce.
//must be a string or buffer.
'0'
})
})
`
map-reduce uses level-trigger to make map reduces durable.
` js
//get all the results in a specific group
//start:[...] implies end:.. to be the end of that group.
mapDb.createReadStream({range: ['all', group]})
//get all the results in under a group.
mapDb.createReadStream({range: ['all', true]})
//get all the top level
mapDb.createReadStream({range: [true]})
`
map-reduce with multiple levels of aggregation.
suppose we are building a database of all the street-food in the world.
the data looks like this:
` js`
{
country: USA | Germany | Cambodia, etc...
state: CA | NY | '', etc...
city: Oakland | New York | Berlin | Phnom Penh, etc...
type: taco | chili-dog | doner | noodles, etc...
}
We will aggregate to counts per-region, that look like this:
` js`
//say: under the key USA
{
'taco': 23497,
'chili-dog': 5643,
etc...
}
first we'll map the raw data to ([country, state, city],type) tuples.
then we'll count up all the instances of a particular type in that region!
` js
var LevelUp = require('levelup')
var SubLevel = require('level-sublevel')
var MapReduce = require('map-reduce')
var db = SubLevel(LevelUp(file))
var mapDb =
MapReduce(
db,
'streetfood',
function (key, value, emit) {
//perform some mapping.
var obj = JSON.parse(value)
//emit(key, value)
//key may be an array of strings.
//value must be a string or buffer.
emit(
[obj.country, obj.state || '', obj.city],
//notice that we are just returning a string.
JSON.stringify(obj.type)
)
},
function (acc, value) {
acc = JSON.parse(acc)
value = JSON.parse(value)
//check if this is top level data, like 'taco' or 'noodle'
if('string' === typeof value) {
//increment by one (remember to set as a number if it was undefined)
acc[value] = (acc[value] || 0) ++
return JSON.stringify(acc)
}
//if we get to here, we are combining two aggregates.
//say, all the cities in a state, or all the countries in the world.
//value and acc will both be objects {taco: number, doner: number2, etc...}
for(var type in value) {
//add the counts for each type together...
//remembering to check that it is set as a value...
acc[type] = (acc[type] || 0) + value[type]
}
//stringify the object, so that it can be written to disk!
return JSON.stringify(acc)
},
'{}')
`
then query it like this:
` js`
mapDb.createReadStream({range: ['USA', 'CA', true]})
.pipe(...)
pass db.get an array, and you can retrive a specific value, by group.
` js
var userMapping = require("map-reduce")(
db,
"userPoints",
function(key, value, emit){
value = JSON.parse(value);
var date = new Date(value.created);
emit([value.user, date.getYear(), date.getMonth()], value.amount);
},
function(acc, value){
return (Number(acc) + Number(value)).toString();
},
0
);
function getTotalPointsForUser(user, year, month, cb){
userMapping.get([user, year, month], cb);
}
``
MIT