Before Universe, exploring and filtering large datasets in javascript meant constant data looping, complicated indexing, and countless lines of code to dissect your data.
With Universe, you can be there in just a few lines of code. You've got better things to do than write intense map-reduce functions or learn the intricate inner-workings of Crossfilter ;)
- Simple, yet powerful query syntax
- Built on, and tightly integrated with Crossfilter, and Reductio - the fastest multi-dimensional JS data frameworks available
- Real-time updates to query results as you filter
- Flexible filtering system
- Automatic and invisible management of data indexing and memory
- Post Aggregation
- Basic Usage (Codepen)
NPM
npm install universe --save
CDN or Download from the npmcdn load or download universe.js or universe.min.js file as part of your application.
Pass universe
an array of objects or a Crossfilter instance:
var universe = require('universe')
var myUniverse = universe([
{date: "2011-11-14T16:17:54Z", quantity: 2, total: 190, tip: 100, type: "tab", productIDs: ["001"]},
{date: "2011-11-14T16:20:19Z", quantity: 2, total: 190, tip: 100, type: "tab", productIDs: ["001", "005"]},
{date: "2011-11-14T16:28:54Z", quantity: 1, total: 300, tip: 200, type: "visa", productIDs: ["004", "005"]},
...
])
.then(function(myUniverse){
// And now you're ready to query! :)
return myUniverse
})
.then(function(myUniverse){
myUniverse.query({
groupBy: 'type' // GroupBy the type key
columns: {
$count: true, // Count the number of records
quantity: { // Create a custom 'quantity' column
$sum: 'quantity' // Sum the quantity column
},
},
// Limit selection to rows where quantity is greater than 50
filter: {
quantity: {
$gt: 50
}
},
})
// Optionally post-aggregate your data
// Reduce all results after 5 to a single result using sums
myUniverse.squash(5, null, {
count: '$sum',
quantity: {
sum: '$sum'
}
})
// See Post-Aggregations for more information
})
.then(function(res) {
// Use your data for tables, charts, data visualiztion, etc.
res.data === [
{"key": "cash","value": {"count": 2,"quantity": {"sum": 3}}},
{"key": "tab","value": {"count": 8,"quantity": {"sum": 16}}},
{"key": "visa","value": {"count": 2,"quantity": {"sum": 2}}}
]
// Or plost the data in DC.js using the underlying crossfilter dimension and group
dc.pieChart('#chart')
.dimension(res.dimension)
.group(res.group)
// Pass the query's universe instance to keep chaining
return res.universe
})
As you filter your data on the universe level, every query's result is updated in real-time to reflect changes in aggregation
// Filter records where 'type' === 'visa'
.then(function(myUniverse) {
return myUniverse.filter('type', 'visa')
})
// Filter records where 'type' === 'visa' or 'tab'
.then(function(myUniverse) {
return myUniverse.filter('type', ['visa', 'tab'])
})
// Filter records where 'total' is between 50 and 100
.then(function(myUniverse) {
return myUniverse.filter('total', [50, 10], true)
})
// Filter records using an expressive and JSON friendly query syntax
.then(function(myUniverse) {
return myUniverse.filter('total', {
$lt: { // Filter to results where total is less than
'$get(total)': { // the "total" property from
'$nthLast(3)': { // the 3rd to the last row from
$column: 'date' // the dataset sorted by the date column
}
}
}
})
})
// Or if you're feeling powerful, just write your own custom filter function
.then(function(myUniverse){
return myUniverse.filter({
total: function(row){
return (row.quantity * row.sum) > 50
}
})
})
// Clear the filters for the 'type' column
.then(function(myUniverse){
return myUniverse.filter('type')
})
// Apply many filters in one go
.then(function(myUniverse){
return myUniverse.filterAll([{
column: 'type',
value: 'visa',
}, {
column: 'quantity',
value: [200, 500],
isRange: true,
}])
})
// Clear all of the filters
.then(function(myUniverse){
return myUniverse.filterAll()
})
// Remove a column index
.then(function(myUniverse){
return myUniverse.clear('total')
})
// Remove all columns
.then(function(myUniverse){
return myUniverse.clear()
})
API #
universe( [data] , {config} ) #
-
Description
- Creates a new universe instance
-
Parameters
[data]
- An array of objects{config}
- Optional configurations for this Universe instance{generatedColumns}
- An object of keys and their respective accessor functions used to dynamically generate columns.
-
Returns a
promise
that is resolved with the universe instance -
[Example](Create a new Universe)
- Generated Columns Example
universe([ {day: '1', price: 30, quantity: 3}, {day: '2', price: 40, quantity: 5} ], { generatedColumns: { total: function(row){return row.price * row.quantity} } }) .then(function(myUniverse){ // data[0].total === 90 // data[1].total === 200 })
- Generated Columns Example
.query( {queryObject} ) #
-
Description
- Creates a new query from a universe instance
-
Parameters
queryObject
:groupBy
- Property name, property string representation, or even a function! (see.column()
method),select
- An object of column aggregations and/or column names$aggregation
- Aggregations are prefixed with a$
columnName
- Creates a nested column with the name provided
filter
- A filter object that is applied to the query (similar to awhere
clause in mySQL)
-
Returns
promise
, resolved with a query results objectdata
- The result of the querygroup
- The crossfilter/reductio group used to build the querydimension
- The crossfilter dimension used to build the querycrossfilter
- The crossfilter that runs this universeuniverse
- The current instance of the universe. Return this to keep chaining via promises
-
[Example](#Explore your data)
.filter( columnKey, filterObject, isArray, replace ) #
-
Description
- Filters everything in the universe to only include rows that match certain conditions. Queries automatically and instantaneously update their values and aggregations.
-
Parameters
columnKey
- The object property to filter on,
-
Returns
promise
resolved with- universe instance
-
[Example](#Query your data)
.filterAll() #
- Description
- Clears all filters accross all dimensiona.
- Returns
promise
resolved with- universe instance
.column( columnKey/columnObject ) #
-
Description
- Use to optionally pre-index a column. Accepts either:
- String or number corresponding to the key or index of the column. eg.
propertyName
or2
- A nested string representation of the property. eg.
a.nested.property
,a.nested[number]
- Multiple singular key shorthand eg.
['prop1', 'prop2', 'prop3']
- A callback function that returns the key (very powerful) eg.
function(d){return d.myProperty}
- String or number corresponding to the key or index of the column. eg.
- Use to optionally pre-index a column. Accepts either:
-
Parameters
columnKey
- the column property or array index you would like to pre-compile eg.
.then(function(universe){ return universe.column('total') })
columnObject
allows you to override the column type, otherwise it is calculated automatically:
.then(function(universe){ return universe.column({ key: columnKey, type: 'number' }) })
-
Returns
promise
resolved with- universe instance
-
[Example](#Pre-compile Columns)
.clear( columnKey/columnObject/[columnKeys/columnObjects] ) #
-
Description
- Clears individual or all column definitions and indexes
-
Parameters
columnKey
- the column property or array of columns you would like to clear eg.
.then(function(universe){ // Single Key return universe.clear('total') // Complex Key return universe.clear({key: ['complex', 'key']}) // Multiple Single Keys return universe.clear(['total', 'quantity']) // Multiple Complex Keys return universe.clear([{key: ['complex', 'key']}, {key: ['another', 'one']}]) })
-
Returns
promise
resolved with- universe instance
-
[Example](#Clean Up)
.add( [data] ) #
- Description
- Adds additional data to a universe instance. This data will be indexed, aggregated and queries/filters immediately updated when added.
- Parameters
[data]
- An new array of objects similar to the original dataset
- Returns
promise
resolved with- universe instance
Post Aggregation #
Post aggregation methods can be run on query results to further modify your data. Just like queries, the results magically and instantly respond to filtering.
- Each post aggregation is very powerful, but not all post aggregations can be chained together.
A majority of the time, you're probably only interested in the end result of a query chain. For this reason, Post Aggregations default to mutating the data of their direct parent (unless the parent is the original query), thereby avoiding unnecessary copying of data.
On the other hand, if you plan on accessing data at any point in the middle of a query chain, you will need to lock()
that query's results. This ensure's it won't be overwritten or mutated by any further post aggregation.
Note: Running more than 1 post aggregation on a query will automatically lock the parent query.
.then(function(universe){
return universe.query({
groupBy: 'tag'
})
})
.then(function(query){
query.lock()
var all = query.data
return query.limit(5)
})
.then(function(query){
var only5 = query.data
all.length === 10
only5.length === 5
})
Without locking the above query before using .limit(5)
, the all
data array would have been mutated by .limit(5)
.sortByKey(descending) #
- Description
- Sort results by key (ascending or descending)
- Parameters
descending
- Pass true to sortKeys in descending order
.then(function(query){ return query.sortByKey(true) })
- Returns
promise
resolved with- query instance
.limit(n, n2) #
- Description
- Limit results to those between
n
andn2
. Ifn2
is not passed, will limit to the firstn
records
- Limit results to those between
- Parameters
n
- Start index. Defaults to 0 ifnull
orundefined
,n2
- End index. Defaults toquery.data.length
ifnull
. Ifundefined
, will limit to the firstn
records instead.
.then(function(query){ // limits results to the first 5 records return query.limit(5) // limits results to records 5 through 10 return query.limit(4, 10) })
- Returns
promise
resolved with- query instance
.squash(n, n2, aggregationMap, keyName) #
-
Description
- Takes records from
n
ton2
and reduces them to a single record using the aggregationMap
- Takes records from
-
Parameters
n
- Start index. Defaults to0
iffalse
-yn2
- End index. Defaults toquery.data.length
iffalse
-yaggregationMap
- A 1:1 map of property to the aggregation to be used when combining the recordskeyName
(optional) - The key to be used for the new record. Defaults toOther
.then(function(universe){ universe.query({ groupBy: 'type', select: { $sum: 'total', otherColumn: { $avg: 'tip' } }) }) .then(function(query){ // Will squash all records after the 5 record query.squash(5, null, { // Sum the sum column sum: '$sum', othercolumn: { // Average the avg column avg: '$avg' } }, 'Everything after 5') // Give the squashed record a new key })
-
Returns
promise
resolved with- query instance
.change(n, n2, changeFields) #
-
Description
- Determines the change from the
n
ton2
using the keys inchangeFields
- Determines the change from the
-
Parameters
n
- Start index. Defaults to0
iffalse
-yn2
- End index. Defaults toquery.data.length
iffalse
-ychangeFields
- An object or array, referencing the fields to measure for change
.then(function(universe){ universe.query({ groupBy: 'type', select: { $sum: 'total', otherColumn: { $avg: 'tip' } } }) }) .then(function(query){ // Measure the change for sum and avg from result 0 to 10 query.change(0, 10, { sum: true otherColumn: { avg: true } }) })
-
Returns
promise
resolved with- query instance
query.data
is now an object:
{ key: ['nKey', 'n2Key'], value: { sumChange: 7, otherColumn: { avgChange: 4 } } }
- query instance
.changeMap(changeMapObj) #
-
Description
- Determines incremental change for each record across the fields defined in
changeMapObj
- Determines incremental change for each record across the fields defined in
-
Parameters
changeMapObj
- An object or array, referencing the fields to measure for change
.then(function(universe){ universe.query({ groupBy: 'type', select: { $sum: 'total', otherColumn: { $avg: 'tip' } } }) }) .then(function(query){ // Measure the change for sum and avg from result 0 to 10 query.change({ sum: true otherColumn: { avg: true } }) })
-
Returns
promise
resolved with- query instance
query.data
records are now decorated with incremental change data:
[...{ key: 'tag5' value: { sum: 5 sumChange: 7, sumChangeFromStart: 0, sumChangeFromEnd: 30, otherColumn: { avgChange: 4 avgChangeFromStart: -4 avgChangeFromEnd: -20 } } }...]
- query instance
.post(callback) #
- Description
- Use a custom callback function to perform your own post aggregations.
- Parameters
callback
- the callback function to execute. It accepts the following parameters:query
- the new query object. A fresh reference (or copy, if the parent is locked) is located atquery.data
. It is highly discouraged to change any other property on this objectparentQuery
- the parent query.
- You may optionally return a promise-like value for asynchronous processing
.post(function(query, parentQuery){ query.data[0].key = 'newKeyName' return Promise.resolve(doSomethingSpecial(query.data)) })
- Returns
promise
resolved with- query instance
Pro Tips #
Don’t want to use arrays in your aggregations? No problem, because this:
.then(function(universe){
universe.query({
select: {
$sum: {
$sum: [
{$max: ['tip', 'total']},
{$min: ['quantity', 'total']}
]
},
}
})
})
… is now easier written like this:
.then(function(universe){
universe.query({
select: {
$sum: {
$sum: {
$max: ['tip', 'total'],
$min: ['quantity', 'total']
}
},
}
})
})
What’s that? Don’t like the verbosity of objects or arrays? Use the new string syntax!
.then(function(universe){
universe.query({
select: {
$sum: '$sum($max(tip,total), $min(quantity,total))'
}
})
})
Pro-Tip: You can also pre-compile column indices before querying. Otherwise, ad-hoc indices are created and managed automagically for you anyway.
.then(function(myUniverse){
return myUniverse.column('a')
return myUniverse.column(['a', 'b', 'c'])
return myUniverse.column({
key: 'd',
type: 'string' // override automatic type detection
})
})