/ Data Analysis

Brushing and linking for big data

Brushing and linking for big data

Falcon

Interactive Visual Analysis for Big Data.

Crossfilter millions of records without latencies. This project is work in progress and not documented yet. Please get in touch if you have questions.

The largest experiments we have done so far is 10M flights in the browser and ~180M flights or ~1.2B stars when connected to MapD.

Demos

cross

Usage

Install with yarn add falcon-vis. You can use two query engines. First ArrowDB reading data from Apache Arrow. This engine works completely in the browser and scales up to ten million rows. Second, MapDDB, which connects to MapD. The indexes are created as ndarrays. Check out the examples to see how to set up an app with your own data. More documentation will follow.

Features

Zoom

You can zoom histograms. Falcon automatically re-bins the data.

zoom

Show and hide base

The base data, which are the original counts without filters, can be displayed behind the filtered counts to provide context. Hiding the base shows the relative distribution of the data.

With base.

base

Without base.

no_base

Circles or Color Heatmap

Heatmap with circles (default). Can show the base (data without filters).

circles

Heatmap with colored cells.

color

Vertical bar, horizontal bar, or text for counts

Horizontal bar.

hbar

Vertical bar.

vbar

Text only.

text

Timeline visualization

You can visualize the timeline of brush interactions in Falcon.

timeline

Falcon with 1.2 billion stars from the GAIA dataset

The GAIA spacecraft measured the positions and distances of stars with unprecedented precision. It collected about 1 billion objects, mainly stars, but also planets, comets, asteroids and quasars among others. Below, we show the dataset loaded in Falcon (with MapD).

gaia

Developers

Install the dependencies with yarn. Then run yarn start to start the flight demo with in memory data. Have a look at the other script commands in package.json.

GitHub