| # Install clusterdock. | |
| pip3 install clusterdock | |
| # Clone the Apache Kafka topology for clusterdock. | |
| git clone https://github.com/clusterdock/topology_apache_kafka.git | |
| # Start Apache Kafka (defaults to node-1.cluster, node-2.cluster, node-3.cluster) | |
| clusterdock -v start topology_apache_kafka --brokers node-1 node-2 node-3 --kafka-version 1.0.0 | |
| # Start StreamSets Data Collector on the same cluster network. |
| {"name":"Vega Visualization","height":300,"padding":"auto","marks":[{"properties":{"enter":{"shape":{"value":"circle"},"x":{"field":"x","scale":"x"},"size":{"mult":30,"field":"y2"},"fill":{"field":"group","scale":"group"},"y":{"field":"y","scale":"y"}}},"from":{"data":"table_dcsw3"},"type":"symbol"}],"axes":[{"layer":"front","offset":20,"properties":{"axis":{"strokeWidth":{"value":0}},"title":{"fontSize":{"value":14}}},"title":"","grid":false,"type":"x","scale":"x","tickSize":0},{"layer":"front","offset":20,"properties":{"axis":{"strokeWidth":{"value":0}},"title":{"fontSize":{"value":14}}},"title":"","grid":false,"type":"y","scale":"y","tickSize":0}],"data":[{"name":"table_dcsw3","values":[{"x":0,"y2":0,"group":1,"y":"Sunday"},{"x":1,"y2":0,"group":1,"y":"Sunday"},{"x":2,"y2":0,"group":1,"y":"Sunday"},{"x":3,"y2":0,"group":1,"y":"Sunday"},{"x":4,"y2":0,"group":1,"y":"Sunday"},{"x":5,"y2":17,"group":1,"y":"Sunday"},{"x":6,"y2":2,"group":1,"y":"Sunday"},{"x":7,"y2":16,"group":1,"y":"Sunday"},{"x":8,"y2":7,"grou |
| select | |
| "V1", | |
| sum(1) as records, | |
| count(distinct "V2") as distinct_keys | |
| from browser | |
| group by "V1" | |
| order by "V1"; | |
| select | |
| "V1", |
Our Virtual Machines are provisioned using Vagrant from a Linux base box to run using VirutalBox. If the Hard Disk space runs out and you cannot remove files to free-up space, you can resize the Hard Disk using some VirtualBox and Linux commands.
The following steps assume you've got a set-up like mine, where:
| using RDatasets, KernelDensity | |
| faithful = dataset("datasets", "faithful"); | |
| a = kde((faithful[:Eruptions],faithful[:Waiting])); | |
| #How do I get cartesian product of x and y, such that it represents same coordinates as reshaped color? | |
| x = collect(a.x) #256-element Array{Float64,1} | |
| y = collect(a.y) #256-element Array{Float64,1} | |
| color = reshape(a.density, 65536) #65536-element Array{Float64,1} |
| { | |
| "name": "Vega Visualization", | |
| "height": 250, | |
| "padding": "auto", | |
| "marks": [ | |
| { | |
| "properties": { | |
| "update": {"fillOpacity": {"value": 1}}, | |
| "hover": {"fillOpacity": {"value": 0.5}}, | |
| "enter": { |
| { | |
| "name": "Vega Visualization", | |
| "height": 450, | |
| "padding": "auto", | |
| "marks": [ | |
| { | |
| "properties": { | |
| "enter": { | |
| "x": { | |
| "field": "x", |
| { | |
| "name": "Vega Visualization", | |
| "height": 500, | |
| "padding": "auto", | |
| "marks": [ | |
| { | |
| "marks": [ | |
| { | |
| "properties": { | |
| "enter": { |
| { | |
| "width": 600, | |
| "height": 300, | |
| "data": [ | |
| { | |
| "name": "obesity", | |
| "values": [ | |
| { | |
| "x": 95, | |
| "y": 95, |
| { | |
| "width": 500, | |
| "height": 200, | |
| "padding": "auto", | |
| "data": [ | |
| { | |
| "name": "table", | |
| "values": [ | |
| {"x": 0, "y": 28, "c":0}, {"x": 0, "y": 55, "c":1}, | |
| {"x": 1, "y": 43, "c":0}, {"x": 1, "y": 91, "c":1}, |