Constructing a Serverless Analytics App to Seize and Question Clickstream Information

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The easiest way to reply questions on consumer habits is usually to collect knowledge. A standard sample is to trace consumer clicks all through a product, then carry out analytical queries on the ensuing knowledge, getting a holistic understanding of consumer habits.

In my case, I used to be curious to get a pulse of developer preferences on a number of divisive questions. So, I constructed a easy survey and gathered tens of 1000’s of knowledge factors from builders on the Web. On this submit, I’ll stroll by how I constructed an online app that:

  • collects free-form JSON knowledge
  • queries dwell knowledge with SQL
  • has no backend servers

To remain targeted on accumulating click on knowledge, we’ll hold the app’s design easy: a single web page presenting a sequence of binary choices, on which clicking will file the customer’s response after which show dwell combination outcomes. (Spoiler alert: you’ll be able to view the outcomes right here.)


binary-survey

Creating the static web page

Maintaining with the spirit of simplicity, we’ll use vanilla HTML/CSS/JS with a little bit of jQuery to construct the app’s frontend. Let’s begin by laying out the HTML construction of the web page.

<!DOCTYPE html>
<html lang="en" dir="ltr">
  <head>
    <title>The Binary Survey</title>
    <script src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
    <script src="https://rockset.com/weblog/script.js"></script> 
  </head>
  <physique>
    <div id="header">
      <h1>The Binary Survey</h1>
      <p>Powered with ❤️ by <b><a href="https://rockset.com">Rockset</a></b></p>
      <h3>Settle the controversy round essential developer points!<br><br>We have surveyed <span id="rely">...</span> builders. Now it is your flip.</h3>
    </div>
    <div id="physique"></div>
  </physique>
</html>

Word that we left the #physique aspect empty—we’ll add the questions right here utilizing Javascript:

// [left option, right option, key]
QUESTIONS = [
  ['tabs', 'spaces', 'tabs_spaces'],
  ['vim', 'emacs', 'vim_emacs'],
]

operate loadQuestions() {    
  for (var i = 0; i < QUESTIONS.size; i++) {
    $('#physique').append(' 
      <div id="q' + i + '" class="query"> 
        <div id="q' + i + '-left" class="choice option-left">' + QUESTIONS[i][0] + '<div class="option-stats"></div></div> 
        <div class="spacer"></div> 
        <div class="immediate"> 
          <div>⟵ (press h)</div> 
          <div class="centered">vote to see outcomes</div> 
          <div>(press l) ⟶</div> 
        </div> 
        <div class="outcomes"> 
          <div class="bar left"><div class="stats"></div></div> 
          <div class="bar proper"><div class="stats"></div></div> 
        </div> 
        <div id="q' + i + '-right" class="choice option-right">' + QUESTIONS[i][1] + '<div class="option-stats"></div></div> 
      </div> 
    ');

    $('#q' + i + '-left').click on(handleClickFalse(i));
    $('#q' + i + '-right').click on(handleClickTrue(i));
  }
}

operate handleClickFalse(index) {
  // ...
}

operate handleClickTrue(index) {
  // ...
}

By including the questions with Javascript, we solely have to jot down the HTML and occasion handlers as soon as. We are able to even regulate the listing of questions at any time by simply modifying the worldwide variable QUESTIONS.

Gathering customized JSON knowledge

Now, we’ve got a webpage the place we need to monitor consumer clicks—a basic case of product analytics. In truth, if we had been instrumenting an present net app as an alternative of constructing from scratch, we might simply begin at this step.

First, we’ll determine how you can mannequin the information we need to acquire as JSON objects, after which we will retailer them in a knowledge backend. For our knowledge layer we are going to use Rockset, a service that accepts JSON knowledge and serves SQL queries, throughout a REST API.

Information mannequin

Since our survey has questions with solely two decisions, we will mannequin every response as a boolean—false for the left-side alternative and true for the right-side alternative. A customer might reply to any variety of questions, so a customer who prefers areas and makes use of vim ought to generate a file that appears like:

{
  'tabs_spaces': true,
  'vim_emacs': false
}

With this mannequin, we will implement the press handlers from above to create and ship this practice JSON object to Rockset:

let vote = {};
const ROCKSET_SERVER = 'https://api.rs2.usw2.rockset.com/v1/orgs/self';
const ROCKSET_APIKEY = '...';

operate handleClickFalse(index) {
  return () => { applyVote(index, false) };
}

operate handleClickTrue(index) {
  return () => { applyVote(index, true) };
}

operate applyVote(index, worth) {
  vote[QUESTIONS[index][2]] = worth;
  saveVote();
}

operate saveVote() {
  // Save to Rockset
  $.ajax({
    url: ROCKSET_SERVER + '/ws/demo/collections/binary_survey/docs',
    headers: {'Authorization': 'ApiKey ' + ROCKSET_APIKEY,
    kind: 'POST',
    knowledge: JSON.stringify(vote)
  });
}

In apply, ROCKSET_APIKEY ought to be set to a worth obtained by logging into the Rockset console. The Rockset assortment which can retailer the paperwork (on this case demo.binary_survey) may also be created and managed within the console.

Updating present responses

Our code up to now has a shortcoming: take into account what occurs when a customer clicks “areas” then clicks “vim.” First, we are going to ship a doc with the response for the primary query. Then we’ll ship one other doc with responses for 2 questions. These get saved as two separate paperwork! As a substitute we would like the second doc to be an replace on the primary.

With Rockset, we will clear up this by giving our paperwork a constant _id subject, which is handled as the first key of a doc in Rockset. We’ll generate this subject as a random identifier for the customer on web page load:

operate onPageLoad() {
  vote['_id'] = 'consumer' + Math.flooring(Math.random() * 2**32);
}

Now let’s run by the earlier situation once more. When the online web page hundreds, the “vote” object will get seeded with an ID:

{
  "_id": "user739701703"
}

When the customer clicks a alternative for one of many questions, a boolean subject is added:

{
  "_id": "user739701703",
  "tabs_spaces": true
}

The customer can proceed so as to add extra responses:

{
  "_id": "user739701703",
  "tabs_spaces": false,
  "vim_emacs": true
}

And even replace earlier responses:

{
  "_id": "user739701703",
  "tabs_spaces": true,
  "vim_emacs": true
}

Each time the response adjustments, the JSON is saved as a Rockset doc and, as a result of the _id subject matches, any earlier response for the present customer is overwritten.

Saving state throughout classes

We’ll add another enhancement to this: for guests who depart the web page and are available again later, we need to hold their responses. In a full-blown app we might have an authentication service to determine classes, a customers desk to persist IDs in, or perhaps a international frontend state to handle the ID. For a splash web page that anybody can go to, such because the survey we’re constructing, we might not have any earlier context for the consumer. On this case, we’ll simply use the browser’s native storage to keep up the customer’s ID.

Let’s modify our Javascript code to implement this mechanism:

const ROCKSET_SERVER = 'https://api.rs2.usw2.rockset.com/v1/orgs/self';
const ROCKSET_APIKEY = '...';

operate handleClickFalse(index) {
  return () => { applyVote(index, false) };
}

operate handleClickTrue(index) {
  return () => { applyVote(index, true) };
}

operate applyVote(index, worth) {
  let vote = loadVote();
  vote[QUESTIONS[index][2]] = worth;
  saveVote(vote);
}

operate loadVote() {
  let vote;

  // Deal with and reset malformed vote
  attempt {
    vote = JSON.parse(localStorage.getItem('vote'));
  } catch {
    vote = null;
  }

  // Set _id if unassigned
  if (!vote || !vote['_id']) {
    vote = {};
    vote['_id'] = 'consumer' + Math.flooring(Math.random() * 2**32);
  }

  return vote;
}

operate saveVote(vote) {
  // Save to native storage
  localStorage.setItem('vote', JSON.stringify(vote));

  // Save to Rockset
  $.ajax({
    url: ROCKSET_SERVER + '/ws/demo/collections/binary_survey/docs',
    headers: {'Authorization': 'ApiKey ' + ROCKSET_APIKEY,
    kind: 'POST',
    knowledge: JSON.stringify(vote)
  });
}

Information-driven app: aggregations on the fly

At this level, we have created a static web page and instrumented it to gather customized click on knowledge. Now let’s put it to make use of! This typically takes one in all two kinds:

  • an inside dashboard informing product selections or triggering alerts round uncommon habits
  • a user-facing characteristic to reinforce a data-driven product

Our survey’s use case falls beneath the latter: as an incentive to reply questions for curious guests, we’ll reveal the dwell outcomes of every query upon clicking a alternative.

To implement this, we’ll write Javascript code to name Rockset’s question API. We need to ship a SQL question that appears like:

SELECT 
    ARRAY_CREATE(COUNT_IF("tabs_spaces"), COUNT("tabs_spaces")) AS q0, 
    ARRAY_CREATE(COUNT_IF("vim_emacs"), COUNT("vim_emacs")) AS q1, 
    # ...
    rely(*) AS whole 
FROM demo.binary_survey

The response will likely be a JSON object with counts for every query (rely of “true” responses and whole rely of responses), together with a rely of distinctive guests.

{
  "q0": [
    102,
    183
  ],
  "q1": [
    32,
    169
  ],
  "q2": [
    146,
    180
  ],
  ...
  "whole": 212
}

We are able to parse this knowledge and set attributes on HTML components to relay the outcomes to the customer. Let’s write this out in Javascript:

const ROCKSET_SERVER = 'https://api.rs2.usw2.rockset.com/v1/orgs/self';
const ROCKSET_APIKEY = '...';
const QUERY = '...';

operate refreshResults() {
  $.ajax({
    url: ROCKSET_SERVER + '/queries',
    headers: {'Authorization': 'ApiKey ' + ROCKSET_APIKEY},
    kind: 'POST',
    success: operate (knowledge) {
      outcomes = knowledge[0];

      // set the customer rely within the header
      $('#rely').html(outcomes['total']);

      // for every query, show the rely and % for all sides (textual content + bar graph)
      for (var i = 0; i < QUESTIONS.size; i++) {
        let left_count = outcomes['q' + i][1] - outcomes['q' + i][0];
        let right_count = outcomes['q' + i][0];
        let left_pct = (left_count / (left_count + right_count) * 100).toFixed(2) + '%';
        let right_pct = (right_count / (left_count + right_count) * 100).toFixed(2) + '%';
        $('#q' + i + ' .left').width(left_pct);
        $('#q' + i + ' .proper').width(right_pct);
        $('#q' + i + ' .left .stats').html('<b>' + left_pct + '</b> (' + left_count + ')');
        $('#q' + i + ' .proper .stats').html('(' + right_count + ') <b>' + right_pct + '</b>');
        $('#q' + i + ' .option-left .option-stats').html('(' + left_pct + ')');
        $('#q' + i + ' .option-right .option-stats').html('(' + right_pct + ')');
      }
    }
  });
}

Even with tens of 1000’s of knowledge factors, this AJAX name returns in round 20ms, so there isn’t a concern executing the question in actual time. In truth, we will replace the outcomes, say each second, to offer the numbers a dwell really feel:

setInterval(refreshResults, 1000);

Ending touches

Entry management

We have written all of the logic for sending knowledge to and retrieving knowledge from Rockset on the shopper aspect of our app. Nonetheless, this exposes our totally privileged Rockset API key publicly, which after all is a giant no-no. It will give anybody full entry to our Rockset account and likewise probably permit a DoS assault. We are able to obtain scoped permissions and request throttling in one in all two methods:

  • use a restricted Rockset API key
  • use a lambda operate as a proxy

The primary is a characteristic still-in-development at Rockset, so for this app we’ll have to make use of the second.

Let’s transfer the listing of questions and the logic that interacts with Rockset to a easy handler in Python, which we’ll deploy as a lambda on AWS:

import json
import os
import requests

APIKEY = os.environ.get('APIKEY') if 'APIKEY' in os.environ else open('APIKEY', 'r').learn().strip()
WORKSPACE = 'demo'
COLLECTION = 'binary_survey'
QUESTIONS = [
    ['tabs', 'spaces', 'tabs_spaces'],
    ['vim', 'emacs', 'vim_emacs'],
]

def questions(occasion, context):
    return {'statusCode': 200, 'headers': {'Entry-Management-Permit-Origin': '*'}, 'physique': json.dumps(QUESTIONS)}

def vote(occasion, context):
    vote = json.hundreds(occasion['body'])
    print({'knowledge': [vote]})
    print(json.dumps({'knowledge': [vote]}))
    r = requests.submit(
        'https://api.rs2.usw2.rockset.com/v1/orgs/self/ws/%s/collections/%s/docs' % (WORKSPACE, COLLECTION),
        headers={'Authorization': 'ApiKey %s' % APIKEY, 'Content material-Kind': 'utility/json'},
        knowledge=json.dumps({'knowledge': [vote]})
    )
    print(r.textual content)
    return {'statusCode': 200, 'headers': {'Entry-Management-Permit-Origin': '*'}, 'physique': 'okay'}

def outcomes(occasion, context):
    question = 'SELECT '
    columns = [q[2] for q in QUESTIONS]
    for i in vary(len(columns)):
        question += 'ARRAY_CREATE(COUNT_IF("%s"), COUNT("%s")) AS qpercentd, n' % (columns[i], columns[i], i)
    question += 'rely(*) AS whole FROM %s.%s' % (WORKSPACE, COLLECTION)
    r = requests.submit(
        'https://api.rs2.usw2.rockset.com/v1/orgs/self/queries',
        headers={'Authorization': 'ApiKey %s' % APIKEY, 'Content material-Kind': 'utility/json'},
        knowledge=json.dumps({'sql': {'question': question}})
    )
    outcomes = json.hundreds(r.textual content)['results']
    return {'statusCode': 200, 'headers': {'Entry-Management-Permit-Origin': '*'}, 'physique': json.dumps(outcomes)}

Our client-side Javascript can now simply make calls to the lambda endpoints, which can act as a relay with the Rockset API.

Including extra questions

A advantage of the best way we have construct the app is we will arbitrarily add extra questions, and every part else will simply work!

QUESTIONS = [
    ['tabs', 'spaces', 'tabs_spaces'],
    ['vim', 'emacs', 'vim_emacs'],
    ['frontend', 'backend', 'frontend_backend'],
    ['objects', 'functions', 'object_functional'],
    ['GraphQL', 'REST', 'graphql_rest'],
    ['Angular', 'React', 'angular_react'],
    ['LaCroix', 'Hint', 'lacroix_hint'],
    ['0-indexing', '1-indexing', '0index_1index'],
    ['SQL', 'NoSQL', 'sql_nosql']
]

Equally, if a customer solely solutions a subset of the questions, no drawback—the client-side app and Rockset can deal with lacking values gracefully.

In truth, these circumstances are typically widespread with product analytics, the place chances are you’ll need to begin monitoring a further attribute on an present occasion or if a consumer is lacking sure attributes. Since we have constructed this app utilizing a schemaless method, we’ve got the pliability to deal with these conditions.

Rendering and styling

We’ve not totally lined the logic but for rendering and styling components on the DOM. You’ll be able to see the complete accomplished supply code right here should you’re curious, however here is a abstract of what is left to do:

  • add some JS to indicate/disguise outcomes and prompts because the customer progresses by the survey
  • add some CSS to make the app look good and adapt the structure for cell guests
  • add in a post-survey-completion congratulatory message

And voila, there we’ve got it! Finish to finish, this app took only a few hours to arrange. It required no spinning up servers or pre-configuring databases, and it was straightforward to adapt whereas growing as there was it was simply recording free-form JSON. To date over 2,500 builders have submitted responses and the outcomes are, if nothing else, attention-grabbing to take a look at.

Outcomes, as of the writing of this weblog, are right here. And the supply code is out there right here.



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