marked-ast-crel/examples/complex.md

Using the AST generated my marked-ast create appropriate HTML elements with crel

# Efficiently Importing Data

---

Taking a look at the Melbourne building footprints as geojson:

```
[gh-pages][doehlman@nicta-djo building-footprints]$ wc -c buildings.json
27318368 buildings.json
```

Baseline RES memory usage of the node repl on my machine is about `8Mb`:

```
[master][doehlman@nicta-djo ogr2ogr]$ top | grep node
22942 doehlman  20   0  656296   8132   4440 S   0.7  0.1   0:00.02 node
```

---

The following items are important:

1. A Bear
2. Squirrels

---

Aditionally, we should ensure we care for the following:

- rivers
  - "short"
  - long

- lakes

---

If I was to read the `buildings.json` file into memory by simply doing the following:

[`require-json.js`](examples/streams/require-json.js)

Memory usage jumps increases by ~ `100MB`

---

## Running with Streams

```
node --trace-gc --expose-gc stream-json.js
```

---

## Test Image

![](https://images.unsplash.com/photo-1627680344745-39619fc10f84)

---

# LevelDB Love

---

## Importing

```js
var WRITE_BUFFER_SIZE = 1 * 1024 * 1024;

var fs = require('fs');
var path = require('path');
var datafile = path.resolve(__dirname, '../../data/melbdata/parking-events/events.csv');
var lexinum = require('lexinum');
var moment = require('moment');
var pull = require('pull-stream');
var batch = require('pull-level-batch');
var toPullStream = require('stream-to-pull-stream');

var csv = require('csv-parser');
var db = require('leveldown')('/tmp/parking-events', {
  writeBufferSize: WRITE_BUFFER_SIZE
});

var reportProgress = process.stdout.write.bind(process.stdout, '.');

function prepObject(data) {
  var arrive = moment(data['Arrival Time'], 'DD/MM/YYYY HH:mm:ss a');
  var deviceId = parseInt(data['Device ID'], 10);
  var key = arrive.valueOf() + ':' + lexinum(deviceId);
  var value = JSON.stringify(data);

  return {
    type: 'put',
    key: key,
    value: JSON.stringify(data)
  };
}

db.open(function(err) {
  if (err) {
    return console.error('could not open db');
  }

  pull(
    toPullStream.source(
      fs.createReadStream(datafile)
      .pipe(csv())
    ),
    pull.map(prepObject),
    batch(WRITE_BUFFER_SIZE),
    pull.asyncMap(db.batch.bind(db)),
    pull.drain(reportProgress, function() {
      console.log('done');
    })
  );
});
```