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Historical Job Postings API+Example

Repository for the statistics API and an example app for the dataset located at https://jobtechdev.se/devguide/datasets/historical.html.

Requirements

  • Anaconda 3.x
  • Apache Spark

Computations

(Python + Spark)
Calculates sparse vectors for occurences of all words/phrases used more than 20 times (~500k) across all job postings. These are saved to a gzipped pickle. Note: This will take several hours if run on a local machine.

API

(Python + flask)
Loads computed sparse vectors into memory. These are used as in-memory bitmaps for statistics calculations. Has a simple interpreter for a query syntax using bit operations (see notebook for examples). For a specific query, outputs sums for various variables such as months, years, employers and occupations.
Link (+query 'javascript'): http://13.94.101.59:5000/realtime1/javascript
Notebook: https://github.com/simonbe/afhistorik/blob/master/notebooks/API_description.ipynb

Example app

(javascript + d3)
Visualizes some of the output from the API.
Link: http://historik.azurewebsites.net