This morning I discovered a new entry in the menu on my Oracle Cloud Infrastructure Tenancy (on Ashburn, USA): the NoSQL Database service had been added overnight. The service offers a key-(schema-less) document store. It also supports ACID transactions, SQL on JSON documents, joins across tables, structured tables and if […]
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HTTP benchmarking using wrk. Parsing output to CSV or JSON using Python
wrk is a modern HTTP benchmarking tool. Using a simple CLI interface you can put simple load on HTTP services and determine latency, response times and the number of successfully processed requests. It has a LuaJIT scripting interface which provides extensibility. A distinguishing feature of wrk compared to for example ab […]
jq – Linux command line tool for interpreting and manipulating JSON documents
I am not the first to discover jq, or even to write about it. However, jq was such a valuable tool for me that I felt obliged to share it with you. And turn it into a Katacoda scenario (Katacoda is on of my other favorite finds). jq is a […]
Dissecting Dutch Death Statistics with Python, Pandas and Plotly in a Jupyter Notebook
The CBS (the Dutch Centraal Bureau Statistiek) keeps track of many thing in The Netherlands. And shares many of its data sets as open data, typically in the form of JSON, CSV or XML files. One of the data sets is publishes is the one on the number of births […]
Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 2: combining and aligning multi rider data for analyzing and visualizing the Race
In this article, I analyze the race that took place in stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly and based on the Strava performance data published by Steven Kruijswijk, Thomas de Gendt, Thibaut Pinot and Marco Haller. In this previous […]
Tour de France Data Analysis using Strava data in Jupyter Notebook with Python, Pandas and Plotly – Step 1: single rider loading, exploration, wrangling, visualization
In this article, I will show how to analyze the performance of Steven Kruijswijk during stage 14 of the 2019 Tour de France in a Jupyter Notebook using Python, Pandas and Plotly. Strava collects data from athletes regarding their activities – such as running, cycling, walking and hiking. Members can […]
Analyzing the 2019 Tour de France in depth using Strava performance data from Race Riders
This year’s Tour de France was quite a spectacle. Great performances, exciting stages, unexpected events: it had it all. Analyzing the race events as they unfolded during the stages of this year’s Tour is something I am keen to attempt. Using Jupyter Notebooks, Python and Pandas and Plotly for visualization, […]
Jupyter Notebook for retrieving JSON data from REST APIs
If data is available from REST APIs, Jupyter Notebooks are a fine vehicle for retrieving that data and storing it in a meaningful, processable format. This article introduces an example of a such a dataset: Oracle OpenWorld 2018 was a conference that took place in October 2018 in San Francisco. […]
The Full Oracle OpenWorld and CodeOne 2018 Conference Session Catalog as JSON data set (for data science purposes)
Oracle OpenWorld and CodeOne 2018 are two co-located conferences that took place in October 2018. Some 2000 sessions presented by over 2500 presenters form the core of these conferences. Many details are known about each of the sessions and the speakers – from title, abstract, room (size), date and time, […]
Serverless Node Function on Oracle Functions runs periodically to produce CSV report on Oracle ObjectStorage from data in ElasticSearch
This article highlights a use case implementation I recently implemented (for a demo session) leveraging Oracle Functions as well as OKE (Oracle Kubernetes Engine), Object Storage and Elastic Search. I will briefly touch upon some of the interesting aspects of implementing this case. The code for the function and […]
Session Catalog for Oracle OpenWorld & CodeOne 2018 in JSON files
The Oracle OpenWorld and CodeOne 2018 conferences took place in the last week of October 2018. Together, over 1500 sessions took place. The session catalog with details for all sessions is accessible at https://events.rainfocus.com/widget/oracle/oow18/catalogcodeone18 – at least at the time of writing. The session information includes title and abstract, track, […]
5 main building blocks of the new Visual Builder Cloud Service
In may 2018 Oracle introduced the new version of Visual Builder Cloud Service. This version is not just aimed at the Citizen Developer, in the end an experienced JavaScript can do nice things with it. In this blog I will have a look at 5 of the 6 main building […]
Oracle REST Data Services (ORDS)
While preparing for writing an article about “Oracle API Platform Cloud Service” I wanted to quickly be able to generate example JSON payload’s based on some tables in the “HR’ schema. To achieve this, I came across “Oracle REST Data Services (ORDS)” and wanted to know more about it. In […]
JSON manipulation in Java 9 JShell
In this article I will demonstrate how we can work with JSON based data – for analysis, exploration, cleansing and processing – in JShell, much like we do in Python. I work with a JSON document with entries for all sessions at the Oracle OpenWorld 2017 conference (https://raw.githubusercontent.com/lucasjellema/scrape-oow17/master/oow2017-sessions-catalog.json) The Java […]
When Screen Scraping became API calling – Gathering Oracle OpenWorld 2017 Session Catalog with Node
A dataset with all sessions of the upcoming Oracle OpenWorld 2017 conference is nice to have – for experiments and demonstrations with many technologies. The session catalog is exposed at a website – https://events.rainfocus.com/catalog/oracle/oow17/catalogoow17 With searching, filtering and scrolling, all available sessions can be inspected. If data is available in […]
Quickest way to get going with Node.js and MongoDB – using the mongodb Node driver and a free MongoDB instance in the cloud with mLab
While preparing for a workshop on Node.js, I ran into the by far quickest way to get some a simple Node.js application running against a MongoDB database. I stumbled into mLab (https://mlab.com/) for database hosting. This company offers various plans for cloud based MongoDB environments – including a free plan […]
Smooth, easy, lightweight – Node.js and Express style REST API with Java SE
It is easy to be seduced by some of the attractive qualities of Node (aka Node.js) – the JavaScript technology that makes server side development fun again. Developing light weight applications that handle HTTP requests in a rapid, straightforward way with little overhead and no bloated infrastructure is easy as […]
Development and Runtime Experiences with a Canonical Data Model Part I: Standards & Guidelines
Introduction In my previous blog I’ve explained what a Canonical Data Model (CDM) is and why you should use it. This blog is about how to do this. I will share my experiences on how to create and use a CDM. I gained these experiences at several projects, small ones, […]
Development and Runtime Experiences with a Canonical Data Model Part II: XML Namespace Standards
This blog is about XML namespace standards. Primary for using them in a Canonical Data Model (CDM), but also interesting for anyone who has to define XML data by creating XML Schema files (XSD). This blogpost is the second part of a trilogy about my experiences in using and developing […]
Development and Runtime Experiences with a Canonical Data Model Part III: Dependency Management & Interface Tailoring
Introduction This blogpost is part III, the last part of a trilogy on how to create and use a Canonical Data Model (CDM). The first blogpost contains part I in which I share my experiences in developing a CDM and provide you with lots of standards and guidelines for creating […]