Copying data to the Cloud from the Command line, this is what this post is all about. Over the last couple of years we have seen vendors offering different object storage platforms/services in the Cloud. Cloud storage typically refers to a hosted object storage service! The following are considered the most known and used Cloud Object Storage platforms and we are going to demonstrate how to copy data to each from the command line. In no particular order I strongly recommend you read and get knowledgeable on each of their offerings and register for a free subscription:
 

Now for each platform we will specifically implement 4 actions (commands):

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Finally the 2017-2018 NHL hockey season has begun! But wait… **PANIC** my little thingy nhlplaybyplay-node for fetching games and play-by-play does not work anymore… Hmmm, after some research it looked like I needed to do some updates and fixes in order to make it work again… Instead I decided to create another Node.js app nhlplaybyplay2-node

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Search for a String in Multiple FilesIn support of an earlier post Fetching NHL Play by Play game data, I was recently asked how could one quickly search for a specific string in multiple JSON files recursively? Well if you are running macOS or Linux grep is your best friend! In a nutshell grep prints lines that contain a match for a pattern. The following is a sample grep and cut command that will list out (output) the games (files) that contains the following string -> “Montréal Canadiens”:

[Want to try it out! You can download and extract sample data which contains all the play by play games from the 2016-2017 season]
 
 
grep -H -R "Montréal Canadiens" /data/20162017/*.json | cut -d: -f1

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Installing TimescaleDB on Azure. First some housekeeping… A time series database is a software system that is optimized for handling time series data, arrays of numbers indexed by time (a datetime or a datetime range). In some fields these time series are called profiles, curves, or traces.


Lately I discovered TimescaleDB, an open source time-series database engineered up from PostgreSQL and packaged as an extension. It is optimized for fast ingest and complex queries. It’s scalable, reliable and easy to use! Please read How it works to understanding how they made it happen and most importantly the following paper: TimescaleDB: SQL made scalable for time-series data. I would also recommend you read the following blog post What the heck is time-series data (and why do I need a time-series database)?

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