Yesterday we had a very cool event at Google’s offices. There were many mobile and web developers that came to hear what is new with Google cloud technologies (among other thing). I’ve used this set of slides because I knew they will be useful to many more developers that miss the event. That is the reason, I’ve used ‘a lot’ of words on each slide.
The event was recorded and I will update this post with the video soon. Have a great 2014! Continue reading
There are many options to extend the powerful spreadsheets that Google offers. One of the cool, new ways to leverage its power is by using a spreadsheet as your ‘front-end’ to a big data processing power (=Big Query). In our world, there is a need to get results as fast as possible and since our data sources grow fast. It’s nice to have a tool that let us ‘see’ (and share) results quickly and easily.
Google BigQuery is a web service that lets you do interactive analysis of massive datasets. When we saying massive we are talking here on billions of rows (or more). It is a scalable and easy to use tool that gives developers and businesses an easy way into powerful data analytics on demand.
As for Google Docs and their powerful sharing capabilities – I guess we don’t need to elaborate here. So, let’s see what are the steps that will let us get data from BigQuery into our Google spreadsheet.
What is Google Compute Engine?Compute Engine is an infrastructure as a service that lets you run your large-scale computing workloads on virtual machines hosted on Google’s infrastructure. Btw, if you wish to have a new machine under your arms in less than 5 minutes – It can be done in 5 easy steps.
Apache Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write. To run programs faster, Spark offers a general execution model that can optimize arbitrary operator graphs, and supports in-memory computing, which lets it query data faster than disk-based engines like Hadoop.
So in order to enjoy from both worlds, we can leverage the great options of large-scale cloud that Compute engine offer us and install Spark on it. Here are the few steps you will need to follow in order to do it.
In this episode of Google Developer Live Israel I’ve covered in the first 6min how to work with Eclipse and Google plugin. This plugin is a great way to manage your app engine projects and to push your code to google cloud. The main goal of this video is to show developer how they can have a server up and running on Google App engine in few minutes. From 6:47 mark you can hear this explanations in hebrew… This part of the talk is tailored mainly for the developers/gamers that are coming to a hackathon event we have during this weekend around Hangout APIs. I am looking forward to see the cool games that will be built on this API…
Two talks in one day…
That’s what I did yesterday for Google Developer Group (GDG) Athens, Greece. It was a great opportunity to talk about the new cool aspects of google cloud platform (Yep, checkout things like: NodeJS on Compute Engine, App engine new support for technologies, Monte Carlo Simulations with App Script, Cloud storage, Big Query and many more). We talked for the first 25min on the new aspects of developing mobile web sites (and/or mobile web apps). In one word – go check out yeoman.io. Of course, there are many more aspects that are in the slides, so feel free to browse them and please let me know if I’ve missed something important that you are using in your mobile web project. Continue reading
In the past, I’ve showed how to run a NodeJS application in Compute Engine. It’s a good case where you wish to test ideas with App Script but when you move them to ‘production’ – NodeJS is the answer. After the Google Developer Live show we had at the end of August, I got few questions on how to install NodeJS inside Compute Engine instance.
Here are the (easy) steps I did before the show in order to save us time: Continue reading
In the past I’ve wrote this post on the different options you can use with Yahoo Finance API. It is time (4 years later!) to a followup post on how to gain more data but this time with NodeJS.
The first idea was to be able to gain information by using different parameters and downloading csv files from Yahoo finance. Something like this GET request will do the magic:
http://finance.yahoo.com/d/quotes.csv?s=NFLX&f=snd1l1yr and from there you can work with the data.
However, there are cases, where you wish to have information that is not part of this set of arguments. Here are two quick examples for such cases: Continue reading
Some of the topic we touch during the show today:
Few minutes ago we finish a great event in Campus TLV. We had the pleasure to have Dr Peter Magnusson (Director of Engineering for App Engine at Google) and Greg DeMichillie (Director Product Management, Cloud Platform at Google). For the ones, that do not know what is GAE: Google App Engine is a complete development stack that uses familiar technologies to build and host applications on the same infrastructure used at Google. It is used by some of the world most successful and demanding global applications such as SnapChat and Khan Academy. We also cover Google Compute Engine which allows everyone to Run large-scale computing workloads on Linux virtual machines hosted on Google’s infrastructure. I’ve spoke about Google Cloud Endpoint and you can watch the full talk on my project’s site.
This is the raw recording form the event of all three talks. I hope to have an edited version soon…
Psst… For the next Cloud meetup – Please sign for IGTCloud group.
This week on Google developers live Israel we wanted to show the power of Big Query. What is Big Query? Well, in todays world when everyone like to use the term “big data” you need to have the capabilities to querying massive datasets. This can be time consuming and expensive without the right knowledge, hardware and infrastructure. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google’s infrastructure. In order to get started quickly and ‘test the water’ there is a powerful online tool that let you query pre-existing datasets like: wikipedia, Github etc’. If you like to type in command line, there is also a command line tool. Before you start your first project you should signup for BigQuery (yes! it’s open now for all). You should log in to the Google APIs Console and make sure you set a new project and allow Big Query API on it. You should also, enable billing if you have not done so in the past. Lastly, head to bigquery.cloud.google.com and click on one of the public datasets that are on the left sidebar. Continue reading
Ido Green 