Google I/O 2014 – What’s interesting in the cloud?

This year there are many interesting sessions on Google Cloud. Here are some that I think you might enjoy watching the live stream (or jump into the room if you are at Moscone center). There are many more great sessions, so the best advice is to check the schedule and plan in advance which one you wish to follow live. You can always catch the other sessions later on developers.google.com channel.

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2014 World Cup Matches And Results

The world cup is the biggest sporting event on the planet. During the last world cup in 2010, 3.2 billion people watched at least one of the games. As I know, many groups are going to ‘make it interesting’ by placing bets on the results, I thought it would be good to have all the data on a spreadsheet. Google sheets are ideal for that as they offer a great ability to share, comment and ‘play’ with the data. You can see the demo spreadsheet: http://goo.gl/ZjdfqE and fork the code from: https://github.com/greenido/WorldCup

For now, we are fetching the info from these end points:

What’s New On Google Cloud Platform

This year at #DevConTLV the main theme was around cloud and databases. In my talk I did my best to emphasis, that in the past 15 years, Google has been building out the world’s fastest, most powerful, highest quality cloud infrastructure on the planet and it is opening it so external developers could enjoy it. There are many services like: App Engine, BigQuery and VMs on Compute engine that all come with the same idea. You (=the developer) should focus on what you good at and not by reinventing the wheel again (and again) by trying to find the secret in memcache optimizations. It’s my 4th year in this event and I can say that it is (without doubt) one of the best developer conferences in Tel Aviv. So if you are around next time, please try to join us. It’s great fun to talk with so many talented developers and the talks that I’ve been to, where very good and informative.

Spark Cluster on Google Compute Engine

What is Spark and Why?

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. In the past, I’ve wrote an intro on how to install Spark on GCE and since then, I wanted to do a follow up on the topic but with more real world example of installing a cluster. Luckily to me, a reader of the blog did the work! So after I got his approval, I wanted to share with you his script.

Big Query And Google Spreadsheet Integration

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.

What is BigQuery?

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.

Integrate BigQuery To Google Spreadsheet

How to Install Spark on Google Compute Engine

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.

What is Spark?

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.

Installation steps

Chrome & Google Cloud Quick Update (GDL-IL)

Some of the topic we touch during the show today:

• The list of all the latest Google Developers Live Israel episodes.
• How to work with Big Query with JavaScript and cloud.google.com/products/big-query for more details on the browser tool, clients libraries and API.
• Compute Engine in 5min – It was a fun short show on GDL-IL about starting your own virtual machine inside compute engine.
• Update from the Chrome arena directly from Peter.sh blog
• Chrome releases updates
• If you wish to test your reponsive design here is one online tool that will help you do that: deviceponsive.com
• cloud.google.com as the one source of true for all Google cloud platform products and services.

Big Query Power With JavaScript

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.