Shine’s good friend Felipe Hoffa from Google was in Melbourne recently, and he took the time to catch up with our resident Google Developer Expert, Graham Polley. But, instead of just sitting down over a boring old coffee, they decided to take an iconic tram ride around the city. To make it even more interesting, they tested out some awesome Google Cloud technologies by using their phones to spin up a Cloud Dataflow cluster of 50 VMs, and process over 10 billion records of data in under 10 minutes! Check out the video they recorded:
“What the Fudge?”
I use Google BigQuery a lot. On a daily basis I run dozens of queries, use it to build massively scalable data pipelines for our clients, and regularly help new users navigating it for the first time. Suffice it to say I’m somewhat accustomed to its little quirks. Unfortunately, the same can’t be said for the new users who are commonly left scratching their heads, and shouting “What the fudge!?” at their monitors.
Here’s the top three WTFs that I regularly hear from new BigQuery users:
Will this post interest me?
If you use (or intend to use) Google Cloud Dataflow, you’ve heard about Apache Beam, or if you’re simply bored in work today and looking to waste some time, then yes, please do read on. This short post will cover why our team finally took the plunge to start porting some of Dataflow applications (using the 1.x Java SDKs) to the new Apache Beam model (2.x Java SDK). Spoiler – it has something to do with this. It will also highlight the biggest changes we needed to make when making the switch (pretty much just fix some compile errors).
Setting the scene
A couple of months ago my colleague Graham Polley wrote about how we got started analysing 8+ years worth of of WSPR (pronounced ‘whisper’) data. What is WSPR? WSPR, or Weak Signal Propagation Reporter, is signal reporting network setup by radio amateurs for monitoring the ability for radio signals to get from one place to another. Why would I care? I’m a geek and I like data. More specifically the things it can tell us about seemingly complex processes. I’m also a radio amateur, and enjoy the technical aspects of communicating around the globe with equipment I’ve built myself.
Beers + ‘WSPR’ = fun
To this day, I’m a firm believer in the benefits of simple, informative, and spontaneous conversations with my colleagues – at least with the ones who can stand me long enough to chat with me . Chewing the fat with other like minded folks over a beer or two is a bloody good thing. It’s how ideas are born, knowledge is shared, and relationships are formed. It’s an important aspect of any business that is sadly all too often overlooked.
The decline of Stack Overflow?
A few months back I read this post from 2015 (yes, I know I’m a little late to the party) about how Stack Overflow (SO) was in serious decline, and heading for total and utter oblivion. In the post, the first item to be called out was that SO “hated new users“:
Stack Overflow has always been a better-than-average resource for finding answers to programming questions. In particular, I have found a number of helpful answers to really obscure questions on the site, many of which helped me get past a road block either at work or in my hobby programming. As such, I decided I’d join the site to see if I could help out. Never before has a website given me a worse first impression.
At the time, I remember thinking that this seemed like somewhat of an unfair statement. That was mostly down to the fact that when I joined the community (many years ago), I had fond memories of a smooth on-boarding, and never experienced any snarky remarks on my initial questions. Yes, gaining traction for noobs is very, very hard, but there is a good reason why it exists.
For me, SO is invaluable. How else would I be able to pretend to know what I’m doing? How else could I copy and paste code from some other person who’s obviously a lot smarter than me, and take all the credit for it? Anyway, once I had read the post, and gotten on with my life (e.g. copying and pasting more code from SO), I did’t think too much more about the post. Maybe I had just been lucky with my foray into the SO community?
However, just last week, I was reminded of that post once again, when I noticed that BigQuery (BQ) now has a public dataset which includes all the data from SO – including user comments and answers. Do you see where I am going with this yet? If not, then don’t worry. Neither did I when I started writing this.
Shine’s very own Pablo Caif will be rocking the stage at the very first YOW! Data conference in Sydney. The conference will be running over two days (22-23 Sep) and is focused big data, analytics, and machine learning. Pablo will give his presentation on Google BigQuery, along with a killer demo of it in action. You can find more details of his talk here.
Pablo will be presenting on the work Shine have done for Telstra, which involves building solutions on GCP to manage and analyse their massive datasets. More specifically, the talk will focus around Google’s two core big data products – BigQuery & Cloud Dataflow.
Pablo will be presenting on Thursday 24th March in the ‘Data & Analytics’ track. Be sure to pop by and say “g’day” if you are going to the event! You can find more information about GCP Next 2016 here.
A few months back, Shine’s Pablo Caif and Graham Polley were welcomed into the Google Developer Expert (GDE) program as a result of their recent work at Telstra. The projects they are working on consist of building bleeding edge big data solutions using tools like BigQuery and Cloud Dataflow on the Google Cloud Platform (GCP). You can read all about that here.
GDE acceptance comes with many benefits and privileges, one of which is a yearly trip to a private summit at a different location each year. With Google footing the bill, they bring all the GDEs (around 250 currently) from around the globe for, let’s admit it, a complete Google geek-out fest for 2 days!
This year the summit was at the Googleplex in Mountain View. Needless to say, Pablo and Graham were chomping at the bit to go. However, in addition to the summit, Google invited them to fly out prior to actual summit itself. They had lined up a few other things especially for the guys. So this was no ordinary trip. Lucky buggers!
We asked both guys to give their individual feedback on the trip, and here’s what they had to say about it. Read on if you want to hear about how the guys spent six days hanging out with Google in America.
One of the projects that I’m currently working on is developing a solution whereby millions of rows per hour are streamed real-time into Google BigQuery. This data is then available for immediate analysis by the business. The business likes this. It’s an extremely interesting, yet challenging project. And we are always looking for ways of improving our streaming infrastructure.
As I explained in a previous blog post, the data/rows that we stream to BigQuery are ad-impressions, which are generated by an ad-server (Google DFP). This was a great accomplishment in its own right, especially after optimising our architecture and adding Redis into the mix. Using Redis added robustness, and stability to our infrastructure. But – there is always a but – we still need to denormalise the data before analysing it.
In this blog post I’ll talk about how you can use Google Cloud Pub/Sub to denormalize your data in real-time before performing analysis on it.