In the first article of this series we looked at general must read programming books and in the second we took a look at the Java world. Now to step up to the plate is one of my favourite languages, the terse,the beautiful,the sublime, Ruby! Ruby is a great dynamic language that has gained a lot of traction largely thanks to the popularity of ROR (Ruby on Rails), so without further ado let’s jump into the best books to level up your skills with Ruby. ...
When people ask how to improve their programming skills invariably they are told to write more code, to dive into open source projects or to build a replica of a well known piece of functionality. All of those tips are great but at the same time they can reinforce bad habits or lead you to the situation where you can make something work but you don’t know why! Why your programming doesn’t work out the way you plan The key to improving your skills is to both practice programming but also to read more on the subject, by reading I don’t mean spending 2 hours on Hacker news everyday (although that can be fun!). A solid concerted effort to work through particular programming books will pay dividends in your future abilities and critical thinking. By expanding your knowledge of core concepts you can spend more time on the domain problem and how to work efficiently rather than coding by coincidence or wondering how your program works… In this article I’m going to provide a selection of books that I have found to be excellent reads that have not bored myself to tears. Not all are obligatory to read and some will be less relevant for the functional programmers or NoSQL people out there. ...
In part 3 of this series we looked at compound keys in more detail and also into persisting view data. Today we are going to look at what to do when Couchbase’s query model can’t fulfill what you need! (Or you need an excuse to play with more cool tech). ###Enter ElasticSearch! Elasticsearch is a search server based on Lucene, it’s great for real time analytics, flexible queries and features such as full text search, fuzzy matching and geo location queries. ...
There are many articles with some great information on how to size your Couchbase cluster but rarely do they mention specific server specifications or details/pricing of tech stacks (Check out this great blog post for sizing Couchbase deployments). In this article we are going to look at how you can build an awesome cloud based solution with a lot of headroom and power for Couchbase for under $1000! While AWS and other cloud vendors such as Heroku and Digital Ocean and others provide a great service and a plethora of features we often find they can be pricey when you want power and performance can be erratic (unless you pay more for dedicated instances). We do love the ability to quickly spin up instances and AWS is one of our main resources for quickly testing out features. (note: these services are great and it’s not bashing them, this is just a different approach). ...
In part 2 of this series we looked at using compound keys for more advanced querying, today we are going to modify our data set slightly so we can explore other querying methods. Our new documents are going to look like this: All that has changed is we’ve added in an ‘offers’ field which is an array that contains 0 or more offer codes that have been ‘claimed’ in our fake system. ...
Basic analytics on our data set In part one of the series here we covered setting up our Couchbase node and populating it with a sample of documents. As a quick refresher here is what one of our sample documents looks like. The query we wrote in the last article allowed us to group new users by year,month,day and so on but also allowed us to retreive a count of how many users had joined between specific dates. ...
Let’s see those new users! Views are the Couchbase way of generating indices so that you can query your data on attributes other than the document key. In this article we are going to explore the Map Reduce system of Couchbase to allow you to access your data in a variety of methods. Views are used for 3 main reasons: Additonal indices on which to query your data Calculating and producing statistics and information Fine filtering of larger data sets The following is incredibly important to remember! ...