Data Drudgery

In a previous blog we saw how to install Spark on EC2. I am doing this so that I can save on the cost of EMR on top of EC2 which can be over two thousand USD per year for large instances. Even for smaller instances the savings can be up to 30%. In this blog entry we will see how to run a spark job on a cluster. You can run Spark jobs in local mode where the job run locally on a single machine. To run Spark jobs on a cluster, a cluster manager is required. Spark has its own simple cluster manager, and its called the Standalone cluster manager. Industry applications usually swap the Standalone cluster manager for either Apache Mesos or Hadoop YARN .For this example I have setup a small cluster with one t2.micro instance (1 vCPU, 1G), which will act as the master and two m3.medium instances (1 vCPU, 3.7G) which will be the workers. Before setting up the cluster make sure that the cluster security group has sufficient permissions and the master and slaves can communicate with each...

In the last part we went through how to get the WoW auction data using the developer APIs. The auction data dump (auctions.json) is updated once every hour. As I noticed, that this dump is updated just before the hour in UTC. So scheduled job to get the updated auction dump every hour should work fine. In this section we will use Spark to do some basic analysis on the auction data. Simple items have a row like the one shown below. Items like legendary equipment, pets will have additional fields like bonusLists, petSpeciesId etc. Let's take a look at a row of auction data. {"auc":1018440074,"item":41114,"owner":"Lougincath", "ownerRealm":"Dalaran","bid":507084,"buyout":1000000,"quantity":1, "timeLeft":"LONG","rand":0,"seed":0,"context":0} Next we will put the auction json data into a dataframe. As the datadump has some additional me...

This is an account of setting up Spark on my small EC2 cluster of two m3.medium spot instances. Spot instances are good way of saving on cost of on demand prices, and you also get the option of retaining your instances till the spot prices are below your chosen maximum bid. There are many well written guides about setting up Spark on an EC2 cluster but I still got stuck at a few places. I will be describing those here, along with what was the reason for getting stuck. This will be helpful for those who face similar problems. I will not go into the details of each step, but delve into details of only the troubleshooting parts.  Step 1: Create an IAM role for EC2 service role. This step is not required for setup of Spark. This is required only when accessing other AWS services. Step 2: Create security group with SSH access from your local work machine. This step is crucial, as without this we cannot SSH into the EC2 machine. Step 3: Launch EC2 instances with IAM ro...

Finally I am getting hands on with data processing and here I am posting a simple aggregate task using Python Spark. The task is to calculate the aggregate spend by customer and display the data in sorted order. Aggregation is a simple reduce job on the key value pairs of customer ID and each individual spend.  Spark provides sorting by key [ sortByKey() ] out of the box, but to sort by value, one needs to provide a lambda to the more generic sortBy() function.