How to Prepare for a Hortonworks Hadoop Certification Exam?

By performing tasks on an actual Hadoop cluster instead of just guessing at multiple-choice questions (MCQs), Hortonworks Certified Professionals have proven competency and Big Data expertise.

The HDP Certified Developer exam is available from any system, anywhere, at any time.

This exam costs around USD 200 per attempt. Hortonworks Data Platform 2.4 is chosen as the framework for exam which also includes Pig, Hive, Sqoop, and Flume.

The candidates will have to perform a list of work on an HDP cluster. To clear the HDPCD exam you need to be good on mostly Hive, Pig, Sqoop and Flume in order to become a successful Hadoop developer. This new test funda is designed in such a way as it will show the true potentials of candidates promising as a valuable resource for the industry with actual hands on knowledge.

Comparison with the Older Version of the Exam

Earlier there used to be a format of MCQ questions but now the exam consists of tasks executed on a live, Hortonworks Data Platform cluster. In This certification test, the candidates will be asked to represent more of their practical skills on Hive and Pig, but the key to clear any of the certifications of Hadoop is that you need to have a crystal clear concept on architecture and yarn first of all. Unless you are aware of the orientation of the cluster and the operations within it, it would be tough for you to feel the data behavior from the practical approach.

Be an Expert with Hive Tables and Pig Latin Scripts

The reference for the course material is also provided by the HDPCD sites which can be used as a reference for the test. To prove your practical knowledge you should be a key player with Hive tables and firing effective queries on it. Also the key skill set includes working on data set using Pig or in other words you should be familiar with concepts of Pig Latin script which can be easily conquered as it is totally operator based and learning those operators doesn’t take a more time of yours. A couple of hours are enough to understand some important operators and their functions.

The Historical Transition

On the other hand, another important factor that has to be kept in consideration is data migration as it is also one of the top technologies adopted by the Hadoop industry as people are shifting to Hadoop from traditional ways of databases (RDBMS) like Oracle SQL and MySQL as the database industry was busy practising these methods of working on structured data from a long time but now this way of dealing with traditional RDBMS can be solved using Hadoop as well, for that it is needed to shift that data from traditional data stores to Hadoop which can be done using Sqoop. Sqoop is another important criterion to clear all the important certifications related to Hadoop as data import and export is also a big demand of Hadoop industry today. So for that reason, you should have a sound knowledge of it using the connectors which makes the migration possible.

Online Data Collection: Another Important Scenario

Talking about the online data collection which is another important scenario in Hadoop ecosystem where flume plays an important role so that the streaming online data can be collected, e.g., consider the example that you have a remote system somewhere around your network from which you want to fetch online data, so this can be accomplished using Flume where you can use telnet to collect online data from your source location. All you need to do is to specify the particular port from which online data will arrive and this is done particularly in the configuration file of flume where you basically define the source from where the data has to be collected (be it web servers or your remotely accessible system) and the destination where the data has to be written (typically HDFS).

 So How Can You Be Prepared for the Certification?

A good knowledge on flume helps you to achieve a plus point in this certification.

When you talk about Hadoop, be it interviews or certifications all you need are basic concepts on Yarn, Hive, Pig, Sqoop, Flume and MapReduce. Whereas MapReduce which is written totally using Java and is the aggregation of Map and Reduce, algorithm plays as the foundation of data processing in Hadoop and is the major construct of the framework.

The theoretical concepts of working of MapReduce are equally important but still if you have a good knowledge on the other skill sets, you can be a good fit for Hadoop.

But remember again – a good understanding of everything is equally important to set the standard.