Smart Strategies to start with Hadoop Development

Hadoop is a powerful web framework used to create web applications easily. And, if you want to start development with Hadoop then in this blog you will get to know about the same.

Some Strategies to begin with Hadoop development are examined underneath-

1. High-level understanding of Hadoop:

To start with Hadoop development, you must have knowledge and understanding of Hadoop, including Hadoop distributed file system (HDFS), MapReduce programming model as well as other technologies and tools like pig, hive, zookeeper, etc. For this, you Can Learn Big Data Hadoop .

2. Great Understanding of Big Data:

You should have a good knowledge of 4v’s of big data which are also known as dimensions of big data, i.e., volume, variety, velocity and veracity. There are various Big Data repository sites from where we can download the data sets for processing and analyzing.

3. Identify Gaps in Existing Hadoop Development:

You have to identify the gaps in existing development of Hadoop because Hadoop big data skills gap is one of the major gap which you have to avoid to develop the smart Hadoop applications. To fill the gaps, organizations should provide big data Hadoop sessions for their existing employees or else hire big data and Hadoop professionals.

4. Developing Data Model:

For any of the development problem, you have to develop use cases because when we gather requirements then we have to define list of steps and build data model which will be possible when we make sequence of action for that particular development problem.

5. Understanding of Object Oriented Programming:

For development purpose in Hadoop, you have to be aware with object oriented programming as well. Because to develop any Hadoop application, you need to use a particular language that may be any programming language such as Python, Java, etc.

6. Installing and Configuring Hadoop:

For starting development in Hadoop, you have to be aware with installing the Hadoop framework as well as configuring that framework like setting replication factor, etc. You can use any of the Hadoop distributions like Cloudera (CDH), Hortonworks (HDP), and MAPR, etc., or else you can learn How install Hadoopframework on UNIX system.

7. A quick comparison between Hadoop and MapReduce:

Hadoop is a product system that empowers the product application that keeps running on ware equipment. Hadoop has two center segments:

HDFS and MapReduce. HDFS permits you to store massive information on servers while MapReduce is a programming model that process substantial information in distributed manner. MapReduce is a heart of Hadoop.

8. Processing of unstructured data-

In today's period, information is producing in homogenous structure like pictures, features, remark, status, etc. Hadoop is made to store any sort of information. In any case, you want to have better look on how to process pictures, audio, or documents, you can use MapReduce, PIG, HIVE and HBASE. It not only stores unstructured information, but also analyze them which is generally more important.

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