Big data has garnered immense interest among many organisations across industries who are looking to get the most out of the information they have. A sub-project of Hadoop, MapReduce is one of the important big data processing tools and have increased in popularity in the recent years. If you want to know more about MapReduce and what are its advantages, read on…
What is MapReduce?
MapReduce in simple terms can be explained as a programming model that allows the scalability of multiple servers in a Hadoop cluster. It can be used to write applications to process huge amounts of data in parallel on clusters of commodity hardware. It is inspired by the map and reduce functions commonly used in functional programming.
A MapReduce program usually executes in three stages — map stage, shuffle stage and reduce stage.
- Map stage – In this stage, the input data is split into fixed sized pieces known as input splits. Each input split is passed through a mapping function to produce output values.
- Shuffle stage – The output values from the map stage is consolidated in the next stage, which is the shuffle stage.
- Reduce stage – The output from the shuffle stage is are combined to return a single value and is stored in the HDFS.
What are the strengths of MapReduce?
Apache Hadoop usually has two parts, the storage part and the processing part. MapReduce falls under the processing part. Some of the various advantages of Hadoop MapReduce are:
- Scalability – The biggest advantage of MapReduce is its level of scalability, which is very high and can scale across thousands of nodes.
- Parallel nature – One of the other major strengths of MapReduce is that it is parallel in nature. It is best to work with both structured and unstructured data at the same time.
- Memory requirements – MapReduce does not require large memory as compared to other Hadoop ecosystems. It can work with minimal amount of memory and still produce results quickly.
- Cost reduction – As MapReduce is highly scalable, it reduces the cost of storage and processing in order to meet the growing data requirements.
Also read>> Top MapReduce Interview Questions
What are the advantages of getting a MapReduce certification?
Big data is a growing field and offers lucrative job opportunities. If you want to start a successful career as a big data developer or a big data architect, you should look at the various advantages a certification in MapReduce offer:
- A certification in MapReduce will showcase your ability and skills in the framework, making it easy for recruiters to understand if you are the right person for the job.
- There can be many candidates vying for the same job or position that you are looking for in an organisation. However, if you are the only one with a certification, it can speak in favour of you.
- Based on a Naukri survey, 67% of the recruiters mentioned that they prefer certified candidates and are also willing to pay higher.
- It strengthens your resume and you can stand out whenever you are applying for a job.
What are the top MapReduce certifications you can go for?
There are a number of Hadoop MapReduce certifications which can help you in becoming a successful big data professional. Some of the mentionable courses in Naukri Learning are:
- Apache Hadoop and MapReduce Essentials Certification – This course has been designed to provide the essential training to candidates on cloud computing with the help of Apache Hadoop and MapReduce. It also offers an understanding of the Hive programming using real-life projects.
- Big Data and Hadoop Spark Developer Certification – Get a comprehensive understanding of big data analysis through Hadoop, using frameworks like MapReduce, Yarn, Spark, Pig, Hive, Impala and HBase.
- Hadoop Analyst Certification – This is an intensive training course that will help candidates to gain valuable practical knowledge on big data analysis using frameworks like MapReduce and HDFS. It will also give you a fundamental understanding of Pig and Impala.
With the above professional online course in MapReduce, you will get to have hands-on experience in working with big data, using Hadoop. Get a Hadoop certification and boost your career.