Hadoop Ecosystem Infographic – Explore Ecosystem Components

Boost your career with Free Big Data Courses!!

Hadoop is the most popular Big Data framework, which can handle huge volumes of data. Hadoop comes with tons of ecosystem tools to solve different Big Data problems. Ecosystem played an important behind the popularity of Hadoop. With the ecosystem components, there are many solutions available for different problems, like unstructured data can be handled with MapReduce, structured data with Hive, machine learning algorithm with Mahout, text search with Lucene, data collection and aggregation using Flume, administration of cluster using Ambari and many more.

Hadoop uses HDFS and MapReduce to process a large amount of data, and Hive for querying that data. Like HDFS, MapReduce, and Hive, there are many other components you can explore through this Hadoop Ecosystem infographic below.

Hadoop Ecosystem Infographic

Hadoop Ecosystem Infographic

Hope this Hadoop Ecosystem Infographic helped you to understand Hadoop well.

Hadoop ecosystem is a platform, which can solve diverse Big Data problems. It can store as well as process 1000s of Petabytes of data quite efficiently. Hadoop is the backbone of all the big data applications.

As discussed above in the Hadoop ecosystem there are tons of components. Let’s start with HDFS – world’s most popular data store, YARN – resource management layer, which manages/allocates/releases resources of the cluster, MapReduce – distributed computing model, which utilizes the power of distributed computing to process the data at lightning fast speed.

If we talk about a few important ecosystem components: Hive – Data warehouse on the top of Hadoop, which provides simplicity of SQL with the power of Hadoop. Pig – top-level data processing engine, which enables users to run a script to process/parse data. HBase – a column-oriented NoSQL DB, which handles the data with random read/write. Drill – Schema-free SQL Query Engine, which provides faster insights without the overhead of data loading, schema creation. Mahout – Scalable machine learning library on top of Hadoop, which provides ML algorithm at a massive scale. Flume – Data collection system, which provides real-time collection and aggregation of Big Data. Ambari – Installation and configuration tool, which can be used for deployment, management, maintenance & monitoring tool.

So, this was all about Hadoop Ecosystem Components. Check the most asked Hadoop Interview Questions.

We are waiting for your valuable feedback. Do share your reviews through comments.

Did you like our efforts? If Yes, please give DataFlair 5 Stars on Google

follow dataflair on YouTube

1 Response

  1. Nihad Almahrooq says:

    Good Infographic for hadoop ecosystem, however I do not see Kafka, or Chukwa does similar jobs or its with Chukwa ?

Leave a Reply

Your email address will not be published. Required fields are marked *