Learn Apache Storm Online
Apache Storm Certification training from love science course equips you with expertise in stream process massive data technology of Apache Storm.
It equips you with expertise in Apache Storm for real-time event process with massive data. The course is developed to modify you to require up big data Hadoop developer responsibilities requiring Apache Storm skills.
By the end of this course, you will be able to describe the concepts of big data and its 3 Vs talk at different sizes of data and describe some use cases of big data, you can also explain the concepts of Apache Hadoop and real-time big data processing and describe some tools for real-time processing of big data.
Volume refers to the data volume and it is the size of digital data. Internet and social media effect as resulted in the explosion of digital data, data has grown from gigabytes to terabytes to petabytes and now we have exabytes. Total data on the internet was only eight exabytes in 2008 and three years later we had 150 exabytes it is growing in a very fast way it reached 670 exabytes in 2013 that was 30% growth per year in another ten years it supposes to exceed seven zettabytes how can we store and handle this much data.
We all know kilobyte and megabyte and gigabyte, the terabyte consist of one thousand gigabytes and one petabyte consist of one thousand terabytes, the new terms like exabyte and zettabyte and yottabyte had added to address big data sizes when we say big data we normally mean sizes like terabytes or more.
As you know and I wrote articles about Apache Hadoop the most popular framework for big data processing. it has to core components HDFS and MapReduce I explained it in previous posts, Hadoop uses HDFS to distribute the data to multiple machines and MapReduce to distribute the process to multiple machines, Hadoop distributes the processing to where the data is and uses the principles of moving to process to data instead to move data to process firstly the data is divided into multiple parts like data 1 data 2 data 3 and so on which can be distributed to multiple machines then the processing is done using CPU of each machine on the data of that machine.
Finishing this course will allow you to describe the concepts of Storm and explain streaming you can also describe the features and use cases for Storm you can also discuss the Storm data model, describe Storm architecture and its components and explain the different types of topologies.
Storm provides the computation system that can be used for real-time analytics, machine learning and unbounded stream processing it can take cautiously produced messages and can output to multiple systems.
Let's talk a little bit about Storm topology, a group of spouts and bolts running in a storm cluster from the Storm topology, spouts and bolts run in parallel there can be multiple spouts and bolts, topology determines how the output of spout is connected to the input of bolts and how the output of the bolt is connected to the input of other bolts.