Processing real-time data using Apache Storm | Big Data Hadoop Full Course
In this video, we're going to talk about processing real-time data using Apache Storm where we have seen and executed provided word count topology written in Java to process real-time data streams and get the aggregated word counts for specific time window.
Below are the commands for this lecture:
start Storm, Kafka through Ambari
cd /usr/hdp/current/storm-client
cd contrib/storm-starter/src/jvm/org/apache/storm/starter
vi WordCountTopology.java
go to ambari login as admin
services- storm- configs- advanced storm-env- Enable Atlas Hook- Enable-Save- restart storm
storm jar /usr/hdp/current/storm-client/contrib/storm-starter/storm-starter-topologies-1.1.0.2.6.5.0-292.jar org.apache.storm.starter.WordCountTopology wordcount
Browser
localhost:8744
cd /usr/hdp/current/storm-client/logs
cd workers-artifacts
tail -f worker.log
In the previous lecture we have seen Apache Storm which is yet another real-time data processing tool designed to handle Big Data. Here we have seen what is Apache Storm, how its compared to other data processing tools like Apache Spark Streaming and Apache Flink and all about its components and Storm architecture in detail.
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HDP Sandbox Installation links:
Oracle VM Virtualbox: https://download.virtualbox.org/virtu...
HDP Sandbox link: https://archive.cloudera.com/hwx-sand...
HDP Sandbox installation guide: https://hortonworks.com/tutorial/sand...
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Audience
This tutorial is made for professionals who are willing to learn the basics of Big Data Analytics using Hadoop Ecosystem and become a Hadoop Developer. Software Professionals, Analytics Professionals, and ETL developers are the key beneficiaries of this course.
Prerequisites
Before you start proceeding with this course, I am assuming that you have some basic knowledge to Core Java, database concepts, and any of the Linux operating system flavors.
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