Gautam Goswami - Real-time Data Streaming, Real-time Data Processing, Real-time Data Analytics | Data Engineering Solution in Bangalore | Apache Kafka Streaming Solutions in Bangalore | Kafka Confluent Cloud Solutions in Bangalore | Kafka Streaming Implementation Support in Bangalore | Apache Kafka Support in Bangalore | Multinode Kafka Cluster Setup in Bangalore | Kafka Application Consulting in Bangalore | Kafka cloud implementation in Bangalore | Kafka infrastructure consulting in Bangalore | Kafka security implementation in Bangalore | Kafka upgrade support in Bangalore | Zookeeper setup support in Bangalore | Zookeeper Solutions in Bangalore | Multinode Zookeeper Setup in Bangalore | Big Data Consulting Service Providers in Bangalore | Data Analytics Consutling Services in Bangalore | Big Data Solution Providers in Bangalore | Big Data Analytics Companies in Bangalore | Data Analytic Services in Bangalore | Big Data Services in Bangalore | Big Data Analytics Solutions in Bangalore | Big Data Analytics Service Providers in Bangalore | Big Data Case Studies | Big Data Companies in Bangalore | Multi Node Hadoop Cluster | Data Lake creation and support | Data Ingestion Services in Bangalore | Koolanch | Artificial Intelliegence Solutions in Bangalore | Predictive Analysis Solution in Bangalore | Machine Learning Solution in Bangalore | Deep Learning Solutions Bangalore | ChatBots for Websites | Text to Speech API | DialogFlow ChatBots | ChatBots using DialogFlow | AI based image processing | AI solution providers in Bangalore | AI based Predictive Analytics | Conversational Bots Development in Bangalore | AI chatbots and voicebots | E-Commerce Solution Providers in Bangalore | Demandware Consulting Service in Bangalore | Demandware Companies in Bangalore | SFCC Consulting Service in Bangalore | SFCC Consulting Companies in Bangalore | SFCC Service Providers in Bangalore | Demandware Contract Staffing in Bangalore | Salesforce Commerce Cloud Consulting Services in Bangalore | SFCC Contract Staffing in Bangalore | Salesforce Commerce Cloud Contract Staffing in Bangalore | Oracle Consulting Services in Bangalore | Oracle Service Providers in Bangalore | Oracle Contract Staffing in Bangalore | OCC Contract Staffing in Bangalore | Oracle Commerce Cloud Consulting in Bangalore | Oracle Commerce Cloud Companies in Bangalore | SAP Hybris Consulting Services in Bangalore | SAP Hybris Service Providers in Bangalore | SAP Hybris Contract Staffing in Bangalore | SAP Hybris Commerce Cloud Consulting in Bangalore | SAP Hybris Companies in Bangalore | SAP Hybris Solutions in Bangalore | Hybris Commerce Solution in India | Hybris Solution Provider Companies | Magento Consulting Services in Bangalore | Magento Service Providers in Bangalore | Magento Contract Staffing in Bangalore | Magento Commerce Cloud Consulting in Bangalore | Magento Companies in Bangalore | Mobile App Development Company in Bangalore | Android App Development Services in Bangalore | Location Tracking Based Mobile App Development | Mobile App Development In Bangalore | Mobility Solution Provider in Bangalore | SQL Server Support Services in Bangalore | SQL Server Support Companies in Bangalore | Data Mining Solution in Bangalore | Custom App Development in Bangalore | Contract Staffing Solution in Bangalore

Network Topology To Create Multi Node Hybrid Cluster For Hadoop Installation

The aim of this article is to provide an outline for creating network topology for Hadoop installation in multi node hybrid cluster with limited available hardware resources. This cluster would be beneficial for learning Hadoop, with lower volume of unstructured data processing using various engines etc. Before the cluster setup: We installed Hadoop on a single node cluster running on Ubuntu 14.04 on top of Windows 10 using VMware workstation player. Later we have copied the .vmx file into multiple...

Data Governance & Security Mechanism in Distributed Data Storage System

We are aware that the traditional data storage mechanism is incapable to hold the massive volume of data generated with lightning speed for further utilization even if we perform vertical scaling, and we have anticipated only one fuel, nothing but DATA to accelerate the movement across all the sectors starting from business to natural resources including medical towards rapid growth. But the question is how to persist this massive volume of data for processing? The answer is, storing the data...

Apache Flink – A 4G Data Processing Engine

Analyzing streaming data in large-scale systems is becoming a focal point day by day to take accurate business decisions due to mushrooming of digital data generation sources around the globe including social media. Real-Time analytics are becoming more attractive due to possibilities of getting insights from the time-value of data (in other words, when data is in motion). Apache Flink, an open source highly innovative stream processor engine has been grounded which helps to take advantage of stream-based approaches. Besides...

Steering number of mapper (MapReduce) in sqoop for parallelism of data ingestion into Hadoop Distributed File System (HDFS)

To import data from most the data source like RDBMS, sqoop internally use mapper. Before delegating the responsibility to the mapper, sqoop performs few initial operations in a sequence once we execute the command on a terminal in any node in the Hadoop cluster. Ideally, in production environment, sqoop installed in the separate node and updated .bashrc file to append sqoop's binary and configuration which helps to execute sqoop command from anywhere in the multi-node cluster. Most of the...

Transfer structured data from Oracle to Hadoop storage system

Using Apache's sqoop, we can transfer structured data from Relational Database Management System to Hadoop distributed file system (HDFS). Because of distributed storage mechanism in Hadoop Distributed File System (HDFS), we can store any format of data in huge volume in terms of capacity. In RDBMS, data persists in the row and column format (Known as Structured Data). In order to process the huge volume of enterprise data, we can leverage HDFS as a basic data lake. In this...

Data Ingestion phase for migrating enterprise data into Hadoop Data Lake

The Big Data solutions helps to achieve valuable information to iron out the accurate strategic business decision. Exponential growth of digitalization, social media, telecommunication etc. are fueling enormous data generation everywhere. Prior to process of huge volume of data, we should have efficient data storage mechanism in a distributed manner to hold any form of data starting from structured to unstructured. Hadoop distributed file systems (HDFS) can be leveraged efficiently as data lake by installing on multi node cluster....

Why Lambda Architecture in Big Data Processing

Due to the exponential growth of digitization, the entire globe is creating minimum 2.5 Quintilian 2500000000000 Million) bytes of data every day and that we can denote as Big Data. Data generation is happening from everywhere starting from social media sites, various sensors, satellite, purchase transaction, Mobile, GPS signals and much more. With the advancement of technology, there is no sign of slowing down of data generation, instead it will grow in massive volume. All the major organizations, retailers,...

Apache Kafka, The next Generation Distributed Messaging System

In Big Data project, the main challenge is to collect an enormous volume of data. We need distributed high throughput messaging systems to overcome it. Apache Kafka is designed to address the challenge. It was originally developed at LinkedIn Corporation and later on became a part of Apache project. A Messaging System is typically responsible for transferring data from one application to another. A message is nothing but the bunch of data/information. To ingest huge volume of data into Hadoop...

Fog Computing

Fog computing also refer to Edge computing . Cisco Systems introduced the term "Fog Computing" and it's not the replacement of cloud computing. Ideally cloud computing points to storing and accessing data and programs over the Internet instead of local computer's hard drive or storage. The cloud is simply a metaphor for the Internet. In Fog computing, data, processing and applications are concentrated in devices at the network edge. Here devices communicate peer-to-peer so that data storage and share...

Basic concept of Data Lake

The left side info graphics represents the basic concept of Data Lake where we can use the approach of ELT (Extraction, loading and then transformation) against traditional ETL (Extraction, Transformation and then loading) process. ETL process implies to traditional data warehousing system where structured data format follows (row and column). By leveraging HDFS (Hadoop Distributed File System), we can develop data lake to store any format data in order to process and analysis. Directly data can be loaded in the Lake...

Author - Gautam Goswami