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11JanJanuary 11, 2021

Data Absorption (Ingestion)

By Kislay KomalAbsorption, accumulate business data, Apache Flume, Apache Kafka, Apache Sqoop, Big Data Analysis service in Bangalore, Big data ingestion architecture, central data repository, creating hadoop data lake, Data Absorption, Data Absorption Service in Bangalore, data analytics, Data ingestion, data ingestion architecture, Data Ingestion Service in Bangalore, Data Lake, data pipeline, distributed centralized repository, Hadoop Data Lake, Hadoop Data Lake Creation, heterogeneous data, how to create hadoop data lake, IDropper, Ingestion, ingestion architecture, Kafka, moving heterogeneous data, poc, preserve business data, production server log files, proof of concept, rdbms, Sqoop, structured data, unstructured data, using apache flumeComments Off

25DecDecember 25, 2020

Data Engineering, Streaming & Cloud Solutions

The data tsunami The term Big Data is a buzzword now-a-days which has no specific formats and defies traditional storage systems. The data can be structured, semi-structured or unstructured and generated faster than ever. For example, information post over social media, video upload in YouTube etc. Machine generated data like data recorded from sensor and logs are also becoming part of big data having more magnitude then human generated data. Though Apache Hadoop is a popular framework for distributed storage and...

17SepSeptember 17, 2017

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...

By Gautam GoswamiData Engineering, Data IngestionData ingestion, Hadoop Distributed File System, HDFS, Map Reduce, parallelism of data ingestion, Sqoop, sqoop for parallelism of data ingestion into Hadoop Distributed File System (HDFS)Comments Off

08SepSeptember 8, 2017

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...

By Gautam GoswamiData Engineering, Hadoop Eco SystemAmazon web service, Apache Sqoop, Apache's sqoop, Data ingestion, Data ingestion mechanism, distributed storage, distributed storage mechanism, enterprise data, Google cloud, Hadoop, Hadoop 2.x, Hadoop Distributed File System, Hadoop storage system, HDFS, huge volume of enterprise data, Microsoft Azure, multi node cluster, Oracle to Hadoop, Sqoop, structured data, Transfer structured data from Oracle to Hadoop, Using Apache sqoopComments Off

29AugAugust 29, 2017

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....

By Gautam GoswamiData Engineering, Data IngestionApache software foundation, Apache Sqoop, ata storage mechanism, ATG database, ATG database schema, cloud service providers, collecting Twitter streaming data, Couchbase, Data ingestion, Data Ingestion phase for migrating enterprise data into Hadoop Data Lake, Data Lake, data storage mechanism, DB2, Digitization, distributed storage, efficient data storage mechanism, ELT, enterprise data, export data from Kafka topic to HDFS, fault-tolerant, Flume, Hadoop, HADOOP Cluster, Hadoop Data Lake, Hadoop distributed file systems, Hadoop multi node cluster, HDFS, Hive, huge data reservoirs, huge volume of data, Ingestion, JDBC connector, JDBC protocol, Kafka, Kafka HDFS connector, Kafka to HDFS, Mainframe, mainframe dataset to HDFS, MapReduce, MapReduce distributed computing, migrating enterprise data, moving large amount of streaming data into HDFS, multi node cluster, multiple delimited text files, MySQL, Netezza, NoSql DB, NoSql Stores, Oracle, Oracle 11g Enterprise Edition, Oracle ATG Platform, parallel import process, parallel processing, pluggable mechanism, PostgreSQL, read the messages from Kafka topic, SQLServer, Sqoop, Sqoop installation, Strom, Using Kafka HDFS connectorComments Off

21AprApril 21, 2017

Irisidea’s Competencies

The technical leadership team is the core strength of Irisidea Technologies. Irisidea's business and technical experts not only work closely with clients to provide cost effective, robust solutions to their business needs, but also dedicate a part of their time regularly in research work and keeping themselves on the edge of technology. Each individual of this team is not only an expert in his domain, but he also strives to expand his knowledge horizon by learning new technologies that...

By Kislay Komal.NET Framework 3.5/4.0, 2008, Ability to quickly learn and get expertise on new domains & technologies, Ability to Work in Harmony with Co-Workers, ADO.NET, AI Application Maintenance, AI Deployment, AI Deployment Environment Setup, AI Development Environment Setup, AI Implementation, AI Support, AI Testing, AJAX, Ambari, Apache Ranger, Application Platforms/Tools, Artificial Intelligence, ASP.NET, ATG Commerce Designing Tools, C#.NET, CMS Tools, Css, Curl, Databases, Deep learning, Demandware, Determination and Persistence, Development and Maintenance, Development Platforms, Development Tools, DHTML, DOM, Dreamweaver CS4, Drupal E-Commerce Platforms, Eclipse, endeca, Enthusiastic & passionate team, Flash CS4, Flexibility to adjust as per the situations project demand, Flume, Frameworks, Hadoop and its ecosystem, Hibernate, Hive, HTML, IBM DB/2, Illustrator Data Bases, j2ee, Java Expertise, Java Scripts, JavaScript, JBoss Java Technologies : Java, Joomla, JProbe, JProfiler, JQuery, JSP, Kafka, Languages, Linux, machine learning, magento, Microsoft Office SharePoint Server (MOSS) 2007, Microsoft SQL Server, Microsoft Technologies Expertise, MS Exchange, MS Office, MS SQL Server 2005/2008, MS-SQL Server, Multi Nodes Hadoop Cluster Management, MySQL, MySQL Profiler, NET, Net Beans, Nifi, OfBiz, Oracle, Oracle Cloud Commerce, Oracle Commerce, Oracle Development Platforms, Oracle-ATG, Photoshop CS4, PHP, Predictive Analytics, ROR, SalesForce Commerce Cloud, SharePoint 2010, SOAP, Social Data Analytics, Spring, Sqoop, Strong communication skills, Struts, Tomcat, Visual Studio 2008/2010, Web Services, Web/Application Servers, website design, Windows, Windows Server 2003, WordPress, WSS 3.0, XHTML, XML, Zen cart, ZookeeperComments Off

Tag - Sqoop

Data Absorption (Ingestion)

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

Transfer structured data from Oracle to Hadoop storage system

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