Apache hadoop ecosystem training

Consulting and IT Services of Expert Compute Solutions focus on defining, optimizing and aligning. We offer the best training and development in emerging technologies like BigData,Hadoop,HIVE,HBASE,NOSQL,PIG,SQOOP,NoSQL and Apache Hadoop Ecosystem. Nearly three quarters of respondents say demand for data-driven insights will accelerate during the next 12 to 18 months. And, most say that there will be a major increase in pace.WellPoint is using big data and analytics to tackle one of the biggest issues in healthcare: how to make more effective decisions about approving medical procedures and getting patients the care they need more quickly.Now companies have reported that the strategies that are helping them the most are the ones that create agile and flexible infrastructures they can build on and pull insights quickly from. Rather than just managing data, companies are now coming up with innovative approaches for making the most of it. Register Soon ! ecpertcompute.in +91 Special discounts for Early bird registration Group discounts available.

Type Computer Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation. Hadoop makes it possible to run applications on systems with thousands of nodes involving thousands of terabytes. Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating uninterrupted in case of a node failure. This approach lowers the risk of catastrophic system failure, even if a significant number of nodes become inoperative. Hadoop was inspired by Google's MapReduce, a software framework in which an application is broken down into numerous small parts. Any of these parts (also called fragments or blocks) can be run on any node in the cluster. Doug Cutting, Hadoop's creator, named the framework after his child's stuffed toy elephant. The current Apache Hadoop ecosystem consists of the Hadoop kernel, MapReduce, the Hadoop distributed file system (HDFS) and a number of related projects such as Apache Hive, HBase and Zookeeper. The Hadoop framework is used by major players including Google, Yahoo and IBM, largely for applications involving search engines and advertising. The preferred operating systems are Windows and Linux but Hadoop can also work with BSD and OS X. Thanks & Regards, Sky InfoTech Corporate Office: A-50,Sec-64,Noida(U.P) Noida- , / Delhi –/ Gurgaon – /

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Hadoop Cluster- Single and Multi node, Hadoop 2.x, Flume, Sqoop, Map-Reduce, PIG, Hive, Hbase, Zookeeper, Oozie etc. will be covered in the course. This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course. We have a dedicated placement cell which provides 100% placement assistance in Hadoop to all the candidates. REGISTRATION FOR SHORT TERM COURSE TRAINING BY DUCAT,,,,,, STARTED NOW!!! (Limited seats) Ducat, Plot No.1, Anand Industrial Estate, Near ITS College, Mohan Nagar, Ghaziabad (UP) Mob: +/ Ph.

Apache Hadoop is an open-source software framework for storage and large scale processing of data-sets on clusters of commodity hardware. Hadoop is an Apache top-level project being built and used by a global community of contributors and users. Hadoop careers? Hadoop Areas of expertise Hadoop Administration, development NoSQL and real time analytics Big Data/Hadoop solution Architecture, Design & Development Social Media, Community & Viral Marketing Business Development, Global Scale Big Data strategy About online training expert trainers Online trainings expert prides itself on ensuring that our online trainers are real time experts.only the online training company deliver online training programs to our valued candidates. As part of online trainings expert continuous improvement in online trainings. Each trainer is regularly assessed to candidates given the best quality of training every time. All our trainers are skilled trainers and addition have the real time experience with proven track record in online trainings. This experience qualifies them as a specialist in their online training delivery in their course. Why Hadoop Online Training Only with online trainings expert? 1. We just do not teach you technology. We Share Our Real time implementation expertise to gain practical skills and knowledge to face customers, implement better solutions further to enlighten your careers. 2. We just do not teach curriculum. We make sure to see that you are up to the industry expectations by giving real time scenarios, providing case studies, and giving project oriented examples. We will also provide well designed Lab Manuals, Study Materials, and Practice Exercises for quick learning process. 3. We just do not make developers or consultants or managers. We make full pledged competitive IT Professionals.

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs • Map-side join • Reduce-Side join and...

HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: • Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool • Tableau 1. Virtualbox/VM Ware • Basics • Installations • Backups • Snapshots 2. Linux • Basics • Installations • Commands 3. Hadoop • Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop • Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System • HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes • Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce • Developing Map ..........

Hadoop administration training course is a comprehensive study of Big Data Administration using Hadoop. The course topics include Introduction to Hadoop and its Architecture, MapReduce and HDFS and MapReduce Abstraction. It further covers best practices to configure, deploy, administer, maintain, monitor and troubleshoot a Hadoop Cluster. Through this course, our trainees are going to be able to acquire those challenging positions that are opening up rapidly in the Big Data field. - Hadoop Developer Course Objectives *Comprehend internals of HDFS and MapReduce. * Learn how to write MapReduce code * Comprehend Hadoop debugging, development, and execution of workflows and algorithms * leverage Hive, Oozie, Pig, Flume, Sqoop, and other Hadoop ecosystem projects * Comprehend Advanced Hadoop API topics. * Monitor and maintain hundreds of servers

Hadoop Online Training in Depth, Writable and WritableComparable Level of coding. Technologies: Core Java, Hadoop, HDFS, Map Reduce, Advance HDFS, Advance MapReduce, Hive, Pig, Advanced Programming Pig, Sqoop, HBase, Flume, Oozie, Zookeeper, Kafka, Falcon, Log4J, MRUnit, POC's, Hadoop Installation in Linux, All other Ecosystem Installation in Linux. Cloudera and Hortonworks. Advanced F/W: Scala, SPARK, Storm, Mahout, R, Matlab Call me + www.hadoopexpert.in Note: This online Training is not like other online training(like entire training on PPT), there will be no PPT's only technical coding in depth and I can say its more technical, I have successfully completed 42 batches online from last 16 months on Hadoop. Successfully completed 8 bactches on Scala, Spark. Prerequisites: Basic Knowledge on Core Java. (If don't know then we have a separate classes for Java) Basic Knowledge on SQL. Look into the course content and compare with others you will see the quality. I can only say one statement "Lets Hadoop.......!"

Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation.Learn Hadoop Online Training at GangBoard

BIGDATA –HADOOP REALTIME TRAINING,JOB SUPPORT,INTERVIEW SUPPORT BY HANDS-ON EXPERTS Phone/WhatsApp: +91-(850) 012-2107 Course Content HADOOP Using Cloudera Development & Admin Course Introduction to BigData, Hadoop:- • Big Data Introduction • Hadoop Introduction • What is Hadoop? Why Hadoop? • Hadoop History? • Different types of Components in Hadoop? • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on… • What is the scope of Hadoop? Deep Drive in HDFS (for Storing the Data):- • Introduction of HDFS • HDFS Design • HDFS role in Hadoop • Features of HDFS • Daemons of Hadoop and its functionality • Name Node • Secondary Name Node • Job Tracker • Data Node • Task Tracker • Anatomy of File Wright • Anatomy of File Read • Network Topology • Nodes • Racks • Data Center • Parallel Copying using DistCp • Basic Configuration for HDFS • Data Organization • Blocks and • Replication • Rack Awareness • Heartbeat Signal • How to Store the Data into HDFS • How to Read the Data from HDFS • Accessing HDFS (Introduction of Basic UNIX commands) • CLI commands MapReduce using Java (Processing the Data):- • Introduction of MapReduce. • MapReduce Architecture • Data flow in MapReduce • Splits • Mapper • Portioning • Sort and shuffle • Combiner • Reducer • Understand Difference Between Block and InputSplit • Role of RecordReader • Basic Configuration of MapReduce • MapReduce life cycle • Driver Code • Mapper • and Reducer • How MapReduce Works • Writing and Executing the Basic MapReduce Program using Java • Submission & Initialization of MapReduce Job. • File Input/output Formats in MapReduce Jobs • Text Input Format • Key Value Input Format • Sequence File Input Format • NLine Input Format • Joins • Map-side Joins • Reducer-side Joins • Word Count Example • Partition MapReduce Program • Side Data Distribution • Distributed Cache (with Program) • Counters (with Program) • Types of Counters • Task Counters • Job Counters • User Defined Counters • Propagation of Counters • Job Scheduling PIG:- • Introduction to Apache PIG • Introduction to PIG Data Flow Engine • MapReduce vs PIG in detail • When should PIG used? • Data Types in PIG • Basic PIG programming • Modes of Execution in PIG • Local Mode and • MapReduce Mode • Execution Mechanisms • Grunt Shell • Script • Embedded • Operators/Transformations in PIG • PIG UDF’s with Program • Word Count Example in PIG • The difference between the MapReduce and PIG SQOOP:- • Introduction to SQOOP • Use of SQOOP • Connect to mySql database • SQOOP commands • Import • Export • Eval • Codegen and etc… • Joins in SQOOP • Export to MySQL HIVE:- • Introduction to HIVE • HIVE Meta Store • HIVE Architecture • Tables in HIVE • Managed Tables • External Tables • Hive Data Types • Primitive Types • Complex Types • Partition • Joins in HIVE • HIVE UDF’s and UADF’s with Programs • Word Count Example HBASE:- • Introduction to HBASE • Basic Configurations of HBASE • Fundamentals of HBase • What is NoSQL? • HBase DataModel • Table and Row • Column Family and Column Qualifier • Cell and its Versioning • Categories of NoSQL Data Bases • Key-Value Database • Document Database • Column Family Database • SQL vs NOSQL • How HBASE is differ from RDBMS • HDFS vs HBase • Client side buffering or bulk uploads • HBase Designing Tables • HBase Operations • Get • Scan • Put • Delete MongoDB:-- • What is MongoDB? • Where to Use? • Configuration On Windows • Inserting the data into MongoDB? • Reading the MongoDB data. Cluster Setup:-- • Downloading and installing the Ubuntu12.x • Installing Java • Installing Hadoop • Creating Cluster • Increasing Decreasing the Cluster size • Monitoring the Cluster Health • Starting and Stopping the Nodes OOZIE • Introduction to OOZIE • Use of OOZIE • Where to use? Hadoop Ecosystem Overview Oozie HBase Pig Sqoop Casandra Chukwa Mahout Zoo Keeper Flume • Case Studies Discussions • Certification Guidance • Real Time Certification and • interview Questions and Answers • Resume Preparation • Providing all Materials nd Links • Real time Project Explanation and Practice

Leo trainings is the first-rate online training & lecture room coaching Institute for Hadoop in united states of america,UK and INDIA. Hadoop is an open source framework. It is provided by Apache to process and analyze very huge volume of data. It is written in Java and currently used by Google, Facebook, LinkedIn, Yahoo, Twitter etc. delivering all programming. ourse Objective Summary During this course, you will learn: Introduction to Big Data and Analytics Introduction to Hadoop Hadoop ecosystem - Concepts Hadoop Map-reduce concepts and features Developing the map-reduce Applications Pig concepts Hive concepts Sqoop concepts Flume Concepts Oozie workflow concepts Impala Concepts Hue Concepts HBASE Concepts ZooKeeper Concepts Real Life Use Cases Reporting Tool Tableau 1.Virtualbox/VM Ware Basics Installations Backups Snapshots 2.Linux Basics Installations Commands 3.Hadoop Why Hadoop? Scaling Distributed Framework Hadoop v/s RDBMS Brief history of hadoop 4.Setup hadoop Pseudo mode Cluster mode Ipv6 Ssh Installation of java, hadoop Configurations of hadoop Hadoop Processes (NN, SNN, JT, DN, TT) Temporary directory UI Common errors when running hadoop cluster, solutions 5.HDFS- Hadoop distributed File System HDFS Design and Architecture HDFS Concepts Interacting HDFS using command line Interacting HDFS using Java APIs Dataflow Blocks Replica 6.Hadoop Processes Name node Secondary name node Job tracker Task tracker Data node 7.Map Reduce Developing Map Reduce Application Phases in Map Reduce Framework Map Reduce Input and Output Formats Advanced Concepts Sample Applications Combiner For more details to contact: Email: info@leotrainings.com Phone: +91-9553323599

​ HADOOP Training in Hyderabad @Sadguru Technologies Course Objective Summary During this course, you will learn: Introduction to Big Data and Analytics • Introduction to Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • Sqoop concepts • Flume Concepts • Oozie workflow concepts • Impala Concepts • Hue Concepts • HBASE Concepts • ZooKeeper Concepts • Real Life Use Cases Reporting Tool Tableau 1. Virtualbox/VM Ware Basics • Installations • Backups • Snapshots 2. Linux Basics • Installations • Commands 3. Hadoop Why Hadoop? • Scaling • Distributed Framework • Hadoop v/s RDBMS • Brief history of hadoop 4. Setup hadoop Pseudo mode • Cluster mode • Ipv6 • Ssh • Installation of java, hadoop • Configurations of hadoop • Hadoop Processes ( NN, SNN, JT, DN, TT) • Temporary directory • UI • Common errors when running hadoop cluster, solutions 5. HDFS- Hadoop distributed File System HDFS Design and Architecture • HDFS Concepts • Interacting HDFS using command line • Interacting HDFS using Java APIs • Dataflow • Blocks • Replica 6. Hadoop Processes Name node • Secondary name node • Job tracker • Task tracker • Data node 7. Map Reduce Developing Map Reduce Application • Phases in Map Reduce Framework • Map Reduce Input and Output Formats • Advanced Concepts • Sample Applications • Combiner 8. Joining datasets in Mapreduce jobs Map-side join • Reduce-Side join 9. Map reduce – customization Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom Output format class 10. Hadoop Programming Languages :- I.HIVE Introduction • Installation and Configuration • Interacting HDFS using HIVE • Map Reduce Programs through HIVE • HIVE Commands • Loading, Filtering, Grouping…. • Data types, Operators….. • Joins, Groups…...

Online Bigdata Hadoop Training is offered by RSTrainings in Hyderabad, RStrainings is providing classroom & Online Training on Hadoop Bigdata. Our Trainers are real time work experience with 12+ years. We allocate Trainings on Hadoop globally UK, India, Aus, Canada, Saudi, Singapore. Briefly about Course: •Introduction to Big Data and Analytics •Introduction to Hadoop •Hadoop ecosystem - Concepts •Hadoop Map-reduce concepts and features •Developing the map-reduce Applications •Pig concepts •Hive concepts •Sqoop concepts •Flume Concepts •Oozie workflow concepts •Impala Concepts •Hue Concepts •HBASE Concepts •ZooKeeper Concepts •Real Life Use Cases Contact for more: Mobile No: +

Online Bigdata Hadoop Training is offered by SBRTrainings in Hyderabad, SBRtrainings is providing classroom & Online Training on Hadoop Bigdata. Our Trainers are real time work experience with 12+ years. We allocate Trainings on Hadoop globally UK, India, Aus, Canada, Saudi, Singapore. Briefly about Course: •Introduction to Big Data and Analytics •Introduction to Hadoop •Hadoop ecosystem - Concepts •Hadoop Map-reduce concepts and features •Developing the map-reduce Applications •Pig concepts •Hive concepts •Sqoop concepts •Flume Concepts •Oozie workflow concepts •Impala Concepts •Hue Concepts •HBASE Concepts •ZooKeeper Concepts •Real Life Use Cases Contact for more: Mobile No: +.