Hadoop ecosystem

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Hadoop for Developers and Administrators Hadoop for Developers and Administrators Syllabus COURSE CONTENT Traning at hadoop school of training Magarpatta city Pune. (+91-93257-93756) www.hadoopschooloftraining.co.in Next level of development and administration Schedule: Day 1:BigData • Why is Big Data important • What is Big Data • Characteristics of Big Data • How did data become so big • Why should you care about Big Data • Use Cases of Big Data Analysis • What are possible options for analyzing big data • Traditional Distributed Systems • Problems with traditional distributed systems • What is Hadoop • History of Hadoop • How does Hadoop solve Big Data problem • Components of Hadoop • What is HDFS • How HDFS works • What is Mapreduce • How Mapreduce works • How Hadoop works as a system Day2: Hadoop ecosystem • Pig • What is Pig • How it works • An example • Hive • What is Hive • How it works • An example • Flume • What is Flume • How it works • An example • Sqoop • What is Sqoop • How it works • An example • Oozie • What is Oozie • How it works • An example • HDFS in detail • Map Reduce in details Day3: Hands On-¬‐ • VMsetup • Setting up Virtual Machine • Installing Hadoop in Pseudo Distributed mode Day 4: Hands On-¬‐ • Programs • Running your first MapReduce Program • Sqoop Hands on • Flume Hands Day 5: • Multinode cluster setup • Setting up a multimode cluster Day 6: • Planning your Hadoop cluster • Considerations for setting up Hadoop Cluster • Hardware considerations • Software considerations • Other considerations Day 7: Disecting the Wordcount Program • Understanding the Driver • Understanding the Mapper • Understanding the Reducer Day 8: • Diving deeper into MapReduce • API • Understanding combiners • Understanding partitioners • Understanding input formats • Understanding output formats • Distributed Cache • Understanding Counters Day 9: • Common Mapreduce patterns • Sorting Serching • Inverted Indexes Day 10: • Common Mapreduce patterns • TF-IDF • Word-Cooccurance Day 11: • Hands on Mapreduce Day 12: • Hands on Mapreduce Day 13: • Introduction to Pig and Hive • Pig program structure and execution process • Joins • Filtering • Group and Co-Group • Schema merging and redefining schema • Pig functions • Motivation and Understanding Hive • Using Hive Command line Interface • Data types and File Formats • Basic DDL operations • Schema Design Day 14: • Hands on Hive and Pig Day 15: • Advanced Hadoop Concepts • Yarn • Hadoop Federation • Authntication in Hadoop • High Availbability Day 16: • Administration Refresher • Setting up hadoop cluster - Considerations • Most important configurations • Installation options Day 17: • Scheduling in Hadoop • FIFO Scheduler • Fair Scheduler Day 18: • Monitoring your Hadoop Cluster • Monitoring tools available • Ganglia • Monitoring best practices Day 19: • Administration Best practices • Hadoop Administration best practices • Tools of the trade Day 20: • Test • Test – 50 questions test (20- Development releated, 20- • Administration related and 10 Hadoop in General Please Contact- Hadoop School of Training Destination Center, Second Floor Magarpatta City Pune: 411013 Phone: India: +91-93257-93756 USA: 001-347-983-8512 www.hadoopschooloftraining.co.in Email: learninghub01@gmail.com Skype: learning.hub01

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 9. Map reduce – customization • Custom Input format class • Hash Partitioner • Custom Partitioner • Sorting techniques • Custom Output format class

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,

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

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 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…. • Sample programs in

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 trainers Required in elegant it services good salary in partime • Introduction to Big Data and Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • HBASE Concepts • Mongo DB Concepts • Sqoop Concepts • Real Life Use Cases Introduction to Big Data and Hadoop • What is Big Data? • What are the challenges for processing big data? • What technologies support big data? • What is Hadoop? • Why Hadoop? • History of Hadoop • Use Cases of Hadoop • Hadoop eco System • HDFS • Map Reduce • Statistics Understanding the Cluster •Typical workflow • Writing files to HDFS • Reading files from HDFS • Rack Awareness • 5 daemons Let's talk Map Reduce • Before Map reduce • Map Reduce Overview • Word Count Problem • Word Count Flow and Solution • Map Reduce Flow • Algorithms for simple problems • Algorithms for complex problems Developing the Map Reduce Application • Data Types • File Formats • Explain the Driver, Mapper and Reducer code • Configuring development environment - Eclipse • Writing Unit Test • Running locally • Running on Cluster • Hands on exercises c • Anatomy of Map Reduce Job run • Job Submission • Job Initialization • Task Assignment • Job Completion • Job Scheduling • Job Failures • Shuffle and sort • Oozie Workflows • Hands on Exercises Map Reduce Types and Formats • MapReduce Types • Input Formats - Input splits & records, text input,binary input, multiple inputs & database input. • Output Formats - text Output, binary output, multiple outputs, lazy output and database output • Hands on Exercises. Map Reduce Features •Counters • Sorting • Joins - Map Side and Reduce Side • Side Data Distribution • MapReduce Combiner • MapReduce Partitioner • MapReduce Distributed Cache • Hands Exercises Hive and PIG • Fundamentals • When to Use PIG and HIVE • Concepts • Hands on Exercises HBASE • CAP Theorem • Hbase Architecture and concepts • Programming and Hands on Exercises Case Studies Discussions Thanks&Regards Elegant IT Services, #nd Floor,Aswath Nagar Varthur main road,Near Railway Fly Over Maratha halli,Land mark: Chemmunar Jewellers,

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 – / Website- http://skyinfotech.in/HADOOP.aspx

Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce framework and managing large data sets with HBase. The topics covered in this course mainly includes- Hive, Pig and setup of Hadoop Cluster. Big Data is a set of unstructured and structured data that is complex in nature and is growing exponentially with each passing day. Organizations are facing a major challenge in storing and utilizing this enormous data. This problem spans across the world because of a serious dearth of skilled programmers. 30 hrs of live online classes by highly qualified Hadoop professionals In-session practice exercises for gaining practical understanding Suitable for database developers, programmers, BI developers and DBA�s bigdata hadoop, hadoop training, data analytics training, bigdata analytics Forrester predicts, CIOs who are late to the Hadoop game will finally make the platform a priority in . Hadoop has evolved as a must-to-know technology and has been a reason for better career, salary and job opportunities for many professionals. Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai-20 To register for upcoming classes weekends(Classroom) July - Fast Track (Classroom)- July Online Class- July

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 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: +91-905-269-9906

​ 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.,

​ 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.,

​ 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…...

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…. • Sample

FOR FREE DEMO contact us at: Phone/WhatsApp: +91-(850) 012-2107 HADOOP ONLINE TRAINING BY REALTIME CORPORATE PROFESSIONALS Hadoop Course Content (we can customize the course content as per your requirement) 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 Phone/WhatsApp: +91-(850) 012-2107

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

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

Learn Hadoop Training in Chennai Are you excited and want to learn big data technologies. Do you feel that internet is all littered free materials but it’s complicated for a newbie? Free internet learning material can be a can worms for a beginner and training is advised for a jump start but then do you feel that big data company offered trainings would cost you an arm and a leg? When you look at webinar trainings by other than institutes, you find it of poor quality and dodgy without guarantee. The world can go upside down while learning a new complicated technology as Hadoop. Become a certified Hadoop developer covers everything you need to know to start a career in Hadoop technology and achieve expertise to a level where you can face certification like Cloudera and Hortonworks with confidence. You can start as a beginner and this course would help you to become a certified professional. This course would take you through the nee and event of big data technologies. Why Choose Hadoop? How to setup Hadoop details HDFS mechanism, how Map Reduce program works in MapReduce classic and YARN. Important consideration you need to take to write Map Reduce program and intro to Hadoop ecosystem. This course has all 30 lectures divided into eight sections with the course, you get the code of all the examples discussed in the course and at the end of each lesson, there are quizzes and questions which will prepare you to face and clear cloudera and Hortonworks certification exams. Who should do this course? Programming Engineers, who are into ETL/Programming and investigating for awesome openings for work in Hadoop. Managers, who are searching for the most recent advancements to be implemented in their association, to meet the momentum & up and coming difficulties of information administration. Any Graduate / Post-Graduate, who is trying an incredible profession towards the front line technologies in IT. Why Hadoop Training in Peridot Systems? Strongly believe that you need not burn a hole in your pocket to learn Hadoop. Our Goal is to create best in class courses to learn Hadoop and related technologies. I am confident that you all love this course as I ensured high standards while creating it but just in case, if you find the course is not right for you, don’t worry. This course come with money back guarantee but if you choose to stay, you have unlimited lifetime access to the course and special offers on my upcoming courses. So get started with the course. Get on track to clear certifications & get flooded with job offers and bag the coolest IT Jobs in the current times, avoid wrong turns, and make the right decision. For details Kamatchi Krupa Apts, No: 84/8, Ground Floor, Venkatarathinam main street, Venkatarathinam Nagar, LB Road, Adyar, Chennai, Tamil Nadu - 600020. Landline : 044 - 4211 5526 , 044- 4550 1165 , 044 - 4265 7099 Mobile : +91- 8056102481 Landmark : 2 Minutes walk able distance from Adyar Telephone Exchange / Adyar Bus depot

Best Hadoop Training Institute 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- 0120 4242224, 9717292598/9717292599 Delhi –9717292601/9717292602 Gurgaon – 9810866624/9810866642

Why Choose Hadoop? How to setup Hadoop details HDFS mechanism, how Map Reduce program works in MapReduce classic and YARN. Important consideration you need to take to write Map Reduce program and intro to Hadoop ecosystem. This course has all 30 lectures divided into eight sections with the course, you get the code of all the examples discussed in the course and at the end of each lesson, there are quizzes and questions which will prepare you to face and clear cloudera and Hortonworks certification exams. Learn Hadoop Training in Chennai Are you excited and want to learn big data technologies. Do you feel that internet is all littered free materials but it’s complicated for a newbie? Free internet learning material can be a can worms for a beginner and training is advised for a jump start but then do you feel that big data company offered trainings would cost you an arm and a leg? When you look at webinar trainings by other than institutes, you find it of poor quality and dodgy without guarantee. The world can go upside down while learning a new complicated technology as Hadoop. Become a certified Hadoop developer covers everything you need to know to start a career in Hadoop technology and achieve expertise to a level where you can face certification like Cloudera and Hortonworks with confidence. You can start as a beginner and this course would help you to become a certified professional. This course would take you through the nee and event of big data technologies. Who should do this course? Programming Engineers, who are into ETL/Programming and investigating for awesome openings for work in Hadoop. Managers, who are searching for the most recent advancements to be implemented in their association, to meet the momentum & up and coming difficulties of information administration. Any Graduate / Post-Graduate, who is trying an incredible profession towards the front line technologies in IT. Why Hadoop Training in Peridot Systems? Strongly believe that you need not burn a hole in your pocket to learn Hadoop. Our Goal is to create best in class courses to learn Hadoop and related technologies. I am confident that you all love this course as I ensured high standards while creating it but just in case, if you find the course is not right for you, don’t worry. This course come with money back guarantee but if you choose to stay, you have unlimited lifetime access to the course and special offers on my upcoming courses. So get started with the course. Get on track to clear certifications & get flooded with job offers and bag the coolest IT Jobs in the current times, avoid wrong turns, and make the right decision. For details Kamatchi Krupa Apts, No: 84/8, Ground Floor, Venkatarathinam main street, Venkatarathinam Nagar, LB Road, Adyar, Chennai, Tamil Nadu - 600020. Landline : 044 - 4211 5526 , 044- 4550 1165 , 044 - 4265 7099 Mobile : +91- 8056102481 Landmark : 2 Minutes walkable distance from Adyar Telephone Exchange / Adyar Bus depot

SADGURU TECHNOLOGIES - 04040154733 8179736190 1.Intro to Hadoop, BigData •What is BigData? •Parallel Computer vs. Distributed Computing •Brief history of Hadoop •RDBMS/SQL vs. Hadoop •Scaling with Hadoop •Intro to the Hadoop ecosystem •Optimal hardware and network configurations for Hadoop 2.HDFS – Hadoop Distributed File System •Linux File system options •NameNode architecture •Secondary NameNode architecture •DataNode architecture •Heartbeats, Rack Awareness, Health Check •Exploring the HDFS Web UI LAB #2: HDFS CMD Line 3.Beginning MapReduce •MapReduce Architecture •JobTracker/TaskTracker •Combiner •Partitioner •Shuffle and Sort •Exploring the MapReduce Web UI •Walkthrough of a simple Java MapReduce example •Use case: Word Count in MapReduce LAB #3: Running MapReduce in Java 4.Advanced MapReduce •Data Types and File Formats. •Driver, Mapper & Reducer Class Code. •Build Map & Reduce programs using Eclipse. •Serialization and File-Based Data Structures •Input/output formats •Counters •Run Map Reduce locally and on cluster. LAB #4: Java MapReduce API 5.Hive for Structured Data •Hive architecture •Hive vs. RDBMS •HiveQL and Hive Shell •Managing tables •Data types and schemas •Querying data •Partitions and Buckets •Intro to User Defined Functions LAB #5: Exploring Hive Commands 6.Overview of NoSql and HBase •Introduction of NoSql. •CAP Theorem. •HBase architecture •HBase versions and origins •HBase vs. RDBMS •Data Modeling •Column Families and Regions LAB #6: Intro to HBase Command Line 7.Working with Sqoop •Introduction to Sqoop •Import Data •Export Data •Sqoop Syntaxes •Database Connection Lab#7: Hands on exercise on Sqoop and mysql DB. Thanks & Regards, SADGURU TECHNOLOGIES H. No: 7-1-621/10, Flat No: 102, Sai Manor Apartment, S.R. Nagar Main Road, Hyderabad-500038, Landmark: Beside Umesh Chandra Statue, Approach Road Parallel to Main Road Mob: 91-8179736190, Ph: 040-40154733 USA: +1 (701) 660-0529

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: +.

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: Phone: +

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: +91-9494347041