File racks

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

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

BEST HADOOP LIVE TRAINING BY REALTIME CORPORATE PROFESSIONALS Hadoop Course Agenda (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

Demo has Scheduled Today BEST HADOOP ONLINE CERTIFICATION LEVEL TRAINING FROM HYDERABAD,INDIA FOR FREE DEMO contact us: Phone/WhatsApp: +91-(850) 012-2107 Interview Questions and Answers, Recorded Video Sessions, Materials, Mock Interviews Assignments Will be provided Hadoop Key Concepts (we can modify the course content as per your requirement) HADOOP Using Cloudera Development & Admin Course Introduction:- • 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

HADOOP ONLINE TRAINING,CORPORATE TRAINING,JOB AND INTERVIEW SUPPORT BY CORPORATE PROFESSIONALS Interview Questions and Answers, Recorded Video Sessions, Materials, Mock Interviews Assignments Will be provided Hadoop Concepts (we can modify the course content as per your requirement) HADOOP ADMIN AND DEVELOPMENT Introduction:- • 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

With 2.6 quintillion bytes of data being produced on a daily basis, there is a fast growing need of big data & Hadoop training to nurture professionals who can manage and analyse massive (tera/petabytes) data-sets to bring out business insights. To do this requires specialized knowledge on various tools like the Hadoop ecosystem. Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary

Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary

With 2.6 quintillion bytes of data being produced on a daily basis, there is a fast growing need of big data & Hadoop training to nurture professionals who can manage and analyse massive (tera/petabytes) data-sets to bring out business insights. To do this requires specialized knowledge on various tools like the Hadoop ecosystem. Through this big data & Hadoop training course, the participants will gain all the skills requisite to be a Hadoop Developer. The participant will learn the installation of Hadoop cluster, understand the basic and advanced concepts of Map Reduce tools used by Big Data analysts like Pig, Hive, Flume, Sqoop and Oozie. The course will train you towards global certifications offered by Cloudera, Hortonworks etc. The course will be very useful for engineers and software professionals with a programming background. HADOOP Online Training by Peopleclick with an excellent and real time faculty. Our Hadoop Big Data course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market, huge number of job openings are there in the IT world. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability. As all our faculty is real time professionals our trainer will cover all the real time scenarios. We have trained many students on Apache Hadoop Big Data, We provide Corporate Trainings and Online trainings throughout the world. We will give you 100% satisfaction guarantee, After completion of Hadoop Training we provide days technical support for required candidates. We will provide 100% certification support, resume preparation and Placements. HADOOP ONLINE TRAINING COURSE CONTENT: We provide both Hadoop Development and Admin Training. 1. INTRODUCTION What is Hadoop? History of Hadoop Building Blocks – Hadoop Eco-System Who is behind Hadoop? What Hadoop is good for and why it is Good 2. HDFS Configuring HDFS Interacting With HDFS HDFS Permissions and Security Additional HDFS Tasks HDFS Overview and Architecture HDFS Installation Hadoop File System Shell File System Java API 3. MAPREDUCE Map/Reduce Overview and Architecture Installation Developing Map/Red Jobs Input and Output Formats Job Configuration Job Submission Practicing Map Reduce Programs (atleast 10 Map Reduce Algorithms) 4. Getting Started With Eclipse IDE Configuring Hadoop API on Eclipse IDE Connecting Eclipse IDE to HDFS 5. Hadoop Streaming 6. Advanced MapReduce Features Custom Data Types Input Formats Output Formats Partitioning Data Reporting Custom Metrics Distributing Auxiliary Job Data 7. Distributing Debug Scripts 8.Using Yahoo Web Services 9. Pig Pig Overview Installation Pig Latin Pig with HDFS 10. Hive Hive Overview Installation Hive QL Hive Unstructured Data Analyzation Hive Semistructured Data Analyzation 11.HBase HBase Overview and Architecture HBase Installation HBase Shell CRUD operations Scanning and Batching Filters HBase Key Design 12.ZooKeeper Zoo Keeper Overview Installation Server Mantainace 13.Sqoop Sqoop Overview Installation Imports and Exports 14.CONFIGURATION Basic Setup Important Directories Selecting Machines Cluster Configurations Small Clusters: 2-10 Nodes Medium Clusters: Nodes Large Clusters: Multiple Racks 15.Integrations 16.Putting it all together Distributed installations Best Practices Benefits of taking the Hadoop & Big Data course •Learn to store, manage, retrieve and analyze Big Data on clusters of servers in the cloud using the Hadoop eco-system •Become one of the most in-demand IT professional in the world today •Don't just learn Hadoop development but also learn how to analyze large amounts of data to bring out insights •Relevant examples and cases make the learning more effective and easier •Gain hands-on knowledge through the problem solving based approach of the course along with working on a project at the end of the course Who should take this course? This course is designed for anyone who: •wants to architect a big data project using Hadoop and its Eco System components •wants to develop Map Reduce programs to handle enormous amounts of data •you have a programming background and want to take your career to another level Pre-requisites •The participants need basic knowledge of core Java for this course. (If you do not have Java knowledge, then do not worry. We provide you with our 'Java Primer for Hadoop' course complimentary with this course so that you can learn the requisite Java skills) •Any experience of Linux environment will be helpful but is not necessary For Further query call us @ or