Brief history

A Brief History of Time: From the Big Bang to Black Holes is a popular-science book on cosmology by British physicist Stephen Hawking.

About Us | Shipping Policy | Restocking fees | Return Policy Author: Jacques Attali Publisher: Paidos Iberica Ediciones S a Release Date: 2007-10 Seller Category: -- Qty Available: 1 Condition: Brand New ISBN: 9788449320514 Title: Breve historia del futuro/ Brief History of the Future (Spanish Edition) Notes: Ships Today. Free Shipping. Please note: You will have only one chance to make me an offer so please be reasonable while making offer. Checkout the lowest price available on internet and I might be able to match it. I will not give away book for almost free. Item is non-refundable if item is sold through best offer. If you use buy it now, item is refundable within 30 days. 24*7 Customer Service.

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The record breaking bestseller, one of the best books on Quantum Physics by, The great Stephen Hawking Sir.

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India's Ancient past - 150 A Brief History of Modern India (2019-2020 Edition) - 150 History of Medieval India - 150 Oxford School Atlas - 200 Anthorpology - 500 Indian polity (Laxmikanth) - 100 Indian Economy (Ramesh Singh) - 200 Public Administration (Laxmikanth) - 250

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, Grouping…. • Data types, Operators….. • Joins, Groups…. • Sample programs in HIVE

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 HIVE II. PIG • Basics • Installation and Configurations • Commands….

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 • 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

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

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

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

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

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 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 ..........

​ 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.,

​ 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

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