Hadoop mongodb

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MongoDB is one of many cross-platform document-oriented databases, and the leading NoSQL database. Instead of using tables and rows like relational databases, it is built on architecture of collections and documents. TIP is leading training institute which is offering Mongo DB classes in Pune. We provide weekend’s batches as preferable for working professionals and graduates. Classes are conducted under guidance of experts who will help you to understand concepts very clearly. Why to prefer us: •100% Job assistance. •Trainers are working professionals in multinational companies. Other Classes we are conducting at Training Institute Pune: 1. SEO Classes. 2. Big Data & Hadoop Classes. 3. Python & Perl Scripting Classes. 4. Sybase Database Classes. 5. ETL Testing & Informatica Testing Classes. 6. Selenium Webdriver Classes. 7. AngularJS 9. Digital Marketing Contact Us: Training Institute Pune Call Us at: + | +

Hadoop also offers a cost effective storage solution for businesses' exploding data sets. The problem with traditional relational database management systems is that it is extremely cost prohibitive to scale to such a degree in order to process such massive volumes of data. Big Data Academy is the brain child of leading Big Data Architects & Consultants in India - with extensive approach on Job Oriented Hands-On Sessions Followed with placement. We believe in quality training which will enable the individuals skillfully effecient & be in phase with the Cutting Edge Technologies in the IT Space. Big data training chennai with Project from Experts! Visit Us: #67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai-20 To register for upcoming classes weekends(Classroom) February - Fast Track (Classroom)- February

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

RCP Technologies is a unique and pioneer institute mainly started with the soul objective of imparting cutting edge, technologically superior and state-of-art, high-end, and career oriented curriculum based courses in Big Data Hadoop and other courses like Data Science, Apache Storm, Spark, Python, Agile, MongoDB, SOA, OSB, Tableau, Cassandra, ADF, Informatica, Obiee, Obia etc. We have trainers who consultants worked in MNC companies. We make sure the best trainers are selected and students gain a lot of knowledge once the training is completed. We don't target lot of students for our training classes but will make sure the exact number of students who are the best fit for carrying out a curriculum are selected. We are not quantity oriented but quality oriented. If you are looking for a professional training in the IT, then we are the best in the business. We have inhouse training facilities along with server setup which makes it a complete corporate environment. For more details call us at share your contact details. What is Hadoop? 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 was born out of a need to process big data, as the amount of generated data continued to rapidly increase. As the Web generated more and more information, it was becoming quite challenging to index the content, so Google created MapReduce in , then Yahoo! created Hadoop as a way to implement the MapReduce function. Hadoop is now an open-source Apache implementation project. 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. As for the more specific functions, Hadoop has a large scale file system (Hadoop Distributed File System or HDFS), it can write programs, it manages the distribution of programs, then accepts the results, and generates a data result set. Only RCP technologies provides training designed by the leaders and committers of Hadoop. We present valuable real world scenario-based training developed by the core architects, builders and operators of Hadoop with unmatched depth and expertise so that you can be assured you are learning from the experts. RCP technologies is a Interactive Learning Portal started by industry experts with an aim to provide Quality Training in Hadoop Technology. RCP Technologies is offering quality Training services to hadoop to students worldwide. HADOOP Classroom & Online Training by RCP Technologies with an excellent and real time faculty. Our Big Data Hadoop course content designed as per the current IT industry requirement. Apache Hadoop is having very good demand in the market. We provide regular and weekend classes as well as Normal track/Fast track based on the learners requirement and availability Visit us at: RCP technologies Pvt Ltd, #302, Annapurna Block,Aditya Enclave, Near Mitrivanam, Ameerpet, Hyderabad. Helpline:

Just Learn Online Big Data Hadoop Certification course is designed to prepare you for your next assignment in the world of Hadoop Tutorial. Hadoop Certification is the market leader among Big Data Technologies and it is an important skill for every professional in this field. This training has been constructed to cater to the current industry requirements with a strong mix of both concepts and hands-on exercises. Hadoop Course Content 1.Introduction to BigData, Hadoop 2.Deep Drive in HDFS (for Storing the Data 3.MapReduce using Java (Processing the 4.PIG 5.SQOOP 6.HIVE 7.HBASE 8.MongoDB 9.Cluster Setup 10.OOZIE 11.Flume • Scalable and reliable big data lectures • Presentations and video lectures to grasp easily • Trouble shooting techniques to deal with big data projects • Instructors with in-depth knowledge on course • Data transformation and analytical techniques • Assignments and online puzzles with guides and answers. INDIA: +91-7207212428,USA: +1-(443) 332-6786

Enroll for Big-Data and Hadoop Developer Certification Training in chennai. Attend world renowned classroom training organized by Peridot systems. To attend free demo contact RUBAN (). COURSE CONTENT: •Module 1: BigData •Module 2: Hadoop •Module 3: HDFS •Module 4: MapReduce •Module 5: HIVE & PIG •Module 6: HBase •Module 7:Introduction to MongoDB For More Details:(RUBAN)

We are offering classroom training on Bigdata / Hadoop. Covers Hadoop, Hive, HBase, Pig, Sqoop, Flume, Oozie, ZooKeeper, NoSQL, Cassandra, MongoDB, Spark, Mahout, and R. Location: Mysore Road, Near Gali Anjaneya Temple. Fully Hands-on training with Experienced Trainer. Also provides Lots of Exercises and Certification Assistance +91 - 9972355965

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

Big Data & Hadoop Training in one month in Aptech Hazra Learn basics of Big-Data& Hadoop Smart Professional - Big Data Aptech's Smart Professional: Big Data course trains you in advance database technologies like Hadoop, used by more than half of Fortune 50 companies. The curriculum trains you from the basic to the advanced level, right from installing & configuring Hadoop, and maintaining the system, to using additional products that integrate with other systems. Course Details •Onlinevarsity - A learning app, exclusively for our students that provides access to study material, e-books, reference material, video tutorials, chats with experts & more •Move applications stored on a computer to a remote location & make them accessible online through standard browsers •Understand concepts & technologies of big data & its management •Develop dynamic web applications in PHP & use MySQL efficiently for those applications •Implement data security during data manipulation & access •Use NoSQL for storage & retrieval of data •DUse MongoDB and Apache Cassandra to handle large amounts of data across servers •Use Hadoop for distributed storage & processing of big data •Use PigLatin, Hive, Hbase for querying & managing databases •Perform analysis & reporting with big data tools Course Covers •Introduction to cloud computing •Introduction to big data •Data security •Working with NoSQL •Data management using MongoDB & Apache Cassandra •Fundamentals of Hadoop •Reporting & analytics with bigdata •Project COURSE DURATION Smart Professional - Big Data is an 8-month course. Classes are typically held 2 hours - a - day / 3 - days - a - week. ELIGIBILITY IT graduates / professionals / engineers

Course Details: •Course Duration: 55 Days •Trainer: Kalyan(10+ Years of ExperIence) •Mode Of Training: Classroom/Online •Contact Person: Gopi We are Providing Hadoop Demo on Every Sunday at 10am With the view of elevating the ongoing demand for the field of Hadoop professional field and regarding its increasing career opportunities ORIEN IT is now offering a “Free Hadoop Demo In Hyderabad” under the guidance of industry experts Attending this demo will surely be acting as a helping hand for providing a clear guidance for your career Big Data Hadoop Course Content: - 1 Introduction to Big Data and Hadoop 2 HDFS (Hadoop Distributed File System) 3 MAPREDUCE 4 YARN (Next Generation Map Reduce) 5 Apache PIG 6 Apache HIVE 7 Cloudera Impala 8 Apache Zookeeper 9 Apache HBase 10 MongoDB 11 Apache Drill 12 Apache SQOOP 13 Apache FLUME 14 Apache Kafka 15 Apache Spark 16 Apache OOZIE 17 Real Time Big Data Projects 18 Pre-Requisites for this Course 19 ORIENIT Hadoop POC's Solution Class 20 Advanced and New technologies architectural discussions Address: --------------- Flat No 204 Annapurna Block Aditya Enclave Ameerpet Hyderabad – 500038

Dear Students, We are starting new batches for below technologies ETL Testing from 7th April at 5:00 A.M IST cost @ 9.5k Informatica From 6th April at 7:00 A.M IST @ 10k Hadoop From 6th April At 6:30 A.M IST @ 12k Java (Core And Advanced) from 13th April At 7:00 A.M IST @ 8k Oracle ADF From 13th April at 7:00 A.M IST @ 11.6k IBI Webfocus MongoDB From 13th April At 7:30 A.M IST @ 9.6k Please Call us at + What's App:- +

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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

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