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Overview: Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients. ABOUT ECORPTRAININGS: Ecorp Trainings are one of the best institute providing quality level of training in E-learning process.This is instructor led online training. We also provide corporate training , if group of people interested in same technology. Contact us for detailed course content & register for a free demo. We also provide support in client interviews , resume preparation , ticket resolving. Contact us for custom designed training course by experts exclusively for yourself. We provide training for almost all IT technologies i.e ; JAVA , DOTNET , SAP ,ORACLE , PEOPLESOFT ,HYPERION etc, contact us if you have any particular need. ECORP TRAININGS. Gtalk ID : ecorptrainings Skype ID : ecorptrainings

Overview: NAnt is a free and open source software tool for automating software build processes. It is similar to Apache Ant, but targeted at the .NET environment rather than Java. The name NAnt comes from the fact that the tool is Not Ant. ABOUT ECORPTRAININGS: Ecorp Trainings are one of the best institute providing quality level of training in E-learning process.This is instructor led online training. We also provide corporate training , if group of people interested in same technology. Contact us for detailed course content & register for a free demo. We also provide support in client interviews , resume preparation , ticket resolving. Contact us for custom designed training course by experts exclusively for yourself. We provide training for almost all IT technologies i.e ; JAVA , DOTNET , SAP ,ORACLE , PEOPLESOFT ,HYPERION etc, contact us if you have any particular need. ECORP TRAININGS. Gtalk ID : ecorptrainings Skype ID : ecorptrainings

Overview: Maven is a build automation tool used primarily for Java projects. Maven addresses two aspects of building software: First, it describes how software is built, and second, it describes its dependencies. Contrary to preceding tools like Apache Ant it uses conventions for the build procedure, and only exceptions need to be written down. An XML file describes the software project being built, its dependencies on other external modules and components, the build order, directories, and required plug-ins. ABOUT ECORPTRAININGS: Ecorp Trainings are one of the best institute providing quality level of training in E-learning process.This is instructor led online training. We also provide corporate training , if group of people interested in same technology. Contact us for detailed course content & register for a free demo. We also provide support in client interviews , resume preparation , ticket resolving. Contact us for custom designed training course by experts exclusively for yourself. We provide training for almost all IT technologies i.e ; JAVA , DOTNET , SAP ,ORACLE , PEOPLESOFT ,HYPERION etc, contact us if you have any particular need. ECORP TRAININGS. Gtalk ID : ecorptrainings Skype ID : ecorptrainings

mso-bidi-theme-font:minor-latin">Apache Spark has become one of the key cluster-computing frame works in the world. Spark can be deployed in numereous ways like in machine Learning, Streaming data and graphic processing. Spark supports programming languages like Python, Scala, Java, and R. Apache Hadoop mso-bidi-theme-font:minor-latin"> is an open-source framework written in Java that allows us to store and process Big Data in a distributed environment, across various clusters of computers using simple programming constructs. To do this, Hadoop uses an algorithm called  Map Reduce mso-bidi-theme-font:minor-latin">, which divides the task into small parts and assigns them to a set of computers. Hadoop also has its own file system,  Hadoop Distributed File System (HDFS),  which is based on  Google File System (GFS). HDFS is designed to run on low-cost hardware. Apache Spark mso-bidi-theme-font:minor-latin"> is an open-source distributed cluster-computing framework. Spark is a data processing engine developed to provide faster and easy-to-use analytics than  Hadoop Ma pReduce. mso-bidi-theme-font:minor-latin;color:#222222;mso-ansi-language:EN-GB">Apache Spark in the big data industry is because of its in-memory data processing that makes it high-speed data processing engine compare to Map Reduce. Apache Spark has huge potential to contribute to Big data related business in the industry.  Apache Spark is a Big data processing interface which provides not only programming interface in the data cluster but also adequate fault tolerance and data parallelism. This open-source platform is efficient in speedy processing of massive datasets. Calibri;mso-bidi-theme-font:minor-latin;color:#222222"> 115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin">Contact us: mso-bidi-theme-font:minor-latin">  http://www.monstercourses.com/ mso-bidi-theme-font:minor-latin">USA:  + 1 772 777 1557 line-height:115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin; color:red"> & +44 702 409 4077 line-height:115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin"> mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin">Skype ID: MonsterCourses Calibri;mso-bidi-theme-font:minor-latin"> mso-bidi-theme-font:minor-latin"> 

mso-bidi-theme-font:minor-latin">Apache Spark has become one of the key cluster-computing frame works in the world. Spark can be deployed in numereous ways like in machine Learning, Streaming data and graphic processing. Spark supports programming languages like Python, Scala, Java, and R. Apache Hadoop mso-bidi-theme-font:minor-latin"> is an open-source framework written in Java that allows us to store and process Big Data in a distributed environment, across various clusters of computers using simple programming constructs. To do this, Hadoop uses an algorithm called  Map Reduce mso-bidi-theme-font:minor-latin">, which divides the task into small parts and assigns them to a set of computers. Hadoop also has its own file system,  Hadoop Distributed File System (HDFS),  which is based on  Google File System (GFS). HDFS is designed to run on low-cost hardware. 115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin">Contact us: mso-bidi-theme-font:minor-latin">  http://www.monstercourses.com/ mso-bidi-theme-font:minor-latin">USA:  + 1 772 777 1557 line-height:115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin; color:red"> & +44 702 409 4077 line-height:115%;mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin"> mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-latin">Skype ID: MonsterCourses Calibri;mso-bidi-theme-font:minor-latin"> mso-bidi-theme-font:minor-latin"> 

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

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

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

​ HADOOP 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…...

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