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    Big Data Hadoop Certification Training

    BY
    Simpliv Learning

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    Mode

    Online

    Duration

    35 Hours

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study, Virtual Classroom
    Mode of Delivery Video and Text Based

    Course and certificate fees

    certificate availability

    Yes

    certificate providing authority

    Simpliv Learning

    The syllabus

    Understanding Big Data and Hadoop

    • Introduction to Big Data & Big Data Challenges  
    • Limitations & Solutions of Big Data Architecture  
    • Hadoop & its Features  
    • Hadoop Ecosystem  
    • Hadoop 2.x Core Components  
    • Hadoop Storage: HDFS (Hadoop Distributed File System)  
    • Hadoop Processing: MapReduce Framework  
    • Different Hadoop Distributions  

    Hadoop Architecture and HDFS

    • Hadoop 2.x Cluster Architecture Preview  
    • Federation and High Availability Architecture Preview  
    • Typical Production Hadoop Cluster  
    • Hadoop Cluster Modes  
    • Common Hadoop Shell Commands Preview  
    • Hadoop 2.x Configuration Files  
    • Single Node Cluster & Multi-Node Cluster set up  
    • Basic Hadoop Administration  

    Hadoop MapReduce Framework

    • Traditional way vs MapReduce way  
    • Why MapReduce  
    • YARN Components  
    • YARN Architecture  
    • YARN MapReduce Application Execution Flow  
    • YARN Workflow  
    • Anatomy of MapReduce Program  
    • Input Splits, Relation between Input Splits and HDFS Blocks  
    • MapReduce: Combiner & Partitioner  

    Advanced Hadoop MapReduce

    • Counters  
    • Distributed Cache  
    • MRunit  
    • Reduce Join  
    • Custom Input Format  
    • Sequence Input Format  
    • XML file Parsing using MapReduce

    Apache Pig

    • Introduction to Apache Pig  
    • MapReduce vs Pig  
    • Pig Components & Pig Execution  
    • Pig Data Types & Data Models in Pig  
    • Pig Latin Programs  
    • Shell and Utility Commands  
    • Pig UDF & Pig Streaming  
    • Testing Pig scripts with Punit  
    • Aviation use-case in PIG  

    Apache Hive

    • Introduction to Apache Hive  
    • Hive vs Pig  
    • Hive Architecture and Components  
    • Hive Metastore  
    • Comparison with Traditional Database  
    • Hive Data Types and Data Models  
    • Hive Partition  
    • Hive Bucketing  
    • Hive Tables (Managed Tables and External Tables)  
    • Importing Data  
    • Querying Data & Managing Outputs  
    • Hive Script & Hive UDF  
    • Retail use case in Hive  

    Advanced Apache Hive and HBase

    • Hive QL: Joining Tables, Dynamic Partitioning  
    • Custom MapReduce Scripts  
    • Hive Indexes and views  
    • Hive Query Optimizers  
    • Hive Thrift Server  
    • Hive UDF  
    • Apache HBase: Introduction to NoSQL Databases and HBase  
    • HBase v/s RDBMS  
    • HBase Components  
    • HBase Architecture  
    • HBase Run Modes  
    • HBase Configuration  
    • HBase Cluster Deployment  

    Advanced Apache HBase

    • HBase Data Model  
    • HBase Shell  
    • HBase Client API  
    • Hive Data Loading Techniques  
    • Apache Zookeeper Introduction  
    • ZooKeeper Data Model  
    • Zookeeper Service  
    • HBase Bulk Loading  
    • Getting and Inserting Data  
    • HBase Filters  

    Processing Distributed Data with Apache Spark

    • What is Spark  
    • Spark Ecosystem  
    • Spark Components  
    • What is Scala  
    • Why Scala  
    • SparkContext  
    • Spark RDD  

    Oozie

    • Oozie  
    • Oozie Components  
    • Oozie Workflow  
    • Scheduling Jobs with Oozie Scheduler  
    • Demo of Oozie Workflow  
    • Oozie Coordinator  
    • Oozie Commands  
    • Oozie Web Console  
    • Oozie for MapReduce  
    • Combining flow of MapReduce Jobs  
    • Hive in Oozie  
    • Hadoop Talend Integration  

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