100% Discount || Sqoop, Hive and Impala for Data Analysts (Formerly CCA 159)

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    Sqoop, Hive and Impala for Data Analysts (Formerly CCA 159)


    • A 64 bit Computer with at least 8 GB RAM is highly desired
    • Access to Multinode Cluster or our ITVersity Labs (Paid Subscription Required)
    • Setup Cloudera QuickStart VM in high end laptops (16 GB RAM and Quad Core) – Instructions Provided but Not Supported
    • Basic Computer Skills
    • Ability to write based SQL Queries and use Linux based environment


    As part of Sqoop, Hive, and Impala for Data Analysts (Formerly CCA 159), you will learn key skills such as Sqoop, Hive, and Impala.

    This comprehensive course covers all aspects of the certification with real-world examples and data sets.

    Overview of Big Data ecosystem

    • Overview Of Distributions and Management Tools
    • Properties and Properties Files – General Guidelines
    • Hadoop Distributed File System
    • YARN and Map Reduce2
    • Submitting Map ReduceJob
    • Determining Number of Mappers and Reducers
    • Understanding YARN and Map Reduce Configuration Properties
    • Review and Override Job Properties
    • Reviewing Map Reduce Job Logs
    • Map Reduce Job Counters
    • Overview of Hive
    • Databases and Query Engines
    • Overview of Data Ingestion in Big Data
    • Data Processing using Spark

    HDFS Commands to manage files

    • Introduction to HDFS for Certification Exams
    • Overview of HDFS and PropertiesFiles
    • Overview of Hadoop CLI
    • Listing Files in HDFS
    • User Spaces or Home Directories in HDFS
    • Creating Directories in HDFS
    • Copying Files and Directories into HDFS
    • File and Directory Permissions Overview
    • Getting Files and Directories from HDFS
    • Previewing Text Files in HDFS
    • Copying or Moving Files and Directories within HDFS
    • Understanding Size of File System and Files
    • Overview of Block Size and ReplicationFactor
    • Getting File Metadata using hdfs fsck
    • Resources and Exercises

    Getting Started with Hive

    • Overview of Hive Language Manual
    • Launching and using Hive CLI
    • Overview of Hive Properties
    • Hive CLI History and hiverc
    • Running HDFS Commands in Hive CLI
    • Understanding Warehouse Directory
    • Creating and Using Hive Databases
    • Creating and Describing Hive Tables
    • Retrieve Matadata of Tables using DESCRIBE
    • Role of Hive Metastore Database
    • Overview of beeline
    • Running Hive Commands and Queries using beeline

    Creating Tables in Hive using Hive QL

    • Creating Tables in Hive – orders
    • Overview of Basic Data Types in Hive
    • Adding Comments to Columns and Tables
    • Loading Data into Hive Tables from Local File System
    • Loading Data into Hive Tables from HDFS
    • Loading Data – Overwrite vs Append
    • Creating External tables in Hive
    • Specifying Location for Hive Tables
    • Difference between Managed Table and External Table
    • Default Delimiters in Hive Tables using Text File
    • Overview of File Formats in Hive
    • Differences between Hive and RDBMS
    • Truncate and Drop tables in Hive
    • Resources and Exercises

    Loading/Inserting data into Hive tables using Hive QL

    • Introduction to Partitioning and Bucketing
    • Creating Tables using Orc Format – order_items
    • Inserting Data into Tables using Stage Tables
    • Load vs. Insert in Hive
    • Creating Partitioned Tables in Hive
    • Adding Partitions to Tables in Hive
    • Loading into Partitions in Hive Tables
    • Inserting Data Into Partitions in Hive Tables
    • Insert Using Dynamic Partition Mode
    • Creating Bucketed Tables in Hive
    • Inserting Data into Bucketed Tables
    • Bucketing with Sorting
    • Overview of ACID Transactions
    • Create Tables for Transactions
    • Inserting Individual Records into Hive Tables
    • Update and Delete Data in Hive Tables

    Overview of functions in Hive

    • Overview of Functions
    • Validating Functions
    • String Manipulation – Case Conversion and Length
    • String Manipulation – substr and split
    • String Manipulation – Trimming and Padding Functions
    • String Manipulation – Reverse and Concatenating Multiple Strings
    • Date Manipulation – Current Date and Timestamp
    • Date Manipulation – Date Arithmetic
    • Date Manipulation – trunc
    • Date Manipulation – Using date format
    • Date Manipulation – Extract Functions
    • Date Manipulation – Dealing with Unix Timestamp
    • Overview of Numeric Functions
    • Data Type Conversion Using Cast
    • Handling Null Values
    • Query Example – Get Word Count


    Who this course is for:

    • Any Big Data Professional or Aspirant who want to learn about Databases and Query Interfaces in Big Data
    • Any Business Intelligence Professional who want to understand Data Analysis in Big Data eco system
    • Any IT Professional who want to prepared for CCA 159 Data Analyst exam

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