Sqoop, Hive And Impala For Data Analysts (Formerly Cca 159)

Hands on Sqoop, Hive and Impala for Data Analysts

What you'll learn
Overview of Big Data ecosystem such as Hadoop HDFS, YARN, Map Reduce, Sqoop, Hive, etc
Overview of HDFS Commands such as put or copyFromLocal, get or copyToLocal, cat, etc along with concepts such as block size, replication factor, etc
Managing Tables in Hive Metastore using DDL Commands
Load or Insert data into Hive Metastore Tables using commands such as LOAD and INSERT
Overview of Functions in Hive to manipulate strings, dates, etc
Writing Basic Hive QL Queries using WHERE, JOIN, GROUP BY, etc
Analytical or Windowing Functions in Hive
Overview of Impala and understanding similarities and differences between Hive and Impala
Getting Started with Sqoop by reviewing official documentation and also exploring commands such as Sqoop eval
Importing Data from RDBMS tables into HDFS using Sqoop Import
Importing Data from RDBMS tables into Hive tables using Sqoop Import
Exporting Data from Hive or HDFS to RDBMS tables using Sqoop Export
Incremental Imports using Sqoop Import into HDFS or Hive Tables
Requirements
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
Description
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 ecosystemOverview Of Distributions and Management ToolsProperties and Properties Files - General GuidelinesHadoop Distributed File SystemYARN and Map Reduce2Submitting Map ReduceJobDetermining Number of Mappers and ReducersUnderstanding YARN and Map Reduce Configuration PropertiesReview and Override Job PropertiesReviewing Map Reduce Job LogsMap Reduce Job CountersOverview of HiveDatabases and Query EnginesOverview of Data Ingestion in Big DataData Processing using SparkHDFS Commands to manage filesIntroduction to HDFS for Certification ExamsOverview of HDFS and PropertiesFilesOverview of Hadoop CLIListing Files in HDFSUser Spaces or Home Directories in HDFSCreating Directories in HDFSCopying Files and Directories into HDFSFile and Directory Permissions OverviewGetting Files and Directories from HDFSPreviewing Text Files in HDFSCopying or Moving Files and Directories within HDFSUnderstanding Size of File System and FilesOverview of Block Size and ReplicationFactorGetting File Metadata using hdfs fsckResources and ExercisesGetting Started with HiveOverview of Hive Language ManualLaunching and using Hive CLIOverview of Hive PropertiesHive CLI History and hivercRunning HDFS Commands in Hive CLIUnderstanding Warehouse DirectoryCreating and Using Hive DatabasesCreating and Describing Hive TablesRetrieve Matadata of Tables using DESCRIBERole of Hive Metastore DatabaseOverview of beelineRunning Hive Commands and Queries using beelineCreating Tables in Hive using Hive QLCreating Tables in Hive - ordersOverview of Basic Data Types in HiveAdding Comments to Columns and TablesLoading Data into Hive Tables from Local File SystemLoading Data into Hive Tables from HDFSLoading Data - Overwrite vs AppendCreating External tables in HiveSpecifying Location for Hive TablesDifference between Managed Table and External TableDefault Delimiters in Hive Tables using Text FileOverview of File Formats in HiveDifferences between Hive and RDBMSTruncate and Drop tables in HiveResources and ExercisesLoading/Inserting data into Hive tables using Hive QLIntroduction to Partitioning and BucketingCreating Tables using Orc Format - order_itemsInserting Data into Tables using Stage TablesLoad vs. Insert in HiveCreating Partitioned Tables in HiveAdding Partitions to Tables in HiveLoading into Partitions in Hive TablesInserting Data Into Partitions in Hive TablesInsert Using Dynamic Partition ModeCreating Bucketed Tables in HiveInserting Data into Bucketed TablesBucketing with SortingOverview of ACID TransactionsCreate Tables for TransactionsInserting Individual Records into Hive TablesUpdate and Delete Data in Hive TablesOverview of functions in HiveOverview of FunctionsValidating FunctionsString Manipulation - Case Conversion and LengthString Manipulation - substr and splitString Manipulation - Trimming and Padding FunctionsString Manipulation - Reverse and Concatenating Multiple StringsDate Manipulation - Current Date and TimestampDate Manipulation - Date ArithmeticDate Manipulation - truncDate Manipulation - Using date formatDate Manipulation - Extract FunctionsDate Manipulation - Dealing with Unix TimestampOverview of Numeric FunctionsData Type Conversion Using CastHandling Null ValuesQuery Example - Get Word CountWriting Basic Queries in HiveOverview of SQL or Hive QLExecution Life Cycle of Hive QueryReviewing Logs of Hive QueriesProjecting Data using Select and Overview of FromDerive Conditional Values using CASE and WHENProjecting Distinct ValuesFiltering Data using Where ClauseBoolean Operations in Where ClauseBoolean OR vs IN OperatorFiltering Data using LIKE OperatorPerforming Basic Aggregations using Aggregate FunctionsPerforming Aggregations using GROUP BYFiltering Aggregated Data Using HAVINGGlobal Sorting using ORDER BYOverview of DISTRIBUTE BYSorting Data within Groups using SORT BYUsing CLUSTERED BYJoining Data Sets and Set Operations in HiveOverview of Nested Sub QueriesNested Sub Queries - Using IN OperatorNested Sub Queries - Using EXISTS OperatorOverview of Joins in HivePerforming Inner Joins using HivePerforming Outer Joins using HivePerforming Full Outer Joins using HiveMap Side Join and Reduce Side Join in HiveJoining in Hive using Legacy SyntaxCross Joins in HiveOverview of Set Operations in HivePerform Set Union between two Hive Query ResultsSet Operations - Intersect and Minus Not SupportedWindowing or Analytics Functions in HivePrepare HR Database in Hive with Employees TableOverview of Analytics or Windowing Functions in HivePerforming Aggregations using Hive QueriesCreate Tables to Get Daily Revenue using CTAS in HiveGetting Lead and Lag using Windowing Functions in HiveGetting First and Last Values using Windowing Functions in HiveApplying Rank using Windowing Functions in HiveApplying Dense Rank using Windowing Functions in HiveApplying Row Number using Windowing Functions in HiveDifference Between rank, dense_rank, and row_number in HiveUnderstanding the order of execution of Hive QueriesOverview of Nested Sub Queries in HiveFiltering Data on Top of Window Functions in HiveGetting Top 5 Products by Revenue for Each Day using Windowing Functions in Hive - RecapRunning Queries using ImpalaIntroduction to ImpalaRole of Impala DaemonsImpala State Store and Catalog ServerOverview of Impala ShellRelationship between Hive and ImpalaOverview of Creating Databases and Tables using ImpalaLoading and Inserting Data into Tables using ImpalaRunning Queries using Impala ShellReviewing Logs of Impala QueriesSynching Hive and Impala - Using Invalidate MetadataRunning Scripts using Impala ShellAssignment - Using NYSE DataAssignment - SolutionGetting Started with SqoopIntroduction to SqoopValidate Source Database - MySQLReview JDBC Jar to Connect to MySQLGetting Help using Sqoop CLIOverview of Sqoop User GuideValidate Sqoop and MySQL Integration using Sqoop List DatabasesListing Tables in Database using SqoopRun Queries in MySQL using Sqoop EvalUnderstanding Logs in SqoopRedirecting Sqoop Job Logs into Log FilesImporting data from MySQL to HDFS using Sqoop ImportOverview of Sqoop Import CommandImport Orders using target-dirImport Order Items using warehouse-dirManaging HDFS DirectoriesSqoop Import Execution FlowReviewing Logs of Sqoop ImportSqoop Import Specifying Number of MappersReview the Output Files generated by Sqoop ImportSqoop Import Supported File FormatsValidating avro files using Avro ToolsSqoop Import Using CompressionApache Sqoop - Importing Data into HDFS - CustomizingIntroduction to customizing Sqoop ImportSqoop Import by Specifying ColumnsSqoop import Using Boundary QuerySqoop import while filtering Unnecessary DataSqoop Import Using Split By to distribute import using non default columnGetting Query Results using Sqoop evalDealing with tables with Composite Keys while using Sqoop ImportDealing with tables with Non Numeric Key Fields while using Sqoop ImportDealing with tables with No Key Fields while using Sqoop ImportUsing autoreset-to-one-mapper to use only one mapper while importing data using Sqoop from tables with no key fieldsDefault Delimiters used by Sqoop Import for Text File FormatSpecifying Delimiters for Sqoop Import using Text File FormatDealing with Null Values using Sqoop ImportImport Mulitple Tables from source database using Sqoop ImportImporting data from MySQL to Hive Tables using Sqoop ImportQuick Overview of HiveCreate Hive Database for Sqoop ImportCreate Empty Hive Table for Sqoop ImportImport Data into Hive Table from source database table using Sqoop ImportManaging Hive Tables while importing data using Sqoop Import using OverwriteManaging Hive Tables while importing data using Sqoop Import - Errors Out If Table Already ExistsUnderstanding Execution Flow of Sqoop Import into Hive tablesReview Files generated by Sqoop Import in Hive TablesSqoop Delimiters vs Hive DelimitersDifferent File Formats supported by Sqoop Import while importing into Hive TablesSqoop Import all Tables into Hive from source databaseExporting Data from HDFS/Hive to MySQL using Sqoop ExportIntroduction to Sqoop ExportPrepare Data for Sqoop ExportCreate Table in MySQL for Sqoop ExportPerform Simple Sqoop Export from HDFS to MySQL tableUnderstanding Execution Flow of Sqoop ExportSpecifying Number of Mappers for Sqoop ExportTroubleshooting the Issues related to Sqoop ExportMerging or Upserting Data using Sqoop Export - OverviewQuick Overview of MySQL - Upsert using Sqoop ExportUpdate Data using Update Key using Sqoop ExportMerging Data using allowInsert in Sqoop ExportSpecifying Columns using Sqoop ExportSpecifying Delimiters using Sqoop ExportUsing Stage Table for Sqoop ExportSubmitting Sqoop Jobs and Incremental Sqoop ImportsIntroduction to Sqoop JobsAdding Password File for Sqoop JobsCreating Sqoop JobRun Sqoop JobOverview of Incremental Loads using SqoopIncremental Sqoop Import - Using WhereIncremental Sqoop Import - Using Append ModeIncremental Sqoop Import - Create TableIncremental Sqoop Import - Create Sqoop JobIncremental Sqoop Import - Execute JobIncremental Sqoop Import - Add Additional DataIncremental Sqoop Import - Rerun JobIncremental Sqoop Import - Using Last ModifiedHere are the objectives for this course.Provide Structure to the DataUse Data Definition Language (DDL) statements to create or alter structures in the metastore for use by Hive and Impala.Create tables using a variety of data types, delimiters, and file formatsCreate new tables using existing tables to define the schemaImprove query performance by creating partitioned tables in the metastoreAlter tables to modify the existing schemaCreate views in order to simplify queriesData AnalysisUse Query Language (QL) statements in Hive and Impala to analyze data on the cluster.Prepare reports using SELECT commands including unions and subqueriesCalculate aggregate statistics, such as sums and averages, during a queryCreate queries against multiple data sources by using join commandsTransform the output format of queries by using built-in functionsPerform queries across a group of rows using windowing functionsExercises will be provided to have enough practice to get better at Sqoop as well as writing queries using Hive and Impala.All the demos are given on our state-of-the-art Big Data cluster. If you do not have multi-node cluster, you can sign up for our labs and practice on our multi-node cluster. You will be able to practice Sqoop and Hive on the cluster.

Overview

Section 1: Introduction

Lecture 1 CCA 159 Certification Exam - Overview

Lecture 2 Tools for preparation

Lecture 3 Getting Details about the Exam

Lecture 4 Signing up for the Exam

Section 2: Using Cloudera QuickStart VM

Lecture 5 Download and Install Virtual Box

Lecture 6 Setup Cloudera QuickStart VM

Lecture 7 Overview of Cloudera QuickStart VM

Lecture 8 Overview of MySQL Databases

Lecture 9 Setup NYSE Database in MySQL

Lecture 10 Overview of HDFS and Setup Datasets

Lecture 11 Overview of Hive and Create External Table

Lecture 12 Validate Sqoop

Section 3: Using ITVersity labs

Lecture 13 Signing up for the labs

Lecture 14 Connecting to the gateway node of the cluster

Lecture 15 Overview of HDFS in the cluster

Lecture 16 Using Hive in the cluster

Lecture 17 Understanding MySQL in the cluster

Lecture 18 Running Sqoop Commands in the cluster

Section 4: Overview of Big Data eco system

Lecture 19 Overview of Distributions and Management Tools such as Ambari

Lecture 20 Properties and Properties Files of Big Data Tools - General Guidelines

Lecture 21 Hadoop Distributed File System - Quick Overview

Lecture 22 Distributed Computing using YARN and Map Reduce 2 - Quick Overview

Lecture 23 Submitting Map Reduce Job in YARN Framework

Lecture 24 Determining Number of Mappers and Reducers

Lecture 25 Understanding YARN and Map Reduce Configuration Properties

Lecture 26 Reviewing and Overriding Map Reduce Job Run Time Properties

Lecture 27 Reviewing Map Reduce Job Logs - using Resource Manager and Job History Server UI

Lecture 28 Map Reduce Job Counters

Lecture 29 Overview of Hive

Lecture 30 Databases in Big Data and Query Engines

Lecture 31 Overview of Data Ingestion Tools in Big Data

Section 5: Overview of HDFS Commands

Lecture 32 Introduction to HDFS for Certification Exams

Lecture 33 Overview of HDFS and Properties Files

Lecture 34 Overview of "hadoop fs" or "hdfs dfs" command

Lecture 35 Listing Files in HDFS

Lecture 36 User Spaces or Home Directories in HDFS

Lecture 37 Creating Directory in HDFS

Lecture 38 Copying Files and Directories into HDFS

Lecture 39 File and Directory Permissions Overview

Lecture 40 Getting Files and Directories from HDFS

Lecture 41 Previewing Text Files in HDFS - cat and tail

Lecture 42 Copying or Moving Files from one HDFS location to other HDFS location

Lecture 43 Understanding Size of the File System and Data Sets - using df and du

Lecture 44 Overview of Block Size and Replication Factor

Lecture 45 Getting metadata of files using "hdfs fsck"

Lecture 46 Resources and Exercises

Section 6: Apache Hive - Getting Started

Lecture 47 Overview of Hive Language Manual

Lecture 48 Launching and Using Hive CLI

Lecture 49 Overview of Hive Properties - SET and .hiverc

Lecture 50 Hive CLI History and .hiverc

Lecture 51 Running HDFS Commands using Hive CLI

Lecture 52 Understanding Warehouse Directory

Lecture 53 Creating Database in Hive and Switching to the Database

Lecture 54 Creating First Table in Hive and list the tables

Lecture 55 Retrieve metadata of Hive Tables using DESCRIBE (EXTENDED and FORMATTED)

Lecture 56 Role of Hive Metastore

Lecture 57 Overview of beeline - Alternative to Hive CLI

Lecture 58 Running Hive Queries using Beeline

Section 7: Apache Hive - Managing Tables in Hive

Lecture 59 Create tables in Hive - orders

Lecture 60 Overview of Data Types in Hive

Lecture 61 Adding Comments to Columns and Tables

Lecture 62 Loading Data into Hive Tables from Local File System

Lecture 63 Loading Data into Hive Tables from HDFS Location

Lecture 64 Loading Data into Hive Tables - Overwrite vs. Append

Lecture 65 Creating External Tables in Hive

Lecture 66 Specifying Location for Hive Tables

Lecture 67 Managed Tables vs. External Tables

Lecture 68 Default Delimiters in Hive Tables using Text File Format

Lecture 69 Overview of File Formats - STORED AS Clause

Lecture 70 Differences between Hive and RDBMS

Lecture 71 Truncating and Dropping tables in Hive

Lecture 72 Resources and Exercises

Section 8: Apache Hive - Managing Tables in Hive - Partitioning and Bucketing

Lecture 73 Introduction to Partitioning and Bucketing in Hive

Lecture 74 Creating Tables using orc File Format - order_items

Lecture 75 Inserting Data into order_items using stage table

Lecture 76 Can we use LOAD Command to get data into order_items with orc file format?

Lecture 77 Creating Partitioned Tables in Hive - orders_part with order_month as key

Lecture 78 Adding Partitions to Tables in Hive

Lecture 79 Loading into Partitions in Hive Tables

Lecture 80 Inserting Data into Partitions in Hive Tables

Lecture 81 Inserting data into Partitioned Tables - Using dynamic partition mode

Lecture 82 Creating Bucketed Tables - orders_buck and order_items_buck

Lecture 83 Inserting Data Into Bucketed Tables

Lecture 84 Bucketing with Sorting

Lecture 85 Overview of ACID Transactions in Hive

Lecture 86 Create Tables for ACID Transactions

Lecture 87 Inserting individual records into Hive Tables

Lecture 88 Updating and Deleting data in Hive Bucketed Tables

Section 9: Apache Hive - Overview of Functions

Lecture 89 Overview of Functions

Lecture 90 Validating Functions

Lecture 91 String Manipulation - Case Conversion and Length

Lecture 92 String Manipulation - substr and split

Lecture 93 String Manipulation - trimming and padding Functions

Lecture 94 String Manipulation - Reverse and Concatenating multiple strings

Lecture 95 Date Manipulation - Getting Current Date and Timestamp

Lecture 96 Date Manipulation - Date Arithmetic

Lecture 97 Date Manipulation - trunc

Lecture 98 Date Manipulation - Extracting information using date_format

Lecture 99 Date Manipulation - Extracting information using year, month, day etc

Lecture 100 Date Manipulation - Dealing with Unix Timestamp

Lecture 101 Overview of Numeric Functions

Lecture 102 Type Cast Functions for Data Type Conversion

Lecture 103 Handling null values using nvl

Lecture 104 Query Example - Get Word Count

Section 10: Apache Hive - Writing Basic Queries

Lecture 105 Overview of SQL

Lecture 106 Hive Query - Execution Life Cycle

Lecture 107 Reviewing Logs for Hive Queries

Lecture 108 Projecting Data using SELECT and Overview of FROM Clause

Lecture 109 Using CASE and WHEN as part of SELECT Clause

Lecture 110 Projecting DISTINCT Values

Lecture 111 Filtering Data using WHERE Clause

Lecture 112 Boolean Operations such as OR and AND using multiple fields

Lecture 113 Boolean OR vs. IN

Lecture 114 Filtering data using LIKE Operator

Lecture 115 Basic Aggregations using Aggregate Functions

Lecture 116 Performing basic aggregations such as SUM, MIN, MAX etc using GROUP BY

Lecture 117 Filtering post aggregation using HAVING

Lecture 118 Global Sorting using ORDER BY

Lecture 119 Overview of DISTRIBUTE BY

Lecture 120 Sorting Data with in groups using DISTRIBUTE BY and SORT BY

Lecture 121 Overview of CLUSTER BY

Section 11: Apache Hive - Writing Basic Queries - Joins and Set Operations

Lecture 122 Overview of Nested Sub Queries

Lecture 123 Nested Sub Queries in WHERE Clause with IN or NOT IN

Lecture 124 Nested Sub Queries in WHERE Clause with EXISTS or NOT EXISTS

Lecture 125 Overview of Joins

Lecture 126 Joining Multiple Tables in Hive

Lecture 127 Outer Joins in Hive

Lecture 128 Full Outer Joins in Hive

Lecture 129 Map Side Join vs. Reduce Side Join

Lecture 130 Joining using Legacy Syntax

Lecture 131 Cartesian between two data sets

Lecture 132 Overview of SET Operations

Lecture 133 Perform Union between two Data Sets

Lecture 134 Not Supported - Perform Intersection or Minus between two Data Sets

Section 12: Apache Hive - Analytics or Windowing Functions

Lecture 135 Prepare HR Database with employees table

Lecture 136 Overview of Analytics Functions or Windowing Functions

Lecture 137 Performing Aggregations

Lecture 138 Create tables to get daily revenue and daily product revenue

Lecture 139 Getting Lead and Lag using Windowing Functions - order by

Lecture 140 Getting Lead and Lag using Windowing Functions - order by and partition by

Lecture 141 Windowing Functions - Using first_value and last_value

Lecture 142 Applying rank Function

Lecture 143 Applying dense_rank Function

Lecture 144 Applying row_number Function

Lecture 145 Difference between rank, dense_rank and row_number

Lecture 146 Understanding Order of Execution

Lecture 147 Quick recap of Nested Sub Queries

Lecture 148 Filtering data using fields derived using analytics or windowing functions

Section 13: Running Queries using Impala

Lecture 149 Introduction to Impala

Lecture 150 Role of Impala Daemons

Lecture 151 Impala State Store and Catalog Server

Lecture 152 Overview of impala-shell

Lecture 153 Relationship between Hive and Impala

Lecture 154 Overview of Creating Databases and Tables in Hive

Lecture 155 Loading and Inserting Data into Impala Tables

Lecture 156 Running Queries using Impala Shell

Lecture 157 Reviewing Logs of Impala Queries

Lecture 158 Synching Hive Metadata with Impala - using INVALIDATE METADATA

Lecture 159 Running Scripts using Impala Shell

Section 14: Apache Sqoop - Getting Started

Lecture 160 Introduction to Sqoop

Lecture 161 Validate Source Database - MySQL

Lecture 162 Review JDBC Jar file to connect to MySQL

Lecture 163 Getting help of Sqoop using Command Line

Lecture 164 Overview of Sqoop User Guide

Lecture 165 Validate Sqoop and MySQL integration using "sqoop list-databases"

Lecture 166 List tables in MySQL using "sqoop list-tables"

Lecture 167 Run Queries in MySQL using "sqoop eval"

Lecture 168 Understanding Logs in Sqoop

Lecture 169 Redirecting Sqoop Logs into files

Section 15: Apache Sqoop - Importing Data into HDFS

Lecture 170 Overview of Sqoop Import Command

Lecture 171 Perform Sqoop Import of orders - –table and –target-dir

Lecture 172 Perform Sqoop import of order_items - –warehouse-dir

Lecture 173 Sqoop Import - Managing HDFS Directories - append or overwrite or fail

Lecture 174 Sqoop Import - Execution Flow

Lecture 175 Reviewing logs of Sqoop Import

Lecture 176 Sqoop Import - Specifying Number of Mappers

Lecture 177 Review the Output Files

Lecture 178 Sqoop Import - Supported File Formats

Lecture 179 Validating avro Files using avro-tools

Lecture 180 Sqoop Import - Using Compression

Section 16: Apache Sqoop - Importing Data into HDFS - Customizing

Lecture 181 Sqoop Import - Customizing - Introduction

Lecture 182 Sqoop Import - Specifying Columns

Lecture 183 Sqoop Import - Using boundary query

Lecture 184 Sqoop Import - Filter unnecessary data

Lecture 185 Sqoop Import - Using Split By

Lecture 186 Sqoop Import - Importing Query Results

Lecture 187 Sqoop Import - Dealing with Composite Keys

Lecture 188 Sqoop Import - Dealing with Primary Key or Split By using Non Numeric Field

Lecture 189 Sqoop Import - Dealing with Tables with out Primary Key

Lecture 190 Sqoop Import - Autoreset to One Mapper

Lecture 191 Sqoop Import - Default Delimiters using Text File Format

Lecture 192 Sqoop Import - Specifying Delimiters - Import NYSE Data with \t as delimiter

Lecture 193 Sqoop Import - Dealing with NULL Values

Lecture 194 Sqoop Import - import-all-tables

Section 17: Apache Sqoop - Importing Data into Hive Tables

Lecture 195 Sqoop Import - Importing Data into Hive tables - Overview

Lecture 196 Quick Overview of Hive

Lecture 197 Sqoop Import - Create Hive Database

Lecture 198 Creating empty Hive Table using create-hive-table

Lecture 199 Sqoop Import - Import orders table to Hive Database

Lecture 200 Sqoop Import - Managing Table using Hive Import - Overwrite

Lecture 201 Sqoop Import - Managing Table using Hive Import - Error out - create-hive-table

Lecture 202 Sqoop Import - Understanding Execution Flow while importing into Hive Table

Lecture 203 Sqoop Import - Review files in Hive Tables

Lecture 204 Sqoop Delimiters vs. Hive Delimiters - Text Files

Lecture 205 Sqoop Import - Hive File Formats

Lecture 206 Sqoop Import all tables - Hive

Section 18: Apache Sqoop - Exporting Data from HDFS to RDBMS

Lecture 207 Introduction

Lecture 208 Prepare data for Export

Lecture 209 Creating Table in MySQL

Lecture 210 Sqoop Export - Perform Simple Export - –table and –export-dir

Lecture 211 Sqoop Export - Execution Flow

Lecture 212 Sqoop Export - Specifying Number of Mappers

Lecture 213 Sqoop Export - Troubleshooting the issues

Lecture 214 Sqoop Export - Merging or Upserting Overview

Lecture 215 Sqoop Export - Quick Overview of MySQL for Upsert

Lecture 216 Sqoop Export - Using update-mode - update-only (default)

Lecture 217 Sqoop Export - Using update-mode - allow-inseert

Lecture 218 Sqoop Export - Specifying Columns

Lecture 219 Sqoop Export - Specifying Delimiters

Lecture 220 Sqoop Export - Using Stage Table

Section 19: Apache Sqoop - Incremental Imports and Jobs

Lecture 221 Overview of Sqoop Jobs

Lecture 222 Adding Password File

Lecture 223 Creating Sqoop Job

Lecture 224 Running Sqoop Job

Lecture 225 Overview of Incremental Imports

Lecture 226 Incremental Import - Using where

Lecture 227 Incremental Import - Append Mode

Lecture 228 Incremental Import - Create training_orders_incr in retail_export

Lecture 229 Incremental Import - Create Job

Lecture 230 Incremental Import - Execute Job

Lecture 231 Incremental Import - Add additional data (order_id > 30000)

Lecture 232 Incremental Import - Rerun the job and validate results

Lecture 233 Incremental Import - Using mode lastmodified

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