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


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