Open Source/Teradata Database Administration

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Teradata Database Administration Course Overview

Enrol for the 3-day Teradata DBA training from Koenig Solutions. This class covers everything from Teradata DBA fundamentals, Teradata Architecture, and Teradata Internals.

Target Audience:

At the completion of this course, all students will have the skills and knowledge to perform their DBA jobs at a very high level.

Learning Objectives:

At the completion of this course, students will have the skills and knowledge to perform their DBA jobs at a very high level. Topics include:

  • Introduction and Good Advice
  • Teradata Architecture Fundamentals the DBA must know
  • The Primary Index is the Axis of all Teradata Systems
  • A DBA’s best friend - The Data Dictionary
  • How Teradata Tracks Objects
  • Creating Users and Databases
  • Profiles
  • Roles
  • Access Rights
  • Collect Statistics
  • Locking
  • Protection Features
  • The Cold, Hard Teradata Facts
  • How Teradata Tracks Objects
  • AMP Worker Tasks
  • Deep Dive Overhead for each Row
  • Compression
  • Data Stored in the Row
  • How Data Rows are Stored in Blocks
  • Disk Cylinders and the Master Index
  • Teradata Virtual Storage (TVS)
  • Teradata Writes and Blocks
  • Access Logging
  • DBQL Query Logging

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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You will learn:

Module 1: Introduction and Good Advice
  • What is Parallel Processing?
  • Start Small and Think Big
  • Give your Enterprise the Tools they need
  • Model the Business with ERwin
  • Educate the Business on the Business by Sharing the Model
  • Load Your Models and have the SQL Built Automatically
  • Five Brilliant Pieces of Teradata (1 of 5) is MPP
  • Five Brilliant Pieces (2 of 5) are Tactical Queries
  • Five Brilliant Pieces (3 of 5) Is a Traffic System
  • Five Brilliant Pieces (4 of 5) Is Viewpoint
  • Five Brilliant Pieces (5 of 5) Are Data Processing Options
  • Support Large Queries, but Monitor them closely
  • Experiment and Improve Loading Data Strategies
  • Compress Your Data with Multi-Value Compression
  • Separate your Production System from Your Test System
  • Parallel Architecture
  • The Teradata Architecture
  • All Teradata Tables are spread across ALL AMPS
  • Teradata Systems can Add AMPs for Linear Scalability
  • AMPs and Parsing Engines (PE’s) live inside SMP Nodes
  • Each Node is Attached via a Network to a Disk Farm
  • Two SMP Nodes Connected Become One MPP System
  • There are Many Nodes in a Teradata Cabinet
  • This is the Visual You Want to Understand Teradata
  • Responsibilities of the DBA
  • The Primary Index is defined when the table is CREATED
  • A Unique Primary Index (UPI)
  • Primary Index in the WHERE Clause - Single-AMP Retrieve
  • A Non-Unique Primary Index (NUPI)
  • Primary Index in the WHERE Clause - Single-AMP Retrieve
  • A conceptual example of a Multi-Column Primary Index
  • Primary Index in the WHERE Clause - Single-AMP Retrieve
  • A conceptual example of a Table with NO PRIMARY INDEX
  • A Full Table Scan is likely on a table with NO Primary Index
  • Table CREATE Examples with four different Primary Indexes
  • What happens when you forget the Primary Index?
  • Why create a table with No Primary Index (NoPI)?
  • The Data Dictionary Resides in User DBC
  • The DBC.DBCInfoV View
  • Querying the Data Dictionary
  • Using the Keyword USER
  • Restricted Views have an X at the End of their Name
  • The V is New with Teradata V12
  • The V and the Restricted X are Now Often Combined
  • A Recap of What We Have Learned So Far
  • The DBC.DatabasesV View
  • The DBC.Users View
  • The DBC.Tables View
  • Using DBC.Tables to find out about Fallback
  • The DBC.Indices View
  • The DBC.Columns View
  • Clever Queries for the DBC.ColumnsV View
  • New V14 - The DBC.PartitioningConstraintsV View
  • The DBC.AccountInfo View
  • The DBC.AMPUsage View
  • Clearing Out the DBC.AMPUsage Data
  • The DBC.AllTempTables
  • The DBC.Triggers
  • The DBC.All_RI_ChildrenV
  • DBC.SessionInfoV Information
  • DBC.LogonOffV
  • AllRoleRights, AllRightsV, UserRightsV and UserGrantedRightsV
  • The DBC.Profiles View
  • RoleMembers, RoleInfo, UserRoleRights and ProfileInfoVX,
  • Understanding that Space is based on a Per-AMP Basis
  • Total Space for a Single Database or User
  • Using the Data Dictionary to see the Space for Everyone
  • Finding the Perm Percent Used
  • Finding the Perm Percent Used with a HAVING Clause
  • Finding the Perm Percent Left with a HAVING Clause
  • Creating a Macro for Perm Percent Used with a Dynamic %
  • Orphaned Spool Files That Need to be deleted
  • Finding Table Sizes
  • Finding Skew in the Tables in a Database
  • Finding Skew in a Table
  • Display the Distribution of a Column per AMP
  • Your Users and Databases
  • DBC Tables used in the Collect Statistics Process
  • The DBC Table DBC.Next
  • DBA Advice - ClearPeakDisk to Reset Peak Space
  • DBA Advice – Clean out these Tables Periodically
  • The DBC.AssociationV View
  • The DBC.JournalsV View
  • DBC.Databases2V is for Unresolved Reference Constraints
  • The DBC.All_RI_ChildrenV for Inconsistent RI
  • The DBC.ShowColChecksV View
  • The DBC.ShowTblChecksV View
  • The DBC.PartitioningConstraintsV View
  • The DBC.AccessLogV View
  • The DBC.AccessLogV View for Today’s Queries
  • The DBC.AccessLogV View Denials for Today
  • DBC.DBQLRulesV
  • DBC.QryLogV
  • DBC.QryLogSummaryV
  • ResUsage Macros
  • Executing the ResUsage Macro DBC.Resnode
  • The DBC.IdCol Table
  • Teradata Assigns each Object a Unique Numeric ID
  • The Table ID
  • The Table ID in Greater Detail
  • Looking at the TableID inside the actual Cylinders
  • A More Detailed View of TableID inside the actual Cylinders
  • The Blocks Below are All Associated with the Same Table
  • Bits, Bytes and More
  • Cylinder Sizes
  • Creating Users and Databases
  • Password Security Meanings
  • Now we have Two Users in the Teradata System
  • A Grant Statement so others Create a Database or User
  • And so the Teradata Hierarchy Begins
  • Creating a Database
  • Users are Given Passwords While Database are Not
  • Teradata Administrator Can CREATE Users
  • The Modify User Statement
  • A Clever Way to Reset a User Password
  • Accounts and their Associated Priorities
  • Creating a User with Multiple Account Priorities
  • Self-Nicing to change Account Priorities
  • Account String Expansion (ASE)
  • The DBC.AccountInfo View
  • The DBC.AMPUsage View
  • Account String Expansion (ASE) in Action
  • Test – Run queries Under All Accounts for TeraTom
  • The DBC.AMPUsage View
  • Profiles
  • Getting Started for Profile Creation
  • Creating A Profile and a User
  • Password Security
  • Password Security Meanings
  • Creating A Profile and then Modifying a User
  • Quiz – What are the Profile Values?
  • Answer to Quiz – What are the Profile Values?
  • Quiz – What are the Profile Values After Null?
  • Answer to Quiz – What Are the Profile Values After Null?
  • The DBC.ProfilesVX View
  • The DBC.ProfilesV View
  • The DBC.AccountInfoVX View
  • ProfileInfoVX, RoleMembers, RoleInfo and UserRoleRights
  • Teradata Administrator Can CREATE Profiles (1 of 2)
  • Teradata Administrator Can CREATE Profiles (2 of 2)
  • Dropping a Profile
  • The Effects of Dropping a Profile
  • Roles
  • Getting Started for Role Creation
  • Create A Role and then Assign that Role It’s Access Rights
  • Create a User and Assign them a Default Role
  • A Role vs. a Profile
  • Granting a Role to a Current User
  • Active Roles
  • Setting Your Active Role to ALL
  • Roles and Valid Objects
  • Roles and Invalid Commands
  • Nesting of Roles
  • Nesting of Roles in Action (1 of 3)
  • Nesting of Roles in Action (2 of 3)
  • Nesting of Roles in Action (3 of 3)
  • Quiz – What Databases Does Mandy Have Access To?
  • Answer – What Databases Does Mandy Have Access To?
  • GRANT WITH ADMIN OPTION Command
  • REVOKE ADMIN OPTION FOR Command
  • RoleMembers, RoleInfo, UserRoleRights and ProfileInfoVX
  • DBC Tables for AllRoleRights, AllRightsV, UserRightsV and UserGrantedRightsV
  • The Objects That Require Access Rights
  • Objects and Available Access Rights
  • A Few Examples to Get You Started
  • There are Three Types of Access Rights
  • A Dinner Invitation of Access Rights
  • One of the Problems with Access Rights
  • The Rights for SysDBA and TeraTom
  • The GRANT Statement
  • Create A Role and then Assign that Role It’s Access Rights
  • GRANT to PUBLIC
  • GRANT To ALL DBC
  • GRANT Using the ALL Keyword
  • GRANT Database Strategy for Users, Views and Tables
  • Inheriting Access Rights
  • GRANT at the Column Level
  • GRANT for the Ability to CREATE Secondary Indexes
  • Access Rights to CREATE Triggers
  • The REVOKE Command
  • DBC Tables for AllRoleRights, AllRightsV, UserRightsV and UserGrantedRightsV
  • The GIVE Statement
  • A DROP User can be Better than a GIVE Statement
  • Removing a Level in the Teradata Hierarchy
  • The Teradata Parsing Engine (Optimizer) is Cost Based
  • The Purpose of Collect Statistics
  • When Teradata Collects Statistics it creates a Histogram
  • The Interval of the Collect Statistics Histogram
  • Histogram Quiz
  • Answers to Histogram Quiz
  • What to COLLECT STATISTICS On?
  • Why Collect Statistics?
  • How do you know if Statistics were collected on a Table?
  • A Huge Hint that No Statistics Have Been Collected
  • The Basic Syntax for COLLECT STATISTICS
  • COLLECT STATISTICS Examples for a better Understanding
  • The New Teradata V14 Way to Collect Statistics
  • COLLECT STATISTICS Directly From another Table
  • Where Does Teradata Keep the Collected Statistics?
  • The Official Syntax for COLLECT STATISTICS
  • How to Recollect STATISTICS on a Table
  • Teradata Always Does a Random AMP Sample
  • Random Sample is Kept in the Table Header in FSG Cache
  • Multiple Random AMP Samplings
  • How a Random AMP gets a Table Row count
  • Random AMP Estimates for NUSI Secondary Indexes
  • USI Random AMP Samples are Not Considered
  • There’s No Random AMP Estimate for Non-Indexed Columns
  • A Summary of the PE Plan if No Statistics Were Collected
  • Stale Statistics Detection and Extrapolation
  • Extrapolation for Future Dates
  • How to Copy a Table with Data and the Statistics
  • How to Copy a Table with NO Data and the Statistics
  • When to COLLECT STATISTICS Using only a SAMPLE
  • Examples of COLLECT STATISTICS Using only a SAMPLE
  • Examples of COLLECT STATISTICS for V14
  • How to Collect Statistics on a PPI Table on the Partition
  • Teradata V12 and V13 Statistics Enhancements
  • Teradata V14 Statistics Enhancements
  • Teradata V14 Summary Statistics
  • Teradata V14 MaxValueLength
  • Teradata V14 MaxIntervals
  • Teradata V14 Sample N Percent
  • Teradata V14.10 Statistics Collection Improvements
  • Teradata V14.10 Statistics Collection Threshold Examples
  • Teradata V14.10 AutoStats feature
  • Teradata Statistics Wizard
  • The Four Major Locks of Teradata
  • The Read Lock
  • The Read Lock and Joins
  • The Write Lock
  • The Exclusive Lock
  • The Three Levels of Locking
  • Locking at the Row Hash Level
  • Locking at the Table Level
  • Locking at the Database Level
  • The Ongoing Battle between Read and Write Locks
  • Compatibility between Read Locks
  • Why Read Locks Wait on Write Locks
  • Why Write Locks Wait on Read Locks
  • The Access Lock is Different from the Other Locks
  • What is the Purpose of an Access Lock?
  • Locking Modifiers - Locking Row, Table or Database
  • All Views should consider the Locking for Access Statement
  • What is a Dead Lock or a Deadly Embrace?
  • Pseudo Tables are designed to minimize Dead Locks
  • Pseudo Tables are referenced in the Explain Plan
  • Incompatible Locks Wait on each Other
  • The Checksum Lock of Teradata
  • The Nowait Option for Locking
  • The Automatic Locking for Access Button inside Nexus
  • Viewpoint Lock Viewer
  • Viewpoint Lock Viewer Lets You Configure Your View
  • What is a Host Utility (HUT) Lock?
  • A List of the Protection Features
  • Transient Journal Protects the Transaction Integrity
  • The Transient Journal in Action
  • A Single Transaction could Involve All AMPs
  • The Secret to turning off the Transient Journal
  • The Transient Journal’s Write Ahead Logging (WAL)
  • A Node with 40 AMPs and 40 Dedicated FSG Caches
  • The Transient Journal’s Write Ahead Logging (WAL)
  • Working Example of the Write Ahead Log (WAL)
  • The First Step in our Example of the Write Ahead Log (WAL)
  • The Second Step in our Example of the Write Ahead Log
  • The Third Step in our Example of the Write Ahead Log
  • The Fourth Step in our Example of the Write Ahead Log
  • The Last Step in our Example of the Write Ahead Log
  • Fallback to Protect against an AMP Failure
  • Fallback Clusters
  • AMPs in a Cluster are Physically Separated
  • The Reason AMPs in a Cluster are Physically Separated
  • The Price you pay for Fallback
  • How to Create a Table with Fallback
  • How to Create a Table with No Fallback
  • How to Alter a Table to Add or Drop Fallback
  • What is a Virtual Disk?
  • Why do AMPs each have Four Physical Disks?
  • Is a Mirror just like Looking into a Mirror?
  • RAID 1 Mirroring – Redundant Array of Independent Disks
  • What does RAID Protect?
  • How Does RAID Fail?
  • Do RAID and Fallback have a Connection?
  • What is a Clique?
  • If a Node goes down the AMPs migrate within the Clique?
  • Does Teradata Reset during a Node Failure?
  • Four Node Cliques
  • Migrating AMPs in Four Node Cliques
  • The Hot Spare Node
  • The Hot Spare Node in Action
  • With a Hot Spare a Second Teradata Reset isn’t Needed
  • A Node, It’s AMPs and their Disks
  • How Cliques are Physically Defined
  • Cliques are cabled so Migrating AMPs can access their Disks
  • A Review of Fallback and Clusters
  • An Example of Fallback and Clusters
  • Summary of the facts for Fallback, Clusters, and Cliques
  • The Permanent Journal
  • Difference between the Transient and the Permanent Journal
  • Difference Between the Before and After Permanent Journal
  • Full System Backup compared to an After Journal
  • How Full System Backups work with the After Journal
  • The Many Different Permanent Journal Options
  • Where is the Permanent Journal Stored?
  • Using Common Sense about Journal Locations
  • After Journals are Never stored in the Same Node or Clique
  • What is a Dual After Journal?
  • What is a Dual Before Journal?
  • What is a Journal?
  • Creating a Table with Fallback and a Before and After Journal
  • Does Fallback Affect a Permanent Journal?
  • Permanent Journal Rules
  • Example 1: Permanent Journal Scenarios to Test the Rules
  • Example 2: Permanent Journal Scenarios to Test the Rules
  • Example 3: Permanent Journal Scenarios to Test the Rules
  • How to Create Database with a Permanent Journal
  • How to Create Database with a Permanent Journal
  • Permanent Journal’s Three Main Areas
  • The Current Journal consists of the Active and Saved Areas
  • Permanent Journal Commands
  • Deleting a Permanent Journal
  • Some Great Advice for Maintaining the Permanent Journals
  • Recovery Using the Permanent Journals
  • The Journals View in DBC (DBC.Journals)
  • Archive Recovery Console (ARC)
  • Reasons You Might Utilize ARC
  • ARC raising the BAR (Backup Archive Restore)
  • ARC Commands in Alphabetical Order
  • An ARC Example of an Archive and then a Restore
  • What is Parallel Processing?
  • The Basics of a Single Computer
  • Teradata Parallel Processes Data
  • Parallel Architecture
  • The Teradata Architecture
  • All Teradata Tables are spread across ALL AMPS
  • Teradata Systems can Add AMPs for Linear Scalability
  • Understand that Teradata can scale to incredible size
  • AMPs and Parsing Engines (PEs) live inside SMP Nodes
  • Each Node is attached via a Network to a Disk Farm
  • Two SMP Nodes Connected Become One MPP System
  • There are Many Nodes in a Teradata Cabinet
  • Inside a Teradata Node
  • The Boardless BYNET and the Physical BYNET
  • The Parsing Engine
  • The AMPs Responsibilities
  • Teradata Parallel Processin
  • Each Table has a Primary Index that is Unique or Non-Unique
  • The Hash Map Determines which AMP will own the Row
  • A Unique Primary Index Spreads the Data Evenly
  • The AMP Adds a Uniqueness Value to Create the Row-ID
  • Each AMP Sorts Their Tables by the Row-ID
  • A Non-Unique Primary Index Skews the Data
  • Comparing the Same Table with Different Primary Indexes
  • Unique Primary Index Queries are a Single AMP Retrieve
  • A Non-Unique Primary Index is also a Single AMP Retrieve
  • Teradata has a No Primary Index Table called a NoPI Table
  • There are Normal Tables and then there are Partitioned Tables
  • A Visual of One Year of Data with Range_N Per Month
  • Partitioning is designed to eliminate the Full Table Scan
  • A Partition # and Row-ID = Row Key
  • An AMP Stores its Rows Sorted in only Two Different Ways
  • AMPs Moves Their Data Blocks into Memory to Read/Write
  • The Most Taxing thing for an AMP is Moving Blocks into Memory
  • Rows are Stored in Data Blocks which are stored in Cylinders
  • Rows for an AMP Stored Inside a Data Block in a Cylinder
  • An AMP’s Master Index is Used to Find the Right Cylinder
  • The Row Reference Array (RRA) Does the Binary Search
  • A Block Splits into Two Blocks at Maximum Block Size
  • Data Blocks Maximum Block Size has Changed (V14.10)
  • The New Block Split with Teradata V14.10
  • The Block Split with Even More Detail in Teradata V14.10
  • There is One Master Index and Thousands of Cylinder Indexes
  • Each Table has a 48-bit TableID
  • Teradata Assigns each Object a Unique Numeric ID
  • The Table ID
  • The Table ID in Greater Detail
  • Looking at the TableID inside the actual Cylinders
  • A More Detailed View of TableID inside the actual Cylinders
  • The Blocks Below are All Associated with the Same Table
  • Bits, Bytes, and More
  • Cylinder Sizes
  • Teradata is a Message Passing System
  • The Parsing Engine Parses the SQL and comes up with a Plan
  • What is an AMP Worker Task (AWT)?
  • Each AMP has 80 AMP Worker Tasks (AWTs)
  • Each Query Takes Up One or More AMP Worker Tasks
  • An All-AMP Query Usually Won’t Use More Than 4 AWTs
  • A Live Example of AWTs in Action
  • There are 24 AWTs Reserved for Internal Work
  • How Utilities Use AWTs
  • Monitoring AMP Worker Tasks with ResAMPCpuByGroup
  • Why Go Deep inside the Overhead of a Row?
  • A Row Layout in Teradata
  • Row Length
  • Row ID
  • How The Row Hash is created for Each Row
  • Unique Primary Indexes have Even Distribution
  • The AMP adds a Uniqueness Value to Its Rows
  • The Row-Hash is 32-bits and so is the Uniqueness Value
  • Non-Unique Primary Indexes have Skewed Data
  • Flag Byte
  • Presence Byte
  • Presence Byte is used to show Null Values in each Row
  • A Close-up look at the Presence Byte for Nulls
  • An Extreme example to look at the Presence Byte for Nulls
  • Quiz – How Many Presence Bits used for these Columns?
  • Answer – How Many Presence Bits used for these Columns?
  • Quiz – How Many Presence Bits used with NOT NULL?
  • Answer – How Many Presence Bits used with NOT NULL?
  • Quiz – Which bit will be Set to a One?
  • Answer – Which bit will be Set to a One?
  • Quiz – How Many Presence Bits Needed Now?
  • Answer – How Many Presence Bits Needed Now?
  • What Happens when we need more than One Presence Byte?
  • An Example that must use a 2nd Presence Byte
  • Quiz – Answer the Presence Bit/Byte Questions?
  • Answers to the – Answer the Presence Bit/Byte Questions?
  • Quiz - How Many Nullable Columns are Possible?
  • Answer- How Many Nullable Columns are Possible?
  • Important Information about Compression
  • Presence Bytes are also used for Compression
  • Why One Byte (8 bits) can represent up to 255 Values
  • Answers to One Byte (8 bits) can represent up to 255 Values
  • Now that you Understand that 8 Bits can Represent 0 – 255
  • A Compression Example that Compresses Two Values
  • A Compression Example that Compresses Three Values
  • Quiz – Name that Compression Value
  • The Next Important Concept in Compression
  • Quiz – Can you Fill in the Compression Values?
  • Answer – Can you Fill in the Compression Values?
  • The Last Major Concept in Compression
  • Quiz – Using One Presence Byte for Multiple Columns
  • Answer – Using One Presence Byte for Multiple Columns
  • Quiz – How Many Presence Bytes are Needed?
  • Answer – How Many Presence Bytes are Needed?
  • Advanced Quiz – Fill in the Presence Bits?
  • Answer to Advanced Quiz – Fill in the Presence Bits?
  • The Cost Vs. the Savings
  • The Cost List of Compression
  • A Deeper Dive Into NULL Values
  • Quiz - How Much Space Did We Just Save?
  • Answer - How Much Space Did We Just Save?
  • Advanced Quiz - How Much Space Did We Just Save?
  • Using the DBC Tables in a Compression Experiment
  • A Compression Test
  • We then moved all Eight Tables to another Database
  • Compression Reports with Nexus and SmartCompress
  • We Then Created Two Global Temporary Tables
  • We Then Created and Executed our Macro
  • Report Comparing Compressed and NonCompressed Tables
  • The Varchar Offset
  • An Example of a Varchar Offset
  • An Example of Two Varchar Columns
  • The Fixed Columns
  • An Example with Multiple Fixed Columns
  • Compressible Columns
  • An Example with Fixed Columns and A Compression Column
  • An Example with A Fixed Column and a Compressed Varchar
  • VARCHAR Columns
  • An Example of a Fixed Column and a Varchar
  • Teradata’s Maximum Row Size
  • Why Go Deep inside Data Blocks?
  • In The Beginning a Table is created
  • Every AMP has the Exact Same Tables
  • Rows are Stored in Blocks
  • Each Table Header and Data Block have the Same TableID
  • AMPs Moves Their Data Blocks into Memory to Read/Write
  • AMPs can Read/Write their Rows once they are in FSG Cache
  • Every Data Block Starts with a Data Block Header
  • Every Data Block Ends with a Data Block Trailer
  • Each Block has a Row Reference Array (RRA)
  • The Row Reference Array (RRA) is in Descending Order
  • A Binary Search is always done through the RRA
  • A Binary Search is a quick Search among thousands of Rows
  • The Ref Array Pointer in the Row Layout in Teradata
  • How Blocks of Data Begin in Teradata
  • How Blocks of Data Grow in Teradata
  • Did You Notice the Row Reference Array (RRA)?
  • A Great Picture of a Single AMP’s Data Block with Details
  • Data Blocks Grow until they Reach Maximum Block Size
  • The Block Split
  • The Block Split with Even More Detail
  • The Block Split Showing Two Blocks with Greater Detail
  • Blocks Continue to Split as Tables Grow Larger
  • Reminder - Data Blocks Maximum Block Size has Changed (V14.10)
  • Reminder - The New Block Split with Teradata V14.10
  • Reminder - The Block Split with Even More Detail in Teradata V14.10
  • Reminder - Teradata V14.10 Block Split Defaults
  • FYI – Some Advanced Information about Data Block Headers
  • Disks have Cylinders which hold Data Blocks
  • Rows are Stored in Data Blocks which are stored in Cylinders
  • A Real World View of Rows inside a Data Block in a Cylinder
  • A Top down View of Cylinders
  • There are Hot, Warm, and Cold Cylinders
  • Cylinders are used for Perm, Spool, Temp, and Journals
  • Synchronized Scan (Sync Scan)
  • EXPLAIN Using a Synchronized Scan
  • Intelligent Memory (Teradata V14.10)
  • Teradata V14.10 Intelligent Memory Gives Data a Temperature
  • Data deemed VeryHot stays in each AMP's Intelligent Memory
  • Intelligent Memory Stays in Memory
  • Each AMP has Their Own Master Index
  • Each Cylinder on an AMP has a Cylinder Index
  • Quiz – What Two Things Does and AMP Read?
  • Answer – What Two Things Does and AMP Read?
  • Quiz – How Many Row Reference Arrays do you See?
  • Answer – How Many Row Reference Arrays do you See?
  • Quiz – How Many Row Reference Arrays are there Now?
  • Answer – How Many Row Reference Arrays do you See?
  • Quiz – How Many Row Reference Arrays in Total?
  • Answer – How Many Row Reference Arrays in Total?
  • Quiz – How Many Cylinder Indexes are Here?
  • Answer – How Many Cylinder Indexes are Here?
  • A More Detailed Illustration of the Master Index
  • A Real-World View of the Master Index
  • An Even More Realistic View of an AMP’s Master Index
  • The Cylinder Index
  • An Even More Realistic View of a Cylinder Index
  • How a Query using the Primary Index works
  • How the AMPs Do a Full Table Scan
  • How An AMP Reads Using a Primary Index
  • Teradata Assigns each Object a Unique Numeric ID
  • The Table ID
  • The Table ID in Greater Detail
  • Looking at the TableID inside the actual Cylinders
  • A More Detailed View of TableID inside the actual Cylinders
  • An Even More Realistic View of a Cylinder Index
  • Bits, Bytes, and More
  • Cylinder Sizes
  • How TVS Monitors and Migrates Tables
  • How TVS Monitors and Migrates Partitioned (PPI) Tables
  • A Summary of the Master and Cylinder Index
  • Solid State Drives (SSD) Vs. Hard Disk Drives (HDD)
  • Teradata Uses Two Types of Disks
  • Traditional Teradata Without Teradata Virtual Storage (TVS)
  • Teradata With TVS in a Conceptual Diagram
  • What TVS is Responsible for Doing
  • The Benefits of Teradata Virtual Storage (TVS)
  • What is a Clique?
  • If a Node goes down the AMPs migrate within the Clique?
  • Review of a Clique
  • Teradata Virtual Storage (TVS) Manages within a Clique
  • Before TVS vs. TVS Today with Teradata V13.10
  • TVS Operates in Two Different Modes
  • TVS Knows the Disks and Which Cylinders are the Fastest
  • A Concept Called Recency
  • Data Placement and Migration
  • Review - Intelligent Memory (Teradata V14.10)
  • Review - Teradata V14.10 Intelligent Memory Gives Data a Temperature
  • Review - Data deemed VeryHot stays in each AMP's Intelligent Memory
  • Review - Intelligent Memory Stays in Memory
  • A Teradata Write
  • Teradata Insert (Option 1 of 3) has enough space for the Insert
  • Teradata Insert (Option 2 of 3) is a Defragment to make Space
  • Teradata Insert (Option 3 of 3) is to Get a Bigger Block
  • Checksum Determines if a New Block is Needed
  • A Reminder of How Rows are Sorted with Block Utilities
  • A Reminder of How Rows are Sorted with SQL Inserts
  • When a Block Reaches Maximum Size, it Splits into Two
  • A Block Split Always Sorts the Rows Perfectly Once Again
  • In Teradata V14.10 the Maximum Block Size is 1 Megabyte
  • Cylinder Sizes
  • Teradata V14 Large Cylinders
  • Quiz on Block Split
  • Answer - Quiz on Block Split
  • Quiz – How many Items are in the Picture?
  • Answer to Quiz – How many Items are in the Picture?
  • Quiz on Teradata V14.10 Block Split
  • Answer - Quiz on Block Split
  • Blocking Terms for Teradata V14 and Below
  • Blocking Terms for Teradata V14.10 and Beyond
  • Block Sizes and Filling of Cylinders
  • Space Fragmentation (1 of 2)
  • Space Fragmentation (2 of 2)
  • What is a Defrag? (1 of 2)
  • What is a Defrag? (2 of 2)
  • What Happens When a Cylinder is Full?
  • What is a Mini-Cylpack? (1 of 2)
  • What is a Mini-Cylpack? (2 of 2)
  • What is a Mini-Cylpack Vs. a Pack Disk?
  • A Pack Disk Picture
  • New Teradata 13.10 Auto Cylinder Pack Feature
  • A Pack Disk Honors the Free Space Percent
  • Free Space Percent
  • Three Examples of the Free Space Percent
  • Simpler Terms for our Free Space Percent Examples
  • The Free Space Percent can be set in Three Ways
  • Two Table Create Examples of Min and Max Block Size
  • The Same Table Creates using KILOBYTES (KBYTES)
  • Why Would I Want Bigger or Smaller Block Sizes?
  • How Does Teradata Manage Space?
  • How Can Many Big Blocks Become Many Small Blocks?
  • Merge Datablocks (13.10 Feature)
  • Merge Datablocks Details
  • Setting Merge Datablocks in DBS Control or at Table Level
  • How Have Customers Previously Handled Shrinking Blocks?
  • Access Logging
  • Security for the DBA
  • The Tables and Views Associated with Access Logging
  • Begin Logging Options
  • Begin Logging, View Rules, See Log Data, and End Logging
  • Begin Logging Examples
  • The DBC.AccessLogV View
  • The DBC.AccessLogV View for Today’s Queries
  • The DBC.AccessLogV View Denials For Today
  • Controlling the Log Files
  • DBQL Query Logging
  • The Tables and Views Associated with DBQL
  • There are Seven Major Tables to Store DBQL Entries
  • The Views for the Major DBQL Tables
  • Begin Query Logging Default Information
  • Begin Query Logging WITH Options
  • Begin Query Logging Examples
  • Begin Query Logging LIMIT Options
  • Begin Query Logging LIMIT Examples
  • SUMMARY and THRESHOLD have Additional Options
  • Begin Query Logging with Additional Options Examples
  • Begin and End Query Logging Examples
  • Replace Query Logging Statement
  • An Inside Look at the View DBC.DBQLRulesV
  • The Columns in the View DBC.DBQLRulesV
  • Begin Logging, View Rules, See Log Data and End Logging
  • DBC.DBQLRulesV
  • DBC.QryLogV
  • DBC.QryLogSummaryV
  • ResUsage
  • Major Tables to Store ResUsage Entries
  • The ResUsage Views
  • ResUsage Macro Information
  • ResUsage Macros
  • Executing the ResUsage Macro DBC.Resnode
  • Executing the ResUsage Macro DBC.Resnode
  • ResAMPCpuByGroup
  • ResCpuByAMP
  • ResCpuByGroup
  • ResCpuByNode
  • ResCpuByPE
  • ResHostByGroup
  • ResHostByLink
  • ResHostTotal
  • ResHostTotalDay
  • ResHostTotalHour
  • ResIvprMigrate
  • ResIvprMigrateHour
  • ResLdvByGroup
  • ResLdvByNode
  • ResMemByGroup
  • ResMemMgmtByNode
  • ResNetByGroup
  • ResNetByNode
  • ResPeCpuByGroup
  • ResScpuDayTotal
  • ResScpuSec
  • ResSvprDetailReadTotal
  • ResSvprPreReadBySec
  • ResSvprQLenAvg
  • ResSvprQLenAvgByVproc
  • ResSvprQLenMaxHour
  • ResSvprReadByVprocSec
  • ResSvprReadTotal
  • ResSvprWriteTotal
  • ResSvprWriteTotalHour
  • ResSyncScan
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Says our CEO-
“It is an interesting story and dates back half a century. My father started a manufacturing business in India in the 1960's for import substitute electromechanical components such as microswitches. German and Japanese goods were held in high esteem so he named his company Essen Deinki (Essen is a well known industrial town in Germany and Deinki is Japanese for electric company). His products were very good quality and the fact that they sounded German and Japanese also helped. He did quite well. In 1970s he branched out into electronic products and again looked for a German name. This time he chose Koenig, and Koenig Electronics was born. In 1990s after graduating from college I was looking for a name for my company and Koenig Solutions sounded just right. Initially we had marketed under the brand of Digital Equipment Corporation but DEC went out of business and we switched to the Koenig name. Koenig is difficult to pronounce and marketeers said it is not a good choice for a B2C brand. But it has proven lucky for us.” – Says Rohit Aggarwal (Founder and CEO - Koenig Solutions)
All our trainers are fluent in English . Majority of our customers are from outside India and our trainers speak in a neutral accent which is easily understandable by students from all nationalities. Our money back guarantee also stands for accent of the trainer.
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