• Database Training

    databaseInterSource offers live instructor-led courses on all important database programming technologies, including Crystal Reports, Microsoft Access, MySQL, Oracle, SQL, SQL Server, SSAS, SSIS, SSRS and Xcelsius.

    These live classes are offered both on client sites, at our Geneva training center, and via a Web interface.

  • About Database

    A database is a collection of data stored and maintained for one or more uses. Most modern databases are managed by a Database Management System (DBMS), a set of computer programs that controls the creation, maintenance, and the use of the database with computer as a platform or of an organization and its end users. It allows organizations to place control of organization-wide database development in the hands of database administrators (DBAs) and other specialists.

    The proper integration of databases can dramatically increase the functionality of all types of applications, whether or not Web-enabled.

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  • Course Details Database

    Classes are offered at client sites, at our Geneva training center, and via a live web conference. For detailed course outlines and scheduled classes, please see below.

    To book training, navigate to the course you need, then:

    • For scheduled online classes, register from the choices indicated.
    • If you need an alternative dates, time or location, or if you want a live classroom course, click on “request an offer for this course,” to complete the form.

    InterSource clients are active globally. Live web courses run during Eastern Standard Time (New York) business hours and are priced in US dollars.

    We also run live web conference classes during European business hours, which can be invoiced in local currencies. To discuss your requirements please contact us on +41 (22) 958 0114.

Amazon Redshift Architecture Training

Course duration

  • 1 day

Course Benefits

  • Learn to gain a deeper knowledge and understanding of the Amazon Redshift Architecture and how to write it.

Course Outline

  1. What is Columnar?
    1. What is Parallel Processing?
    2. The Basics of a Single Computer
    3. Data in Memory is Fast as Lightning
    4. Parallel Processing of Data
    5. A Table has Columns and Rows
    6. Each Parallel Process Organizes the Rows inside a Data Block
    7. Moving Data Blocks is Like Checking in Luggage
    8. Facts That Are Disturbing
    9. Why Columnar?
    10. Row Based Blocks vs. Columnar Based Blocks
    11. As Row-Based Tables Get Bigger, the Blocks Split
    12. Data Blocks Are Processed One at a Time Per Unit
    13. Columnar Tables Store Each Column in Separate Blocks
    14. Visualize the Data – Rows vs. Columns
    15. Row Based Blocks Can Waste Memory Space and Resources
    16. The Architecture of Redshift
    17. Redshift has Linear Scalability
    18. Distribution Styles
    19. Distribution Key Where the Data is Unique
    20. Another Way to Create A Table
    21. Distribution Key Where the Data is Non-Unique
    22. Distribution Key is ALL
    23. Even Distribution Key
    24. Matching Distribution Keys for Co-Location of Joins
    25. Big Table / Small Table Joins
    26. Fact and Dimension Table Distribution Key Designs
    27. Improving Performance By Defining a Sort Key
    28. Sort Keys Help Group By, Order By and Window Functions
    29. Each Block Comes With Metadata
    30. How Data Might Look On A Slice
    31. Creating Three Tables with Different Sort Key Strategies
    32. A Table with a Distribution Key and a Single-Sortkey
    33. A Normal Sort Key Example
    34. Creating a Table with an Interleaved Sort Key
    35. Interleaved Vs. a Normal Sort Key
    36. The ANALYZE Command Collects Statistics
    37. Redshift Automatically ANALYZES Some Create Statements
    38. What is a Vacuum?
    39. When is a Good Time to Vacuum?
    40. The VACUUM Command Grooms a Table
    41. Database Limits
    42. Creating a Database
    43. Creating a User
    44. Dropping a User
    45. Inserting into a Table
    46. Renaming a Table or a Column
    47. Adding and Dropping a Column to a Table
  2. Best Practices for Table Design
    1. Converting Table Structures to Redshift
    2. Converting Table Structures to Redshift Finale
    3. Best Practices for Designing Tables
    4. Choose the Best Sort Key
    5. Each Block Comes with Metadata
    6. Creating a Sort Key
    7. Sort Keys Help Group By, Order By and Window Functions
    8. Choose a Great Distribution Key
    9. Distribution Key Where the Data is Unique
    10. Matching Distribution Keys for Co-Location of Joins
    11. Big Table / Small Table Joins
    12. Define Primary Key and Foreign Key Constraints
    13. Primary Key and Foreign Key Examples
    14. Use the Smallest Column Size When Creating Tables
    15. Use Date/Time Data Types for Date Columns
    16. Specify Redundant Predicates on the Sort Column
    17. Setting the Statement_Timeout to Abort Long Queries
  3. System Tables
    1. Redshift Has System Tables that Log to Disk (Prefix STL)
    2. Redshift Has System Tables that are Virtual (STV Prefix)
    3. Redshift Has System Catalog Tables Visible to Users
    4. Amazon Redshift System Tables
    5. Trouble Shooting Catalog Table pg_table_def
    6. Seeing the System Tables in your Nexus Tree
    7. Catalog Table pg_table_def
    8. Checking Tables for Skew (Poor Distribution)
    9. Checking All Statements That Used the Analyze Command
    10. Checking Tables for Skew (Poor Distribution)
    11. Checking for Details About the Last Copy Operation
    12. Checking When a Table Has Last Been Analyzed
    13. Checking for Column Information on a Table
    14. System tables for troubleshooting data loads
    15. Determining Whether a Query is Writing to Disk
    16. Showing Alert events
    17. Showing the Last Queries Run on the System
    18. Showing Queries that Last More than One Second
    19. Listing Queries From Longest to Shortest for a Particular Day
    20. Reporting Queries with High CPU Time
    21. Reporting Queries of Nested Loops Returning Many Rows
    22. Finding Queries Aborted Because of a Monitoring Rule
    23. The Number of MB blocks used by each column in a Table
    24. Checking if a Table is Distributed Over All Slices
    25. List Schemas and Tables in a Database from the PG Catalog
    26. A View to See the State of the system Queues for Workloads
    27. SELECT From the WLM_QUEUE_STATE_VW View
    28. WLM_QUEUE_STATE_VW View Definitions
    29. A View Showing the State of Current Queries and Queues
    30. WLM_QUERY_STATE_VW View Definitions
  4. Compression
    1. Compression Types
    2. Byte Dictionary Compression
    3. Delta Encoding
    4. LZO Encoding
    5. Mostly Encoding
    6. Runlength encoding
    7. Text255 and Text 32k Encodings
    9. Copy
  5. Temporary Tables
    1. Create Table Syntax
    2. Basic Temporary Table Examples
    3. More Advanced Temporary Table Examples
    4. Advanced Temporary Table Examples
    5. Table Limits and CTAS
    6. Performing a Deep Copy
    7. Deep Copy Using the Original DDL
    8. Deep Copy Using a CTAS
    9. Deep Copy Using a Create Table LIKE
    10. Deep Copy by Creating a Temp Table and Truncating Original
    11. CREATING A Derived Table
    12. The Three Components of a Derived Table
    13. Naming the Derived Table
    14. Aliasing the Column Names in The Derived Table
    15. Visualize This Derived Table
    16. Most Derived Tables are Used To Join To Other Tables
    17. Multiple Ways to Alias the Columns in a Derived Table
    18. Our Join Example with a Different Column Aliasing Style
    19. Column Aliasing Can Default For Normal Columns
    20. CREATING A Derived Table using the WITH Command
    21. Our Join Example With The WITH Syntax
    22. WITH Statement That Uses a SELECT *
    23. A WITH Clause That Produces Two Tables
    24. The Same Derived Query shown Three Different Ways
    25. Clever Tricks on Aliasing Columns in a Derived Table
    26. A Derived Table lives only for the lifetime of a single query
    27. An Example of Two Derived Tables in a Single Query
    28. Connecting To Redshift Via Nexus
  6. Explain
    1. Three Ways to Run an EXPLAIN
    2. EXPLAIN – Steps, Segments and Streams
    3. EXPLAIN Terms For Scans and Joins
    4. EXPLAIN Terms For Aggregation and Sorts
    5. EXPLAIN Terms For Set Operators and Miscellaneous Terms
    6. EXPLAIN Terms For Set Operators and Miscellaneous Terms
    7. EXPLAIN Example and the Cost
    8. EXPLAIN Example and the Rows
    9. EXPLAIN Example and the Width
    10. Simple EXPLAIN Example and the Costs
    11. Look for These Keywords to Track Data Movement
    12. EXPLAIN Join Example Using DS_BCAST_INNER
    13. EXPLAIN Join Example Using DS_DIST_NONE
    14. EXPLAIN Showing DS_DIST_NONE Visually
    15. EXPLAIN With a Warning
    16. EXPLAIN For Ordered Analytics Such as CSUM
    17. EXPLAIN For Scalar Aggregate Functions
    18. EXPLAIN For Hash Aggregate Functions
    19. EXPLAIN Using Limit, Merge and Sort
    20. EXPLAIN Using a WHERE Clause Filter
    21. EXPLAIN Using the Keyword Distinct
    22. EXPLAIN for Subqueries
  7. User Defined Functions
    1. Creating a User Defined Scalar Function
    2. Function Syntax
    3. Creating a Simple Function
    4. Creating a Function That Shows the Sunday Date of the Week
    5. Create a Flight_Table that Holds Longitude and Latitude
    6. A Function Example for Measuring Distance in Miles
    7. A Function Example for Measuring Distance
    8. Create a Flight_Table that Holds Longitude and Latitude
    9. A Function Example for Comparing Two Numbers
    10. A Function Example Using Multiple Tables
    11. SQL that Utilizes Two User Defined Functions (UDFs)
    12. Function Volatility
    13. Amazon Redshift Vs. Python Data Types
    14. Privileges
  8. Workload Management
    1. Create the WLM_QUEUE_STATE_VW View
    2. SELECT From the WLM_QUEUE_STATE_VW View
    3. WLM_QUEUE_STATE_VW View Definitions
    4. Create the WLM_QUERY_STATE_VW View
    5. WLM_QUERY_STATE_VW View Definitions
    6. Open Up Two Sessions in your Nexus
    7. SELECT From our WLM_QUERY_STATE_VW View
    8. Run a Long-Running Query in Tab
    9. In Tab Run These Two Queries
    10. After Setup of Four Queues
    11. How to use the SET command to Place a Query in a Queue
    12. Checking which Queue the Query is Executing In?
    13. How to Reset the Query Group
    14. Creating and Altering a Group
    15. Admin User Can Still SET to a Different Queue if they Want
    16. Overriding the Concurrency Level
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

Since its founding in 1995, InterSource has been providing high quality and highly customized training solutions to clients worldwide. With over 500 course titles constantly updated and numerous course customization and creation possibilities, we have the capability to meet your I.T. training needs.
Instructor-led courses are offered via a live Web connection, at client sites throughout Europe, and at our Geneva Training Center.