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Kognitio Architecture and SQL
Duration
3 Days
Course
ARKG-100
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Kognitio Architecture and SQL course is designed to provide students with a deeper knowledge and understanding of the Kognitio Architecture and Kognitio SQL and how to write it. Students will learn the Kognitio Architecture and Kognitio SQL starting at the most basic level and going to the most advanced level with many examples.Objectives
Upon completion of the Kognitio Architecture and SQL course, students will be able to:
- Identify and apply basic SQL functions
- Understand the WHERE clause
- Contrast Distinct vs. Group by
- Recognize and apply functions, such as:
- Aggregation, Join, Date, OLAP, View, Sub-query and Statistical Aggregate
- Recognize and produce Temporary Tables
- Define and distinguish Strings
- Interrogate the Data
- Set Operators
- Demonstrate knowledge of the Data Manipulation Language (DML)
Audience
- Anyone who has a desire to learn Kognitio SQL from beginners to an advanced audience.
Prerequisites
- None
Topics
- What is Parallel Processing?
- The Basics of a Single Computer
- Data in Memory is fast as Lightning
- Parallel Processing Of Data
- Kognitio is an In-Memory System
- Kognitio has Three Table Distribution Options
- Kognitio has Linear Scalability
- Kognitio has Three Table Distribution Options
- Round Robin Technique
- Random Distribution
- A Table that is distributed by Hash
- Tables that join are excellent candidates for Hashed Tables
- Hash Distribution
- A Table that is distributed by Hash by Multiple Columns
- The Reasons for a Multi-Column HASHED Distribution Key
- Creating a Table that is replicated across all Nodes
- Replicated Distribution
- The Concept is all about the Joins
- Kognitio allows you to create Images
- Creating a Table Image to place a Table in Memory
- Partitioning an Image
- Partitioning an Image View
- CREATE OR REPLACE TABLE IMAGE
- DEFRAG TABLE IMAGE
- Nexus is Available on the Cloud
- Nexus Queries Every Major System
- How to Use Nexus
- Why is Nexus Special?
- Visualization and Automatic SQL
- Cross-System Joins
- The Amazing Hub System
- Save Answer Sets as Tables
- Automated Data Movement
- Nexus makes the Servers Talk Directly
- The Garden of Analysis
- The Garden of Analysis:
- Grouping Sets Tab
- Grouping Sets Answer Sets
- Join Tab
- Charts/Graphs Tab
- Dynamic Charts Tab
- Dashboard Tab
- Getting to the Super Join Builder
- The Super Join Builder is the First Entry in the Menu
- The Super Join Builder Shows Tables Visually
- Using the Add Join Button
- What to Do When No Tables are Joinable?
- Drag a Joinable Object into the Super Join Builder
- You Will See the Add Custom Join Window
- Defining the Join Columns
- Your Tables Will Appear Together
- Select the Columns You Want on the Report
- Check out the SQL Tab to See the SQL that has been built
- SQL Tab
- Hit Execute to get the Report inside the Super Join Builder
- The Report is delivered inside the Super Join Builder
- Let's Join Two Tables Again
- The Tabs of the Super Join Builder Philosophy:
- One Query
- Objects Tab
- Columns Tab
- Sorting Tab
- Joins Tab
- SQL Tab
- Metadata Tab
- Analytics Tab
- Getting a Simple CSUM in the Analytics Tab – OLAP
- Getting a Simple CSUM – The SQL Automatically Generated
- The Answer Set of the CSUM
- Getting all of the OLAP functions in the Analytics Tab
- A Five Table Join Using the Menu
- The First Table is placed in the Super Join Builder
- Using the Add Join Cascading Menu
- All Five Tables Are In the Super Join Builder
- A Five Table Join Two Steps (Cube)
- Choose Cube with Columns from the Left Top of the Table
- All Tables are Cubed (Joined Together Instantly)
- Choose Cube and then Choose Your Columns
- How to join Kognitio, Oracle and SQL Server Tables
- The Kognitio Table is now in the Super Join Builder
- Drag the Joining Oracle Table to the Super Join Builder
- Defining the Join Columns
- Choose the Columns You Want on Your Report
- Defining the Join Columns
- All Three Tables are now in the Super Join Builder
- Change the Hub and Run the Join on Oracle and SQL Server
- Simply Amazing - Change the Hub to the Garden of Analysis
- Have the Answer Set Saved Automatically to Any System
- Introduction
- Setting the Default Schema
- SELECT * (All Columns) in a Table
- Fully Qualifying a Database, Schema and Table
- ORDER BY Defaults to Ascending
- NULL Values sort Last in Ascending Mode (Default)
- NULL Values sort First in Descending Mode (DESC)
- Major Sort vs. Minor Sorts
- Multiple Sort Keys using Names vs. Numbers
- Sorts are Alphabetical, NOT Logical
- Using A CASE Statement to Sort Logically
- How to ALIAS a Column Name
- A Missing Comma can by Mistake become an Alias
- Comments using Double Dashes are Single Line Comments
- Comments for Multi-Lines as Double Dashes per Line
- A Great Technique for Comments to Look for SQL Errors
- The WHERE Clause limits Returning Rows
- Double Quoted Aliases are for Reserved Words and Spaces
- Character Data needs Single Quotes in the WHERE Clause
- Character Data needs Single Quotes, but Numbers Don’t
- Comparisons against a Null Value
- Use IS NULL or IS NOT NULL when dealing with NULLs
- Using Greater Than or Equal To (>=)
- AND in the WHERE Clause
- Troubleshooting AND
- OR in the WHERE Clause
- Using Different Columns in an AND Statement
- What is the Order of Precedence?
- Using Parentheses to change the Order of Precedence
- Using an IN List in place of OR
- The IN List is an Excellent Technique
- IN List vs. OR brings the same Results
- The IN List Can Use Character Data
- Using a NOT IN List
- Null Values in a NOT IN List Bring Back No Rows
- A Technique for Handling Nulls with a NOT IN List
- BETWEEN is Inclusive
- NOT BETWEEN is Also Inclusive
- LIKE uses Wildcards Percent ‘%’ and Underscore ‘_’
- LIKE command Underscore is Wildcard for one Character
- The ilike Command
- LIKE Command Works Differently on Char Vs Varchar
- Troubleshooting LIKE Command on Character Data
- Introducing the TRIM Command
- Introducing the RTRIM Command
- Numbers are Right Justified and Character Data is Left
- An example of Data with Left and Right Justification
- A Visual of CHARACTER Data vs. VARCHAR Data
- Escape Character in the LIKE Command changes Wildcards
- Escape Characters Turn off Wildcards in the LIKE Command
- Using ILIKE with an AND/OR Clause to Find Multiple Letters
- Keywords
- The Distinct Command
- Distinct vs. GROUP BY
- TOP Command
- Just Place the TOP n in front of any Query
- The 3 Rules of Aggregation
- There are Five Aggregates
- Troubleshooting Aggregates
- GROUP BY when Aggregates and Normal Columns Mix
- GROUP BY delivers one row per Group
- GROUP BY Dept_No or GROUP BY 1 the same thing
- Limiting Rows and Improving Performance with WHERE
- WHERE Clause in Aggregation limits unneeded Calculations
- Keyword HAVING tests Aggregates after they are totaled
- Keyword HAVING is like an Extra WHERE Clause for Totals
- Keyword HAVING tests Aggregates after they are totaled
- Getting the Average Values per Column
- A Two-Table Join Using Traditional Syntax
- A two-table join using Non-ANSI Syntax with Table Alias
- You Can Fully Qualify All Columns
- A two-table join using ANSI Syntax
- Both Queries have the same Results and Performance
- LEFT OUTER JOIN
- RIGHT OUTER JOIN
- FULL OUTER JOIN
- Which Tables are the Left and which Tables are Right?
- INNER JOIN with Additional AND Clause
- ANSI INNER JOIN with Additional AND and WHERE Clause
- OUTER JOIN with Additional WHERE and AND Clause
- Evaluation Order for Outer Queries
- The DREADED Product Join
- The DREADED Product Join Results
- The Horrifying Cartesian Product Join
- The ANSI Cartesian Join will ERROR
- The CROSS JOIN
- The Self Join
- How would you join these two tables?
- An Associative Table is a Bridge that Joins Two Tables
- The 5-Table Join – Logical Insurance Model
- Current_Date, Current_Time, Current_Timestamp
- Current_Timestamp with Milliseconds
- Current_Timestamp with Microseconds
- Current_Timestamp and SYSDATE are Synonyms
- The Now Function
- Adding Days, Weeks and Months to a Date
- Add or Subtract Days from a date
- The EXTRACT Command
- EXTRACT from DATES and TIME
- EXTRACT of the Month on Aggregate Queries
- Deriving a Timestamp from a Date and Time
- Formatting Dates and Dollar Amounts
- TO_DATE
- TO_TIME
- TO_TIMESTAMP
- Using CASE and Extract to reformat Dates
- Using CAST and SUBSTRING to reformat Dates
- Using the DAYOFWEEK and the DECODE Function
- Intervals
- More Interval Examples
- TO_CHAR Details
- TO_CHAR, TO_DATE, TO_TIME and TO_TIMESTAMP
- An IN List Ignores Duplicates
- The Subquery
- The Three Steps of How a Basic Subquery Works
- These are Equivalent Queries
- Should you use a Subquery of a Join?
- The Basics of a Correlated Subquery
- The Top Query always runs first in a Correlated Subquery
- Correlated Subquery Example vs. a Join with a Derived Table
- How the Double Parameter Subquery Works
- More on how the Double Parameter Subquery Works
- How to handle a NOT IN with Potential NULL Values
- IN is equivalent to =ANY
- Using a Correlated Exists
- How a Correlated Exists matches up
- The Correlated NOT Exists
- The Row_Number Command
- Using a Derived Table and Row_Number
- Finding the First and Last Occurrence
- RANK Defaults to Ascending Order
- Getting RANK to Sort in DESC Order
- RANK OVER and PARTITION BY
- RANK and DENSE RANK
- CSUM
- The ANSI CSUM – Getting a Sequential Number
- Troubleshooting the ANSI OLAP on a GROUP BY
- Reset with a PARTITION BY Statement
- PARTITION BY only Resets a Single OLAP not ALL of them
- Moving SUM
- ANSI Moving Window is Current Row and Preceding n Rows
- How ANSI Moving SUM Handles the Sort
- Moving SUM every 3-rows Vs a Continuous Average
- PARTITION BY Resets an ANSI OLAP
- Moving Average
- The Moving Window is Current Row and Preceding
- Moving Average every 3-rows Vs a Continuous Average
- PARTITION BY Resets an ANSI OLAP
- Moving Difference
- PERCENT_RANK OVER
- COUNT OVER for a Sequential Number
- Troubleshooting COUNT OVER
- The MAX OVER Command
- MAX OVER with PARTITION BY Reset
- Troubleshooting MAX OVER
- The MIN OVER Command
- Troubleshooting MIN OVER
- Finding a Value of a Column in the Next Row with MIN
- Ordered Analytics OVER
- CURRENT ROW AND UNBOUNDED FOLLOWING
- Different Windowing Options
- The CSUM for Each Product_Id and the Next Start Date
- Ntile
- FIRST_VALUE
- LAST_VALUE
- LEAD
- LAG
- SUM (SUM(n))
- There are Two Types of Temporary Tables
- CREATING A Derived Table
- Naming the Derived Table
- Aliasing the Column Names in the Derived Table
- CREATING a Derived Table using the WITH Command
- The Same Derived Query shown Three Different Ways
- Most Derived Tables Are Used To Join To Other Tables
- The Three Components of a Derived Table
- Visualize This Derived Table
- A Derived Table and CAST Statements
- A Derived example Using the WITH Syntax
- Clever Tricks on Aliasing Columns in a Derived Table
- An example of Two Derived Tables in a Single Query
- MULTIPLE Derived Tables using the WITH Command
- Finding the First and Last Occurrence
- Three Steps to Creating a Temporary Table
- Two Versions of Creating a Temporary Table
- ON COMMIT DELETE ROWS is the Kognitio Default
- Important Temporary Table Information
- How to Use the ON COMMIT DELETE ROWS Option
- Create Table AS
- Creating a Temporary Table Using a CTAS that Joins Multiple Tables
- Create Table LIKE
- The LENGTH Command
- UPPER and LOWER Commands
- Using the LOWER Command
- Using the UPPER Command
- Non-Letters are Unaffected by UPPER and LOWER
- The CHARACTERS and TRIM Commands
- LENGTH, CHARACTER_LENGTH and OCTET_LENGTH
- Concatenation
- The SUBSTRING Command
- SUBSTRING and SUBSTR are equal, but use different syntax
- The POSITION Command finds a Letters Position
- Concatenation
- Concatenation and SUBSTRING
- Four Concatenations Together
- Troubleshooting Concatenation
- The NULLIF Command
- The COALESCE Command
- CAST (Convert and Store)
- Using an ELSE in the Case Statement
- Using an ELSE as a Safety Net
- Rules for a Valued Case Statement
- Rules for a Searched Case Statement
- Valued Case Vs. A Searched Case
- The CASE Challenge
- Combining Searched Case and Valued Case
- A Trick for getting a Horizontal Case
- Put a CASE in the ORDER BY
- Nested Case
- Rules of Set Operators
- INTERSECT Explained Logically
- UNION Explained Logically
- UNION ALL Explained Logically
- EXCEPT/MINUS Explained Logically
- An Equal Amount of Columns in both SELECT List
- Columns in the SELECT list should be from the same Domain
- The Top Query handles all Aliases
- The Bottom Query does the ORDER BY
- UNION Vs UNION ALL
- Using UNION ALL and Literals
- A Great example of how EXCEPT works
- USING Multiple SET Operators in a Single Request
- Changing the Order of Precedence with Parentheses
- Using UNION ALL for speed in Merging Data Sets
- The Fundamentals of Views
- Creating a Simple View to Restrict Sensitive Columns/ Rows
- Basic Rules for Views
- Exception to the ORDER BY Rule inside a View
- Views sometimes CREATED for Formatting
- Creating a View to Join Tables Together
- Another Way to Alias Columns in a View CREATE
- The Standard Way Most Aliasing is done
- What Happens When Both Aliasing Options Are Present
- Resolving Aliasing Problems in a View CREATE
- Answer to Resolving Aliasing Problems in a View CREATE
- Aggregates on View Aggregates
- Kognitio Has Three Table Distribution Options
- A Table that is distributed via a Round Robin Technique
- Round Robin Technique is the Default
- A Table that is distributed by Hash
- Tables that join are excellent candidates for Hashed Tables
- A Table that is distributed by Hash by Multiple Columns
- The Reasons for a Multi-Column HASHED Distribution Key
- Creating a Table that is replicated across all Nodes
- How to create tables with Referential Integrity
- Creating a Table Image to place a Table in Memory
- CREATE OR REPLACE TABLE IMAGE
- DEFRAG TABLE IMAGE
- Create Table AS WITH DATA or WITH NO DATA
- Another Version of Create Table AS
- CREATE Table FOR and FROM
- Create Table LIKE
- String Data Types
- Numeric Data Types
- Date, Time and Timestamp Data Types
- INSERT Syntax # 1-3
- INSERT/SELECT Command
- Two UPDATE Examples
- Subquery UPDATE Command Syntax
- Join UPDATE Command Syntax
- DELETE and TRUNCATE Examples
- To DELETE or to TRUNCATE
- Subquery and Join DELETE Command Syntax
- How to See an EXPLAIN Plan
- Seeing an EXPLAIN Plan with Nexus
- The Eight Rules to Reading an EXPLAIN Plan
- Interpreting Keywords in an EXPLAIN Plan
- Interpreting an EXPLAIN Plan
- A Single Segment Retrieve – The Fastest Query
- EXPLAIN With an ORDER BY Statement
- EXPLAIN ANALYZE
- EXPLAIN With a Range Query on a Table Partitioned By Day
- EXPLAIN That Uses a B-Tree Index Scan
- EXPLAIN That Uses a Bitmap Scan
- EXPLAIN With a Simple Subquery
- EXPLAIN With a Columnar Query
- EXPLAIN With a Clustered Index
- The Most Important Concept for Joins is the Distribution Key
- EXPLAIN With Join that has to Move Data
- EXPLAIN With Join that has to Move Data
- Changing the Join Query Changes the EXPLAIN Plan
- Analyzing the Tables Structures for a 3-Table Join
- An EXPLAIN For a 3-Table Join
- Explain of a Derived Table vs. a Correlated Subquery
- Explain of the Correlated Subquery
- Explain of the Derived Table
- The Stats Table
- Numeric Manipulation Functions
- Ceiling Gets the Smallest Integer Not Smaller Than X
- Floor Finds the Largest Integer Not Greater Than X
- The Round Function and Precision
- The STDDEV_POP Function
- The STDDEV_SAMP Function
- The VAR_POP Function
- The VAR_SAMP Function
- The CORR Function
- The COVAR_POP Function
- The COVAR_SAMP Function
- The REGR_INTERCEPT Function
- Another REGR_INTERCEPT Example so you can compare
- The REGR_SLOPE Function
- The REGR_AVGX Function
- The REGR_AVGY Function
- The REGR_COUNT Function
- The REGR_R2 Function
- The REGR_SXX Function
- The REGR_SXY Function
- The REGR_SYY Function
- Using GROUP BY
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