Teradata SQL Alchemy

TERADATA SQL

By

B M Kumar

Teradata COE - Alchemy

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Agenda

• Basic RDBMS Concepts and Teradata SQL

• Teradata Extensions ( HELP & SHOW)

• Data Types and Conversions

• Logical & Conditional Expressions, Attribute & String Functions

• Data Definitions

• Data Manipulations

• Views and Macros

• Joins

• Sub queries

• Set Operators

• Aggregations, Totals and Subtotals

• Rankings, Samplings, and Built-In Functions

• BTEQ ( Basic Teradata Query)


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Basic RDBMS Concepts and Teradata SQL


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Teradata Extensions


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Data Types and Conversions


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Logical & Conditional ExpressionsAnd Output Attributes


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Logical and Conditional Expressions


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Output Attributes


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Definition


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Data Manipulation


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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Views and Macros


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JOINS


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Joins


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Sub Queries


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Sub Queries


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Sub Queries


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Sub Queries


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Sub Queries


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Sub Queries


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Set Operators


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Set Operators


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Set Operators


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Set Operators


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Set Operators


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Set Operators


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Set Operators


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Aggregations, Totals and Subtotals


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Rankings, Samplings, and Built-In Functions


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Rankings


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Rankings


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Rankings


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Rankings


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Rankings


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Rankings


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Rankings with Partition BYSELECT storeid ,prodid

,sales,RANK( ) OVER (PARTITION BY storeid, prodid

ORDER BY sales DESC) AS "Ranking"FROM salestblQUALIFY Ranking <= 3;storeid prodid sales Ranking----------- ------ ----------- -----------1001 A 100000.00 11001 C 60000.00 11001 D 35000.00 11001 F 150000.00 11002 A 40000.00 11002 C 35000.00 11002 D 25000.00 11003 A 30000.00 11003 B 65000.00 11003 C 20000.00 11003 D 50000.00 1 Things To Notice•An additional PARTITION BY clause is added. •In this case, the scope is sales by product within store. •Each product exists only once in each store. •Thus, each row gets a rank of 1. each store.


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TOP N Overview

The TOP N function provides the ability to produce:

•The top (or bottom) N rows of results based on specified criteria.

•The top (or bottom) N percentage of rows based on specified criteria.

•These results either with or without ties (more than one row has identical criteria

values).

•Sample rows arbitrarily without regard to rankings or order.

This improvement has been achieved by implementing the following new

syntax to the SQL lexicon:

TOP {decimal | integer} [PERCENT] [WITH TIES]

The following meaning is associated with these options:

•TOP 10 – Return the top ten rows according to criteria

•TOP 15 PERCENT – Return the top 15% of rows according to criteria

•TOP 10 WITH TIES – If more that one row has the same criteria value, return all

•TOP 15 PERCENT WITH TIES – If more than one row has the same criteria

value, return all


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TOP N• Show all department budgets ordered by budget amount descending. To

answer this query, the TOP N feature is not needed.

SELECT department_number , budget_amount

FROM department ORDER BY 2 DESC;

Note: Null sorts following the valid budget amounts.

department_number budget_amount

----------------- -------------

401 982300.00

403 932000.00

301 465600.00

100 400000.00

402 308000.00

501 308000.00

201 293800.00

302 226000.00

600 ?


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TOP NTOP N With and Without TIES

SELECT TOP 5

department_number

, budget_amount

FROM department

ORDER BY 2 DESC;


----------------- -------------

401 982300.00

403 932000.00

301 465600.00

100 400000.00

501 308000.00

Things to notice:

ORDER BY defines the sequencing of the result set.

It therefore defines the ranking criteria.

To get the TOP highest amounts, you must use ORDER with DESC.

TOP N where N is an integer up to 18 digits in length.

SELECT TOP 5 WITH TIES

department_number

, budget_amount

FROM department

ORDER BY 2 DESC;


----------------- -------------

401 982300.00

403 932000.00

301 465600.00

100 400000.00

501 308000.00

402 308000.00

Things to notice:

Even though TOP 5 is specified, six rows are returned.

Because there is a tie for the fifth position, both rows are returned.

This only occurs when WITH TIES is specified.

WITH TIES returns multiple tied rows when there is a tie for the 'last' position.

It will return all rows containing the 'tied' value, but it will only count it as one row.

Tied rows which are not in the last position, are each counted separately toward the N total.


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SAMPLEThe SAMPLE function allows a user to specify a sample of results returned by a specified SELECT statement. The sample

can be represented as either a percentage of the returned rows or as an absolute number.

Sampling is useful for many purposes, including generating samples of production data for purposes of testing out new

applications.

Stratified sampling:

the ability to generate different sized samples from different groupings of the data.

Consider the distribution of departments within the employee table.

SELECT department_number

,COUNT (*)

FROM employee

GROUP BY 1

ORDER BY 1;

• department_number Count(*)----------------- -----------

100 1

201 2

301 3

302 1

401 7

402 2

403 6

501 4


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SAMPLECreate five groupings of employees based on the range of department numbers.

SELECT CASE WHEN department_number BETWEEN 100 AND 199 THEN 'GROUP 1'

WHEN department_number BETWEEN 200 AND 299 THEN 'GROUP 2'




ELSE NULL END AS Group_Name ,COUNT (*) FROM employee

GROUP BY 1 ORDER BY 1;

Group_Name Count(*)

---------- -----------

GROUP 1 1

GROUP 2 2

GROUP 3 4

GROUP 4 15

GROUP 5 4

SELECT last_name (CHAR(10)) ,department_number (FORMAT '999') AS Deptno , SAMPLEID FROM employee SAMPLE

WHEN department_number BETWEEN 100 AND 199 THEN .25





END ORDER BY 2;

last_name Deptno SampleId

---------- ------ -----------

Short 201 2 (.25 * 2 = .50 ROUNDING TO 1)

Stein 301 3 (.25 * 4 = 1)

Phillips 401 4 (.25 * 15 = 3.75 ROUNDING TO 4)

Rogers 401 4

Villegas 403 4

Hopkins 403 4

Ratzlaff 501 5 (.25 * 4 = 1)

Things to notice:

•SAMPLEID reflects the sample pool into which each row falls.

•In some cases, the fractional amount is less than a full row, thus no rows are returned for that sampling.

•No rows are returned for SAMPLEID 1 because 25% of one row rounds to zero.


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Built-In Functions


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String Functions


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String Functions


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String Functions


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String Functions


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String Functions


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String Functions


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String Functions


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String Functions


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BTEQ (Basic Teradata Query)


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BTEQ


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BTEQ


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BTEQ


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BTEQ


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BTEQ


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Questions

Documents

Teradata SQL Alchemy