Chapter 4 - Aggregation
“Teradata climbed Aggregate Mountain and delivered a better way to Sum It.”
- Tera-Tom Coffing
Quiz – You calculate the Answer Set in your own Mind
Aggregation_Table |
|
Employee_No |
Salary |
423400 |
100000.00 |
423401 |
100000.00 |
423402 |
NULL |
SELECT AVG(Salary) as "AVG"
,Count(Salary) as SalCnt
,Count(*) as RowCnt
FROM Aggregation_Table ;
What would the result set be from the above query? The next slide shows answers!
Answer – You calculate the Answer Set in your own Mind
SELECT AVG(Salary) as "AVG"
,Count(Salary) as SalCnt
,Count(*) as RowCnt
FROM Aggregation_Table ;
Here are your answers!
The 3 Rules of Aggregation
1) Aggregates Ignore Null Values.
2) Aggregates WANT to come back in one row.
3) You CAN’T mix Aggregates with normal columns
unless you use a GROUP BY.
There are Five Aggregates
There are FIVE AGGREGATES which are the following:
MIN – The Minimum Value.
MAX – The Maximum Value.
AVG – The Average of the Column Values.
SUM – The Sum Total of the Column Values.
COUNT – The Count of the Column Values.
SELECT MIN (Salary)
,MAX (Salary)
,SUM (Salary)
,AVG (Salary)
,Count(*)
FROM Employee_Table ;
“Don’t count the days, make the days count.”
– Mohammed Ali
The five aggregates are listed above. Mohammed Ali was way off in his quote. He meant to say, "Don’t you count the days, make the data count for you".
Quiz – How many rows come back?
How many rows will the above query produce in the result set?
Answer – How many rows come back?
How many rows will the above query produce in the result set? The answer is one.
Troubleshooting Aggregates
If you have a normal column (non aggregate) in your query, you must have a corresponding GROUP BY statement.
GROUP BY when Aggregates and Normal Columns Mix
If you have a normal column (non aggregate) in your query, you must have a corresponding GROUP BY statement.
GROUP BY Delivers one row per Group
Group By Dept_No command allow for the Aggregates to be calculated per Dept_No. The data has also been sorted with the ORDER BY statement.
GROUP BY Dept_No or GROUP BY 1 the same thing
Both queries above produce the same result. The GROUP BY allows you to either name the column or use the number in the SELECT list just like the ORDER BY.
Limiting Rows and Improving Performance with WHERE
Will Dept_No 300 be calculated? Of course you know it will . . . NOT!.
WHERE Clause in Aggregation limits unneeded Calculations
The system eliminates reading any other Dept_No’s other than 200 and 400. This means that only Dept_No’s of 200 and 400 will come off the disk to be calculated.
Keyword HAVING tests Aggregates after they are Totaled
The HAVING Clause only works on Aggregate Totals. The WHERE filters rows to be excluded from calculation, but the HAVING filters the Aggregate totals after the calculations, thus eliminating certain Aggregate totals.
Aggregates Return Null on Empty Tables
When an aggregate is run against an empty table it returns a null value.
Keyword HAVING is like an Extra WHERE Clause for Totals
The HAVING Clause only works on Aggregate Totals, and in the above example, only Count(*) > 2 can return.
Getting the Average Values Per Column
SELECT 'Product_ID' AS "Column Name"
,COUNT(*) / COUNT(DISTINCT(Product_ID)) AS "Avg Rows"
FROM Sales_Table ;
Column Name |
Avg Rows |
Product_ID |
7 |
SELECT 'Sale_Date' AS "Column Name"
,COUNT(*) / COUNT(DISTINCT(Sale_Date)) AS "Avg Rows"
FROM Sales_Table ;
Column Name |
Avg Rows |
Sale_Date |
3 |
The first query retrieved the average rows per value for the column Product_ID. The example below did the same, but for the column Sale_Date.
Average Values Per Column For all Columns in a Table
SELECT 'Product_ID' AS "Column Name"
,COUNT(*) / COUNT(DISTINCT(Product_ID))
AS "Avg Rows"
,'Sale_Date' AS "Column Name2"
,COUNT(*) / COUNT(DISTINCT(Sale_Date))
AS "Avg Rows2"
FROM Sales_Table ;
The query above retrieved the average rows per value for both columns in the table.
Three types of Advanced Grouping
There are three advanced grouping options:
GROUP BY Grouping Sets
GROUP BY Rollup
GROUP BY Cube
SELECT Product_ID
,EXTRACT (MONTH FROM Sale_Date) AS MTH
,EXTRACT (YEAR FROM Sale_Date) AS YR
,SUM(Daily_Sales) AS SUM_Daily_Sales
FROM Sales_Table
GROUP BY GROUPING SETS (Product_ID, MTH, YR)
ORDER BY Product_ID Desc, MTH Desc, YR Desc;
Be prepared to be amazed. There are three advanced options listed above for grouping data. Each is more powerful that the one before. The next pages will give great examples.
GROUP BY Grouping Sets
GROUP BY GROUPING Sets above will show you what your Daily_Sales were for each Product_ID, for each month, and for each year.
GROUP BY Rollup
GROUP BY ROLLUP displays what the Daily_Sales were for each Product_ID, for each distinct month, for each month per year and for each year, plus a grand total.
GROUP BY Rollup Result Set
This is the full result set from the previous GROUP BY ROLLUP query.
GROUP BY Cube
GROUP BY ROLLUP displays Daily_Sales were for each Product_ID, for each distinct month, for each month per year and for each year, plus a grand total.
GROUP BY CUBE Result Set
GROUP BY CUBE Result Set
In Nexus, just right click on the Sales_Table and choose Super Join Builder. Then select all the columns. Then choose the Analytics tab on the top right. Choose Grouping Sets in the Analytics Tab. Then drag the Product_ID column to the Product. Drag the Sale_Date to the Date Column. Then drag the Daily_Sales column to the Sum. Then Check Box all the Group By Functions on the right of the screen. Then hit Execute or Send SQL to Nexus. Done!