Q1: After using the Group By function, why does it only output one row of each group at most? Does this mean that having is supposed to filter the group rather than filter the records in each group?
Q2: I want to find the records in each group whose ages are greater than the average age of that group. I tried the following, but it returns nothing. How should I fix this?
SELECT *, avg(age) FROM Mytable Group By country Having age > avg(age)
Thanks!!!!
You can calculate the average age for each country in a subquery and join that to your table for filtering:
SELECT mt.*, MtAvg.AvgAge
FROM Mytable mt
inner join
(
select mtavgs.country
, avg(mtavgs.age) as AvgAge
from Mytable mtavgs
group by mtavgs.country
) MTAvg
on mtavg.country=mt.country
and mt.Age > mtavg.AvgAge
GROUP BY returns always 1 row per unique combination of values in the GROUP BY columns listed (provided that they are not removed by a HAVING clause). The subquery in our example (alias: MTAvg) will calculate a single row per country. We will use its results for filtering the main table rows by applying the condition in the INNER JOIN clause; we will also report that average by including the calculated average age.
GROUP BY is a keyword that is called an aggregate function. Check this out here for further reading SQL Group By tutorial
What it does is it lumps all the results together into one row. In your example it would lump all the results with the same country together.
Not quite sure what exactly your query needs to be to solve your exact problem. I would however look into what are called window functions in SQL. I believe what you first need to do is write a window function to find the average age in each group. Then you can write a query to return the results you need
Depending on your dbms type and version, you may be able to use a "window function" that will calculate the average per country and with this approach it makes the calculation available on every row. Once that data is present as a "derived table" you can simply use a where clause to filter for the ages that are greater then the calculated average per country.
SELECT mt.*
FROM (
SELECT *
, avg(age) OVER(PARTITION BY country) AS AvgAge
FROM Mytable
) mt
WHERE mt.Age > mt.AvgAge
Related
I understand why the first query needs a GROUP BY, as it doesn't know which date to apply the sum to, but I don't understand why this is the case with the second query. The value that ultimately is the max amount is already contained in the table - it is not calculated like SUM is. thank you
-- First Query
select
sum(OrderSales),OrderDates
From Orders
-- Second Query
select
max(FilmOscarWins),FilmName
From tblFilm
It is not the SUM and MAX that require the GROUP BY, it is the unaggregated column.
If you just write this, you will get a single row, for the maximum value of the FilmOscarWins column across the whole table:
select
max(FilmOscarWins)
From
tblFilm
If the most Oscars any film won was 12, that one row will say 12. But there could be multiple films, all of which won 12 Oscars, so if we ask for the FilmName alongside that 12, there is no single answer.
By adding the Group By, we fundamentally change the query: instead of returning one number for the whole table, it will return one row for each group - which in this case, means one row for each film.
If you do want to get a list of all those films which had the maximum 12 Oscars, you have to do something more complicated, such as using a sub-query to first find that single number (12) and then find all the rows matching it:
select
FilmOscarWins,
FilmName
From
tblFilm
Where FilmOscarWins = (
select
max(FilmOscarWins)
From
tblFilm
)
If you want the film with the most Oscar wins, then use select top:
select top (1) f.*
From tblFilm f
order by FilmOscarWins desc;
In an aggregation query, the select columns need to be consistent with the group by columns -- the unaggregated columns in the select must match the group by.
I have observed that Count function can be used without the usage of aggregate function Group by. Like for example:
Select Count(*) from Employee
It would surely return the count of all the rows without the usage of aggregate function. Then where do we really need the usage of group by?
Omitting the GROUP BY implies that the entire table is one group. Sometimes you want there to be multiple groups. Consider the following example:
SELECT month, SUM(sales) AS total_sales
FROM all_sales
GROUP BY month;
This query gives you a month-by-month breakdown of sales. If you omitted month and the GROUP BY clause, you would only receive the total sales of all time which may not have the granularity you require.
You can also group by multiple columns, giving finer detail still:
SELECT state, city, COUNT(*) AS population
FROM all_people
GROUP BY state, city;
Additionally, using a GROUP BY allows us to use HAVING clauses. Which lets us filter groups. Using the above example, we can filter the result to cities with over 1,000,000 people:
SELECT state, city, COUNT(*) AS population
FROM all_people
GROUP BY state, city
HAVING COUNT(*) > 1000000;
The group by clause is used to break up aggregate results to groups of unique values. E.g., let's say you don't want to know how many employees you have, but how many by each first name (e.g., two Gregs, one Adam and three Scotts):
SELECT first_name, COUNT(*)
FROM employee
GROUP BY first_name
I am trying to pull information from two columns titled clientstate and clientrevenue in my table. I want clientstate to show up as the state, and have only distinct names in it, and under client revenue I want the average revenue per state, and that will only show up if there are at least two clients from that state. I am very new at this, so what I have is pretty iffy:
SELECT clientstate, clientrevenue
FROM client
GROUP BY clientrevenue
HAVING COUNT (*) >=2;
Where am I going wrong here?
SELECT clientstate AS [State]
, AVG(clientrevenue) AS [Average Revenue]
FROM client
GROUP BY clientstate
Grouping by ClientRevenue will try to group similar values and that doesn't have a logical sense.
First, in order to get distinct states, clientstate column needs to be used in the GROUP BY statement.
Thus, the code would be :
SELECT clientstate, AVG(clientrevenue)
FROM Source_Table
GROUP BY clientstate --this would get you distinct states
Now, considering the 2 clients per state, it's rather a condition than a HAVING statement. HAVING statement limits your query results according to the aggregate function you are using. For instance, in the code aforementioned, the aggregate function is AVG(clientrevenue). So, we can only use it in HAVING. we can not add count(*) unless it was used in SELECT.
So, you need to add it as a condition like
SELECT clientstate, AVG(clientrevenue)
FROM Source_Table A
WHERE (SELECT count(DISTINCT client_ID) FROM Source_Table B
WHERE A.clientstate = B.clientstate) >= 2 --Condition
GROUP BY clientstate --this would get you distinct states
I'm struggling to understand what this query is doing:
SELECT branch_name, count(distinct customer_name)
FROM depositor, account
WHERE depositor.account_number = account.account_number
GROUP BY branch_name
What's the need of GROUP BY?
You must use GROUP BY in order to use an aggregate function like COUNT in this manner (using an aggregate function to aggregate data corresponding to one or more values within the table).
The query essentially selects distinct branch_names using that column as the grouping column, then within the group it counts the distinct customer_names.
You couldn't use COUNT to get the number of distinct customer_names per branch_name without the GROUP BY clause (at least not with a simple query specification - you can use other means, joins, subqueries etc...).
It's giving you the total distinct customers for each branch; GROUP BY is used for grouping COUNT function.
It could be written also as:
SELECT branch_name, count(distinct customer_name)
FROM depositor INNER JOIN account
ON depositor.account_number = account.account_number
GROUP BY branch_name
Let's take a step away from SQL for a moment at look at the relational trainging language Tutorial D.
Because the two relations (tables) are joined on the common attribute (column) name account_number, we can use a natural join:
depositor JOIN account
(Because the result is a relation, which by definition has only distinct tuples (rows), we don't need a DISTINCT keyword.)
Now we just need to aggregate using SUMMARIZE..BY:
SUMMARIZE (depositor JOIN account)
BY { branch_name }
ADD ( COUNT ( customer_name ) AS customer_tally )
Back in SQLland, the GROUP BY branch_name is doing the same as SUMMARIZE..BY { branch_name }. Because SQL has a very rigid structure, the branch_name column must be repeated in the SELECT clause.
If you want to COUNT something (see SELECT-Part of the statement), you have to use GROUP BY in order to tell the query what to aggregate. The GROUP BY statement is used in conjunction with the aggregate functions to group the result-set by one or more columns.
Neglecting it will lead to SQL errors in most RDBMS, or senseless results in others.
Useful link:
http://www.w3schools.com/sql/sql_groupby.asp
I am running the following queries against a database:
CREATE TEMPORARY TABLE med_error_third_party_tmp
SELECT `med_error_category`.description AS category, `med_error_third_party_category`.error_count AS error_count
FROM
`med_error_category` INNER JOIN `med_error_third_party_category` ON med_error_category.`id` = `med_error_third_party_category`.`category`
WHERE
year = 2003
GROUP BY `med_error_category`.id;
The only problem is that when I create the temporary table and do a select * on it then it returns multiple rows, but the query above only returns one row. It seems to always return a single row unless I specify a GROUP BY, but then it returns a percentage of 1.0 like it should with a GROUP BY.
SELECT category,
error_count/SUM(error_count) AS percentage
FROM med_error_third_party_tmp;
Here are the server specs:
Server version: 5.0.77
Protocol version: 10
Server: Localhost via UNIX socket
Does anybody see a problem with this that is causing the problem?
Standard SQL requires you to specify a GROUP BY clause if any column is not wrapped in an aggregate function (IE: MIN, MAX, COUNT, SUM, AVG, etc), but MySQL supports "hidden columns in the GROUP BY" -- which is why:
SELECT category,
error_count/SUM(error_count) AS percentage
FROM med_error_third_party_tmp;
...runs without error. The problem with the functionality is that because there's no GROUP BY, the SUM is the SUM of the error_count column for the entire table. But the other column values are completely arbitrary - they can't be relied upon.
This:
SELECT category,
error_count/(SELECT SUM(error_count)
FROM med_error_third_party_tmp) AS percentage
FROM med_error_third_party_tmp;
...will give you a percentage on a per row basis -- category values will be duplicated because there's no grouping.
This:
SELECT category,
SUM(error_count)/x.total AS percentage
FROM med_error_third_party_tmp
JOIN (SELECT SUM(error_count) AS total
FROM med_error_third_party_tmp) x
GROUP BY category
...will gives you a percentage per category of the sum of the categories error_count values vs the sum of the error_count values for the entire table.
another way to do it - without the temp table as seperate item...
select category, error_count/sum(error_count) "Percentage"
from (SELECT mec.description category
, metpc.error_count
FROM med_error_category mec
, med_error_third_party_category metpc
WHERE mec.id = metpc.category
AND year = 2003
GROUP BY mec.id
);
i think you will notice that the percentage is unchanging over the categories. This is probably not what you want - you probably want to group the errors by category as well.