What is the difference between HAVING and WHERE in an SQL SELECT statement?
EDIT: I have marked Steven's answer as the correct one as it contained the key bit of information on the link:
When GROUP BY is not used, HAVING behaves like a WHERE clause
The situation I had seen the WHERE in did not have GROUP BY and is where my confusion started. Of course, until you know this you can't specify it in the question.
HAVING: is used to check conditions after the aggregation takes place.
WHERE: is used to check conditions before the aggregation takes place.
This code:
select City, CNT=Count(1)
From Address
Where State = 'MA'
Group By City
Gives you a table of all cities in MA and the number of addresses in each city.
This code:
select City, CNT=Count(1)
From Address
Where State = 'MA'
Group By City
Having Count(1)>5
Gives you a table of cities in MA with more than 5 addresses and the number of addresses in each city.
HAVING specifies a search condition for a
group or an aggregate function used in SELECT statement.
Source
Number one difference for me: if HAVING was removed from the SQL language then life would go on more or less as before. Certainly, a minority queries would need to be rewritten using a derived table, CTE, etc but they would arguably be easier to understand and maintain as a result. Maybe vendors' optimizer code would need to be rewritten to account for this, again an opportunity for improvement within the industry.
Now consider for a moment removing WHERE from the language. This time the majority of queries in existence would need to be rewritten without an obvious alternative construct. Coders would have to get creative e.g. inner join to a table known to contain exactly one row (e.g. DUAL in Oracle) using the ON clause to simulate the prior WHERE clause. Such constructions would be contrived; it would be obvious there was something was missing from the language and the situation would be worse as a result.
TL;DR we could lose HAVING tomorrow and things would be no worse, possibly better, but the same cannot be said of WHERE.
From the answers here, it seems that many folk don't realize that a HAVING clause may be used without a GROUP BY clause. In this case, the HAVING clause is applied to the entire table expression and requires that only constants appear in the SELECT clause. Typically the HAVING clause will involve aggregates.
This is more useful than it sounds. For example, consider this query to test whether the name column is unique for all values in T:
SELECT 1 AS result
FROM T
HAVING COUNT( DISTINCT name ) = COUNT( name );
There are only two possible results: if the HAVING clause is true then the result with be a single row containing the value 1, otherwise the result will be the empty set.
The HAVING clause was added to SQL because the WHERE keyword could not be used with aggregate functions.
Check out this w3schools link for more information
Syntax:
SELECT column_name, aggregate_function(column_name)
FROM table_name
WHERE column_name operator value
GROUP BY column_name
HAVING aggregate_function(column_name) operator value
A query such as this:
SELECT column_name, COUNT( column_name ) AS column_name_tally
FROM table_name
WHERE column_name < 3
GROUP
BY column_name
HAVING COUNT( column_name ) >= 3;
...may be rewritten using a derived table (and omitting the HAVING) like this:
SELECT column_name, column_name_tally
FROM (
SELECT column_name, COUNT(column_name) AS column_name_tally
FROM table_name
WHERE column_name < 3
GROUP
BY column_name
) pointless_range_variable_required_here
WHERE column_name_tally >= 3;
The difference between the two is in the relationship to the GROUP BY clause:
WHERE comes before GROUP BY; SQL evaluates the WHERE clause before it groups records.
HAVING comes after GROUP BY; SQL evaluates HAVING after it groups records.
References
SQLite SELECT Statement Syntax/Railroad Diagram
Informix SELECT Statement Syntax/Railroad Diagram
HAVING is used when you are using an aggregate such as GROUP BY.
SELECT edc_country, COUNT(*)
FROM Ed_Centers
GROUP BY edc_country
HAVING COUNT(*) > 1
ORDER BY edc_country;
WHERE is applied as a limitation on the set returned by SQL; it uses SQL's built-in set oeprations and indexes and therefore is the fastest way to filter result sets. Always use WHERE whenever possible.
HAVING is necessary for some aggregate filters. It filters the query AFTER sql has retrieved, assembled, and sorted the results. Therefore, it is much slower than WHERE and should be avoided except in those situations that require it.
SQL Server will let you get away with using HAVING even when WHERE would be much faster. Don't do it.
WHERE clause does not work for aggregate functions
means : you should not use like this
bonus : table name
SELECT name
FROM bonus
GROUP BY name
WHERE sum(salary) > 200
HERE Instead of using WHERE clause you have to use HAVING..
without using GROUP BY clause, HAVING clause just works as WHERE clause
SELECT name
FROM bonus
GROUP BY name
HAVING sum(salary) > 200
Difference b/w WHERE and HAVING clause:
The main difference between WHERE and HAVING clause is, WHERE is used for row operations and HAVING is used for column operations.
Why we need HAVING clause?
As we know, aggregate functions can only be performed on columns, so we can not use aggregate functions in WHERE clause. Therefore, we use aggregate functions in HAVING clause.
One way to think of it is that the having clause is an additional filter to the where clause.
A WHERE clause is used filters records from a result. The filter occurs before any groupings are made. A HAVING clause is used to filter values from a group
In an Aggregate query, (Any query Where an aggregate function is used) Predicates in a where clause are evaluated before the aggregated intermediate result set is generated,
Predicates in a Having clause are applied to the aggregate result set AFTER it has been generated. That's why predicate conditions on aggregate values must be placed in Having clause, not in the Where clause, and why you can use aliases defined in the Select clause in a Having Clause, but not in a Where Clause.
I had a problem and found out another difference between WHERE and HAVING. It does not act the same way on indexed columns.
WHERE my_indexed_row = 123 will show rows and automatically perform a "ORDER ASC" on other indexed rows.
HAVING my_indexed_row = 123 shows everything from the oldest "inserted" row to the newest one, no ordering.
When GROUP BY is not used, the WHERE and HAVING clauses are essentially equivalent.
However, when GROUP BY is used:
The WHERE clause is used to filter records from a result. The
filtering occurs before any groupings are made.
The HAVING clause is used to filter values from a group (i.e., to
check conditions after aggregation into groups has been performed).
Resource from Here
From here.
the SQL standard requires that HAVING
must reference only columns in the
GROUP BY clause or columns used in
aggregate functions
as opposed to the WHERE clause which is applied to database rows
While working on a project, this was also my question. As stated above, the HAVING checks the condition on the query result already found. But WHERE is for checking condition while query runs.
Let me give an example to illustrate this. Suppose you have a database table like this.
usertable{ int userid, date datefield, int dailyincome }
Suppose, the following rows are in table:
1, 2011-05-20, 100
1, 2011-05-21, 50
1, 2011-05-30, 10
2, 2011-05-30, 10
2, 2011-05-20, 20
Now, we want to get the userids and sum(dailyincome) whose sum(dailyincome)>100
If we write:
SELECT userid, sum(dailyincome) FROM usertable WHERE
sum(dailyincome)>100 GROUP BY userid
This will be an error. The correct query would be:
SELECT userid, sum(dailyincome) FROM usertable GROUP BY userid HAVING
sum(dailyincome)>100
WHERE clause is used for comparing values in the base table, whereas the HAVING clause can be used for filtering the results of aggregate functions in the result set of the query
Click here!
When GROUP BY is not used, the WHERE and HAVING clauses are essentially equivalent.
However, when GROUP BY is used:
The WHERE clause is used to filter records from a result. The
filtering occurs before any groupings are made.
The HAVING clause is
used to filter values from a group (i.e., to check conditions after
aggregation into groups has been performed).
I use HAVING for constraining a query based on the results of an aggregate function. E.G. select * in blahblahblah group by SOMETHING having count(SOMETHING)>0
Related
Are the following queries identical, or might I get different results (in any major DB system, e.g. MSSQL, MySQL, Postgres, SQLite):
Doing both in the same query:
SELECT group, some_agg_func(some_value)
FROM my_table
GROUP BY group
ORDER BY some_other_value
vs. ordering in a subquery:
SELECT group, some_agg_func(some_value)
FROM (
SELECT group, some_value
FROM my_table
ORDER BY some_other_value
) as alias
GROUP BY group
Looking at the first sample:
SELECT group, some_agg_func(some_value)
FROM my_table
GROUP BY group
ORDER BY some_other_value
Let's think about what GROUP BY does by looking at this imaginary sample data:
A B
- -
1 1
1 2
Then think about this query:
SELECT A
FROM SampleData
GROUP BY A
ORDER BY B
The GROUP BY clause puts the two rows into a single group. Then we want to order by B... but the two rows in the group have different values for B. Which should it use?
Obviously in this situation it doesn't really matter: there's only one row in the results, so the order is not relevant. But generally, how does the database know what to do?
The database could guess which one you want, or just take the first value, or the last — whatever those mean in a setting where the data is unordered by definition. And in fact this is what MySql will try to do for you: it will try to guess are your meaning. But this response is really inappropriate. You specified an in-exact query; the only correct thing to do is throw an error, which is what most databases will do.
Now let's look at the second sample:
SELECT group, some_agg_func(some_value)
FROM (
SELECT group, some_value
FROM my_table
ORDER BY some_other_value
) as alias
GROUP BY group
Here it is important to remember databases have their roots in relational set theory, and what we think of as "tables" are more formally described as Unordered Relations. Again: the idea of being "unordered" is baked into the very nature of a table at the deepest level.
In this case the inner query can run and create results in the specified order, and then the outer query can use that with GROUP BY to create a new set... but just like tables, query results are unordered relations. Without an ORDER BY clause the final result is also unordered by definition.
Now you might tend to get results in the order you want, but the reality is all bets are off. In fact, the databases that run this query will tend to give you results in the order in which they first encountered each group, which will not tend to match the ORDER BY because the GROUP BY expression is looking at completely different columns. Other databases (Sql Server is in this group) will not even allow the query to run, though I might prefer a warning here.
So now we come to the final section, where we must re-think the question, like this:
How can I use GROUP BY on the one group column, while also ordering by some_other_column not in the group?
The answer is each group can contain multiple rows, and so you must tell the database which row to look at to get the correct (specific) some_other_column value. The typical way to do this is with another aggregate function, which might look like this:
SELECT group, some_agg_func(some_value)
FROM my_table
GROUP BY group
ORDER BY some_other_agg_func(some_other_column)
That code will run without error on pretty much any database.
Just be careful here. On one hand, when people want to do this it's often for the common case where they know every record for some_other_column in each group will have the same value. For example, you might GROUP BY UserID, but ORDER BY Email, where of course every record with the same UserID should have the same Email address. As humans, we have the ability to make that kind of inference. Computers, however, don't handle that kind of thinking as well, and so we help it out with an extra aggregate function like MIN() or MAX().
On the other hand, if you're not careful sometimes the two different aggregate functions don't match up, and you end up showing the value from one row in the group, while using a completely different row from the group for the ORDER BY expression in a way that is not good.
Tables are unordered sets of data. A query result is a table. So if you select from a subquery that contains an ORDER BY clause, that clause means nothing; the data set is unordered by definition. The DBMS is free to ignore the ORDER BY clause. Some DBMS may even issue a warning or error, but I suppose it's more common that the ORDER BY clause just has no effect - at least not guaranteed.
In this query
SELECT group, some_agg_func(some_value)
FROM my_table
GROUP BY group
ORDER BY some_other_value
you try to order your results by some_other_value. If this is meant to be a column, you can't, because that other column is no part of your results. You'll get a syntax error. If some_other_value is a fixed value, then there is nothing ordered, because you'd have the same sort key for every row. But it can be an expression based on your result data (group key and aggreation results) and you can order your result rows by that.
In this query
SELECT group, some_agg_func(some_value)
FROM (
SELECT group, some_value
FROM my_table
ORDER BY some_other_value
) as alias
GROUP BY group
the ORDER BY clause has no effect. You could just as well just select FROM my_table directly:
SELECT group, some_agg_func(some_value)
FROM my_table as alias
GROUP BY group
This gets the results unordered (or at least the order you see is not guaranteed to be thus every time you run that query), because your query doesn't have an ORDER BY clause.
I am still confused by the syntax rules of using GROUP BY. I understand we use GROUP BY when there is some aggregate function. If I have even one aggregate function in a SQL statement, do I need to put all of my selected columns into my GROUP BY statement? I don't have a specific query to ask about but when I try to do joins, I get errors. In particular, when I use a count(*) in a statement and/or a join, I just seem to mess it up.
I use BigQuery at my job. I am regularly floored by strange gaps in knowledge.
Thank you!
This is a little complicated.
First, no aggregation functions are needed in an aggregation query. So this is allowed:
select a
from t
group by a;
This is equivalent, by the way, to:
select distinct a
from t;
If there are aggregation functions, then no group by is needed. So, this is allowed:
select max(a)
from t;
Such an aggregation query -- with no group by -- always returns one row. This is true even if the table is empty or a where clause filters out all the rows. In that case, most aggregation functions return NULL, with the notable exception of count() that returns 0.
Next, if you mix aggregation functions and non-aggregation expressions in the select, then in general you want the non-aggregation, non-constant expressions in the group by. I should note that you can do:
select a, concat(a, 'bcd'), count(*)
from t
group by a;
This should work, but sometimes BigQuery gets confused and will want the expression in the group by.
Finally, the SQL standard supports a query like this:
select t.*, count(*)
from t join
u
using (foo)
group by t.a;
When a is the primary key (or equivalent) in t. However, BigQuery does not have primary keys, so this is not relevant to that database.
I am looking for clarification on this. I am writing two queries below:
We have a table of employee name with columns ID , name , salary
1. Select name from employee
where sum(salary) > 1000 ;
2. Select name from employee
where substring_index(name,' ',1) = 'nishant' ;
Query 1 doesn't work but Query 2 does work. From my development experience, I feel the possible explanation to this is:
The sum() works on a set of values specified in the argument. Here
'salary' column is passed , so it must add up all the values of this
column. But inside where clause, the records are checked one by one ,
like first record 1 is checked for the test and so on. Thus
sum(salary) will not be computed as it needs access to all the column
values and then only it will return a value.
Query 2 works as substring_index() works on a single value and hence here it works on the value supplied to it.
Can you please validate my understanding.
The reason you can't use SUM() in the WHERE clause is the order of evaluation of clauses.
FROM tells you where to read rows from. Right as rows are read from disk to memory, they are checked for the WHERE conditions. (Actually in many cases rows that fail the WHERE clause will not even be read from disk. "Conditions" are formally known as predicates and some predicates are used - by the query execution engine - to decide which rows are read from the base tables. These are called access predicates.) As you can see, the WHERE clause is applied to each row as it is presented to the engine.
On the other hand, aggregation is done only after all rows (that verify all the predicates) have been read.
Think about this: SUM() applies ONLY to the rows that satisfy the WHERE conditions. If you put SUM() in the WHERE clause, you are asking for circular logic. Does a new row pass the WHERE clause? How would I know? If it will pass, then I must include it in the SUM, but if not, it should not be included in the SUM. So how do I even evaluate the SUM condition?
Why can't we use aggregate function in where clause
Aggregate functions work on sets of data. A WHERE clause doesn't have access to entire set, but only to the row that it is currently working on.
You can of course use HAVING clause:
select name from employee
group by name having sum(salary) > 1000;
If you must use WHERE, you can use a subquery:
select name from (
select name, sum(salary) total_salary from employee
group by name
) t where total_salary > 1000;
sum() is an aggregation function. In general, you would expect it to work with group by. Hence, your first query is missing a group by. In a group by query, having is used for filtering after the aggregation:
Select name
from employee
group by name
having sum(salary) > 1000 ;
Using having works since the query goes direct to the rows in that column while where fails since the query keep looping back and forth whenever conditions is not met.
New qith SQL my group by is not working and I am wanting it to pull the most recent POReleases.DateReceived date and group by part number. Here is what I have
SELECT POReleases.PONum, POReleases.PartNo, POReleases.JobNo, POReleases.Qty, POReleases.QtyRejected, POReleases.QtyCanceled, POReleases.DueDate, POReleases.DateReceived, PODet.ProdCode, PODet.Unit, PODet.UnitCost, PODet.QtyOrd, PODet.QtyRec, PODet.QtyReject, PODet.QtyCancel
FROM Waples.dbo.PODet PODet, Waples.dbo.POReleases POReleases
WHERE PODet.PartNo = POReleases.PartNo AND PODet.PONum = POReleases.PONum AND ((POReleases.DateReceived>{ts '2010-01-01 00:00:00'}))
GROUP BY PartNo
For starters, columns specified in the GROUP BY should be present in the select statement too. Here in your case only "PartNo" is used in GROUP BY clause whereas so many columns are used in the SELECT statement.
You can try WITH CTE to achieve this,
WITH CTE AS (
SELECT *, ROW_NUMBER() OVER( PARTITION BY PartNo ORDER BY POReleases.DateReceived DESC) AS PartNoCount
FROM TABLENAME
) SELECT * FROM CTE
When you write an SQL statement, you should think about the logical flow, which might be technically slightly inaccurate due to optimizations, but still, it is a good thing to think about it like this:
without the from clause specifying the source relation, the filter cannot be evaluated, so at least logically, the from is the first thing to evaluate
without the where clause specifying which records should be kept from the source relation, the filtered records cannot be grouped, so, at least logically, the where precedes the group by
without the group by, specifying the groups, you cannot select values from the groups, so, at least logically, group by precedes select
So, the projection (select) is executed on the groups of filtered records, which are groups themselves. Since the groups have an attribute, namely PartNo, it becomes an aggregated column. The other columns, which were reachable before the group by, can no longer be reached in the select. If you want to reach them, you need to group by them as well, or use aggregated functions for them, since if you have a group by, you will be able to select only the aggregated columns, which are either aggregated functions or columns which became aggregated due to their presence in the group by.
Since you did not specify how this query is not working, I will have to assume that you have a syntax error in the selection, due to the fact that you refer to columns which are not aggregated. Also, you might want to use join instead of Descartes multiplication and finally, if you want to filter the groups, not the records of the initial relation (which is the result of a Descartes multiplication in your case), then you might consider using a having clause.
I have a query
SELECT bk_publisher, bk_price FROM books
GROUP BY bk_price, bk_publisher
and
SELECT bk_publisher ,bk_price FROM books
both are returning the same results. Means i have 12 records in my table and both queries returning the 12 records. What is the difference ? Although i am using group by, which is use with aggregate functions. But i want to know is group by making any difference here ?
SELECT bk_publisher, bk_price FROM books
GROUP BY bk_price, bk_publisher
Will result distinct pairs of (publisher, price), even if your table contains duplicated data.
SQL group by helps you group different results by some identical value (using aggregation functions on other values)
In your case it doesn't mean anything, but when you want to aggregate values based on identical field, you use group by.
For example, if you want to get the max price of a publisher:
SELECT bk_publisher, max(bk_price) FROM books
GROUP BY bk_publisher
The GROUP BY statement is used to group the result-set by one or more columns.Group by is used when you have repeating data and you want single record for each entry.
When you use GROUP BY, it will squeeze multiple rows having identical columns listed in GROUP BY as single row in output.
It also means that in general, all other columns mentioned in SELECT list must be wrapped in aggregate functions like sum(), avg(), count(), etc.
Some SQL engines like MySQL permit not using aggregates, but many people consider this a bug.
GROUP BY clause is apparently showing no effect because there is no repeating combination of bk_price, bk_publisher values.