Context: I'm fiddling with SQL in SQLFiddle Postgres 9.6. I'm trying to apply aggregate functions to 2 columns in the outer query that are dependent on the existence of values from a subquery.
I'm having a hard time determining whether the query is correct using the WHERE clause instead of HAVING.The SQL executes but I'm not confident that it's generating the intended results.
Question: Can someone help me understand if this is the correct way to perform the aggregation? And if not how can I modify the query to get the intended results if including HAVING requires GROUPING BY user_id in the outer query which kinda defeats the purpose.
Intended Results: I want to count the number of actions a user takes before progressing to a new action. I only want to count the number of Read Article events if a user (user_id) made it to the next action (View Product) I'm going to use the aggregation to calculate some averages.
Sample output:
Query:
SELECT event_type as action_a,
COUNT(event_type) as action_a_count,
COUNT(DISTINCT user_id) as unique_users
FROM events
WHERE event_type in ('Read Article')
AND user_id in
(
SELECT DISTINCT(user_id) as user_id
FROM events
WHERE event_type in ('View Product')
)
GROUP BY event_type
Your query is good. With WHERE event_type = 'Read Article' you filter events rows. Thus only those rows must be aggregated.
You could use HAVING event_type = 'Read Article' instead, because you are grouping by that column, too. That would mean you would first look up users for all rows and would aggregate over all desired user rows and only then dismiss undesired event_types. This would give the DBMS much more work to do.
Conclusion: Use WHERE to reduce the rows as soon as possible, so the DBMS can work on smaller data sets. This will Speed up your queries.
HAVING and WHERE do appear to have overlap but there are differences, WHERE checks a row for equality whereas HAVING is used to check against aggregate sets, the most basic example would be finding duplicates in a table with a
SELECT column_name, count(*)
FROM table_name
GROUP BY column_name
HAVING count(*) > 1
This query would need to count the rows before filtering, thus uses HAVING. In your case, filtering for equality using WHERE is fine because it only needs to take a single row into account.
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.
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.
In Postgres 9.4, I have a table which contains user's emails sent by different senders. I need to generate the list of the recent distinct senders, I'm using following query:
SELECT DISTINCT ON (tableA.senderName)
tableA.senderName,tableA.received,tableA.someOtherColumn
FROM tableA
WHERE tableA.received BETWEEN timeA AND timeB
ORDER BY tableA.senderName,tableA.received DESC
Since tableA contains all messages of all senders, this query gives me only the recent messages of the distinct senders and works quite well.
Actually, I have the whole query (except the WHERE clause, since timeA and timeB differ everytime) in a view and then I just SELECT * from this view using the particular timeA and timeB in the WHERE clause.
Now consider the following query:
SELECT SUM(ts_rank_cd(tableA.precompTSVector,constantTSQuery)) AS score
FROM tableA
WHERE tableA.precomTSVector ## constantTSQuery
AND tableA.sender = someParticularSender
AND tableA.received BETWEEN timeA AND timeB
which gives the total score of searching some constant TS query against all messages of a particular sender within the given time range.
I would like to incorporate this query (perhaps as a subquery) into my view so that I can also see the "score" for each distinct sender. The obvious problem is that the "score query" is dependent on the actual timeA and timeB in the WHERE clause. These times are not known until the view itself is queried.
EDIT: A different problem is the someOtherColumn being also selected in the first query (and potentially some other columns which I would also like to incorporate in the view) - since the an aggregate function is being used.
Any ideas how to achieve this? Or perhaps some different approach is welcome!
SELECT DISTINCT ON (senderName)
senderName, received -- add more columns as you please
, SUM(ts_rank_cd(precompTSVector,constantTSQuery))
FILTER (WHERE precomTSVector ## constantTSQuery)
OVER (PARTITION BY senderName) AS score
FROM tableA
WHERE received BETWEEN timeA AND timeB
ORDER BY senderName, received DESC;
First you need to get DISTINCT ON right:
Select first row in each GROUP BY group?
DISTINCT ON is applied after aggregate functions, that's why you can combine both in a single SELECT. Consider the sequence of events in a SELECT query:
Best way to get result count before LIMIT was applied
About the new aggregate FILTER clause (requires Postgres 9.4):
How can I simplify this game statistics query?
You need to run this as window function, if you want to add more (unaggregated) columns.
If received can be NULL, you'll want to use DESC NULLS LAST:
PostgreSQL sort by datetime asc, null first?
Depending on data distribution and cardinalities, other query techniques may or may not be faster:
Optimize GROUP BY query to retrieve latest record per user
I'm writing a function in ColdFusion that returns the first couple of records that match the user's input, as well as the total count of matching records in the entire database. The function will be used to feed an autocomplete, so speed/efficiency are its top concerns. For example, if the function receives input "bl", it might return {sampleMatches:["blue", "blade", "blunt"], totalMatches:5000}
I attempted to do this in a single query for speed purposes, and ended up with something that looked like this:
select record, count(*) over ()
from table
where criteria like :criteria
and rownum <= :desiredCount
The problem with this solution is that count(*) over () always returns the value of :desiredCount. I saw a similar question to mine here, but my app will not have permissions to create a temp table. So is there a way to solve my problem in one query? Is there a better way to solve it? Thanks!
I'm writing this on top of my head, so you should definitely have to time this, but I believe that using following CTE
only requires you to write the conditions once
only returns the amount of records you specify
has the correct total count added to each record
and is evaluated only once
SQL Statement
WITH q AS (
SELECT record
FROM table
WHERE criteria like :criteria
)
SELECT q1.*, q2.*
FROM q q1
CROSS JOIN (
SELECT COUNT(*) FROM q
) q2
WHERE rownum <= :desiredCount
A nested subquery should return the results you want
select record, cnt
from (select record, count(*) over () cnt
from table
where criteria like :criteria)
where rownum <= :desiredCount
This will, however, force Oracle to completely process the query in order to generate the accurate count. This seems unlikely to be what you want if you're trying to do an autocomplete particularly when Oracle may decide that it would be more efficient to do a table scan on table if :criteria is just b since that predicate isn't selective enough. Are you really sure that you need a completely accurate count of the number of results? Are you sure that your table is small enough/ your system is fast enough/ your predicates are selective enough for that to be a requirement that you could realistically meet? Would it be possible to return a less-expensive (but less-accurate) estimate of the number of rows? Or to limit the count to something smaller (say, 100) and have the UI display something like "and 100+ more results"?
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