Related
I have this data and i need to combine all lines in a row in field fullname and get a single value from 3 equals from order field. How can i do that without using a group by?
Existing data
id order fullname
1 32 Jack Stinky Potato
2 32 Kevin Enormous Cucumber
3 32 Jerald Sad Onion
Expecting result
32 Jack Stinky Potato, Kevin Enormous Cucumber, Jerald Sad Onion
using group by would write
select order, wm_concat(fullname) from EmployeeCards
group by order
or this, but it doesn't rational.
select wm_concat(unique order), wm_concat(fullname) from EmployeeCards
or just select (unique order), wm_concat(fullname) from EmployeeCards
don't working. Which aggregate function shoul i use to get a single value? Thanks
Use LISTAGG:
SELECT
"order",
LISTAGG(fullname, ',') WITHIN GROUP (ORDER BY id) AS fullnames
FROM EmployeeCards
GROUP BY
"order";
Demo
Also, please avoid naming your database objects (e.g. tables, columns, etc.) using reserved SQL keywords, such as ORDER.
I have a table that has many columns around 50 columns that have datetime data that represent steps user takes when he/she do a procedure
SELECT UserID, Intro_Req_DateTime, Intro_Onset_DateTime, Intro_Comp_DateTime, Info_Req_DateTime, Info_Onset_DateTime, Info_Comp_DateTime,
Start_Req_DateTime, Start_Onset_DateTime, Start_Comp_DateTime,
Check_Req_DateTime, Check_Onset_DateTime, Check_Comp_DateTime,
Validate_Req_DateTime, Validate_Onset_DateTime, Validate_Comp_DateTime,
....
FROM MyTable
I want to find the Step the user did after certain datetime
example I want to find user ABC what the first step he did after 2 May 2019 17:25:36
I cannot use case to check this will take ages to code
is there an easier way to do that?
P.S. Thanks for everyone suggested redesigning the database.. not all databases can be redesigned, this database is for one of the big systems we have and it is been used for more than 20 years. redesigning is out of the equation.
You can use CROSS APPLY to unpivot the values. The syntax for UNPIVOT is rather cumbersome.
The actual query text should be rather manageable. No need for complicated CASE statements. Yes, you will have to explicitly list all 50 column names in the query text, you can't avoid that, but it will be only once.
SELECT TOP(1)
A.StepName
,A.dt
FROM
MyTable
CROSS APPLY
(
VALUES
('Intro_Req', Intro_Req_DateTime)
,('Intro_Onset', Intro_Onset_DateTime)
,('Intro_Comp', Intro_Comp_DateTime)
.........
) AS A (StepName, dt)
WHERE
MyTable.UserID = 'ABC'
AND A.dt > '2019-05-02T17:25:36'
ORDER BY dt DESC;
See also How to unpivot columns using CROSS APPLY in SQL Server 2012
The best way is to design your table with your action type and datetime that action was done. Then you can use a simple where clause to find what you want. The table should be like the table below:
ID ActionType ActionDatetime
----------- ----------- -------------------
1492 1 2019-05-13 10:10:10
1494 2 2019-05-13 11:10:10
1496 3 2019-05-13 12:10:10
1498 4 2019-05-13 13:10:10
1500 5 2019-05-13 14:10:10
But in your current solution, you should use UNPIVOT to get what you want. You can find more information in this LINK.
How do I rank salespeople by # customers grouped by department (with ties included)?
For example, given this table, I want to create the Rank column on the right. How should I do this in Access?
SalesPerson Dept #Customers Rank
Bill DeptA 20 1
Ted DeptA 30 2
Jane DeptA 40 3
Bill DeptB 50 1
Mary DeptB 60 2
I already know how to do a simple ranking with this SQL code. But I don't know how to rework this to accept grouping.
Select Count(*) from [Tbl] Where [#Customers] < [Tblx]![#Customers] )+1
Also, there's plenty of answers for this using SQL Server's Rank() function, but I need to do this in Access. Suggestions, please?
SELECT *, (select count(*) from tbl as tbl2 where
tbl.customers > tbl2.customers and tbl.dept = tbl2.dept) + 1 as rank from tbl
Just add the dept field to the subquery...
Great solution with subquery! Except for huge recordsets, the subquery solution gets very slow. Its better(quicker) to use a Self JOIN, look at the folowing solution: self join
SELECT tbl1.SalesPerson , count(*) AS Rank
FROM tbl AS tbl1 INNER JOIN tbl AS tbl2 ON tbl1.DEPT = tbl2.DEPT
AND tbl1.#Customers < tbl2.#Customers
GROUP BY tbl1.SalesPerson
I know this is an old thread. But since I spent a great deal of time on a very similar problem and was greatly helped by the former answers given here, I would like to share what I have found to be a MUCH faster way. (Beware, it is more complicated.)
First make another table called "Individualizer". This will have one field containing a list of numbers 1 through the-highest-rank-that-you-need.
Next create a VBA module and paste this into it:
'Global Declarations Section.
Option Explicit
Global Cntr
'*************************************************************
' Function: Qcntr()
'
' Purpose: This function will increment and return a dynamic
' counter. This function should be called from a query.
'*************************************************************
Function QCntr(x) As Long
Cntr = Cntr + 1
QCntr = Cntr
End Function
'**************************************************************
' Function: SetToZero()
'
' Purpose: This function will reset the global Cntr to 0. This
' function should be called each time before running a query
' containing the Qcntr() function.
'**************************************************************
Function SetToZero()
Cntr = 0
End Function
Save it as Module1.
Next, create Query1 like this:
SELECT Table1.Dept, Count(Table1.Salesperson) AS CountOfSalesperson
FROM Table1
GROUP BY Table1.Dept;
Create a MakeTable query called Query2 like this:
SELECT SetToZero() AS Expr1, QCntr([ID]) AS Rank, Query1.Dept,
Query1.CountOfSalesperson, Individualizer.ID
INTO Qtable1
FROM Query1
INNER JOIN Individualizer
ON Query1.CountOfSalesperson >= Individualizer.ID;
Create another MakeTable query called Query3 like this:
SELECT SetToZero() AS Expr1, QCntr([Identifier]) AS Rank,
[Salesperson] & [Dept] & [#Customers] AS Identifier, Table1.Salesperson,
Table1.Dept, Table1.[#Customers]
INTO Qtable2
FROM Table1;
If you have another field already that uniquely identifies every row you wouldn't need to create an Identifier field.
Run Query2 and Query3 to create the tables.
Create a fourth query called Query4 like this:
SELECT Qtable2.Salesperson, Qtable2.Dept, Qtable2.[#Customers], Qtable1.ID AS Rank
FROM Qtable1
INNER JOIN Qtable2 ON Qtable1.Rank = Qtable2.Rank;
Query4 returns the result you are looking for.
Practically, you would want to write a VBA function to run Query2 and Query3 and then call that function from a button placed in a convenient location.
Now I know this sounds ridiculously complicated for the example you gave. But in real life, I am sure your table is more complicated than this. Hopefully my examples can be applied to your actual situation. In my database with over 12,000 records this method is by FAR the fastest (as in: 6 seconds with 12,000 records compared to over 1 minute with 262 records ranked with the subquery method).
The real secret for me was the MakeTable query because this ranking method is useless unless you immediately output the results to a table. But, this does limit the situations that it can be applied to.
P.S. I forgot to mention that in my database I was not pulling results directly from a table. The records had already gone through a string of queries and multiple calculations before they needed to be ranked. This probably contributed greatly to the huge difference in speed between the two methods in my situation. If you are pulling records directly from a table, you might not notice nearly as big an improvement.
You need to do some math. I typically take advantage of the combination of a counter field and an "offset" field. You're aiming for a table which looks like this (#Customers isn't necessary, but will give you a visual that you're doing it properly):
SalesPerson Dept #Customers Ctr Offset
Bill DeptA 20 1 1
Ted DeptA 30 2 1
Jane DeptA 40 3 1
Bill DeptB 50 4 4
Mary DeptB 60 5 4
So, to give rank, you'd do [Ctr]-[Offset]+1 AS Rank
build a table with SalesPerson, Dept, Ctr, and Offset
insert into that table, ordered by Dept and #Customers (so that they're all sorted properly)
Update Offset to be the MIN(Ctr), grouping on Dept
Perform your math calculation to determine Rank
Clear out the table so you're ready to use it again next time.
To add to this and any other related Access Ranking or Rank Tie Breaker how-tos for other versions of Access, ranking should not be performed on crosstab queries if your FROM clause happens to NOT contain a table but a query that is either a crosstab query or a query that contains within it elsewhere a crosstab query.
The code referenced above where a SELECT statement within a SELECT statment is used (sub query),
"SELECT *, (select count(*) from tbl as tbl2 where tbl.customers > tbl2.customers and tbl.dept = tbl2.dept) + 1 as rank from tbl"
will not work and will always fail expressing a error on portion of the code where "tbl.customers > tbl2.customers" cannot be found.
In my situation on a past project, I was referencing a query instead of a table and within that query I had referenced a crosstab query thus failing and producing an error. I was able to resolve this by creating a table from the crosstab query first, and when I referenced the newly created table in the FROM clause, it started working for me.
So in final, normally you can reference a query or table in the FROM clause of the SELECT statement as what was shared previously above to do ranking, but be carefull as to if you are referencing a query instead of a table, that query must Not be a crosstab query or reference another query that is a crosstab query.
Hope this helps anyone else that may have had problems looking for a possible reason if you happen to reference the statements above and you are not referencing a table in your FROM clause within your own project. Also, performing subqueries on aliases with crosstab queries in Access probably isn't good idea or best practice either so stray away from that if/when possible.
If you found this useful, and wish that Access would allow the use of a scrolling mouse in a passthru query editor, give me a like please.
I normally pick tips and ideas from here and sometimes end up building amazing things from it!
Today, (well let’s say for the past one week), I have been tinkering with Ranking of data in Access and to the best of my ability, I did not anticipate what I was going to do something so complex as to take me a week to figure it out! I picked titbits from two main sites:
https://usefulgyaan.wordpress.com/2013/04/23/ranking-in-ms-access/ (seen that clever ‘>=’ part, and the self joins? Amazing… it helped me to build my solution from just one query, as opposed to the complex method suggested above by asonoftheMighty (not discrediting you… just didn’t want to try it for now; may be when I get to large data I might want to try that as well…)
Right here, from Paul Abott above ( ‘and tbl.dept = tbl2.dept’)… I was lost after ranking because I was placing AND YearID = 1, etc, then the ranking would end up happening only for sub-sets, you guessed right, when YearID = 1! But I had a lot of different scenarios…
Well, I gave that story partly to thank the contributors mentioned, because what I did is to me one of the most complex of the ranking that I think can help you in almost any situation, and since I benefited from others, I would like to share here what I hope may benefit others as well.
Forgive me that I am not able to post my table structures here, it is a lot of related tables. I will only post the query, so if you need to you may develop your tables to end up with that kind of query. But here is my scenario:
You have students in a school. They go through class 1 to 4, can either be in stream A or B, or none when the class is too small. They each take 4 exams (this part is not important now), so you get the total score for my case. That’s it. Huh??
Ok. Lets rank them this way:
We want to know the ranking of
• all students who ever passed through this school (best ever student)
• all students in a particular academic year (student of the year)
• students of a particular class (but remember a student will have passed through all classes, so basically his/her rank in each of those classes for the different years) this is the usual ranking that appears in report cards
• students in their streams (above comment applies)
• I would also like to know the population against which we ranked this student in each category
… all in one table/query. Now you get the point?
(I normally like to do as much of my 'programming' in the database/queries to give me visuals and to reduce the amount of code I will later have to right. I actually won't use this query in my application :), but it let's me know where and how to send my parameters to the query it came from, and what results to expect in my rdlc)
Don't you worry, here it is:
SELECT Sc.StudentID, Sc.StudentName, Sc.Mark,
(SELECT COUNT(Sch.Mark) FROM [StudentScoreRankTermQ] AS Sch WHERE (Sch.Mark >= Sc.Mark)) AS SchoolRank,
(SELECT Count(s.StudentID) FROM StudentScoreRankTermQ AS s) As SchoolTotal,
(SELECT COUNT(Yr.Mark) FROM [StudentScoreRankTermQ] AS Yr WHERE (Yr.Mark >= Sc.Mark) AND (Yr.YearID = Sc.YearID) ) AS YearRank,
(SELECT COUNT(StudentID) FROM StudentScoreRankTermQ AS Yt WHERE (Yt.YearID = Sc.YearID) ) AS YearTotal,
(SELECT COUNT(Cl.Mark) FROM [StudentScoreRankTermQ] AS Cl WHERE (Cl.Mark >= Sc.Mark) AND (Cl.YearID = Sc.YearID) AND (Cl.TermID = Sc.TermID) AND (Cl.ClassID=Sc.ClassID)) AS ClassRank,
(SELECT COUNT(StudentID) FROM StudentScoreRankTermQ AS C WHERE (C.YearID = Sc.YearID) AND (C.TermID = Sc.TermID) AND (C.ClassID = Sc.ClassID) ) AS ClassTotal,
(SELECT COUNT(Str.Mark) FROM [StudentScoreRankTermQ] AS Str WHERE (Str.Mark >= Sc.Mark) AND (Str.YearID = Sc.YearID) AND (Str.TermID = Sc.TermID) AND (Str.ClassID=Sc.ClassID) AND (Str.StreamID = Sc.StreamID) ) AS StreamRank,
(SELECT COUNT(StudentID) FROM StudentScoreRankTermQ AS St WHERE (St.YearID = Sc.YearID) AND (St.TermID = Sc.TermID) AND (St.ClassID = Sc.ClassID) AND (St.StreamID = Sc.StreamID) ) AS StreamTotal,
Sc.CalendarYear, Sc.Term, Sc.ClassNo, Sc.Stream, Sc.StreamID, Sc.YearID, Sc.TermID, Sc.ClassID
FROM StudentScoreRankTermQ AS Sc
ORDER BY Sc.Mark DESC;
You should get something like this:
+-----------+-------------+------+------------+-------------+----------+-----------+-----------+------------+------------+-------------+------+------+-------+--------+
| StudentID | StudentName | Mark | SchoolRank | SchoolTotal | YearRank | YearTotal | ClassRank | ClassTotal | StreamRank | StreamTotal | Year | Term | Class | Stream |
+-----------+-------------+------+------------+-------------+----------+-----------+-----------+------------+------------+-------------+------+------+-------+--------+
| 1 | Jane | 200 | 1 | 20 | 2 | 12 | 1 | 9 | 1 | 5 | 2017 | I | 2 | A |
| 2 | Tom | 199 | 2 | 20 | 1 | 12 | 3 | 9 | 1 | 4 | 2016 | I | 1 | B |
+-----------+-------------+------+------------+-------------+----------+-----------+-----------+------------+------------+-------------+------+------+-------+--------+
Use the separators | to reconstruct the result table
Just an idea about the tables, each student will be related to a class. Each class relates to years. Each stream relates to a class. Each term relates to a year. Each exam relates to a term and student and a class and a year; a student can be in class 1A in 2016 and moves on to class 2b in 2017, etc…
Let me also add that this a beta result, I have not tested it well enough and I do not yet have an opportunity to create a lot of data to see the performance. My first glance at it told me that it is good. So if you find reasons or alerts you want to point my way, please do so in comments so I may keep learning!
Basically, I'm dealing with a horribly set up table that I'd love to rebuild, but am not sure I can at this point.
So, the table is of addresses, and it has a ton of similar entries for the same address. But there are sometimes slight variations in the address (i.e., a room # is tacked on IN THE SAME COLUMN, ugh).
Like this:
id | place_name | place_street
1 | Place Name One | 1001 Mercury Blvd
2 | Place Name Two | 2388 Jupiter Street
3 | Place Name One | 1001 Mercury Blvd, Suite A
4 | Place Name, One | 1001 Mercury Boulevard
5 | Place Nam Two | 2388 Jupiter Street, Rm 101
What I would like to do is in SQL (this is mssql), if possible, is do a query that is like:
SELECT DISTINCT place_name, place_street where [the first 4 letters of the place_name are the same] && [the first 4 characters of the place_street are the same].
to, I guess at this point, get:
Plac | 1001
Plac | 2388
Basically, then I can figure out what are the main addresses I have to break out into another table to normalize this, because the rest are just slight derivations.
I hope that makes sense.
I've done some research and I see people using regular expressions in SQL, but a lot of them seem to be using C scripts or something. Do I have to write regex functions and save them into the SQL Server before executing any regular expressions?
Any direction on whether I can just write them in SQL or if I have another step to go through would be great.
Or on how to approach this problem.
Thanks in advance!
Use the SQL function LEFT:
SELECT DISTINCT LEFT(place_name, 4)
I don't think you need regular expressions to get the results you describe. You just want to trim the columns and group by the results, which will effectively give you distinct values.
SELECT left(place_name, 4), left(place_street, 4), count(*)
FROM AddressTable
GROUP BY left(place_name, 4), left(place_street, 4)
The count(*) column isn't necessary, but it gives you some idea of which values might have the most (possibly) duplicate address rows in common.
I would recommend you look into Fuzzy Search Operations in SQL Server. You can match the results much better than what you are trying to do. Just google sql server fuzzy search.
Assuming at least SQL Server 2005 for the CTE:
;with cteCommonAddresses as (
select left(place_name, 4) as LeftName, left(place_street,4) as LeftStreet
from Address
group by left(place_name, 4), left(place_street,4)
having count(*) > 1
)
select a.id, a.place_name, a.place_street
from cteCommonAddresses c
inner join Address a
on c.LeftName = left(a.place_name,4)
and c.LeftStreet = left(a.place_street,4)
order by a.place_name, a.place_street, a.id
I learned something simple about SQL the other day:
SELECT c FROM myTbl GROUP BY C
Has the same result as:
SELECT DISTINCT C FROM myTbl
What I am curious of, is there anything different in the way an SQL engine processes the command, or are they truly the same thing?
I personally prefer the distinct syntax, but I am sure it's more out of habit than anything else.
EDIT: This is not a question about aggregates. The use of GROUP BY with aggregate functions is understood.
MusiGenesis' response is functionally the correct one with regard to your question as stated; the SQL Server is smart enough to realize that if you are using "Group By" and not using any aggregate functions, then what you actually mean is "Distinct" - and therefore it generates an execution plan as if you'd simply used "Distinct."
However, I think it's important to note Hank's response as well - cavalier treatment of "Group By" and "Distinct" could lead to some pernicious gotchas down the line if you're not careful. It's not entirely correct to say that this is "not a question about aggregates" because you're asking about the functional difference between two SQL query keywords, one of which is meant to be used with aggregates and one of which is not.
A hammer can work to drive in a screw sometimes, but if you've got a screwdriver handy, why bother?
(for the purposes of this analogy, Hammer : Screwdriver :: GroupBy : Distinct and screw => get list of unique values in a table column)
GROUP BY lets you use aggregate functions, like AVG, MAX, MIN, SUM, and COUNT.
On the other hand DISTINCT just removes duplicates.
For example, if you have a bunch of purchase records, and you want to know how much was spent by each department, you might do something like:
SELECT department, SUM(amount) FROM purchases GROUP BY department
This will give you one row per department, containing the department name and the sum of all of the amount values in all rows for that department.
What's the difference from a mere duplicate removal functionality point of view
Apart from the fact that unlike DISTINCT, GROUP BY allows for aggregating data per group (which has been mentioned by many other answers), the most important difference in my opinion is the fact that the two operations "happen" at two very different steps in the logical order of operations that are executed in a SELECT statement.
Here are the most important operations:
FROM (including JOIN, APPLY, etc.)
WHERE
GROUP BY (can remove duplicates)
Aggregations
HAVING
Window functions
SELECT
DISTINCT (can remove duplicates)
UNION, INTERSECT, EXCEPT (can remove duplicates)
ORDER BY
OFFSET
LIMIT
As you can see, the logical order of each operation influences what can be done with it and how it influences subsequent operations. In particular, the fact that the GROUP BY operation "happens before" the SELECT operation (the projection) means that:
It doesn't depend on the projection (which can be an advantage)
It cannot use any values from the projection (which can be a disadvantage)
1. It doesn't depend on the projection
An example where not depending on the projection is useful is if you want to calculate window functions on distinct values:
SELECT rating, row_number() OVER (ORDER BY rating) AS rn
FROM film
GROUP BY rating
When run against the Sakila database, this yields:
rating rn
-----------
G 1
NC-17 2
PG 3
PG-13 4
R 5
The same couldn't be achieved with DISTINCT easily:
SELECT DISTINCT rating, row_number() OVER (ORDER BY rating) AS rn
FROM film
That query is "wrong" and yields something like:
rating rn
------------
G 1
G 2
G 3
...
G 178
NC-17 179
NC-17 180
...
This is not what we wanted. The DISTINCT operation "happens after" the projection, so we can no longer remove DISTINCT ratings because the window function was already calculated and projected. In order to use DISTINCT, we'd have to nest that part of the query:
SELECT rating, row_number() OVER (ORDER BY rating) AS rn
FROM (
SELECT DISTINCT rating FROM film
) f
Side-note: In this particular case, we could also use DENSE_RANK()
SELECT DISTINCT rating, dense_rank() OVER (ORDER BY rating) AS rn
FROM film
2. It cannot use any values from the projection
One of SQL's drawbacks is its verbosity at times. For the same reason as what we've seen before (namely the logical order of operations), we cannot "easily" group by something we're projecting.
This is invalid SQL:
SELECT first_name || ' ' || last_name AS name
FROM customer
GROUP BY name
This is valid (repeating the expression)
SELECT first_name || ' ' || last_name AS name
FROM customer
GROUP BY first_name || ' ' || last_name
This is valid, too (nesting the expression)
SELECT name
FROM (
SELECT first_name || ' ' || last_name AS name
FROM customer
) c
GROUP BY name
I've written about this topic more in depth in a blog post
There is no difference (in SQL Server, at least). Both queries use the same execution plan.
http://sqlmag.com/database-performance-tuning/distinct-vs-group
Maybe there is a difference, if there are sub-queries involved:
http://blog.sqlauthority.com/2007/03/29/sql-server-difference-between-distinct-and-group-by-distinct-vs-group-by/
There is no difference (Oracle-style):
http://asktom.oracle.com/pls/asktom/f?p=100:11:0::::P11_QUESTION_ID:32961403234212
Use DISTINCT if you just want to remove duplicates. Use GROUPY BY if you want to apply aggregate operators (MAX, SUM, GROUP_CONCAT, ..., or a HAVING clause).
I expect there is the possibility for subtle differences in their execution.
I checked the execution plans for two functionally equivalent queries along these lines in Oracle 10g:
core> select sta from zip group by sta;
---------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 58 | 174 | 44 (19)| 00:00:01 |
| 1 | HASH GROUP BY | | 58 | 174 | 44 (19)| 00:00:01 |
| 2 | TABLE ACCESS FULL| ZIP | 42303 | 123K| 38 (6)| 00:00:01 |
---------------------------------------------------------------------------
core> select distinct sta from zip;
---------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 58 | 174 | 44 (19)| 00:00:01 |
| 1 | HASH UNIQUE | | 58 | 174 | 44 (19)| 00:00:01 |
| 2 | TABLE ACCESS FULL| ZIP | 42303 | 123K| 38 (6)| 00:00:01 |
---------------------------------------------------------------------------
The middle operation is slightly different: "HASH GROUP BY" vs. "HASH UNIQUE", but the estimated costs etc. are identical. I then executed these with tracing on and the actual operation counts were the same for both (except that the second one didn't have to do any physical reads due to caching).
But I think that because the operation names are different, the execution would follow somewhat different code paths and that opens the possibility of more significant differences.
I think you should prefer the DISTINCT syntax for this purpose. It's not just habit, it more clearly indicates the purpose of the query.
For the query you posted, they are identical. But for other queries that may not be true.
For example, it's not the same as:
SELECT C FROM myTbl GROUP BY C, D
I read all the above comments but didn't see anyone pointed to the main difference between Group By and Distinct apart from the aggregation bit.
Distinct returns all the rows then de-duplicates them whereas Group By de-deduplicate the rows as they're read by the algorithm one by one.
This means they can produce different results!
For example, the below codes generate different results:
SELECT distinct ROW_NUMBER() OVER (ORDER BY Name), Name FROM NamesTable
SELECT ROW_NUMBER() OVER (ORDER BY Name), Name FROM NamesTable
GROUP BY Name
If there are 10 names in the table where 1 of which is a duplicate of another then the first query returns 10 rows whereas the second query returns 9 rows.
The reason is what I said above so they can behave differently!
If you use DISTINCT with multiple columns, the result set won't be grouped as it will with GROUP BY, and you can't use aggregate functions with DISTINCT.
GROUP BY has a very specific meaning that is distinct (heh) from the DISTINCT function.
GROUP BY causes the query results to be grouped using the chosen expression, aggregate functions can then be applied, and these will act on each group, rather than the entire resultset.
Here's an example that might help:
Given a table that looks like this:
name
------
barry
dave
bill
dave
dave
barry
john
This query:
SELECT name, count(*) AS count FROM table GROUP BY name;
Will produce output like this:
name count
-------------
barry 2
dave 3
bill 1
john 1
Which is obviously very different from using DISTINCT. If you want to group your results, use GROUP BY, if you just want a unique list of a specific column, use DISTINCT. This will give your database a chance to optimise the query for your needs.
If you are using a GROUP BY without any aggregate function then internally it will treated as DISTINCT, so in this case there is no difference between GROUP BY and DISTINCT.
But when you are provided with DISTINCT clause better to use it for finding your unique records because the objective of GROUP BY is to achieve aggregation.
They have different semantics, even if they happen to have equivalent results on your particular data.
Please don't use GROUP BY when you mean DISTINCT, even if they happen to work the same. I'm assuming you're trying to shave off milliseconds from queries, and I have to point out that developer time is orders of magnitude more expensive than computer time.
In Teradata perspective :
From a result set point of view, it does not matter if you use DISTINCT or GROUP BY in Teradata. The answer set will be the same.
From a performance point of view, it is not the same.
To understand what impacts performance, you need to know what happens on Teradata when executing a statement with DISTINCT or GROUP BY.
In the case of DISTINCT, the rows are redistributed immediately without any preaggregation taking place, while in the case of GROUP BY, in a first step a preaggregation is done and only then are the unique values redistributed across the AMPs.
Don’t think now that GROUP BY is always better from a performance point of view. When you have many different values, the preaggregation step of GROUP BY is not very efficient. Teradata has to sort the data to remove duplicates. In this case, it may be better to the redistribution first, i.e. use the DISTINCT statement. Only if there are many duplicate values, the GROUP BY statement is probably the better choice as only once the deduplication step takes place, after redistribution.
In short, DISTINCT vs. GROUP BY in Teradata means:
GROUP BY -> for many duplicates
DISTINCT -> no or a few duplicates only .
At times, when using DISTINCT, you run out of spool space on an AMP. The reason is that redistribution takes place immediately, and skewing could cause AMPs to run out of space.
If this happens, you have probably a better chance with GROUP BY, as duplicates are already removed in a first step, and less data is moved across the AMPs.
group by is used in aggregate operations -- like when you want to get a count of Bs broken down by column C
select C, count(B) from myTbl group by C
distinct is what it sounds like -- you get unique rows.
In sql server 2005, it looks like the query optimizer is able to optimize away the difference in the simplistic examples I ran. Dunno if you can count on that in all situations, though.
In that particular query there is no difference. But, of course, if you add any aggregate columns then you'll have to use group by.
You're only noticing that because you are selecting a single column.
Try selecting two fields and see what happens.
Group By is intended to be used like this:
SELECT name, SUM(transaction) FROM myTbl GROUP BY name
Which would show the sum of all transactions for each person.
From a 'SQL the language' perspective the two constructs are equivalent and which one you choose is one of those 'lifestyle' choices we all have to make. I think there is a good case for DISTINCT being more explicit (and therefore is more considerate to the person who will inherit your code etc) but that doesn't mean the GROUP BY construct is an invalid choice.
I think this 'GROUP BY is for aggregates' is the wrong emphasis. Folk should be aware that the set function (MAX, MIN, COUNT, etc) can be omitted so that they can understand the coder's intent when it is.
The ideal optimizer will recognize equivalent SQL constructs and will always pick the ideal plan accordingly. For your real life SQL engine of choice, you must test :)
PS note the position of the DISTINCT keyword in the select clause may produce different results e.g. contrast:
SELECT COUNT(DISTINCT C) FROM myTbl;
SELECT DISTINCT COUNT(C) FROM myTbl;
I know it's an old post. But it happens that I had a query that used group by just to return distinct values when using that query in toad and oracle reports everything worked fine, I mean a good response time. When we migrated from Oracle 9i to 11g the response time in Toad was excellent but in the reporte it took about 35 minutes to finish the report when using previous version it took about 5 minutes.
The solution was to change the group by and use DISTINCT and now the report runs in about 30 secs.
I hope this is useful for someone with the same situation.
Sometimes they may give you the same results but they are meant to be used in different sense/case. The main difference is in syntax.
Minutely notice the example below. DISTINCT is used to filter out the duplicate set of values. (6, cs, 9.1) and (1, cs, 5.5) are two different sets. So DISTINCT is going to display both the rows while GROUP BY Branch is going to display only one set.
SELECT * FROM student;
+------+--------+------+
| Id | Branch | CGPA |
+------+--------+------+
| 3 | civil | 7.2 |
| 2 | mech | 6.3 |
| 6 | cs | 9.1 |
| 4 | eee | 8.2 |
| 1 | cs | 5.5 |
+------+--------+------+
5 rows in set (0.001 sec)
SELECT DISTINCT * FROM student;
+------+--------+------+
| Id | Branch | CGPA |
+------+--------+------+
| 3 | civil | 7.2 |
| 2 | mech | 6.3 |
| 6 | cs | 9.1 |
| 4 | eee | 8.2 |
| 1 | cs | 5.5 |
+------+--------+------+
5 rows in set (0.001 sec)
SELECT * FROM student GROUP BY Branch;
+------+--------+------+
| Id | Branch | CGPA |
+------+--------+------+
| 3 | civil | 7.2 |
| 6 | cs | 9.1 |
| 4 | eee | 8.2 |
| 2 | mech | 6.3 |
+------+--------+------+
4 rows in set (0.001 sec)
Sometimes the results that can be achieved by GROUP BY clause is not possible to achieved by DISTINCT without using some extra clause or conditions. E.g in above case.
To get the same result as DISTINCT you have to pass all the column names in GROUP BY clause like below. So see the syntactical difference. You must have knowledge about all the column names to use GROUP BY clause in that case.
SELECT * FROM student GROUP BY Id, Branch, CGPA;
+------+--------+------+
| Id | Branch | CGPA |
+------+--------+------+
| 1 | cs | 5.5 |
| 2 | mech | 6.3 |
| 3 | civil | 7.2 |
| 4 | eee | 8.2 |
| 6 | cs | 9.1 |
+------+--------+------+
Also I have noticed GROUP BY displays the results in ascending order by default which DISTINCT does not. But I am not sure about this. It may be differ vendor wise.
Source : https://dbjpanda.me/dbms/languages/sql/sql-syntax-with-examples#group-by
In terms of usage, GROUP BY is used for grouping those rows you want to calculate. DISTINCT will not do any calculation. It will show no duplicate rows.
I always used DISTINCT if I want to present data without duplicates.
If I want to do calculations like summing up the total quantity of mangoes, I will use GROUP BY
In Hive (HQL), GROUP BY can be way faster than DISTINCT, because the former does not require comparing all fields in the table.
See: https://sqlperformance.com/2017/01/t-sql-queries/surprises-assumptions-group-by-distinct.
The way I always understood it is that using distinct is the same as grouping by every field you selected in the order you selected them.
i.e:
select distinct a, b, c from table;
is the same as:
select a, b, c from table group by a, b, c
Funtional efficiency is totally different.
If you would like to select only "return value" except duplicate one, use distinct is better than group by. Because "group by" include ( sorting + removing ) , "distinct" include ( removing )
Generally we can use DISTINCT for eliminate the duplicates on Specific Column in the table.
In Case of 'GROUP BY' we can Apply the Aggregation Functions like
AVG, MAX, MIN, SUM, and COUNT on Specific column and fetch
the column name and it aggregation function result on the same column.
Example :
select specialColumn,sum(specialColumn) from yourTableName group by specialColumn;
There is no significantly difference between group by and distinct clause except the usage of aggregate functions.
Both can be used to distinguish the values but if in performance point of view group by is better.
When distinct keyword is used , internally it used sort operation which can be view in execution plan.
Try simple example
Declare #tmpresult table
(
Id tinyint
)
Insert into #tmpresult
Select 5
Union all
Select 2
Union all
Select 3
Union all
Select 4
Select distinct
Id
From #tmpresult