Is VB.NET's Aggregate query fatally flawed when used as the first (outer) clause of a Linq expression with multiple Into clauses because each Into clause is executed separately?
The "obvious" answer to SELECT MIN(ZoneMin), MAX(ZoneMin) FROM Plant in LINQ to SQL is
Dim limits = Aggregate p In Plants Select p.ZoneMin Into Min(), Max()
However, this answer actually retrieves each of Min and Max (and if you include other aggregate functions like Count and Average) in separate SQL queries. This can be easily seen in LINQPad.
Is there a transaction (or something else making these queries atomic) not shown by LINQPad, or is this a race condition waiting to happen? (And so you have to do the tricks shown in the answer to the above question to force a single query that returns multiple aggregates.)
In summary, is there a LINQ-to-SQL query using Aggregate that returns multiple aggregate functions in a single (or at least "atomic") query?
(I also say "obvious" because the obvious answer to me, Aggregate p In Plants Into Min(p.ZoneMin), Max(p.ZoneMin), actually retrieves the whole table twice, even when optimised, and then uses the Linq-to-Entities Min and Max to obtain the result :-( )
I thought Aggregate wasn't VB-specific, but it looks like C# does not have this query expression, so I've changed the .net to vb.net.
Although it doesn't use the Aggregate keyword, you can do multiple functions in a single query using the following syntax:
Dim query = From book In books _
Group By key = book.Subject Into Group _
Select id = key, _
BookCount = Group.Count, _
TotalPrice = Group.Sum(Function(_book) _book.Price), _
LowPrice = Group.Min(Function(_book) _book.Price), _
HighPrice = Group.Max(Function(_book) _book.Price), _
AveragePrice = Group.Average(Function(_book) _book.Price)
There does appear to be an issue with the Aggregate clause implementation though. Consider the following query from Northwind:
Aggregate o in Orders
into Sum(o.Freight),
Average(o.Freight),
Max(o.Freight)
This issues 3 database requests. The first two perform separate aggregate clauses. The third pulls the entire table back to the client and performs the Max on the client through Linq to Objects.
To answer my broader question: is Aggregate broken for producing separate SQL queries without transactions?
All of LINQ can cause that if you don't carefully adjust your queries to only result in a single SELECT, and that may not be possible, without "giving up", retrieving a larger result in a single query and then using Linq-to-Objects to aggregate or otherwise manipulate the data. This 'query' for example.
So it is, in general, up to the programmer to ensure transactions are added around LINQ queries that may cause multiple queries. We just need to know for sure which LINQ queries may transform into multiple SQL queries.
Related
So I have the following model in Django:
class MemberLoyalty(models.Model):
date_time = models.DateField(primary_key=True)
member = models.ForeignKey(Member, models.DO_NOTHING)
loyalty_value = models.IntegerField()
My goal is to have all the tuples grouped by the member with the most recent date. There are many ways to do it, one of them is using a subquery that groups by the member with max date_time and filtering member_loyalty with its results. The working sql for this solution is as follows:
SELECT
*
FROM
member_loyalty
WHERE
(date_time , member_id) IN (SELECT
max(date_time), member_id
FROM
member_loyalty
GROUP BY member_id);
Another way to do this would be by joining with the subquery.
How could i translate this on a django query? I could not find a way to filter with two fields using IN, nor a way to join with a subquery using a specific ON statement.
I've tried:
cls.objects.values('member_id', 'loyalty_value').annotate(latest_date=Max('date_time'))
But it starts grouping by the loyalty_value.
Also tried building the subquery, but cant find how to join it or use it on a filter:
subquery = cls.objects.values('member_id').annotate(max_date=Max('date_time'))
Also, I am using Mysql so I can not make use of the .distinct('param') method.
This is a typical greatest-per-group query. Stack-overflow even has a tag for it.
I believe the most efficient way to do it with the recent versions of Django is via a window query. Something along the lines should do the trick.
MemberLoyalty.objects.all().annotate(my_max=Window(
expression=Max('date_time'),
partition_by=F('member')
)).filter(my_max=F('date_time'))
Update: This actually won't work, because Window annotations are not filterable. I think in order to filter on window annotation you need to wrap it inside a Subquery, but with Subquery you are actually not obligated to use a Window function, there is another way to do it, which is my next example.
If either MySQL or Django does not support window queries, then a Subquery comes into play.
MemberLoyalty.objects.filter(
date_time=Subquery(
(MemberLoyalty.objects
.filter(member=OuterRef('member'))
.values('member')
.annotate(max_date=Max('date_time'))
.values('max_date')[:1]
)
)
)
If event Subqueries are not available (pre Django 1.11) then this should also work:
MemberLoyalty.objects.annotate(
max_date=Max('member__memberloyalty_set__date_time')
).filter(max_date=F('date_time'))
I'm setting up an AR query that is basically meant to find an average of a few values that span three different tables. I'm getting hung up on how to embed the result of a particular Count query inside of the Active Record select statement.
Just by itself, this query returns "3":
Order.where(user_id: 319).count => 3
My question is, can I embed this into a select statement as a SQL alias similar to below:
Table.xxxxxx.select("Order.where(user_id: 319).count AS count,user_id, SUM(quantity*current_price) AS revenue").xxxxx
It seems to be throwing an error and generally not recognizing what I'm trying to do when I declare that first count alias. Any ideas on the syntax?
Well, after examining a bit, I cleared my mind into the ActiveRecord select() syntax.
It's a method that can take a variable length of parameters. So, your failing :
Table.xxxxxx.select("Order.where(user_id: 319).count AS count,user_id, SUM(quantity*current_price) AS revenue").xxxxx
After replacing proper SQL for your misplaced ActiveRecord statement, should be more of like this [be careful, you can't use as count in most cases, count is reserved]:
Table.xxxxx.select("(SELECT count(id) from orders where user_id=319) as usercount", "user_id","SUM(quantity*current_price) AS revenue").xxxx
But I guess you should need more a per-user_id-table.
So, I'd skip Models and go to direct SQL, always being careful to avoid injections:
ActiveRecord::Base.connection.execute('SELECT COUNT(orders.id) as usercount, users.id from users, orders where users.id=orders.user_id group by users.id')
This is simplified of course, you can apply the rest of the data (which I currently do not know) accordingly. The above simplified, not full solution, could be written also as:
Order.joins(:user).select("count(orders.id) as usercount, users.id").group(:user_id)
I suppose I have always naively assumed that scalar functions in the select part of a SQL query will only get applied to the rows that meet all the criteria of the where clause.
Today I was debugging some code from a vendor and had that assumption challenged. The only reason I can think of for this code failing is that the Substring() function is getting called on data that should have been filtered out by the WHERE clause. But it appears that the substring call is being applied before the filtering happens, the query is failing.
Here is an example of what I mean. Let's say we have two tables, each with 2 columns and having 2 rows and 1 row respectively. The first column in each is just an id. NAME is just a string, and NAME_LENGTH tells us how many characters in the name with the same ID. Note that only names with more than one character have a corresponding row in the LONG_NAMES table.
NAMES: ID, NAME
1, "Peter"
2, "X"
LONG_NAMES: ID, NAME_LENGTH
1, 5
If I want a query to print each name with the last 3 letters cut off, I might first try something like this (assuming SQL Server syntax for now):
SELECT substring(NAME,1,len(NAME)-3)
FROM NAMES;
I would soon find out that this would give me an error, because when it reaches "X" it will try using a negative number for in the substring call, and it will fail.
The way my vendor decided to solve this was by filtering out rows where the strings were too short for the len - 3 query to work. He did it by joining to another table:
SELECT substring(NAMES.NAME,1,len(NAMES.NAME)-3)
FROM NAMES
INNER JOIN LONG_NAMES
ON NAMES.ID = LONG_NAMES.ID;
At first glance, this query looks like it might work. The join condition will eliminate any rows that have NAME fields short enough for the substring call to fail.
However, from what I can observe, SQL Server will sometimes try to calculate the the substring expression for everything in the table, and then apply the join to filter out rows. Is this supposed to happen this way? Is there a documented order of operations where I can find out when certain things will happen? Is it specific to a particular Database engine or part of the SQL standard? If I decided to include some predicate on my NAMES table to filter out short names, (like len(NAME) > 3), could SQL Server also choose to apply that after trying to apply the substring? If so then it seems the only safe way to do a substring would be to wrap it in a "case when" construct in the select?
Martin gave this link that pretty much explains what is going on - the query optimizer has free rein to reorder things however it likes. I am including this as an answer so I can accept something. Martin, if you create an answer with your link in it i will gladly accept that instead of this one.
I do want to leave my question here because I think it is a tricky one to search for, and my particular phrasing of the issue may be easier for someone else to find in the future.
TSQL divide by zero encountered despite no columns containing 0
EDIT: As more responses have come in, I am again confused. It does not seem clear yet when exactly the optimizer is allowed to evaluate things in the select clause. I guess I'll have to go find the SQL standard myself and see if i can make sense of it.
Joe Celko, who helped write early SQL standards, has posted something similar to this several times in various USENET newsfroups. (I'm skipping over the clauses that don't apply to your SELECT statement.) He usually said something like "This is how statements are supposed to act like they work". In other words, SQL implementations should behave exactly as if they did these steps, without actually being required to do each of these steps.
Build a working table from all of
the table constructors in the FROM
clause.
Remove from the working table those
rows that do not satisfy the WHERE
clause.
Construct the expressions in the
SELECT clause against the working table.
So, following this, no SQL dbms should act like it evaluates functions in the SELECT clause before it acts like it applies the WHERE clause.
In a recent posting, Joe expands the steps to include CTEs.
CJ Date and Hugh Darwen say essentially the same thing in chapter 11 ("Table Expressions") of their book A Guide to the SQL Standard. They also note that this chapter corresponds to the "Query Specification" section (sections?) in the SQL standards.
You are thinking about something called query execution plan. It's based on query optimization rules, indexes, temporaty buffers and execution time statistics. If you are using SQL Managment Studio you have toolbox over your query editor where you can look at estimated execution plan, it shows how your query will change to gain some speed. So if just used your Name table and it is in buffer, engine might first try to subquery your data, and then join it with other table.
I am wondering how others would handle a scenario like such:
Say I have multiple choices for a user to choose from.
Like, Color, Size, Make, Model, etc.
What is the best solution or practice for handling the build of your query for this scneario?
so if they select 6 of the 8 possible colors, 4 of the possible 7 makes, and 8 of the 12 possible brands?
You could do dynamic OR statements or dynamic IN Statements, but I am trying to figure out if there is a better solution for handling this "WHERE" criteria type logic?
EDIT:
I am getting some really good feedback (thanks everyone)...one other thing to note is that some of the selections could even be like (40 of the selections out of the possible 46) so kind of large. Thanks again!
Thanks,
S
What I would suggest doing is creating a function that takes in a delimited list of makeIds, colorIds, etc. This is probably going to be an int (or whatever your key is). And splits them into a table for you.
Your SP will take in a list of makes, colors, etc as you've said above.
YourSP '1,4,7,11', '1,6,7', '6'....
Inside your SP you'll call your splitting function, which will return a table-
SELECT * FROM
Cars C
JOIN YourFunction(#models) YF ON YF.Id = C.ModelId
JOIN YourFunction(#colors) YF2 ON YF2.Id = C.ColorId
Then, if they select nothing they get nothing. If they select everything, they'll get everything.
What is the best solution or practice for handling the build of your query for this scenario?
Dynamic SQL.
A single parameter represents two states - NULL/non-existent, or having a value. Two more means squaring the number of parameters to get the number of total possibilities: 2 yields 4, 3 yields 9, etc. A single, non-dynamic query can contain all the possibilities but will perform horribly between the use of:
ORs
overall non-sargability
and inability to reuse the query plan
...when compared to a dynamic SQL query that constructs the query out of only the absolutely necessary parts.
The query plan is cached in SQL Server 2005+, if you use the sp_executesql command - it is not if you only use EXEC.
I highly recommend reading The Curse and Blessing of Dynamic SQL.
For something this complex, you may want a session table that you update when the user selects their criteria. Then you can join the session table to your items table.
This solution may not scale well to thousands of users, so be careful.
If you want to create dynamic SQL it won't matter if you use the OR approach or the IN approach. SQL Server will process the statements the same way (maybe with little variation in some situations.)
You may also consider using temp tables for this scenario. You can insert the selections for each criteria into temp tables (e.g., #tmpColor, #tmpSize, #tmpMake, etc.). Then you can create a non-dynamic SELECT statement. Something like the following may work:
SELECT <column list>
FROM MyTable
WHERE MyTable.ColorID in (SELECT ColorID FROM #tmpColor)
OR MyTable.SizeID in (SELECT SizeID FROM #tmpSize)
OR MyTable.MakeID in (SELECT MakeID FROM #tmpMake)
The dynamic OR/IN and the temp table solutions work fine if each condition is independent of the other conditions. In other words, if you need to select rows where ((Color is Red and Size is Medium) or (Color is Green and Size is Large)) you'll need to try other solutions.
My company has just started using LINQ and I still am having a little trouble with the abstractness (if thats a word) of the LINQ command and the SQL, my question is
Dim query = (From o In data.Addresses _
Select o.Name).Count
In the above in my mind, the SQL is returning all rows and the does a count on the number rows in the IQueryable result, so I would be better with
Dim lstring = Aggregate o In data.Addresses _
Into Count()
Or am I over thinking the way LINQ works ? Using VB Express at home so I can't see the actual SQL that is being sent to the database (I think) as I don't have access to the SQL profiler
As mentioned, these are functionally equivalent, one just uses query syntax.
As mentioned in my comment, if you evaluate the following as a VB Statement(s) in LINQPad:
Dim lstring = Aggregate o In Test _
Into Count()
You get this in the generated SQL output window:
SELECT COUNT(*) AS [value]
FROM [Test] AS [t0]
Which is the same as the following VB LINQ expression as evaluated:
(From o In Test_
Select o.Symbol).Count
You get the exact same result.
I'm not familiar with Visual Basic, but based on
http://msdn.microsoft.com/en-us/library/bb546138.aspx
Those two approaches are the same. One uses method syntax and the other uses query syntax.
You can find out for sure by using SQL Profiler as the queries run.
PS - The "point" of LINQ is you can easily do query operations without leaving code/VB-land.
An important thing here, is that the code you give will work with a wide variety of data sources. It will hopefully do so in a very efficient way, though that can't be fully guaranteed. It certainly will be done in an efficient way with a SQL source (being converted into a SELECT COUNT(*) SQL query. It will be done efficiently if the source was an in-memory collection (it gets converted to calling the Count property). It isn't done very efficiently if the source is an enumerable that is not a collection (in this case it does read everything and count as it goes), but in that case there really isn't a more efficient way of doing this.
In each case it has done the same conceptual operation, in the most efficient manner possible, without you having to worry about the details. No big deal with counting, but a bigger deal in more complex cases.
To a certain extent, you are right when you say "in my mind, the SQL is returning all rows and the does a count on the number rows". Conceptually that is what is happening in that query, but the implementation may differ. Compare with how the real query in SQL may not match the literal interpretation of the SQL command, to allow the most efficient approach to be picked.
I think you are missing the point as Linq with SQL has late binding the search is done when you need it so when you say I need the count number then a Query is created.
Before that Linq for SQL creates Expression trees that will be "translated" in to SQL when you need it....
http://weblogs.asp.net/scottgu/archive/2007/05/19/using-linq-to-sql-part-1.aspx
http://msdn.microsoft.com/en-us/netframework/aa904594.aspx
How to debug see Scott
http://weblogs.asp.net/scottgu/archive/2007/07/31/linq-to-sql-debug-visualizer.aspx
(source: scottgu.com)