I am trying to convert a T-SQL query to MS Access SQL and getting a syntax error that I am struggling to find. My MS Access SQL query looks like this:
INSERT INTO IndvRFM_PreSort (CustNum, IndvID, IndvRScore, IndRecency, IndvFreq, IndvMonVal )
SELECT
IndvMast.CustNum, IndvMast.IndvID, IndvMast.IndvRScore,
IndvMast.IndRecency, IndvMast.IndvFreq, IndvMast.IndvMonVal
FROM
IndvMast
INNER JOIN
OHdrMast ON IndvMast.IndvID = OHdrMast.IndvID
INNER JOIN
MyParameterSettings on 1=1].ProdClass
INNER JOIN
[SalesTerritoryFilter_Check all that apply] ON IndvMast.SalesTerr = [SalesTerritoryFilter_Check all that apply].SalesTerr
WHERE
(((OHdrMast.OrdDate) >= [MyParameterSettings].[RFM_StartDate]))
GROUP BY
IndvMast.CustNum, IndvMast.IndvID, IndvMast.IndvRScore,
IndvMast.IndRecency, IndvMast.IndvFreq, IndvMast.IndvMonVal,
[CustTypeFilter_Check all that apply].IncludeInRFM,
[ProductClassFilter_Check all that apply].IncludeInRFM,
[SourceCodeFilter_Check all that apply].IncludeInRFM,
IndvMast.FlgDontUse
I have reviewed differences between MS Access SQL and T-SQL at http://rogersaccessblog.blogspot.com/2013/05/what-are-differences-between-access-sql.html and a few other locations but with no luck.
All help is appreciated.
update: I have removed many lines trying to find the syntax error and I am still getting the same error when running just (which runs fine using T-SQL):
SELECT
IndvMast.CustNum, IndvMast.IndvID, IndvMast.IndvRScore,
IndvMast.IndRecency, IndvMast.IndvFreq, IndvMast.IndvMonVal
FROM
IndvMast
INNER JOIN
OHdrMast ON IndvMast.IndvID = OHdrMast.IndvID
INNER JOIN
[My Parameter Settings] ON 1 = 1
There are a number of items in your query that should also have failed in any SQL-compliant database:
You have fields from tables in GROUP BY not referenced in FROM or JOIN clauses.
Number of fields in SELECT query do not match number of fields in INSERT INTO clause.
The MyParameterSettings table is not properly joined with valid ON expression.
Strictly MS Access SQL items:
For more than one join, MS Access SQL requires paired parentheses but even this can get tricky if some tables are joined together and their paired result joins to outer where you get nested joins.
Expressions like ON 1=1 must be used in WHERE clause and for cross join tables as MyParameterSettings appears to be, use comma-separated tables.
For above reasons and more, it is advised for beginners to this SQL dialect to use the Query Design builder providing table diagrams and links (if you have the MS Access GUI .exe of course). Then, once all tables connect graphically with at least one field selected, jump into SQL view for any nuanced scripting logic.
Below is an adjustment to SQL statement to demonstrate the parentheses pairings and for best practices, uses table aliases especially with long table names.
INSERT INTO IndvRFM_PreSort (CustNum, IndvID, IndvRScore, IndRecency, IndvFreq, IndvMonVal)
SELECT
i.CustNum, i.IndvID, i.IndvRScore, i.IndRecency, i.IndvFreq, i.IndvMonVal
FROM
[MyParameterSettings] p, (IndvMast i
INNER JOIN
OHdrMast o ON i.IndvID = o.IndvID)
INNER JOIN
[SalesTerritoryFilter_Check all that apply] s ON i.SalesTerr = s.SalesTerr
WHERE
(o.OrdDate >= p.[RFM_StartDate])
GROUP BY
i.CustNum, i.IndvID, i.IndvRScore, i.IndRecency, i.IndvFreq, i.IndvMonVal
And in your smaller SQL subset, the last table does not need an ON 1=1 condition and may be redundant as well in SQL Server. Simply a comma separate table will suffice if you intend for cross join. The same is done in above example:
SELECT
IndvMast.CustNum, IndvMast.IndvID, IndvMast.IndvRScore,
IndvMast.IndRecency, IndvMast.IndvFreq, IndvMast.IndvMonVal
FROM
[My Parameter Settings], IndvMast
INNER JOIN
OHdrMast ON IndvMast.IndvID = OHdrMast.IndvID
I suppose there are some errors in your query, the first (more important).
Why do you use HAVING clause to add these conditions?
HAVING (((IndvMast.IndRecency)>(date()-7200))
AND (([CustTypeFilter_Check all that apply].IncludeInRFM)=1)
AND (([ProductClassFilter_Check all that apply].IncludeInRFM)=1)
AND (([SourceCodeFilter_Check all that apply].IncludeInRFM)=1)
AND ((IndvMast.FlgDontUse) Is Null))
HAVING usually used about conditions on aggregate functions (COUNT, SUM, MAX, MIN, AVG), for scalar value you must put in WHERE clause.
The second: You have 12 parenthesis opened and 11 closed in HAVING clause
Related
I have recently noticed that SQL Server 2016 appears to be ignoring left joins if any column is not used in the select or where clause. Also not found in Actual execution plan.
This is good for if anyone added extra join but still not affecting performance.
I have query that took 9 sec, if I add column in select clause for Left join tables but without that only 1 sec.
Can anyone please check and suggest, Is that true or not?
Query with Actual execution plan. You can see there is no any table from left join in execution plan.
I'm not 100% sure what the question is asking, but a SQL optimizer can ignore left join. Consider this type of query:
select a.*
from a left join
b
on a.b_id = b.id;
If b.id is declared as unique (or equivalently a primary key) then the above query returns exactly the same result set as:
select a.*
from a;
I am not per se aware that SQL Server started putting this optimization in 2016. But the optimization is perfectly valid and (I believe) other optimizers do implement it.
Remember, SQL is a declarative language, not a procedural language. The SQL query describes the result set, not how it is produced.
If you have a left join and your matching condition don't return any data from the joined table it will return data as inner join return, when select statement does not contains columns from right tables. Not only in ms server 2016 but most of the DB's.
Left join reduces the performance of the query if there are large amount of data available in join tables.
I would like to JOIN 2 databases.
1 database is keyword_data (keyword mapping)
1 database is filled with Google rankings and other metrics
Somehow I cannot JOIN these two databases.
Some context:
DATA SET NAME: visibility
TABLE 1
keyword_data
VALUES
keyword
universe
category
search_volume
cpc
DATA SET NAME: visibility
TABLE 2
results
VALUES
Date
Keyword
Website
Position
In order to receive ranking data by date I wrote the following SQL line.
SELECT Date, Position, Website FROM `visibility.results` Keyword INNER
JOIN `visibility.keyword_data` keyword ON `visibility.results` Keyword
= `visibility.keyword_data` keyword GROUP BY Date;
(besides that, 100 other lines with no success ;-) )
I am using Google BigQuery for this with standard SQL (unchecked Legacy SQL).
How can I JOIN those 2 data tables?
How familiar are you with SQL? I think you're using aliases wrong, something like this should work
SELECT r.Date, r.Position, r.Website
FROM `visibility.results` AS r
INNER JOIN `visibility.keyword_data` AS k
ON r.Keyword = k.keyword
GROUP BY DATE
First of all i have never worked with Google big query but there is a couple of things wrong in my opinion with this query.
To start with you join tables by including the name of the table then you provide the key that the tables are joined by. Also if you don't use aggregate functions (MIN/MAX etc.) in your select statement you must include all values in the group by clause as well. In reference I can provide you a solution that would work if you would of used Microsoft SQL Server if that would be of any help because if you reference here the syntax is quite similar.
SELECT results.Date AS DATE,
,results.Position AS POSITION
,results.Website AS WEBSITE
FROM visibility.dbo.keyword_data AS keyword_data
INNER JOIN visibility.dbo.results AS results
ON results.keyword = keyword_data.keyword
GROUP BY results.Date
,results.Position
,results.Website
I have a query which works, goes like this:
Select
count(InsuranceOrderLine.AntallPotensiale) as potensiale,
COUNT(InsuranceOrderLine.AntallSolgt) as Solgt,
InsuranceProduct.Name,
InsuranceProductCategory.Name as Kategori
From
InsuranceOrderLine, InsuranceProduct, InsuranceProductCategory
where
InsuranceOrderLine.FKInsuranceProductId = InsuranceProduct.InsuranceProductID
and InsuranceProduct.FKInsuranceProductCategory = InsuranceProductCategory.InsuranceProductCategoryID
Group by
InsuranceProduct.name, InsuranceProductCategory.Name
This query over returns what I need, but when I try to add more table (InsuranceOrder) to be able to get the regardingUser column, then all the count values are way high.
Select
count(InsuranceOrderLine.AntallPotensiale) as Potensiale,
COUNT(InsuranceOrderLine.AntallSolgt) as Solgt,
InsuranceProduct.Name,
InsuranceProductCategory.Name as Kategori,
RegardingUser
From
InsuranceOrderLine, InsuranceProduct, InsuranceProductCategory, InsuranceSalesLead
where
InsuranceOrderLine.FKInsuranceProductId = InsuranceProduct.InsuranceProductID
and InsuranceProduct.FKInsuranceProductCategory = InsuranceProductCategory.InsuranceProductCategoryID
Group by
InsuranceProduct.name, InsuranceProductCategory.Name,RegardingUser
Thanks in advance
You're adding one more table to your FROM statement, but you don't specify any JOIN condition for that table - so your previous result set will do a FULL OUTER JOIN (cartesian product) with your new table! Of course you'll get duplication of data....
That's one of the reasons that I'm recommending never to use that old, legacy style JOIN - do not simply list a comma-separated bunch of tables in your FROM statement.
Always use the new ANSI standard JOIN syntax with INNER JOIN, LEFT OUTER JOIN and so on:
SELECT
count(iol.AntallPotensiale) as Potensiale,
COUNT(iol.AntallSolgt) as Solgt,
ip.Name,
ipc.Name as Kategori,
isl.RegardingUser
FROM
dbo.InsuranceOrderLine iol
INNER JOIN
dbo.InsuranceProduct ip ON iol.FKInsuranceProductId = ip.InsuranceProductID
INNER JOIN
dbo.InsuranceProductCategory ipc ON ip.FKInsuranceProductCategory = ipc.InsuranceProductCategoryID
INNER JOIN
dbo.InsuranceSalesLead isl ON ???????? -- JOIN condition missing here !!
When you do this, you first of all see right away that you're missing a JOIN condition here - how is this new table InsuranceSalesLead linked to any of the other tables already used in this SQL statement??
And secondly, your intent is much clearer, since the JOIN conditions linking the tables are where they belong - right with the JOIN - and don't clutter up your WHERE clauses ...
It looks like you added the table join which slightly multiplies count of rows - make sure, that you properly joining the table. And be careful with aggregate functions over several joined tables - joins very often lead to duplicates
This question already has answers here:
Closed 12 years ago.
Possible Duplicate:
INNER JOIN versus WHERE clause — any difference?
What is the difference between an INNER JOIN query and an implicit join query (i.e. listing multiple tables after the FROM keyword)?
For example, given the following two tables:
CREATE TABLE Statuses(
id INT PRIMARY KEY,
description VARCHAR(50)
);
INSERT INTO Statuses VALUES (1, 'status');
CREATE TABLE Documents(
id INT PRIMARY KEY,
statusId INT REFERENCES Statuses(id)
);
INSERT INTO Documents VALUES (9, 1);
What is the difference between the below two SQL queries?
From the testing I've done, they return the same result. Do they do the same thing? Are there situations where they will return different result sets?
-- Using implicit join (listing multiple tables)
SELECT s.description
FROM Documents d, Statuses s
WHERE d.statusId = s.id
AND d.id = 9;
-- Using INNER JOIN
SELECT s.description
FROM Documents d
INNER JOIN Statuses s ON d.statusId = s.id
WHERE d.id = 9;
There is no reason to ever use an implicit join (the one with the commas). Yes for inner joins it will return the same results. However, it is subject to inadvertent cross joins especially in complex queries and it is harder for maintenance because the left/right outer join syntax (deprecated in SQL Server, where it doesn't work correctly right now anyway) differs from vendor to vendor. Since you shouldn't mix implicit and explict joins in the same query (you can get wrong results), needing to change something to a left join means rewriting the entire query.
If you do it the first way, people under the age of 30 will probably chuckle at you, but as long as you're doing an inner join, they produce the same result and the optimizer will generate the same execution plan (at least as far as I've ever been able to tell).
This does of course presume that the where clause in the first query is how you would be joining in the second query.
This will probably get closed as a duplicate, btw.
The nice part of the second method is that it helps separates the join condition (on ...) from the filter condition (where ...). This can help make the intent of the query more readable.
The join condition will typically be more descriptive of the structure of the database and the relation between the tables. e.g., the salary table is related to the employee table by the EmployeeID column, and queries involving those two tables will probably always join on that column.
The filter condition is more descriptive of the specific task being performed by the query. If the query is FindRichPeople, the where clause might be "where salaries.Salary > 1000000"... thats describing the task at hand, not the database structure.
Note that the SQL compiler doesn't see it that way... if it decides that it will be faster to cross join and then filter the results, it will cross join and filter the results. It doesn't care what is in the ON clause and whats in the WHERE clause. But, that typically wont happen if the on clause matches a foreign key or joins to a primary key or indexed column. As far as operating correctly, they are identical; as far as writing readable, maintainable code, the second way is probably a little better.
there is no difference as far as I know is the second one with the inner join the new way to write such statements and the first one the old method.
The first one does a Cartesian product on all record within those two tables then filters by the where clause.
The second only joins on records that meet the requirements of your ON clause.
EDIT: As others have indicated, the optimization engine will take care of an attempt on a Cartesian product and will result in the same query more or less.
A bit same. Can help you out.
Left join vs multiple tables in SQL (a)
Left join vs multiple tables in SQL (b)
In the example you've given, the queries are equivalent; if you're using SQL Server, run the query and display the actual exection plan to see what the server's doing internally.
For simplicity, assume all relevant fields are NOT NULL.
You can do:
SELECT
table1.this, table2.that, table2.somethingelse
FROM
table1, table2
WHERE
table1.foreignkey = table2.primarykey
AND (some other conditions)
Or else:
SELECT
table1.this, table2.that, table2.somethingelse
FROM
table1 INNER JOIN table2
ON table1.foreignkey = table2.primarykey
WHERE
(some other conditions)
Do these two work on the same way in MySQL?
INNER JOIN is ANSI syntax that you should use.
It is generally considered more readable, especially when you join lots of tables.
It can also be easily replaced with an OUTER JOIN whenever a need arises.
The WHERE syntax is more relational model oriented.
A result of two tables JOINed is a cartesian product of the tables to which a filter is applied which selects only those rows with joining columns matching.
It's easier to see this with the WHERE syntax.
As for your example, in MySQL (and in SQL generally) these two queries are synonyms.
Also, note that MySQL also has a STRAIGHT_JOIN clause.
Using this clause, you can control the JOIN order: which table is scanned in the outer loop and which one is in the inner loop.
You cannot control this in MySQL using WHERE syntax.
Others have pointed out that INNER JOIN helps human readability, and that's a top priority, I agree.
Let me try to explain why the join syntax is more readable.
A basic SELECT query is this:
SELECT stuff
FROM tables
WHERE conditions
The SELECT clause tells us what we're getting back; the FROM clause tells us where we're getting it from, and the WHERE clause tells us which ones we're getting.
JOIN is a statement about the tables, how they are bound together (conceptually, actually, into a single table).
Any query elements that control the tables - where we're getting stuff from - semantically belong to the FROM clause (and of course, that's where JOIN elements go). Putting joining-elements into the WHERE clause conflates the which and the where-from, that's why the JOIN syntax is preferred.
Applying conditional statements in ON / WHERE
Here I have explained the logical query processing steps.
Reference: Inside Microsoft® SQL Server™ 2005 T-SQL Querying
Publisher: Microsoft Press
Pub Date: March 07, 2006
Print ISBN-10: 0-7356-2313-9
Print ISBN-13: 978-0-7356-2313-2
Pages: 640
Inside Microsoft® SQL Server™ 2005 T-SQL Querying
(8) SELECT (9) DISTINCT (11) TOP <top_specification> <select_list>
(1) FROM <left_table>
(3) <join_type> JOIN <right_table>
(2) ON <join_condition>
(4) WHERE <where_condition>
(5) GROUP BY <group_by_list>
(6) WITH {CUBE | ROLLUP}
(7) HAVING <having_condition>
(10) ORDER BY <order_by_list>
The first noticeable aspect of SQL that is different than other programming languages is the order in which the code is processed. In most programming languages, the code is processed in the order in which it is written. In SQL, the first clause that is processed is the FROM clause, while the SELECT clause, which appears first, is processed almost last.
Each step generates a virtual table that is used as the input to the following step. These virtual tables are not available to the caller (client application or outer query). Only the table generated by the final step is returned to the caller. If a certain clause is not specified in a query, the corresponding step is simply skipped.
Brief Description of Logical Query Processing Phases
Don't worry too much if the description of the steps doesn't seem to make much sense for now. These are provided as a reference. Sections that come after the scenario example will cover the steps in much more detail.
FROM: A Cartesian product (cross join) is performed between the first two tables in the FROM clause, and as a result, virtual table VT1 is generated.
ON: The ON filter is applied to VT1. Only rows for which the <join_condition> is TRUE are inserted to VT2.
OUTER (join): If an OUTER JOIN is specified (as opposed to a CROSS JOIN or an INNER JOIN), rows from the preserved table or tables for which a match was not found are added to the rows from VT2 as outer rows, generating VT3. If more than two tables appear in the FROM clause, steps 1 through 3 are applied repeatedly between the result of the last join and the next table in the FROM clause until all tables are processed.
WHERE: The WHERE filter is applied to VT3. Only rows for which the <where_condition> is TRUE are inserted to VT4.
GROUP BY: The rows from VT4 are arranged in groups based on the column list specified in the GROUP BY clause. VT5 is generated.
CUBE | ROLLUP: Supergroups (groups of groups) are added to the rows from VT5, generating VT6.
HAVING: The HAVING filter is applied to VT6. Only groups for which the <having_condition> is TRUE are inserted to VT7.
SELECT: The SELECT list is processed, generating VT8.
DISTINCT: Duplicate rows are removed from VT8. VT9 is generated.
ORDER BY: The rows from VT9 are sorted according to the column list specified in the ORDER BY clause. A cursor is generated (VC10).
TOP: The specified number or percentage of rows is selected from the beginning of VC10. Table VT11 is generated and returned to the caller.
Therefore, (INNER JOIN) ON will filter the data (the data count of VT will be reduced here itself) before applying the WHERE clause. The subsequent join conditions will be executed with filtered data which improves performance. After that, only the WHERE condition will apply filter conditions.
(Applying conditional statements in ON / WHERE will not make much difference in few cases. This depends on how many tables you have joined and the number of rows available in each join tables)
The implicit join ANSI syntax is older, less obvious, and not recommended.
In addition, the relational algebra allows interchangeability of the predicates in the WHERE clause and the INNER JOIN, so even INNER JOIN queries with WHERE clauses can have the predicates rearranged by the optimizer.
I recommend you write the queries in the most readable way possible.
Sometimes this includes making the INNER JOIN relatively "incomplete" and putting some of the criteria in the WHERE simply to make the lists of filtering criteria more easily maintainable.
For example, instead of:
SELECT *
FROM Customers c
INNER JOIN CustomerAccounts ca
ON ca.CustomerID = c.CustomerID
AND c.State = 'NY'
INNER JOIN Accounts a
ON ca.AccountID = a.AccountID
AND a.Status = 1
Write:
SELECT *
FROM Customers c
INNER JOIN CustomerAccounts ca
ON ca.CustomerID = c.CustomerID
INNER JOIN Accounts a
ON ca.AccountID = a.AccountID
WHERE c.State = 'NY'
AND a.Status = 1
But it depends, of course.
Implicit joins (which is what your first query is known as) become much much more confusing, hard to read, and hard to maintain once you need to start adding more tables to your query. Imagine doing that same query and type of join on four or five different tables ... it's a nightmare.
Using an explicit join (your second example) is much more readable and easy to maintain.
I'll also point out that using the older syntax is more subject to error. If you use inner joins without an ON clause, you will get a syntax error. If you use the older syntax and forget one of the join conditions in the where clause, you will get a cross join. The developers often fix this by adding the distinct keyword (rather than fixing the join because they still don't realize the join itself is broken) which may appear to cure the problem but will slow down the query considerably.
Additionally for maintenance if you have a cross join in the old syntax, how will the maintainer know if you meant to have one (there are situations where cross joins are needed) or if it was an accident that should be fixed?
Let me point you to this question to see why the implicit syntax is bad if you use left joins.
Sybase *= to Ansi Standard with 2 different outer tables for same inner table
Plus (personal rant here), the standard using the explicit joins is over 20 years old, which means implicit join syntax has been outdated for those 20 years. Would you write application code using a syntax that has been outdated for 20 years? Why do you want to write database code that is?
The SQL:2003 standard changed some precedence rules so a JOIN statement takes precedence over a "comma" join. This can actually change the results of your query depending on how it is setup. This cause some problems for some people when MySQL 5.0.12 switched to adhering to the standard.
So in your example, your queries would work the same. But if you added a third table:
SELECT ... FROM table1, table2 JOIN table3 ON ... WHERE ...
Prior to MySQL 5.0.12, table1 and table2 would be joined first, then table3. Now (5.0.12 and on), table2 and table3 are joined first, then table1. It doesn't always change the results, but it can and you may not even realize it.
I never use the "comma" syntax anymore, opting for your second example. It's a lot more readable anyway, the JOIN conditions are with the JOINs, not separated into a separate query section.
They have a different human-readable meaning.
However, depending on the query optimizer, they may have the same meaning to the machine.
You should always code to be readable.
That is to say, if this is a built-in relationship, use the explicit join. if you are matching on weakly related data, use the where clause.
I know you're talking about MySQL, but anyway:
In Oracle 9 explicit joins and implicit joins would generate different execution plans. AFAIK that has been solved in Oracle 10+: there's no such difference anymore.
If you are often programming dynamic stored procedures, you will fall in love with your second example (using where). If you have various input parameters and lots of morph mess, then that is the only way. Otherwise, they both will run the same query plan so there is definitely no obvious difference in classic queries.
ANSI join syntax is definitely more portable.
I'm going through an upgrade of Microsoft SQL Server, and I would also mention that the =* and *= syntax for outer joins in SQL Server is not supported (without compatibility mode) for 2005 SQL server and later.
I have two points for the implicit join (The second example):
Tell the database what you want, not what it should do.
You can write all tables in a clear list that is not cluttered by join conditions. Then you can much easier read what tables are all mentioned. The conditions come all in the WHERE part, where they are also all lined up one below the other. Using the JOIN keyword mixes up tables and conditions.