i've been recently working in mysql and in one of the requests i wrote :
SELECT SIGLE_EEP, ID_SOUS_MODULE, LIBELLE
FROM mef_edi.eep a, mef_edi.envoi e, mef_edi.sous_module s
WHERE a.ID_EEP = e.ID_EEP
AND a.ID_SOUS_MODULE = s.ID_SOUS_MODULE;
and they told me :
Column ID_SOUS_MODULE in field list is ambiguous
What should i do ?
More than one table has a column named ID_SOUS_MODULE.
So you need to name the table every time you mention the column to specify which table you mean.
Change
SELECT ID_SOUS_MODULE
for instance to
SELECT a.ID_SOUS_MODULE
I agree with the answer above, you may have duplicate column names across your 3 tables, assigning the table id (a, e, s) as noted above will avoid that issue in the select. In addition to what #juergen said you may want to get rid of that cartesian join by using an inner or left join (inner seems to be what your going for). The way you are joining your table you are joining every possible combination of rows together than filtering. using a proper join will get you better performance in the long run as your table line counts grow. Here is an example of a non cartesian join:
SELECT SIGLE_EEP, ID_SOUS_MODULE, LIBELLE
FROM mef_edi.eep a
INNER JOIN mef_edi.envoi e ON (a.ID_EEP = e.ID_EEP)
INNER JOIN mef_edi.sous_module s ON (a.ID_SOUS_MODULE = s.ID_SOUS_MODULE)
Related
I am trying to use the existing Except clause in Bigquery. Please find my query below
select * EXCEPT (b.hosp_id, b.person_id,c.hosp_id) from
person a
inner join hospital b
on a.hosp_id= b.hosp_id
inner join reading c
on a.hosp_id= c.hosp_id
As you can see I am using 3 tables. All the 3 tables have the hosp_id column, so I would like to remove duplicate columns which are b.hosp_id and c.hosp_id. Simlarly, I would like to remove b.person_id column as well.
When I execute the above query, I get the syntax error as shown below
Syntax error: Expected ")" or "," but got "." at [9:19]
Please note that all the columns that I am using in Except clause is present in the tables used. Additional info is all the tables used are temp tables created using with clause. When I do the same manually by selecting column of interest, it works fine. But I have several columns and can't do this manually.
Can you help? I am trying to learn Bigquery. Your inputs would help
I use the EXCEPT on a per-table basis:
select p.* EXCEPT (hosp_id, person_id),
h.*,
r.* EXCEPT (hosp_id)
from person p inner join
hospital h
on p.hosp_id = h.hosp_id inner join
reading r
on p.hosp_id = r.hosp_id;
Note that this also uses meaningful abbreviations for table aliases, which makes the query much simpler to understand.
In your case, I don't think you need EXCEPT at all if you use the USING clause.
Try this instead:
select * EXCEPT (person_id) from
person a
inner join hospital b
using (hosp_id)
inner join reading c
using (hosp_id)
You can only put column names (not paths) in the EXCEPT list, and you can simply avoid projecting the duplicate columns with USING instead of ON.
I have run this query in adventureworks but the result is run successfully but i only get the columns instead of the data with columns how so?
select
a.BusinessEntityID,b.bonus,b.SalesLastYear
from
[Sales].[SalesPersonQuotaHistory] a
inner join
[Sales].[SalesPerson] b
on
a.SalesQuota = b.SalesQuota
My best guess is that instead of joining the tables on SalesQuota, you should be joining them on something else - An ID field, typically.
I don't have Adventureworks here, but judging from the names of the tables and the columns that you've provided, I would assume that there's a SalesPersonID field of some sort that actually connects a Salesperson's quota history to the Salesperson him/herself.
I would expect that you're looking for something closer to this:
SELECT
a.BusinessEntityID
,b.bonus
,b.SalesLastYear
FROM [Sales].[SalesPersonQuotaHistory] a
INNER JOIN [Sales].[SalesPerson] b
ON a.SalesPersonID = b.SalesPersonID
General Knowledge:
INNER JOIN means "Show me only entries (rows) that have a matching value on both sides of the condition." (i.e. The value in Table A matches the value in Table B).
So ON a.SalesQuota = b.SalesQuota means "Only where the value of SalesQuota in Table A matches the value of SalesQuota in Table B."
I'm not sure what the purpose of this query could be, since it is entirely possible that two salespeople have the same values in both tables, and then you would get duplicate rows (because the values of SalesQuota would match in both cases), or that the values wouldn't match at all, and then you wouldn't get any rows - I suspect that is what's happening to you.
Consider the conditions of what you're trying to join. Are you really trying to join quota amounts, or are you trying to retrieve quota information for specific salespeople? The answer should help guide your JOIN conditions.
I have two tables. Both have lot of columns. Now I have a common column called ID on which I would join.
Now since this variable ID is present in both the tables if I do simply this
select a.*,b.*
from table_a as a
left join table_b as b on a.id=b.id
This will give an error as id is duplicate (present in both the tables and getting included for both).
I don't want to write down separately each column of b in the select statement. I have lots of columns and that is a pain. Can I rename the ID column of b in the join statement itself similar to SAS data merge statements?
I am using Postgres.
Postgres would not give you an error for duplicate output column names, but some clients do. (Duplicate names are also not very useful.)
Either way, use the USING clause as join condition to fold the two join columns into one:
SELECT *
FROM tbl_a a
LEFT JOIN tbl_b b USING (id);
While you join the same table (self-join) there will be more duplicate column names. The query would make hardly any sense to begin with. This starts to make sense for different tables. Like you stated in your question to begin with: I have two tables ...
To avoid all duplicate column names, you have to list them in the SELECT clause explicitly - possibly dealing out column aliases to get both instances with different names.
Or you can use a NATURAL join - if that fits your unexplained use case:
SELECT *
FROM tbl_a a
NATURAL LEFT JOIN tbl_b b;
This joins on all columns that share the same name and folds those automatically - exactly the same as listing all common column names in a USING clause. You need to be aware of rules for possible NULL values ...
Details in the manual.
My code is such:
SELECT COUNT(*)
FROM earned_dollars a
LEFT JOIN product_reference b ON a.product_code = b.product_code
WHERE a.activity_year = '2015'
I'm trying to match two tables based on their product codes. I would expect the same number of results back from this as total records in table a (with a year of 2015). But for some reason I'm getting close to 3 million.
Table a has about 40,000,000 records and table b has 2000. When I run this statement without the join I get 2,500,000 results, so I would expect this even with the left join, but somehow I'm getting 300,000,000. Any ideas? I even refered to the diagram in this post.
it means either your left join is using only part of foreign key, which causes row multiplication, or there are simply duplicate rows in the joined table.
use COUNT(DISTINCT a.product_code)
What is the question are are trying to answer with the tsql?
instead of select count(*) try select a.product_code, b.product_code. That will show you which records match and which don't.
Should also add a where b.product_code is not null. That should exclude the records that don't match.
b is the parent table and a is the child table? try a right join instead.
Or use the table's unique identifier, i.e.
SELECT COUNT(a.earned_dollars_id)
Not sure what your datamodel looks like and how it is structured, but i'm guessing you only care about earned_dollars?
SELECT COUNT(*)
FROM earned_dollars a
WHERE a.activity_year = '2015'
and exists (select 1 from product_reference b ON a.product_code = b.product_code)
I have a very large view containing 5 million records containing repeated names with each row having unique transaction number. Another view of 9000 records containing unique names is also present. Now I want to retrieve records in first view whose names are present in second view
select * from v1 where name in (select name from v2)
But the query is taking very long to run. Is there any short cut method?
Did you try just using a INNER JOIN. This will return all rows that exist in both tables:
select v1.*
from v1
INNER JOIN v2
on v1.name = v2.name
If you need help learning JOIN syntax, here is a great visual explanation.
You can add the DISTINCT keyword which will remove any duplicate values that the query returns.
use JOIN.
The DISTINCT will allow you to return only unique records from the list since you are joining from the other table and there could be possibilities that a record may have more than one matches on the other table.
SELECT DISTINCT a.*
FROM v1 a
INNER JOIN v2 b
ON a.name = b.name
For faster performance, add an index on column NAME on both tables since you are joining through it.
To further gain more knowledge about joins, kindly visit the link below:
Visual Representation of SQL Joins