I have 3 columns in table A. I am trying to design a query that will call out all the values (in the three columns) that do not apepar in the 1 column I have in table B. If it helps to make it more clear, table B is a list of currencies in ISO codes and table A is three columns of currencies being used, I am identifying all those values that are NOT using ISO codes to denote their currency.
Currently, I can't seem to get them all to match to the one column, so I made 2 more columns in table B so I can match them individually. My constraints are, I cannot change table A and I must do this in one query. What I got so far is below.
SELECT m.Currency1, i.ISO_Code, m.Currency2 , i.ISO_Code1, m.Currency3, i.ISO_Code2
FROM A AS m
LEFT JOIN B AS i
ON m.Currency=i.ISO_Code
AND m.Currency2=i.ISO_Code1
AND m.Currency3=i.ISO_Code2
WHERE i.ISO_Code is NULL
OR i.ISO_Code1 is NULL
OR i.ISO_Code2 is NULL;
I wouldn't bother making multiple columns in 'B'. I played with this in SQLFiddle and got it to work.
Something like this:
SELECT
m.Currency1, i.ISO_Code,
m.Currency2, j.ISO_Code AS ISO_Code1,
m.Currency3, k.ISO_Code AS ISO_Code2
FROM A AS m
LEFT JOIN B as i
ON m.Currency1 = i.ISO_Code
LEFT JOIN B as j
ON m.Currency2 = j.ISO_Code
LEFT JOIN B as k
ON m.Currency3 = k.ISO_Code
WHERE
i.ISO_Code IS NULL OR
j.ISO_Code IS NULL OR
k.ISO_Code IS NULL
Related
Just to level set: i'm working within a Vertica database using SQL.
Let's say i have two tables: Table A and Table B. Let's also say that Table A is my final/master table used for data vis within Tableau (or something akin), and that Table B feeds certain columns into Table A based on matches within a tertiary table, Table C (which is not relevant to this conversation).
As is, Table A has columns:
ProgramName [varchar(50)]
CustomerName [varchar(50)]
Total_Cost [numeric(18,4)]
As is, Table B has columns:
CustomerCode [varchar(10)]
Total_Cost [numeric(18,4)]
What I would like to do is update Table A's CustomerName column to equal CustomerCode in Table B where the columns of total_cost_dollars equal each other across tables.
I've run this left join query to ensure that, when I do update Table A's CustomerName to equal CustomerCode, the total cost columns are exact/true matches for my entire data set.
SELECT
A.ProgramName,
A.CustomerName,
A.total_cost_dollars,
B.CustomerCode,
B.total_cost_dollars
FROM
TableA A
LEFT JOIN
TableB B
ON
B.total_cost_dollars = A.total_cost_dollars
WHERE
A.CustomerName IS NULL;
Any idea on how to solve this problem?
Since Vertica supports merge query, you can use merge statement:
merge into TableA A
using TableB B
ON (B.total_cost_dollars = A.total_cost_dollars)
when matched then
update
set
A.CustomerName = B.CustomerCode
where
A.CustomerName IS NULL;
I have 2 tables with 1 column in common. I want to select all data from table1 and want to restrict it with a condition. The thing I could not do is writing the where condition with the non-common column.
Here is the code:
$sql="SELECT kategoriler.adi as katadi, urunler.* FROM `urunler`
LEFT JOIN `kategoriler`
ON urunler.kategori_id=kategoriler.Id
WHERE urunler.kategori_id=$id
OR
kategoriler.ust_id = $id";
ust_id is a parent column of kategori_id and kategoriler.Id. I want to select the child values of it.
(Btw as you can see the common columns are urunler.kategori_id and kategoriler.Id)
I have a list of 12 strings (strings of numbers) that I need to compare to an existing table in Oracle. However I don't want to create a table just to do the compare; that takes more time than it is worth.
select
column_value as account_number
from
table(sys.odcivarchar2list('27001', '900480', '589358', '130740',
'807958', '579813', '1000100462', '656025',
'11046', '945287', '18193', '897603'))
This provides the correct result.
Now I want to compare that list of 12 against an actual table with account numbers to find the missing values. Normally with two tables I would do a left join table1.account_number = table2.account_number and table two results will have blanks. When I attempt that using the above, all I get are the results where the two records are equal.
select column_value as account_number, k.acct_num
from table(sys.odcivarchar2list('27001',
'900480',
'589358',
'130740',
'807958',
'579813',
'1000100462',
'656025',
'11046',
'945287',
'18193',
'897603'
)) left join
isi_owner.t_known_acct k on column_value = k.acct_num
9 match, but 3 should be included in table1 and blank in table2
Thoughts?
Sean
I have a little problem - since im not very experienced in SQL - about joining the same table on multiple values. Imagine there is table 1 (called Strings):
id value
1 value1
2 value2
and then there is table 2 (called Maps):
id name description
1 1 2
so name is reference into the Strings table, as is description. Without the second field referencing the Strings table it would be no problem, id just do an inner join on Strings.id = Maps.name. But now id like to obtain the actual string also for description. What would be the best approach for a SELECT that returns me both? Right now it looks like this:
SELECT Maps.id, Strings.value AS mapName FROM Maps INNER JOIN Strings ON Strings.id = Maps.name;
But that obviously only covers one of the localized names. Thank you in advance.
You can do this with two joins to the same table:
SELECT m.id, sname.value AS mapName, sdesc.value as description
FROM Maps m INNER JOIN
Strings sname
ON sname.id = m.name INNER JOIN
Strings desc
ON sdesc.id = m.description;
Note the use of table aliases to distinguish between the two tables.
As long as you want to get a single value from another table, you can use subqueries to do these lookups:
SELECT id,
(SELECT value FROM Strings WHERE id = Maps.name) AS name,
(SELECT value FROM Strings WHERE id = Maps.description) AS description
FROM Maps
Currently struggling with finding a way to validate 2 tables (efficiently lots of rows for Table A)
I have two tables
Table A
ID
A
B
C
Table matched
ID Number
A 1
A 2
A 9
B 1
B 9
C 2
I am trying to write a SQL Server query that basically checks to make sure for every value in Table A there exists a row for a variable set of values ( 1, 2,9)
The example above is incorrect because t should have for every record in A a corresponding record in Table matched for each value (1,2,9). The end goal is:
Table matched
ID Number
A 1
A 2
A 9
B 1
B 2
B 9
C 1
C 2
C 9
I know its confusing, but in general for every X in ( some set ) there should be a corresponding record in Table matched. I have obviously simplified things.
Please let me know if you all need clarification.
Use:
SELECT a.id
FROM TABLE_A a
JOIN TABLE_B b ON b.id = a.id
WHERE b.number IN (1, 2, 9)
GROUP BY a.id
HAVING COUNT(DISTINCT b.number) = 3
The DISTINCT in the COUNT ensures that duplicates (IE: A having two records in TABLE_B with the value "2") from being falsely considered a correct record. It can be omitted if the number column either has a unique or primary key constraint on it.
The HAVING COUNT(...) must equal the number of values provided in the IN clause.
Create a temp table of values you want. You can do this dynamically if the values 1, 2 and 9 are in some table you can query from.
Then, SELECT FROM tempTable WHERE NOT IN (SELECT * FROM TableMatched)
I had this situation one time. My solution was as follows.
In addition to TableA and TableMatched, there was a table that defined the rows that should exist in TableMatched for each row in TableA. Let’s call it TableMatchedDomain.
The application then accessed TableMatched through a view that controlled the returned rows, like this:
create view TableMatchedView
select a.ID,
d.Number,
m.OtherValues
from TableA a
join TableMatchedDomain d
left join TableMatched m on m.ID = a.ID and m.Number = d.Number
This way, the rows returned were always correct. If there were missing rows from TableMatched, then the Numbers were still returned but with OtherValues as null. If there were extra values in TableMatched, then they were not returned at all, as though they didn't exist. By changing the rows in TableMatchedDomain, this behavior could be controlled very easily. If a value were removed TableMatchedDomain, then it would disappear from the view. If it were added back again in the future, then the corresponding OtherValues would appear again as they were before.
The reason I designed it this way was that I felt that establishing an invarient on the row configuration in TableMatched was too brittle and, even worse, introduced redundancy. So I removed the restriction from groups of rows (in TableMatched) and instead made the entire contents of another table (TableMatchedDomain) define the correct form of the data.