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
Related
I have two tables in Bigquery from two different data sources, lets say x and y. I want to join these two tables on os_name, tracker_name, date, country columns. For that i am using concat function and joining like this:
full outer join x on concat(x.date,x.os_name,x.tracker_name, x.country) = concat(y.date,y.os_name,y.tracker_name,y.country_code)
as a query result common columns also gets duplicated. like in the result there is os_name and os_name_1, country_code, country_code_1 etc. columns. I don't want that. Final columns should be as in the example below in Final Table Schema.
I want to return all records from both sides. For example if there is no match in table y
y_install, and y_purcase will be 0, and vice versa.
X TABLE SCHEMA:
os_name,
tracker_name,
date ,
country
install
purchase
Y TABLE SCHEMA:
os_name,
tracker_name,
date,
country,
y_install,
y_purchase
Final Table Schema required:
os_name,
tracker_name,
date ,
country
install
purchase,
y_install,
y_purchase
I am going to schedule the query and write results to destination table at given interval.
Can you help me out with this query.
Regarding the final table, I don't understand whether you want to return first NON NULL result or whether you want to have e.g. an array which will contain both results from both tables in case both tables a valid value. In my sample table, do you want row 1,2 (actually the same thing) or 3?
row_number
x_install
y_install
final_table_install
1
23
50
23
2
NULL
50
50
3
23
50
[23,50]
It comes out that What I wanted to use was union all. First, I added the non-common columns to the two tables so that the schemas of the two tables are equal. So I was able to vertically merge tables using union all. Thanks for trying to help out anyway.
I have two SQL tables, example below:
Table 1 (column types varchar, integer, numeric)
A
B
C
D
A007
22
14.02
_Z 1
A008
36
15.06
_Z 1
Table 2 (column types varchar)
A
B
C
D
A009,A010,A011
33,35,36
16.06,17.06
_Z 1,_Z 2
A003,A007,A009
14,22,85
13.01,17.05,14.02
_Z 1
Is there a way to compare individual rows of the first table with the rows of the second table and find out which row of the first table does not occur in the values of any row of the second table?
As can be seen, the first row of table 1 occurs in the values of the second row of table 2.
However, the second row of table 1 does not occur in the values of the rows of table 2, therefore the desired output is row 2 of table 1.
Desired output table:
A
B
C
D
A008
36
15.06
_Z 1
What I have tried so far:
My solution was to create a table containing all possible combinations of column values for each row of the second table (with the same column data types as the columns of the first table) and then use SELECT * FROM TABLE1 EXCEPT SELECT * FROM TABLE2 to get the difference rows.
The solution worked (for relatively small tables) but I am currently in a situation where generating all combinations of column values for each row of the second table (which in my case has 500 rows) results in a table containing millions of rows, so I am looking for another solution, where I can use the original table with 500 rows.
Thank you in advance for any possible answer, preferably one that could also work in the IBM DB2 database.
We can use a LIKE trick here along with string concatenation:
SELECT t1.*
FROM Table1 t1
WHERE NOT EXISTS (
SELECT 1
FROM Table2 t2
WHERE ',' || t2.A || ',' LIKE '%,' || t1.A || ',%'
);
Note that it would be a preferable table design for Table2 to not store CSV values in this way. Instead, get every A value onto a separate row.
Problem
I have a situation in which I have two tables in which I would like the entries from table 2 (lets call it table_2) to be matched up with the entries in table 1 (table_1) such that there are no duplicates rows of table_2 used in the match up.
Discussion
Specifically, in this case there are datetime stamps in each table (field is utcdatetime). For each row in table_1, I want to find the row in table_2 in which has the closed utcdatetime to the table 1 utcdatetime such that the table2.utcdatetime is older than the table_1 utcdatetime and within 30 minutes of the table 1 utcdatetime. Here is the catch, I do not want any repeats. If a row in table 2 gets gobbled up in a match on an earlier row in table 1, then I do not want it considered for a match later.
This has currently been implemented in a Python routine, but it is slow to iterate over all of the rows in table 1 as it is large. I thought I was there with a single SQL statement, but I found that my current SQL results in duplicate table 2 rows in the output data.
I would recommend using a nested select to get whatever results you're looking for.
For instance:
select *
from person p
where p.name_first = 'SCCJS'
and not exists (select 'x' from person p2 where p2.person_id != p.person_id
and p.name_first = 'SCCJS' and p.name_last = 'SC')
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
I was surprised by the outcome of these two queries. I was expecting same from both. I have two tables that share a common field but there is not a relationship set up. The table (A) has a field EventID varchar(10) and table (B) has a field XXNumber varchar(15).
Values from table B column XXNumber are referenced in table A column EventID. Even though XXNumber can hold 15 chars, none of the 179K rows of data is longer than 10 chars.
So the requirement was:
"To avoid Duplicate table B and table A entries, if the XXNumber is contained in a table A >“Event ID” number, then it should not be counted."
To see how many common records I have I ran this query first - call it query alpha"
SELECT dbo.TableB.XXNumber FROM dbo.TableB WHERE dbo.TableB.XXNumber in
( select distinct dbo.TableA.EventId FROM dbo.TableA )
The result was 5322 rows.
The following query - call it query delta which looks like this:
SELECT DISTINCT dbo.TableB.XXNumber, dbo.TableB.EventId
FROM dbo.TableB INNER JOIN dbo.TableA ON dbo.TableB.XXNumber= dbo.TableB.EventId
haas returned 4308 rows.
Shouldn't the resulting number of rows be the same?
The WHERE ID IN () version will select all rows that match each distinct value in the list (regardless of whether you code DISTINCT indide the inner select or not - that's irrelevant). If a given value appears in the parent table more than once, you'll get multipke rows selected from the parent table for that single value found in the child table.
The INNER JOIN version will select each row from the parent table once for every successful join, so if there are 3 rows in the child table with the value, and 2 in the parent, then there will be 6 rows rows in the result for that value.
To make them "the same", add 'DISTINCT' to your main select.
To explain what you're seeing, we'd need to know more about your actual data.