I have read-only access to a database and there are two tables that contain information I need. both tables have the same numbers in row a in referee to an account. I want to query the result of all accounts in table 1 that have "AD" in column B and where the account has values "4" in column C in of table 2. below is an example.
table 1 |
-------- |
A | B | |
_______ |
1 AC |
2 AD |
3 AC |
4 AD |
___________
table 2 |
-------- |
A | B | C |
__________|
1 AB 4 |
2 AB 5 |
3 AB 4 |
4 AB 4 |
I have tried the query
SELECT * FROM Table 1 WHERE column B = 'AD' and WHERE column C = '4' FROM TABLE 2
you can use inner Join instead,
Like this:
SELECT
t1.*
FROM
Table1 t1 JOIN Table2 t2 ON t1.A = t2.A
WHERE
t2.C = 4 AND t1.B = 'AD'
There isn't quite enough info here for me to help. There isn't common data between the two tables to link them.
Your query above is missing a join between the two tables, and you only need to state the where clause once, additional criteria can be added by using 'and.....'
Related
I am copying data from few tables in SQL server A to B. I have a set of staging tables in B and need to update some of those staging tables based on updated values in final target table in B.
Example:
Server B:
StagingTable1:
ID | NAME | CITY
1 ABC XYZ
2 BCD XXX
StagingTable2:
ID | AGE | Table1ID(FK)
10 15 1
20 16 2
After Copying StagingTable1 to TargetTable1 (ID's get auto polulated and I get new ID's, now ID 1 becomes 2 and ID 2 becomes 3)
TargetTable1:
ID | NAME | CITY
1 PQR YYY (pre-existing record)
2 ABC XYZ
3 BCD XXX
So now before I can copy the StagingTable2 I need to update the Table1ID column in it by correct values from TargetTable1.
StagingTable2 should become:
ID | AGE | Table1ID(FK)
10 15 2
20 16 3
I am writing a stored procedure for this and not sure how do I lookup and update the records in staging tables?
Assuming that (name, city) tuples are unique in StagingTable1 and TargetTable1, you can use an updatable common table expression to generate the new mapping and assign the corresponding values:
with cte as (
select st2.Table1ID, tt1.id
from StagingTable2 st2
inner join StagingTable1 st1 on st1.ID = st2.Table1ID
inner join TargetTable1 tt1 on tt1.name = st1.name and tt1.city = st1.city
)
update cte set Table1ID = id
Demo on DB Fiddle - content of StagingTable2 after the update:
id | age | Table1ID
-: | --: | -------:
10 | 15 | 2
20 | 16 | 3
I'm trying to join two tables together in SQL where the columns contain a different number of unique entries.
When I use a full join the additional entries in the column joined on are missing.
The code I'm using is (in a SAS proc SQL):
proc sql;
create table table3 as
select table1.*, table2.*
from table1 full join table2
on table1.id = table2.id;
quit;
Visual example of problem (can't show actual tables as contain sensitive data)
Table 1
id | count1
1 | 2
2 | 3
3 | 2
Table 2
id | count2
1 | 4
2 | 5
3 | 6
4 | 2
Table 3
id | counta | countb
1 | 2 | 4
2 | 3 | 5
3 | 2 | 6
- | - | 2 <----- I want don't want the id column to be blank in this row
I hope I've explained my problem clearly enough, thanks in advance for your help.
The id from table 1 is blank because the row from table2 has no match in table 1. Try looking at the output from this query:
select coalesce(table1.id, table2.id) as id, table1.count1, table2.count2
from table1 full join table2
on table1.id = table2.id;
Coalesce works from left to right returning the first non null value (it can take more than 2 arguments). If the id in table 1 is null it uses the id from table 2 instead
I recommend also to alias all tables in queries, so I’d have written this:
SELECT
COALESCE(t1.id, t2.id) as id,
t1.count1,
t2.count2
FROM
table1 t1
FULL OUTER JOIN
table2 t2
ON
t1.id = t2.id;
Simply select coalesce(t1.id, t2.id), will return the first non-null id value.
after some transformation I have a result from a cross join (from table a and b) where I want to do some analysis on. The table for this looks like this:
+-----+------+------+------+------+-----+------+------+------+------+
| id | 10_1 | 10_2 | 11_1 | 11_2 | id | 10_1 | 10_2 | 11_1 | 11_2 |
+-----+------+------+------+------+-----+------+------+------+------+
| 111 | 1 | 0 | 1 | 0 | 222 | 1 | 0 | 1 | 0 |
| 111 | 1 | 0 | 1 | 0 | 333 | 0 | 0 | 0 | 0 |
| 111 | 1 | 0 | 1 | 0 | 444 | 1 | 0 | 1 | 1 |
| 112 | 0 | 1 | 1 | 0 | 222 | 1 | 0 | 1 | 0 |
+-----+------+------+------+------+-----+------+------+------+------+
The ids in the first column are different from the ids in the sixth column.
In a row are always two different IDs that are matched with each other. The other columns always have either 0 or 1 as a value.
I am now trying to find out how many values(meaning both have "1" in 10_1, 10_2 etc) two IDs have on average in common, but I don't really know how to do so.
I was trying something like this as a start:
SELECT SUM(CASE WHEN a.10_1 = 1 AND b.10_1 = 1 then 1 end)
But this would obviously only count how often two ids have 10_1 in common. I could make something like this for example for different columns:
SELECT SUM(CASE WHEN (a.10_1 = 1 AND b.10_1 = 1)
OR (a.10_2 = 1 AND b.10_1 = 1) OR [...] then 1 end)
To count in general how often two IDs have one thing in common, but this would of course also count if they have two or more things in common. Plus, I would also like to know how often two IDS have two things, three things etc in common.
One "problem" in my case is also that I have like ~30 columns I want to look at, so I can hardly write down for each case every possible combination.
Does anyone know how I can approach my problem in a better way?
Thanks in advance.
Edit:
A possible result could look like this:
+-----------+---------+
| in_common | count |
+-----------+---------+
| 0 | 100 |
| 1 | 500 |
| 2 | 1500 |
| 3 | 5000 |
| 4 | 3000 |
+-----------+---------+
With the codes as column names, you're going to have to write some code that explicitly references each column name. To keep that to a minimum, you could write those references in a single union statement that normalizes the data, such as:
select id, '10_1' where "10_1" = 1
union
select id, '10_2' where "10_2" = 1
union
select id, '11_1' where "11_1" = 1
union
select id, '11_2' where "11_2" = 1;
This needs to be modified to include whatever additional columns you need to link up different IDs. For the purpose of this illustration, I assume the following data model
create table p (
id integer not null primary key,
sex character(1) not null,
age integer not null
);
create table t1 (
id integer not null,
code character varying(4) not null,
constraint pk_t1 primary key (id, code)
);
Though your data evidently does not currently resemble this structure, normalizing your data into a form like this would allow you to apply the following solution to summarize your data in the desired form.
select
in_common,
count(*) as count
from (
select
count(*) as in_common
from (
select
a.id as a_id, a.code,
b.id as b_id, b.code
from
(select p.*, t1.code
from p left join t1 on p.id=t1.id
) as a
inner join (select p.*, t1.code
from p left join t1 on p.id=t1.id
) as b on b.sex <> a.sex and b.age between a.age-10 and a.age+10
where
a.id < b.id
and a.code = b.code
) as c
group by
a_id, b_id
) as summ
group by
in_common;
The proposed solution requires first to take one step back from the cross-join table, as the identical column names are super annoying. Instead, we take the ids from the two tables and put them in a temporary table. The following query gets the result wanted in the question. It assumes table_a and table_b from the question are the same and called tbl, but this assumption is not needed and tbl can be replaced by table_a and table_b in the two sub-SELECT queries. It looks complicated and uses the JSON trick to flatten the columns, but it works here:
WITH idtable AS (
SELECT a.id as id_1, b.id as id_2 FROM
-- put cross join of table a and table b here
)
SELECT in_common,
count(*)
FROM
(SELECT idtable.*,
sum(CASE
WHEN meltedR.value::text=meltedL.value::text THEN 1
ELSE 0
END) AS in_common
FROM idtable
JOIN
(SELECT tbl.id,
b.*
FROM tbl, -- change here to table_a
json_each(row_to_json(tbl)) b -- and here too
WHERE KEY<>'id' ) meltedL ON (idtable.id_1 = meltedL.id)
JOIN
(SELECT tbl.id,
b.*
FROM tbl, -- change here to table_b
json_each(row_to_json(tbl)) b -- and here too
WHERE KEY<>'id' ) meltedR ON (idtable.id_2 = meltedR.id
AND meltedL.key = meltedR.key)
GROUP BY idtable.id_1,
idtable.id_2) tt
GROUP BY in_common ORDER BY in_common;
The output here looks like this:
in_common | count
-----------+-------
2 | 2
3 | 1
4 | 1
(3 rows)
I have two tables on SQL-Server. One containing clients, and one a client profile lookup table. So a bit like this (note that Fred doesn't have any values in the lookup table):
Table: Clients Table: Profile
ID | Name | Status ClientID | Type | Value
----------------------- -----------------------
1 | John | Current 1 | x | 1
2 | Peter | Past 1 | y | 2
3 | Fred | Current 2 | x | 3
2 | y | 4
I then am trying to create a tmp table that needs to contain all current clients like this:
ID | Name | TypeY
==================
1 | John | 2
3 | Fred |
My knowledge of SQL is limited, but I think I should be able to do this with a Left Join, so I tried this (#tmpClient is already created):
insert into #tmpClient
select a.ID, a.Name, b.Value
from Clients a
left join Profile b
on a.ID = b.ClientID
where a.Status = 'Current' and b.Type = 'y'
However this will always miss Fred out of the temporary table. I am probably doing something very simple wrong, but as I said I am missing the SQL skills to work this one out. Please can someone help me with getting this query right.
You have to move the predicate concerning the second table of the LEFT JOIN operation from WHERE to ON clause:
insert into #tmpClient
select a.ID, a.Name, b.Value
from Clients a
left join Profile b
on a.ID = b.ClientID and b.Type = 'y'
where a.Status = 'Current'
I have two tables with a many to many relationship and I am trying to merge the 2 tables in a select statement. I want to see all of the records from both tables, but only match 1 record from table A to 1 record to table b, so null values are ok.
For example table A has 20 records that match only 15 records from table B. I want to see all 20 records, the 5 that are unable to be matched can show null.
Table 1
Something | Code#
apple | 75
pizza | 75
orange | 6
Ball | 75
green | 4
red | 6
Table 2
date | id#
Feb-15 | 75
Feb-11 | 75
Jan-10 | 6
Apr-08 | 4
The result I need is
Something | Date | Code# | ID#
apple | Feb-15 | 75 | 75
pizza | Feb-11 | 75 | 75
orange | Jan-10 | 6 | 6
Ball | NULL | 75 | NULL
green | Apr-08 | 4 | 4
red | NULL | 6 | NULL
I'm imagining something like this. You want to pair of the rows side by side but one side is going to have more than the others.
select * /* change to whatever you need */
from
(
select *, row_number() over (partition by "code#" order by "something") as rn
from tableA
) as a
full outer join /* sounds like maybe left outer join will work too */
(
select *, row_number() over (partition by "id#" order by "date" desc) as rn
from tableB
) as b
on b."id#" = a."code#" and b.rn = a.rn
Actually I don't know how you're going to get "ball" to comes after "apple" and "pizza" without some other column to sort on. Rows in SQL tables don't have any ordering and you can't rely on the default listing from select *... or assume that the order of insertion is significant.
A regular Left-join should do it for you.
select tableA.*
, tableB.*
from tableA
left join tableB
on tableB.PrimaryKey = tableA.PrimaryKey
we would need to see the table structure to tell you for sure, but essentially you join on the full key (if possible)
SELECT * FROM TABLEA A
JOIN TABLEB B ON
A.FULLKEY = B.FULLKEY
Left outer join
Question changed
Make that a full outer join
select table1.*, table2.*
from table1
full outer join table2
on table1.Code# = table2.id#
This is probably not a true many to many but I think this is what you are asking for