Want to create a query that will join 3 tables together (a, b, c). Then update a specific cell in b.1, based on the subtraction of two specific cells in table b( b.2 - b.3).
Any help would be appreciated.
UPDATE b
SET b.c1 = b.c2 - b.c3
FROM a
JOIN b ON ...
JOIN c ON ...
Related
sorry for the late response.
For a key in table A, there may be 2 or more records present in tables B and C. That is, one another column in these tables will have a date value which would be making the keys unique. So I want to extract the record that has maximum date value. And that's why I am using the max function. I know that the subquery which I have coded should not be included in the ON clause and it would do the filtering before the join statement. So eventually I want to know how to mention the max clause in the query.
Example:
Table A
Key - AAAAA
Table B:
Record 1
Key - AAAAA
Date - 2017-10-01
Record 2
Key - AAAAA
Date - 2017-10-05
I want the only the record AAAAA/2017-10-05 to be selected from the table B
Basically records from table A where A.c3 = 'Y' should be extracted first (assume it gives 500 records)
Then join these 500 records with tables B and C (left outer, to have all the matching records and the non-matching records should have nulls in the columns from the tables B and C)
In tables B and C, if more than 1 record present with different dates, the maximum date field should be extracted.
Hence final output should contain 500 records.
This is all you need for what you describe
SELECT A.A1, A.A2, B.B1, B.B2, C.C1, C.C2
FROM TABLE1 A
LEFT OUTER JOIN TABLE2 B
ON A.A1 = B.B1
LEFT OUTER JOIN TABLE3 C
ON A.A1 = C.C1
WHERE A.C3 = ‘Y’
These lines are causing your problem...basically forcing your outer joins to an inner joins.
AND B.C3 = (SELECT MAX(B3) FROM TABLE2 T1
WHERE T1.B1 = B.B1)
AND C.C3 = (SELECT MAX(C3) FROM TABLE3 T1
WHERE T1.C1 = C.C1)
If there's no match in B or C , then B.C3 and/or C.C3 will be NULL and NULL can't be = to anything (or <> to anything for that matter)
What are you trying to accomplish with the above that you've not included in the question?
Just do it?
SELECT A.A1, A.A2, B.B1, B.B2, C.C1, C.C2
FROM TABLE1 A
LEFT OUTER JOIN TABLE2 B
ON A.A1 = B.B1
LEFT OUTER JOIN TABLE3 C
ON A.A1 = C.C1
WHERE A.C3 = 'Y' and (B.B1 is null or C.B1 is null)
I am joining tbl_A to tbl_B, on column CustomerID in tbl_A to column Output in tbl_B which contains customer ID. However, tbl_B has all other information in related rows that I do not want to lose when joining. I tried to join using like, but I lost rows that did not contain customer ID in the output column.
Here is my join query in Hive:
select a.*, b.Output from tbl_A a
left join tbl_B b
On b.Output like concat('%', a.CustomerID, '%')
However, I lose other rows from output.
You could also achieve the objective by a simple hive query like this :)
select a.*, b.Output
from tbl_A a, tbl_B b
where b.Output like concat('%', a.CustomerID, '%')
I would suggest first extract all ID's from free floating field which in your case is 'Output' column in table B into a separate table. Then join this table with ID's to Table B again to populate in each row the ID and then this second joined table which is table B with ID's to table A.
Hope this helps.
I have the need to join a huge table (10 million plus rows) to a lookup table (15k plus rows) with an OR condition. Something like:
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t2.d)
FROM table1 t1
JOIN table2 t2 ON t1.c = t2.c OR t1.d = t2.d;
This is because table1 can have c or d as NULL, and I'd like to join on whichever is available, leaving out the rest. The query plan says there is a Nested Loop, which I realize is because of the OR condition. Is there a clean, efficient way of solving this problem? I'm using Redshift.
EDIT: I am trying to run this with a UNION, but it doesn't seem to be any faster than before.
If you have a preferred column you can NVL() (aka COALESCE()) them and join on that.
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t2.d)
FROM table1 t1
JOIN table2 t2
ON t1.c = NVL(t2.c,t2.d);
I'd also suggest that you should set the lookup table to DISTSTYLE ALL to ensure that the larger table is not redistributed.
[ Also, 10 million rows isn't big for Redshift. Not trying to be snotty just saying that we get excellent performance on Redshift even when querying (and joining) tables with hundreds of billions of rows. ]
How about doing two (left) joins? With the small lookup table performance shouldn't be too bad even.
SELECT t1.a, t1.b, nvl(t1.c, t2.c), nvl(t1.d, t3.d)
FROM table1 t1
LEFT JOIN table2 t2 ON t1.d = t2.d and t1.c is null
LEFT JOIN table2 t3 ON t1.c = t3.c and t1.d is null
Your original query only returns rows that match at least one of c or d in the lookup table. If that's not guaranteed you may need to add filters...for example rows in t1 where both c and d are null or have values not present in table2.
Don't really need the null checks in the joins, but might be slightly faster.
I was trying to get only selected rows from table A(not all rows) and rows matching table A from table B, but it shows only matching rows from table A and table B, excluding rest of the selected rows from table A.
I used this condition,
SELECT A.CategoryName,B.discount
from A LEFT JOIN B ON A.CategoryCode = B.CategoryCode
WHERE A.itemtype='F' and B.party_code=2
i have 2 tables:
table 1: A with 3 columns
CategoryName,CategoryCode(PK),ItemType
table 2: B with 2 columns
CategoryCode(FK),Discount,PartyCode(FK)(from another table)
NOTE: working in access 2007
For non-matching rows from table B, party_code = NULL, so your where clause will evaluate to false and therefore the row won't be returned. So, you need to filter the "B" records before joining. Try
SELECT A.CategoryName,B.discount
from A LEFT JOIN B ON A.CategoryCode = B.CategoryCode and B.party_code=2
WHERE A.itemtype='F'
[EDIT] That doesn't work in Access. next try.
You can create a query to do your filter. Let's call it "B_filtered". This is just
SELECT * FROM B where party_code = 2
(You could make the "2" a parameter to make it more flexible).
Then, just use this query in your actual query.
SELECT A.CategoryName,B_filtered.discount
from A LEFT JOIN B_filtered ON A.CategoryCode = B_filtered.CategoryCode
WHERE A.itemtype='F'
[EDIT]
Just Googled - I think you can do this directly with a subquery.
SELECT A.CategoryName,B_filtered.discount
from A LEFT JOIN (SELECT * FROM B where party_code = 2) AS B_filtered ON A.CategoryCode = B_filtered.CategoryCode
WHERE A.itemtype='F'
What mlinth proposed is correct, and would work for most other SQL languages. The query below is the same basic concept but using a null condition.
Try:
SELECT A.CategoryName,B.discount
from A LEFT JOIN B ON A.CategoryCode = B.CategoryCode
WHERE A.itemtype='F' and (B.party_code=2 OR B.party_code IS NULL)
If party_code is nullable, switch to using the PK or another non-nullable field.
I have a hive table A with 5 columns, the first column(A.key) is the key and I want to keep all 5 columns. I want to select 2 columns from B, say B.key1 and B.key2 and 2 columns from C, say C.key1 and C.key2. I want to join these columns with A.key = B.key1 and B.key2 = C.key1
What I want is a new external table D that has the following columns. B.key2 and C.key2 values should be given NULL if no matching happened.
A.key, A_col1, A_col2, A_col3, A_col4, B.key2, C.key2
What should be the correct hive query command? I got a max split error for my initial try.
Does this work?
create external table D as
select A.key, A.col1, A.col2, A.col3, A.col4, B.key2, C.key2
from A left outer join B on A.key = B.key1 left outer join C on A.key = C.key2;
If not, could you post more info about the "max split error" you mentioned? Copy+paste specific error message text is good.