So I'm trying to update data from a temporary table into a main table.
Let's call these tables temp, and services.
The pseudocode would be something like this...
Sort temp by inserted_on
When service_id and location match in both tables:
If temp.column1 is not null, replace services.column1
If temp.column2 is not null, replace services.column2
etc...
I've got this bit working, although when I have multiple source rows in the temp table that match the condition, not all fields are being updated.
For example, I might have two rows with identical service_id and location, in one row column1 is null and column2 has a value, and in the next row the opposite is true. I need to update these one by one in the order they came in, and overwrite old data if necessary.
I also need to join the temp table inside the UPDATE to retrieve the keys I'm matching on.
I've tried the below code, but it only seems to be updating certain rows, and I can't quite figure out what the logic is behind it.
I'm not worried about the order, I'm just trying to figure out why it's leaving some blanks when there is data ready to fill the gaps.
UPDATE sloc
SET
sloc.ata = COALESCE(tmp.ata, sloc.ata),
sloc.atd = COALESCE(tmp.atd, sloc.atd),
sloc.atp = COALESCE(tmp.atp, sloc.atp),
sloc.eta = COALESCE(tmp.eta, sloc.eta),
sloc.etd = COALESCE(tmp.etd, sloc.etd),
sloc.etp = COALESCE(tmp.etp, sloc.etp),
sloc.plat = COALESCE(tmp.plat, sloc.plat),
sloc.plats_up = COALESCE(tmp.plats_up, sloc.plats_up),
sloc.cis_plats_up = COALESCE(tmp.cis_plats_up, sloc.cis_plats_up)
FROM
services_locations sloc
INNER JOIN services svc ON svc.id = sloc.sid
INNER JOIN ref_tiploc tloc ON tloc.id = sloc.tpl_id
INNER JOIN trainstatus_tmp tmp ON svc.rid = tmp.rid AND tloc.tpl = tmp.tpl
Related
So, I have a table table with three columns I am interested in : value, entity and field_entity.
There are other columns that are not important for this question. There are many different types of entity, and some of them can have the same field_entity, but those two columns determine what the column value refers to (if it is an id number for a person or the address or some other thing)
If I need the name of a person I would do something like this:
select value from table where entity = 'person' and field_entity = 'person_name';
My problem is I need to get a lot of different values (names, last names, address, documents, etc.), so the way I am doing it now is using a left join like this:
select
doc_type.value as doc_type,
doc.value as doc,
status.value as status
from
table doc
-- Get doc type
left join table doc_type
on doc.entity = doc_type.entity
and doc.transaction_id = doc_type.transaction_id
and doc_type.field_entity = 'document_type'
-- Get Status
left join table status
on doc.entity = status.entity
and doc.transaction_id = status.transaction_id
and status.field_entity = 'status'
where doc.entity = 'users' and doc.field_entity = 'document' and doc.transaction_id = 11111;
There are 16 values or more, and this can get a bit bulky and difficult to maintain, so I was wondering if some of you can point out a better way to do this?
Thanks!
I assume that you are not in position to alter the table structure, but can you add views to the database? If so, you can create views based on the different types of entities in your table.
For example:
CREATE VIEW view_person AS
SELECT value AS name
FROM doc
WHERE doc.entity = 'person'
AND doc.field_entity = 'name';
Then you can write clearer queries:
SELECT view_person.name FROM view_person;
I am trying to update field value from one table to another.
Item with bomRev='A' in Destination table look like show below
Same Item bomRev='A' in source table looks like
I want to update partid field in destination table for bomRev=A by the value in Source filed i want to destination looks exactly like the source.
I tried this but no luck
UPDATE [MIBOMD]
SET [MIBOMD].[partId] = [assy].[partId]
FROM [MIBOMD] INNER JOIN [assy] ON [MIBOMD].[partId] = [assy].[partId]
WHERE bomRev='A' and [bomItem]='600797' AND [MIBOMD].[partId]!=[assy].[partId];
UPDATE m
SET [partId] = a.[partId]
FROM
[MIBOMD] m
INNER JOIN
[assy] a
ON m.[bomItem] = a.[ItemId]
AND m.bomEntry = a.bomEntry
WHERE
m.bomRev='A'
AND m.[bomItem]='600797'
AND m.[partId]!=a.[partId];
You actually were pretty close! Just a couple of key differences. Before I explain I have used Table Aliases in the code I provided it is a shorthand way of referring to the table throughout the query that will make it a little easier to follow and read. To Alias a table after the table name in the from statement simply add a space and an alias or a space " AS " alias.
Now your Join as on partid in your version and that was your main issue. Because you want the records where partid are not the same so you can change the partid of the assy table. Looking at your dataset I was able to determine that the shared key was mibomd.bomItem and assy.ItemId. After clearing that up everything should be good.
Per your comment the only other thing that needed to be added was a second condition on the join to make it unique. [MIBOMD].bomEntry = assy.bomEntry
A little about join conditions. Typically you always want to figure out what the unique relationship between the 2 tables are (bomItem = ItemId and bomEntry = bomEntry) and that is what will go in the ON area of the join. Rarely that will be different and will be for very specific purposes.
Per your comment on how to insert the missing records
INSERT INTO MIBOMD (bomItem, bomRev, bomEntry, lineNbr, dType, partId)
SELECT
bomItem = a.ItemId
,bomRev = 'A' --or change the value to what you want
,a.bomEntry
,lineNbr = ???? --not sure how you are figure this out do if you wan it to be the next line number you can figure that out automatically if you need
,a.partId
FROM
assy a
LEFT JOIN MIBOMD m
ON a.ItemId = m.bomItem
AND a.bomEntry = m.bomEntry
WHERE
m.bomItem IS NULL
This time you would use a left join from assy to mibomd and figure out when they don't match mibomd.bomItem IS NULL
I have one table named: ORDERS
this table contains OrderNumber's which belong to the same person and same address lines for that person.
However sometimes the data is inconsistent;
as example looking at the table screenshot: Orders table with bad data to fix -
you all can noticed that orderNumber 1 has a name associated to and addresses line1-2-3-4. sometimes those are all different by some character or even null.
my goal is to update all those 3 lines with one set of data that is already there and set equally all the 3 rows.
to make more clear the result expected should be like this:
enter image description here
i am currently using a MERGE statement to avoid a CURSOR (for loop )
but i am having problems to make it work
here the SQL
MERGE INTO ORDERS O USING
(SELECT
INNER.ORDERNUMBER,
INNER.NAME,
INNER.LINE1,
INNER.LINE2,
INNER.LINE3,
INNER.LINE4
FROM ORDERS INNER
) TEMP
ON( O.ORDERNUMBER = TEMP.ORDERNUMBER )
WHEN MATCHED THEN
UPDATE
SET
O.NAME = TEMP.NAME,
O.LINE1 = TEMP.LINE1,
O.LINE2 = TEMP.LINE2,
O.LINE3 = TEMP.LINE3,
O.LINE4 = TEMP.LINE4;
the biggest issues i am facing is to pick a single row out of the 3 randomly - it does not matter whihc of the data - row i pick to update the line/s
as long i make the records exaclty the same for an order number.
i also used ROWNUM =1 but it in multip[le updates will only output one row and update maybe thousand of lines with the same address and name whihch belong to an order number.
order number is the join column to use ...
kind regards
A simple correlated subquery in an update statement should work:
update orders t1
set (t1.name, t1.line1, t1.line2, t1.line3, t1.line4) =
(select t2.name, t2.line1, t2.line2, t2.line3, t2.line4
from orders t2
where t2.OrderNumber = t1.OrderNumber
and rownum < 2)
I have moved an expiration date from one table to another. Since I created the new column, some new dates have been added, but most are still set to NULL.
I need to copy the dates from the original table and column (a) to the new table and column (b) only if b is NULL and this is marked as a system.
I have created the below statement, but it throws an error. I think I might have to use FROM, but I'm relatively new to T-SQL, and have had no experience with it before. Does anyone see where I have made my mistake?
UPDATE purchs
SET purchs.dexpiredate = client.dexpire
FROM
INNER JOIN client ON client.iclientid = purchs.iclientid
INNER JOIN feature ON purchs.ifeatureid = feature.ifeatureid
WHERE feature.lsystem = 1 and purchs.dexpiredate IS NULL
GO
UPDATE p
SET p.dexpiredate = c.dexpire
FROM purchs p
INNER JOIN client c ON c.iclientid = p.iclientid
INNER JOIN feature f ON f.ifeatureid = p.ifeatureid
WHERE
f.lsystem = 1 and
p.dexpiredate IS NULL
I have a table CustPurchase (name, purchase) and another table CustID (id, name).
I altered the CustPurchase table to have an id field. Now, I want to populate this newly created field by referencing the customer ids from the CustID table, using:
UPDATE CustPurchase
SET CustPurchase.id = CustID.id
WHERE CustPurchase.name = CustID.name;
I keep getting syntax errors!
I believe you are after the useful UPDATE FROM syntax.
UPDATE CustPurchase SET id = CI.id
FROM
CustPurchase CP
inner join CustID CI on (CI.name = CP.name)
This might have to be the following:
UPDATE CustPurchase SET id = CI.id
FROM
CustID CI
WHERE
CI.name = CustPurchase.name
Sorry, I'm away from my Postgres machine; however, based upon the reference, it looks like this is allowable. The trouble is whether or not to include the source table in the from_list.
Joining by name is not an ideal choice, but this should work:
UPDATE custpurchase
SET id = (SELECT c.id
FROM CUSTID c
WHERE c.name = custpurchase.name)
The caveat is that if there's no match, the value attempting to be inserted would be NULL. Assuming the id column won't allow NULL but will allow duplicate values:
UPDATE custpurchase
SET id = (SELECT COALESCE(c.id, -99)
FROM CUSTID c
WHERE c.name = custpurchase.name)
COALESCE will return the first non-NULL value. Making this a value outside of what you'd normally expect will make it easier to isolate such records & deal with appropriately.
Otherwise, you'll have to do the updating "by hand", on a name by name basis, to correct instances that SQL could not.