I've taken over a oracle DB which is a bit of a mess.
There is a data table, which collect various data sets. However 2 of the fields were put as free sections with no validation against each one.
I'm planning to make this a joint drop-down from data from a junction table to collect correct combinations that are allowed. But first I need the flag the incorrect information, so I can forward this on to be changed. using oracle. how do I validated the 2 tables against each other and flag. I think its some joins and case but just can not figure this one out.
I need to show the relevant junction ID and err in not in the junction table. Please example below. All help will be welcome.
Maybe some thing like -
SELECT D.Job_date,
D.acc,
D.task,
NVL (to_Char(J.a_t_id), 'err') AS Junc_tbl_id
FROM DATA_TBL D
LEFT JOIN Junc_tbl J ON D.acc = J.acc AND D.task = J.task;
Here is the sqlfiddle.
Related
SELECT DISTINCT
...
...
...
FROM Reviews Rev
INNER JOIN Reviews SubRev ON Subrev.W_ID=Rev.ID
WHERE Rev.Status='Approved'
This is a small part of a long query that I've been trying to understand for a day now. What is happening with the join? Reviews table appears to be joined with itself, under different aliases. Why is this done? What does it achieve? Also, ID field of the Reviews table is null for the entries that are nevertheless selected and returned. This is correct, but I don't understand how that can happen if the W_ID field is not null.
It allows you to join one row from the table to a different row in the table.
I've both seen this done, and used it myself, in cases where you maybe have a relationship between those rows.
Real-world examples:
An old version of a record and a newer version
Some sort of hierarchical relationship (e.g. if the table contains records of people, you can record that someone is a parent of someone else). There are probably plenty of other possible use cases, too.
SQL allows you to create a foreign key which relates between two different columns in the same table.
I have a table joined from two other tables. I would like this table to stay updated with entries in the other two tables.
First Table is "employees"
I am using the ID, Last_Name, and First_Name.
And the second Table is "EmployeeTimeCardActions"
using columns ID, ActionTime, ActionDate, ShiftStart, and ActionType.
ID is my common column that the join was created by..Joined Table...
Because I usually have a comment saying I did not include enough information, I do not need a exact specific code sample and I think I have included everything needed. If there is a good reason to include more I will, I just try to keep as little company information public as possible
Sounds like you're having your data duplicated across tables. Not a smart idea at all. You can update data in one table when a row is updated in a different one via triggers but this is a TERRIBLE approach. If you want to display data joined from 2 tables, the right approach here is using an SQL VIEW which will display the current data.
I have the following tables:
In table 2 (yellow looking fields), the first field is part of the following:
name1 RECORD NULLABLE
name1. name2 RECORD REPEATED
name1.name2. date_inserted TIMESTAMP NULLABLE
As you can see the last (sub-row?) of the row 25 is greyed because it is part of the repeated record name1.name2
I am trying to join table 2, with table 1(orange looking fields) on another field. I have 0 experience with records or repeated records but using FLATTEN() I managed to join them.
The problem is, I noticed that some dates from the 2nd after the join return NULL although there aren't any NULLS before it. So since I can't figure out what the greyed cells are I guess I am doing something wrong.
All this sums up to: How can I totally flatten all tables that I want to use so that there won't be any records at all and so I can go through the data with simple SQL statements? Please provide an example as well. Looking for something generic.
How can I totally flatten all tables that I want to use so that there won't be any records at all and so I can go through the data with simple SQL statements?
It really depends on the schemas you are working with. You can preprocess them, flatten the arrays and rename the structs fields, then use that as your base table to work with simple SQL statements
For your scenario, you can start by flattening the table 2, name2 column like this
SELECT
name2.date_inserted -- Add additional fields you want on the result
FROM table2, table2.name1.name2
You can do CROSS JOIN and LEFT JOIN to further adjust your results.
Please provide an example as well. Looking for something generic.
I'm not sure about a generic approach, since each schema would probably have distinct requirements. The key concept is to know how to flatten arrays and how to query struct with arrays and arrays of structs
You can find plenty examples in that documentation
I'm trying to achieve 2 joins. If I run the 1st join alone it pulls 4 lots of results, which is correct. However when I add the 2nd join which queries the same reference table using the results from the select statement it pulls in additional results. Please see attached. The squared section should not be being returned
So I removed the 2nd join to try and explain better. See pic2. I'm trying to get another column which looks up InvolvedInternalID against the initial reference table IRIS.Practice.idvClient.
Your database is simply doing as you tell it. When you add in the second join (confusingly aliased as tb1 in a 3 table query) the database is finding matching rows that obey the predicate/truth statement in the ON part of the join
If you don't want those rows in there then one of two things must be the case:
1) The truth you specified in the ON clause is faulty; for example saying SELECT * FROM person INNER JOIN shoes ON person.age = shoes.size is faulty - two people with age 13 and two shoes with size 13 will produce 4 results, and shoe size has nothing to do with age anyway
2) There were rows in the table joined in that didn't apply to the results you were looking for, but you forgot to filter them out by putting some WHERE (or additional restriction in the ON) clause. Example, a table holds all historical data as well as current, and the current record is the one with a NULL in the DeletedOn column. If you forget to say WHERE deletedon IS NULL then your data will multiply as all the past rows that don't apply to your query are brought in
Don't alias tables with tbX, tbY etc.. Make the names meaningful! Not only do aliases like tbX have no relation to the original table name (so you encounter tbX, and then have to go searching the rest of the query to find where it's declared so you can say "ah, it's the addresses table") but in this case you join idvclient in twice, but give them unhelpful aliases like tb1, tb3 when really you should have aliased them with something that describes the relationship between them and the rest of the query tables
For example, ParentClient and SubClient or OriginatingClient/HandlingClient would be better names, if these tables are in some relationship with each other.
Whatever the purpose of joining this table in twice is, alias it in relation to the purpose. It may make what you've done wriong easier to spot, for example "oh, of course.. i'm missing a WHERE parentclient.type = 'parent'" (or WHERE handlingclient.handlingdate is not null etc..)
The first step to wisdom is by calling things their proper names
Let's say i have 1 query, 1 main table and 2 left joins. Query looks like (for example)
SELECT "E.name",
D."title"
FROM "Employees" AS E
LEFT JOIN "Department" AS D
ON E."depid" = D."id_dep"
So now i want to change the information directly in the DBGrid. I put dataset into Edit mode, but as a result i can only edit columns which refers to Employees table, and not Department.
I know, that this method is not very correct, it would be easier and more correct to use UPDATE request, but this is a requirment of the customer. Thank you for reply
Instead of one query you should use two datasets with Master-Detail Relationship to work on each dataset (Create, Read, Update, Delete).
The documentation will guide you on how to Creating Master-Detail Relationships