I have two oracle databases who share database objects for example:
Table: PRICE
I am looking to come up with a efficient way of comparing the table object between the two databases. I expect them to be identical, but there can be differences as a new patch could be applied to one of the environments let's say.
I have been looking at potential solutions and I had a look at using Oracle's DBMS_COMPARISON package to compare the two database on the object:
Here is the Link
The issue I am having is that my requirement involves looking at key, values for each of the objects. For example:
Table Key Compare
PRICE Code,Type,Date,Currency Price
USER USER_ID FIRST_NAME, LAST_NAME, DOB
My question is...is there a way I can specify the key columns and specify the field to compare? Or Do I need to create temp tables and then compare the temp tables instead of the actual tables?
I'm looking to output the column where the difference is in. Appreciate if you guys can show me an example :)
Thanks in Advance
Related
I have a table let's say products like this:
Id
Description
Category_Id
Location_Id
Seller
what is the correct way of storing the id of category and location? I was told by a programmer that i have to make a table let's say tblChoices like this:
Id
Code
Value
and to use as value of code 'category' for categories and value of code 'location' for locations. then store the description in the value field.
Is this the correct approach or is it better to use a table for category, and a different table for location? How the 2 ways affect speed of retrieving data? the one way surely has less tables but uses the same table many times with joins to retrieve data
The general approach is to use a different table for categories and for locations.
Why? You can declare foreign key relationships, which in turn help you maintain data integrity.
There are some situations where you might want to store all reference tables in a single table -- for instance, it can be easier to translate the database into another language.
In general, though, you want separate reference tables. After all, you might have additional columns such as categories.long_term or locations.country.
I have lots of sql tables. The tables are "dependent" , i.e. constraints on foreign keys are defined between the tables.
I need to transfer the tables from sql to csv. What is correct way to do that:
Define tables exactly as they are defined in sql? (What should I do with the foreign keys?)
Try to generate other tables by joining the existing ones based on foreign keys in order to hide the foreign keys dependencies?
May be there are other options? What are the pros and cons ?
Thanks,
Note:This is need for another application that run some anylitics on the data
I would suggest to create a view in SQL which contains all information from all tables you need in your CSV later.
The view already implements the dependencies (link of two rows from different tables) and linkes all together in one table.
It would be way easier than your second proposal to create a new table because the view will do all the work for you.
I guess you will need your dependencies.
So you should not ignore them.
Here a quick example how they work:
Lets say you have 2 Tables the first one is named persons and the second one is cars. In the persons table you have 3 columns: ID, Name, Age. In the second one you have ID, Car. To see which person has which car you just check which id from the first table has which value for car in the second one.
If you link them together in a view the result is one single table with the columns ID, Person, Age, Car.
Same does the view.
Later you can simply export the view to CSV.
Maybe I can help you better if you define your needs a bit more detailed.
What kind of data is in your tables, how are they linked(what are the primary/secondary keys).
I have a problem with finding a way to represent multiple tables hash tables into a single table.
Say I have 3 tables with the format:
Table1(Table1_PK1,Table1_PK2,Table1_PK3,Table1_Hash)
Table2(Table2_PK1,Table2_PK2,Table2_Hash)
Table3(Table3_Pk1,Table3_PK2,Table3_PK3,Table3_PK4,Table3_PK5,Table3_Hash)
Table1_PK1,Table1_PK2,Table1_PK3... are columns and they might have different datatypes (VARCHAR, INT or DATETIME ...).
My question is if there is a way to create a single table (fixed number of columns) that can represent all of these 3 tables (may be more in practical).
I am trying to do this for my database tool. Each table actual a table which contains primary keys and a hash data associating with them.
Since you're apparently building a database tool, not a database, it might make more sense to do this in application code rather than in a database table.
In a different answer, you commented
I am still looking for a dynamic way to do it without knowing how many primary keys a table can have.
A table can have only one primary key. That primary key can consist of more than one column, though. (You already knew this; you were just using the wrong words, which might confuse others.)
A table can also have an arbitrary number of other keys, which will be either declared (as NOT NULL UNIQUE) or "undeclared" (by creating an index that guarantees uniqueness over a set of columns).
You can look all that stuff up at run time in one or both of two ways. (Links go to documentation for PostgreSQL.)
System tables, sometimes called system catalogs
information_schema views
As far as I know, all modern SQL platforms implement at least one of these interfaces. The information_schema views are covered in the SQL standards, but there seems to be some room for interpretation. They don't look quite the same on all platforms.
Why combine the 3 tables into one? Would be really bad db design. But here's a way to do it:
The one table will have a column for each of the 3 tables' columns you want in the final table. I am making the assumption that TableX_Hash is the same type, so that remains as one unique column:
Table_All_in_One (
Table1_PK1,
Table1_PK2,
Table1_PK3,
# space just for clarity of grouping
Table2_PK1,
Table2_PK2,
Table3_PK1,
Table3_PK2,
Table3_PK3,
Table3_PK4,
Table3_PK5,
TableX_Hash # Assuming all the _Hash'es are the same type+length,
# otherwise, add Table1_Hash, Table2_Hash, Table3_Hash
# This can be your new primary key
)
The Primary Keys (PKx) are required to be non-NULL only in their own tables. For this table, they have to allow nulls. The idea is that each row of this new table will only hold the data for one of the tables. The other columns will be empty for that row. If you want to associate the row of one table with another, you can add that to the same row or add FK_Table1_Hash, FK_Table2_Hash and FK_Table3_Hash columns which will refer to the TableX_Hash value of a record.
PS: I wonder if what you are really looking for is a View and not this really bad all-in-one table.
Edit: Combining them into one "without knowing how many primary keys a table can have." as per your comment:
Store all the _PKs concatenated into one column:
Table_All_in_One (
New_PK,
TableX_Hash,
Table1_PKx, # Concatenated PKs of Table1
Table2_PKx, # Concatenated PKs of Table2, etc.
...,
# OR just one
TableX_PKs, # concatenate all the PK's into one VARCHAR field
# Add a pipe `|` between them optionally.
Table_Num # If using just one, then you'll need to store the table number
)
You will not be able to conveniently pick records based on part of their composite primary key. It will always have to be TableX_PKs = CONCAT_WS('|', Table1_PK1, Table1_PK2, ...). So your only dependency is the number of PKs in the original column.
In order to model a bunch of tables you will need 3 tables. An entity table that contains the table names of the tables you wish to set up this way called a factor or entity table. A Factor_detail table that contains all the columns and their associated properties of the tables. A table, factor_detail_value, for storing things like lookup values for lookup tables. I'm trying to learn more about this myself as well because we are using this technique at work as well. Genrate sql on the fly for any table so encoded, and store the data in a repository pertiinant to the data itself. This way if a table changes and you need to add a column or change a datatype, you can add a row to the factor detail table without affecting a database shut down in production. In most businesses a four hour shut down to make a sql data table change can cost thousands of dollars. If you are dealing with insurance for example, each additional state that you sell insurance in has different requirements for being able to seel it and that will result in table changes. We reduced our table count way down from over 700 tables in this manner also we can make changes without database shut down thus avoiding the loss in revenue.
I have a table of People, and a table of Service Tickets. Service Tickets refer to 1+ People, and over time People are likely to be associated with multiple Tickets. What is the best way to represent this relationship in a SQL database?
It seems like my two options are to create 'enough' columns to contain all the person id's i should need, or a single huge string column that is processed CSV style after being fetched from the database. Both of these options have a maximum capacity, which seems like a bad design, and the second design means we can't join using the person id's.
A little background - I'm implementing a fairly small database as part of the backend for a class project. I've never really worked with SQL and what I know is self taught.
I feel like this is has to be a duplicate question, but I'm unable to find anything similar.
No, if this si a MANY to MANY relation ship, creat the table accordingly.
Create a table, something like
PeopleServiceLink:
PersonID,
ServieTicketID,
PRIMARY KEY (PersonID, ServieTicketID)
Have a read hear at Understanding SQL: Many to Many Relationships
For many-to-many relationship generally create three tables: Tickets(id, ...), People(id,...) and join table like TicketsPeopleJoin(ticketId, peopleId)
Create a separate tickets_people table which has person_id & ticket_id columns.
Relationship tables mostly contain two columns: IDTABLE1, and IDTABLE2.
Only thing that seems to change between relationship tables is the names of those two columns, and table name.
Would it be better if we create one table Relationships and in this table we place 3 columns:
TABLE_NAME, IDTABLE1, IDTABLE2, and then use this table for all relationships?
Is this a good/acceptable solution in web/desktop application development? What would be downside of this?
Note:
Thank you all for feedback. I appreciate it.
But, I think you are taking it a bit too far... Every solution works until one point.
As data storage simple text file is good till certain point, than excel is better, than MS Access, than SQL Server, than...
To be honest, I haven't seen any argument that states why this solution is bad for small projects (with DB size of few GB).
It would be a monster of a table; it would also be cumbersome. Performance-wise, such a table would not be a great idea. Also, foreign keys are impossible to add to such a table. I really can't see a lot of advantages to such a solution.
Bad idea.
How would you enforce the foreign keys if IDTABLE1 could contain ids from any table at all?
To achieve acceptable performance on joins without a load of unnecessary IO to bring in completely unrelated rows you would need a composite index with leading column TABLE_NAME that basically ends up partitioning the table into sections anyway.
Obviously even with this pseudo partitioning going on you would still be wasting a lot of space in the table/indexes just repeating the table name for each row.
Isn't it a big IF that you're only going to store the 2 ID fields? If I have a StudentCourse (or better yet Enrollment) table that has StudentID & CourseID, but wouldn't EnrollmentDate go in this table as well since not all students enroll on the first day of class. Seems like a bad idea to add this column to an already bloated table where most records will be null.
The benefit of a single table could be a requirement that the application has the ability to allow user/admin to create these relationships with data (Similar to have a single lookup or reference list table) and avoid having to create a new table to address these User Created References. Needing dynamic querying may benefit as well. An application that requires such dynamic data structure requirements might be better suited for a schemaless or nosql database.