Abstract
I have one main table with columns named A through Z. I have a dozen other tables that also have strictly letter-named columns (same data types too), just not all columns from A to Z. (e.g. one tables may contain columns A,C,H while another contains columns A,B,C,X,Y,Z etc)
Assuming main table has defaults for all columns A through Z, is there a way to select every other tables' records into it without specifying each column name?
I know it is best to be explicit, but in reality I'm dealing with hundreds of fields, not 26, so I'm hoping there's a better way that's eluded me.
Concrete
I am trying to store annual data in one table (has additional year column). Each year, all existing fields remain from the previous year, but new fields may be added. I have imported each year's data into its own table (25 of them) and would like to consolidate. Most recent year/main table contains hundreds of columns.
I found a similar question here Insert into table from another with different columns count (MySql) but answer lists all columns explicitly in insert.
Understanding that there could be various reasons to do this, I think you would better off be looking at something like table inheritance to provide a unified query interface for previous tables. There are of course difficulties here. But that is probably a better solution if you can. Note the adding new fields would be very different if you go with inheritance.
The next option you would have would be to create an SQL mapping for each table to the archive table. So if you have an additional year int field, you need to fill you could:
CREATE FUNCTION mytable_to_archive(mytable) returns archive language sql as
$$
select $1.*, null::int as year;
$$ IMMUTABLE;
Note for performance reasons, this just takes in a tuple, and returns a tuple. No db lookups. Then you could:
INSERT INTO archive
SELECT (mytable_to_archive(mytable)).* from mytable;
Related
I have different tables in my scheme with different columns, but I want to store data of when was the table modified or when was the data stored, so I added some columns to specify that.
I realized that I had to add the same "modification_date" and "modification_time" columns to all my tables, so I thought about making a new table called DATA_INFO so I won't need to do so, but every table has a different PRIMARY KEY and I don't know which one to add as FOREIGN KEY to the DATA_INFO table.
I don't know if I have to maybe add all of them or is there another way to do what I need.
It's better to have the same "modification_datetime" column in all tables, rather than trying to keep that data in a central table.
That's what we have done at every shop I've worked in.
I want to emphasize that a separate table is not reasonable for this purpose. The lack of an obvious foreign key is a hint.
Unlike Tab Allerman, tables that I create are much less likely to be updated, so I have three additional columns on most tables:
CreatedBy -- the user who created the row
CreatedAt -- when the row was creatd
CreatedOn -- the system where the table was created
The most important point is that this information can -- in many databases -- be implemented using default values rather than triggers. That is a big advantage of working within a single row. The fewer triggers, the better.
In our database we have many tables with a 'Notes' column. This is important functionality, but for most rows the value of Notes is null. These tables have many columns and we would like to remove some columns for better legibility.
We could add one Notes table for every table that has a notes column. But this would create clutter of a different kind- too many small tables.
My idea is to create a generic Notes table and also a reference table. The Notes table would have a column for the notes text, a column for the id of the row being linked to, and a foreign key to the reference table. The reference table would have a text value for each table for which we need notes. Using these two tables we should be able to link the note back to whichever table and column it came from.
By using this solution, we remove any cases of null values from notes and also slim down some of our tables. All at the modest price of two additional tables. It feels very 'hacky' to me however. Is there a reason why using a 'generic' id column or a reference table of other tables is a bad idea from a DB management perspective?
Managing the references to disparate entities can be really challenging in SQL Server. Postgres, by contrast, supports inheritance which makes this much simpler.
So, my recommendation is to add a notes column to every entity where you want notes. You an add a view to bring all the notes together if you need a view of all the notes.
This has minimal impact on performance or data size. There is no additional overhead for a varchar column, other than the additional NULL bit -- and that is pretty minimal.
IMO, the other solution of managing two tables doesn't bring in much efficiency but adds complexity to the solution. You should probably stick with the the notes column in the original table with datatype as varchar.
Generic id column is not bad inherently but the use of it generally gives smell of bad/hacky design.
Additionaly for SQL Server you can use sparse for the note columns to reduce size.
But i used a similary approach myself. (Note column needed for many columns to write info / changerequest / lockcomment. But normally never used).
Works fine and can be programmed genericaly in source.
But if you need only one comment column per table i wood prefer sparse
I want to try and create a boolean table with the same structure as another table. I know how to create the table but my issue is the updating.
Lets say i have the table A1 with 10 columns with different attributes for a person such as, height, run speed, name, hair colour etc.
I then want to be able to modifiy this table by either removing or adding columns to table A1 and these updates apply to my other column B1 so it has the same columns but a boolean value (the boolean value is not based on A1).
My first question is if it's doable.
My second is: Will the updates be super ineffecient for lets say 200-300 records.
(I could probably create an external program that reads the table and manually removes and adds columns via ADD/DROP sql statements, but i was hoping there was a more dynamic/efficent solution)
What you want, as another answer posted, is EAV schema "entity - attribute - value". This allows you to dynamically add new attributes without changing any physical table schema. It is also horrible for performance (but with only a few hundred entities it shouldn't be too bad).
Another equally ugly solution is to add as many columns as you think you'll ever need, named Attribute_1, Attribute_2, etc. Then you have a lookup table which allows you to map attributes to their definitions.
This is less flexible than the EAV schema, but allows you to index on specific attributes so that your queries are a little more performant.
Another solution would be to use XML data types to hold the attributes and values. SQL Server has built-in functionality for XML data, while it's not as easy to use as normal SQL, it does work quite well.
Rather than add and subtract columns to the table. I would suggest that you have a table with the fixed attributes. Then have another table which stores additional attributes (the names of the columns) then a third table which holds the id of the person, the is off the attribute and the value of the attribute.
For example the user table :
UserId
Firstname
Surname
The attribute table
AttrId
AttrName
The UserAttribute table:
UserId
AttrId
AttrValue
For this to answer your question you could have two sets of these tables but the AttrValue would be boolean for the second table.
An intermediate option is to go for multiple spare columns in the table and use the attribute table to store a column name and a boolean to indicate if the column is in use
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 am refactoring an old Oracle 10g schema to try to introduce some normalization. In one of the larger tables, there is a text field that has at most, 10-15 possible values. In my mind, it seems that this field is an example of unnecessary data duplication and should be extracted to a separate table.
After examining the data, I cannot find one relevant piece of information that could be associated with that text value. Basically, if I pulled that value out and put it into its own table, it would be the only field in that table. It exists today as more of a 'flag' field. Should I create a two-column table with a surrogate key, keep it as it is, or do something entirely different? Am I doing more harm than good by trying to minimize data duplication on this field?
You might save some space by extracting the column to a separate table. This is called a lookup table. It can give you a couple of other benefits:
You can declare a foreign key constraint to the lookup table, so you can rely on the column in the main table never having any value other than the 10-15 values you want.
It's easy to query for a concise list of all permitted values, by querying the lookup table. This can be faster than using SELECT DISTINCT on the main table's column. It also returns values that are permitted, but not currently used in the main table.
If you change a value in the lookup table, it automatically applies to all rows in the main table that reference it.
However, creating a lookup table with one column is not strictly normalization. You're just replacing one value with another. The attribute in the main table either already supports a normal form, or not.
Using surrogate keys (vs. natural keys) also has nothing to do with normalization. A lot of people make this mistake.
However, if you move other attributes into the lookup table, attributes that depend only on the lookup value and therefore would create repeating groups (violating 3NF) in the main table if you left them there, then that would be normalization.
If you want normalization break it out.
I think of these types of data in DBs as the equivalent of enums in C,C++,C#. Mostly you put them in the table as documentation.
I often have an ID, Name, Description, and auditing columns for them (eg modified by, modified date, create date, create by, active.) The description field is rarely used.
Example (some might say there are more than just 2)
Gender
ID Name Audit Columns...
1 Male
2 Female
Then in your contacts you would have a GenderID column which would link to this one.
Of course you don't "need" the table. You could have external documentation somewhere that says 1=Male, 2=Female -- but I think these tables serve to document a system.
If it's really a free-entry text field that's not re-used somewhere else in the database, and there's just a single field without repeated instances, I'd probably go ahead and leave it as it is. If you're determined to break it out I'd create a 'validation' table with a surrogate key and the text value, then put the surrogate key in the base table.
Share and enjoy.
Are these 10-15 values actually meaningful, or are they really just flags? If they're meaningful pieces of text and it seems wasteful to replicate them, then sure create a lookup table. But if they're just arbitrary flag values, then your new table will be nothing more than a mapping from one arbitrary value to another, and not terribly helpful.
A completely separate question is whether all or most of the rows in your big table even have a value for this column. If not, then indeed you have a good opportunity for normalization and can create a separate table linking the primary key from your base table with the flag value.
Edit: One thing. If there's some chance that one of these "flag" values is likely to be wholesale replaced with another value at some point in the future, that would be another good reason to create a table.