A bit of background...my company utilizes a piece of software that stores information about a mortgage loan in independent fields. These fields are broken up across many tables in the loan database.
My current dilemma revolves around designing a view(s) that will allow me to find mismatched data on a subset of loans from the underwriting side of our software and the lock side of our software.
Here is a quick example of the data returned from the two views that already exist:
UW View
transID | DTIField | LTVField | MIField
50000 | 37.5 | 85.0 | 1
Lock View
transID | DTIField | LTVField | MIField
50000 | 42.0 | 85.0 | 0
In the above situation, the view should return the fields that are not matching (in this case the DTIField and the MIField). I have built a comparison view that uses a series of CASE statements to return either a 0 for not matched or a 1 for matched already:
transID | DTIField | LTVField | MIField
50000 | 0 | 1 | 0
This is fine in itself but it is creating a bit of an issue downstream on the reporting side. We want to be able to build a report that would display only those transIDs that have mismatched data and show which columns are not matched. Crystal Reports is the reporting solution in question.
Some specifics about the data sets...we have 27 items of the loan that we are comparing (so a total 54 fields). There are over 4000 loans in the system and growing. There are already indexes on the transID fields.
How would you structure the view to return all the data needed for the report? We can do a good amount of work in Crystal Reports but ideally much of the logic would be handled in MSSQL.
Thanks for any assistance.
I think there should be no issue in comparing the 27 columns for a given row. Since you'll be reading the row just once and comparing the columns on that row in both the tables, it shouldn't really pose any performance issues. You can use some hash functions HASHBYTES to assign a hash value to the combination of these 27 fields in both the tables and then use this field to compare which rows should be returned by the view. This should result in some performance improvement. Testing will reveal more.
I have to create a database combined with 4 types of xls files, for example A, B, C and D. Every year new file is created, starting from 2004. A have 7 sheets with 800-1000 rows, B - D have one sheet with max 200 rows.
Everyone knows that people are lazy, so in excel files, address data are stored differently in each sheet. One of them, from 2008, have address data stored separately, but every other sheets have this data combined into one column.
Sooo, here is a question - how should I design a datatable? Something like this?
+---------+----------+----------+-------------+--------------------------------+
| Street | House Nr | City | Postal Code | Combined Address |
+---------+----------+----------+-------------+--------------------------------+
| Street1 | 20 | Somwhere | 00-000 | null |
| Street2 | 98 | Elswhere | 99-999 | null |
| null | null | null | null | Somwhere 00-000, street3 29 |
| null | null | null | null | st. Street2 65 12-345 Elswhere |
+---------+----------+----------+-------------+--------------------------------+
There will be a lot of nulls, so maybe best solution would be 2 different tables?
Most important thing is that users will search by using this data, and in the future add data into that database without excel files.
There are at least two different angles of view here: Normalization and efficiency, leading to different results.
Normalization
If this is the most important criterion you would make even three tables. Obviously Combined Address needs a place of it's own, but also Postal Code and City have to be stored into another table, because there is a dependency between them. Just one of the two, most probably Postal Code will stay. (Yes, there even is sth. about Street and Postal Code too, but I'm clearly not going to be pedantic.)
Efficiency
Normalization as an end in itself doesn't necessarily make the best result. If you permit yourself to be a bit sloppy on that and leave it the way it is in the model you posted, things might become easier in coding. You could use a trigger to make sure Combined Address is never null or use a (materialized) view that pretends it is and just search in Combined Address for the time being.
Imagine the effort if you use different tables and there is a need for referencing these addresses in other tables (Which table to use when? How to provide a unique id? Clearly a problem.).
So, decide on what's more important.
If I'm not mistaken we are taking about some 2000 rows or some 8000 rows if it is '7 sheets with 800-1000 rows each' actually. Even if the latter applies this isn't a number that makes data correction impracticable. If the number of different input pattern in the combined column is low, you might be able to do this (partly) automatically and just have some-one prove reading.
So you might want to think about a future redesign as well and choose what's more convenient in this case.
Taking MySQL as an example DB to perform this in (although I'm not restricted to Relational flavours at this stage) and Java style syntax for model / db interaction.
I'd like the ability to allow versioning of individual column values (and their corresponding types) as and when users edit objects. This is primarily in an attempt to drop the amount of storage required for frequent edits of complex objects.
A simple example might be
- Food (Table)
- id (INT)
- name (VARCHAR(255))
- weight (DECIMAL)
So we could insert an object into the database that looks like...
Food banana = new Food("Banana",0.3);
giving us
+----+--------+--------+
| id | name | weight |
+----+--------+--------+
| 1 | Banana | 0.3 |
+----+--------+--------+
if we then want to update the weight we might use
banana.weight = 0.4;
banana.save();
+----+--------+--------+
| id | name | weight |
+----+--------+--------+
| 1 | Banana | 0.4 |
+----+--------+--------+
Obviously though this is going to overwrite the data.
I could add a revision column to this table, which could be incremented as items are saved, and set a composite key that combines id/version, but this would still mean storing ALL attributes of this object for every single revision
- Food (Table)
- id (INT)
- name (VARCHAR(255))
- weight (DECIMAL)
- revision (INT)
+----+--------+--------+----------+
| id | name | weight | revision |
+----+--------+--------+----------+
| 1 | Banana | 0.3 | 1 |
| 1 | Banana | 0.4 | 2 |
+----+--------+--------+----------+
But in this instance we're going to be storing every single piece of data about every single item. This isn't massively efficient if users are making minor revisions to larger objects where Text fields or even BLOB data may be part of the object.
What I'd really like, would be the ability to selectively store data discretely, so the weight could possible be saved in a separate DB in its own right, that would be able to reference the table, row and column that it relates to.
This could then be smashed together with a VIEW of the table, that could sort of impose any later revisions of individual column data into the mix to create the latest version, but without the need to store ALL data for each small revision.
+----+--------+--------+
| id | name | weight |
+----+--------+--------+
| 1 | Banana | 0.3 |
+----+--------+--------+
+-----+------------+-------------+-----------+-----------+----------+
| ID | TABLE_NAME | COLUMN_NAME | OBJECT_ID | BLOB_DATA | REVISION |
+-----+------------+-------------+-----------+-----------+----------+
| 456 | Food | weight | 1 | 0.4 | 2 |
+-----+------------+-------------+-----------+-----------+----------+
Not sure how successful storing any data as blob to then CAST back to original DTYPE might be, but thought since I was inventing functionality here, why not go nuts.
This method of storage would also be fairly dangerous, since table and column names are entirely subject to change, but hopefully this at least outlines the sort of behaviour I'm thinking of.
A table in 6NF has one CK (candidate key) (in SQL a PK) and at most one other column. Essentially 6NF allows each pre-6NF table's column's update time/version and value recorded in an anomaly-free way. You decompose a table by dropping a non-prime column while adding a table with it plus an old CK's columns. For temporal/versioning applications you further add a time/version column and the new CK is the old one plus it.
Adding a column of time/whatever interval (in SQL start time and end time columns) instead of time to a CK allows a kind of data compression by recording longest uninterupted stretches of time or other dimension through which a column had the same value. One queries by an original CK plus the time whose value you want. You dont need this for your purposes but the initial process of normalizing to 6NF and the addition of a time/whatever column should be explained in temporal tutorials.
Read about temporal databases (which deal both with "valid" data that is times and time intervals but also "transaction" times/versions of database updates) and 6NF and its role in them. (Snodgrass/TSQL2 is bad, Date/Darwen/Lorentzos is good and SQL is problematic.)
Your final suggested table is an example of EAV. This is usually an anti-pattern. It encodes a database in to one or more tables that are effectively metadata. But since the DBMS doesn't know that you lose much of its functionality. EAV is not called for if DDL is sufficient to manage tables with columns that you need. Just declare appropriate tables in each database. Which is really one database, since you expect transactions affecting both. From that link:
You are using a DBMS anti-pattern EAV. You are (trying to) build part of a DBMS into your program + database. The DBMS already exists to manage data and metadata. Use it.
Do not have a class/table of metatdata. Just have attributes of movies be fields/columns of Movies.
The notion that one needs to use EAV "so every entity type can be
extended with custom fields" is mistaken. Just implement via calls
that update metadata tables sometimes instead of just updating regular
tables: DDL instead of DML.
Context: simple webapp game for personal learning purposes, using postgres. I can design it however I want.
2 tables 1 view (there are additional tables view references that aren't important)
Table: Research
col: research_id (foreign key to an outside table)
col: category (integer foreign key to category table)
col: percent (integer)
constraint (unique combination of the three columns)
Table: Category
col: category_id (primary key auto inc)
col: name(varchar(255))
notes: this table exists to capture the 4 categories of research I want in business logic and which I assume is not best practice to hardcode as columns in the db
View: Research_view
col: research_id (from research table)
col: foo1 (one of the categories from category table)
col: foo2 (etc...)
col: other cols from other joins
notes:has insert/update/delete statements that uses above tables appropriately
The research table itself I worry qualifies as a "Skinny Table" (hadn't heard the term until I just saw it in the Ibatis manning book). For example test data within it looks like:
| research_id | percent | category |
| 1 | 25 | 1 |
| 1 | 25 | 2 |
| 1 | 25 | 3 |
| 1 | 25 | 4 |
| 2 | 20 | 1 |
| 2 | 30 | 2 |
| 2 | 25 | 3 |
| 2 | 25 | 4 |
1) Does it make sense to have all columns in a table collectively define unique entries?
2) Does this 'smell' to you?
Couple of notes to start:
constraint (unique combination of the three columns)
It makes no sense to have a unique constraint that includes a single-column primary key. Including that column will cause every row to be unique.
notes: this table exists to capture the 4 categories of research I want in business logic and which I assume is not best practice to hardcode as columns in the db
If a research item/entity is required to have all four categories defined for it to be valid, they should absolutely be columns in the research table. I can't tell definitively from your statement whether this is the case or not, but your assumption is faulty if looked at in isolation. Let your model reflect reality as closely as possible.
Another factor is whether it's a requirement that additional categories may be added to the system post-deployment. Whether the categories are intended to be flexible vs. fixed should absolutely influence the design.
1) Does it make sense to have all columns in a table collectively
define unique entries?
I would say it's not common, but can imagine there are situations where it might be appropriate.
2) Does this 'smell' to you?
Hard to say without more details.
All that said, if the intent is to view and add research items with all four categories, I would say (again) that you should consider whether the four categories are semantically attributes of the research entity.
As a random example, things like height and weight might be considered categories of a person, but they would likely be stored flat on the person table, and not in a separate table.
Consider this table:
+-------+-------+-------+-------+
| name |hobby1 |hobby2 |hobby3 |
+-------+-------+-------+-------+
| kris | ball | swim | dance |
| james | eat | sing | sleep |
| amy | swim | eat | watch |
+-------+-------+-------+-------+
There is no priority on the types of hobbies, thus all the hobbies belong to the same domain. That is, the hobbies in the table can be moved on any hobby# column. It doesn't matter on which column, a particular hobby can be in any column.
Which database normalization rule does this table violate?
Edit
Q. Is "the list of hobbies [...] in an arbitrary order"?
A. Yes.
Q. Does the table have a primary key?
A. Yes, suppose the key is an AUTO_INCREMENT column type named user_id.
The question is if the columns hobby# are repeating groups or not.
Sidenote: This is not a homework. It's kind of a debate, which started in the comments of the question SQL - match records from one table to another table based on several columns. I believe this question is a clear example of the 1NF violation.
However, the other guy believes that I "have fallen fowl of one of the fallacies of 1NF." That argument is based on the section "The ambiguity of Repeating Groups" of the article Facts and Fallacies about First Normal Form.
I am not writing this to humiliate him, me, or whomever. I am writing this, because I might be wrong, and there is something I am clearly missing and maybe this guy is not explaining it good enough to me.
You say that the hobbies belong to the same domain and that they can move around in the columns. If by this you mean that for any specific name the list of hobbies is in an arbitrary order and kriss could just as easily have dance, ball, swim as ball, swim, dance, then I would say you have a repeating group and the table violates 1NF.
If, on the other hand, there is some fundamental semantic difference between a particular person's first and second hobbies, then there may be an argument for saying that the hobbies are not repeating groups and the table may be in 3NF (assuming that hobby columns are FK to a hobby table). I would suggest that this argument, if it exists, is weak.
One other factor to consider is why there are precisely 3 hobbies and whether more or fewer hobbies are a potential concern. This factor is important not so much for normalization as for flexibility of design. This is one reason I would split the hobbies into rows, even if they are semantically different from one-another.
Your three-hobby table design probably violates what I usually call the spirit of the original 1NF (probably for the reasons given by dportas and others).
It turns out however, that it is extremely difficult to find [a set of] formal and precise "measurable" criteria that accurately express that original "spirit". That's what your other guy was trying to explain talking about "the ambiguity of repeating groups".
Stress "formal", "precise" and "measurable" here. Definitions for all other normal forms exist that satisfy "formal", "precise" and "measurable" (i.e. objectively observable). For 1NF it's just hard (/impossible ???) to do. If you want to see why, try this :
You stated that the question was "whether those three hobby columns constitute a repeating group". Answer this question with "yes", and then provide a rigorous formal underpinning for your answer.
You cannot just say "the column names are the same, except for the numbered suffix". Making a violation of such a rule objectively observable/measurable would require to enumerate all the possible ways of suffixing.
You cannot just say "swim, tennis" could equally well be "tennis, swim", because getting to know that for sure requires inspecting the external predicate of the table. If that is just "person <name> has hobby <hobby1> and also has <hobby2>" , then indeed both are equally valid (aside : and due to the closed world assumption it would in fact require all possible permutations of the hobbies to be present in the table !!!). However, if that external predicate is "person <name> spends the most time on <hobby1> and the least on <hobby2>", then "swim, tennis" could NOT equally well be "tennis,swim". But how do you make such interpretations of the external predicate of the table objective (for ALL POSSIBLE PREDICATES) ???
etc. etc.
This clearly "looks" like a design error.
It's not not a design error when this data is simply stored and retrieved. You need only 3 of the hobbies and you don't intend to use this data in any other way than retrieve.
Let's consider this relationship:
Hobby1 is the main hobby at some point in a person's life (before 18 years of age for example)
Hobby2 is the hobby at another point (19-30)
Hobby3 is her hobby at a another one.
Then this table seems definitely well designed and while the 1NF convention is respected the naming arguably "sucks".
In the case of an indiscriminate storage of hobbies this is clearly wrong in most if not all cases I can think of right now. Your table has duplicate rows which goes against the 1NF principles.
Let's not consider the reduced efficiency of SQL requests to access data from this table when you need to sort the results for paging or any other practical reason.
Let's take into consideration the effort required to work with your data when your database will be used by another developer or team:
The data here is "scattered". You have to look in multiple columns to aggregate related data.
You are limited to only 3 of the hobbies.
You can't use simple rules to establish unicity (same hobby only once per user).
You basically create frustration, anger and hatred and the Force is disturbed.
Well,
The point is that, as long as all hobby1, hobby2 and hobby3 values are not null, AND names are unique, this table could be considered more or less as abbiding by 1NF rules (see here for example ...)
But does everybody has 3 hobbies? Of course not! Do not forget that databases are basically supposed to hold data as a representation of reality! So, away of all theories, one cannot say that everybody has 3 hobbies, except if ... our table is done to hold data related to people that have three hobbies without any preference between them!
This said, and supposing that we are in the general case, the correct model could be
+------------+-------+
| id_person |name |
+------------+-------+
for the persons (do not forget to unique key. I do not think 'name' is a good one
+------------+-------+
| id_hobby |name |
+------------+-------+
for the hobbies. id_hobby key is theoretically not mandatory, as hobby name can be the key ...
+------------+-----------+
| id_person |id_hobby |
+------------+-----------+
for the link between persons and hobbies, as the physical representation of the many-to-many link that exists between persons and their hobbies.
My proposal is basic, and satisfies theory. It can be improved in many ways ...
Without knowing what keys exist and what dependencies the table is supposed to satisfy it's impossible to determine for sure what Normal Form it satisfies. All we can do is make guesses based on your attribute names.
Does the table have a key? Suppose for the sake of example that Name is a candidate key. If there is exactly one value permitted for each of the other attributes for each tuple (which means that no attribute can be null) then the table is in at least First Normal Form.
If any of the columns in the table accept nulls then then the table violates first normal form. Assuming no nulls, #dportas has already provided the correct answer.
The table does not violate first normal form.
First normal form does not have any prohibition against multiple columns of the same type. As long as they have distinct column names, it is fine.
The prohibition against "Repeating Groups" concerns nested records - a structure which is common in hierarchical databases, but typically not possible in relational databases.
The table using repeating groups would look something like this:
+-------+--------+
| name |hobbies |
+-------+--------+
| kris |+-----+ |
| ||ball | |
| |+-----+ |
| ||swim | |
| |+-----+ |
| ||dance| |
| |+-----+ |
+-------+--------+
| james |+-----+ |
| ||eat | |
| |+-----+ |
| ||sing | |
| |+-----+ |
| ||sleep| |
| |+-----+ |
+-------+--------+
| amy |+-----+ |
| ||swim | |
| |+-----+ |
| ||eat | |
| |+-----+ |
| ||watch| |
| |+-----+ |
+-------+--------+
In a table conforming to 1NF all values can be located though table name, primary key, and column name. But this is not possible with repeated groups, which require further navigation.