My application has one table called 'events' and each event has approx 30 standard fields, but also user defined fields that could be any name or type, in an 'eventdata' table. Users can define these event data tables, by specifying x number of fields (either text/double/datetime/boolean) and the names of these fields. This 'eventdata' (table) can be different for each 'event'.
My current approach is to create a lookup table for the definitions. So if i need to query all 'event' and 'eventdata' per record, i do so in a M-D relaitionship using two queries (i.e. select * from events, then for each record in 'events', select * from 'some table').
Is there a better approach to doing this? I have implemented this so far, but most of my queries require two distinct calls to the DB - i cannot simply join my master 'events' table with different 'eventdata' tables for each record in in 'events'.
I guess my main question is: can i join my master table with different detail tables for each record?
E.g.
SELECT E.*, E.Tablename
FROM events E
LEFT JOIN 'E.tablename' T ON E._ID = T.ID
If not, is there a better way to design my database considering i have no idea on how many user defined fields there may be and what type they will be.
There are four ways of handling this.
Add several additional fields named "Custom1", "Custom2", "Custom3", etc. These should have a datatype of varchar(?) or similiar
Add a field to hold the unstructured data (like an XML column).
Create a table of name /value pairs which are associated with some type of template. Let them manage the template. You'll have to use pivot tables or similiar to get the data out.
Use a database like MongoDB or another NoSql style product to store this.
The above said, The first one has the advantage of being fast but limits the number of custom fields to the number you defined. Older main frame type applications work this way. SalesForce CRM used to.
The second option means that each record can have it's own custom fields. However, depending on your database there are definite challenges here. Tried this, don't recommend it.
The third one is generally harder to code for but allows for extreme flexibility. SalesForce and other applications have gone this route; including a couple I'm responsible for. The downside is that Microsoft apparently acquired a patent on doing things this way and is in the process of suing a few companies over it. Personally, I think that's bullcrap; but whatever. Point is, use at your own risk.
The fourth option is interesting. We've played with it a bit and the performance is great while coding is pretty darn simple. This might be your best bet for the unstructured data.
Those type of joins won't work because you will need to pivot the eventdata table to make it columns instead of rows. Therefore it depends on which database technology you are using.
Here is an example with MySQL: How to pivot a MySQL entity-attribute-value schema
My approach would be to avoid using a different table for each event, if that's possible.
I would use something like:
Event (EventId, ..., ...)
EventColumnType (EventColumnTypeId, EventTypeId, ColumnName)
EventColumnData (EventColumnTypeId, Data)
You are them limited to the type of data you can store (everything would have to be strings, for example), but you the number of events and columns are unrestricted.
What I'm getting from your description is you have an event table, and then a separate EventData table for each and every event.
Rather than that, why not have a single EventCustomFields table that contains a foreign key to the event table, a field Name (event+field being the PK) and a field value.
Sure it's not the best. You'd be stuck serializing the value or storing everything as a string. And you'd still be stuck doing two queries, one for the event table and one to get it's custom fields, but at least you wouldn't have a new table for every event in the system (yuck x10)
Another, (arguably worse) option is to serialize the custom fields into a single column of the and then deserialize when you need. So your query would be something like
Select E.*, C.*
From events E, customFields C
Where E.ID = C.ID
Is it possible to just impose a limit on your users? I know the tables underneath Sharepoint 2007 had a bunch of columns for custom data that were just named like CustomString1, CustomDate2, etc. That may end up easier than some of the approaches above, where everything is in one column (though that's an approach I've taken as well), and I would think it would scale up better.
The answer to your main question is: no. You can't have different rows in the result set with different columns. The result set is kind of like a table, so each row has to have the same columns. You can fake it with padding and dummy columns, but that's probably not much better.
You could try defining a fixed event data table, with (say) ten of each type of column. Then you'd store the usage metadata in a separate table and just read that in at system startup. The metadata would tell you that event type "foo" has a field "name" mapped to column string0 in the event data table, a field named "reporter" mapped to column string1, and a field named "reportDate" mapped to column date0. It's ugly and wastes space, but it's reasonably flexible. If you're in charge of the database, you can even define a view on the table so to the client it looks like a "normal" table. If the clients create their own tables and just stick the table name in the event record, then obviously this won't fly.
If you're really hardcore you can write a database procedure to query the table structures and serialize everything to a lilst of key/type/value tuples and return that in one long string as the last column, but that's probably not much handier than what you're doing now.
Related
To keep this as short as possible I'm going to use and example.
So let's say I have a simple database that has the following tables:
company - ( "idcompany", "name", "createdOn" )
user - ( "iduser", "idcompany", "name", "dob", "createdOn" )
event - ( "idevent", "idcompany", "name", "description", "date", "createdOn" )
Many users can be linked to a single company as well as multiple events and many events can be linked to a single company. All companies, users and events have columns as show above in common. However, what if I wanted to give my customers the ability to add custom fields to both their users and their events for any unique extra information they wish to store. These extra fields would be on a company wide basis, not on a per record basis ( so a company adding a custom field to their users would add it to all of their users not just one specific user ). The custom fields also need to be sesrchable and have the ability to be reported on, ideally automatically with some sort of report wizard. Considering the database is expected to have lots of traffic as well as lots of custom fields, what is the best solution for this?
My current research and findings in possible solutions:
To have generic placeholder columns such as "custom1", "custom2" etc.
** This is not viable as there will eventually be too many custom columns and there will be too many NULL values stored in the database
To have 3x tables per current table. eg: user, user-custom-field, user-custom-field-value. The user table being the same. The user-custom-field table containing the information about the new field such as name, data type etc. And the user-custom-field-value table containing the value for the custom field
** This one is more of a contender if it were not for its complexity and table size implications. I think it will be impossible to avoid a user-custom-field table if I want to automatically report on these fields as I will have to store the information on how to report on these fields here. However, In order to pull almost any data you would have to do a million joins on the user-custom-field-value table as well as the fact that your now storing column data as rows which in a database expected to have a lot of traffic as well as a lot of custom fields would soon cause a problem.
Create a new user and event table for each new company that is added to the system removing the company id from within those tables and instead using it in the table name ( eg user56, 56 being the company id ). Then allowing the user to trigger DB commands that add the new custom columns to the tables giving them the power to decide if it has a default value or auto increments etc.
** Everytime I have seen this solution it has always instantly been shut down by people saying it would be unmanageable as you would eventually get thousands of tables. However nobody really explains what they mean by unmanageable. Firstly as far as my understanding goes, more tables is actually more efficient and produces faster search times as the tables are much smaller. Secondly, yes I understand that making any common table changes would be difficult but all you would have to do is run a script that changes all your tables for each company. Finally I actually see benefits using this method as it would seperate company data making it impossible for one to accidentally access another's data via a potential bug, plus it would potentially give the ability to back up and restore company data individually. If someone could elaborate on why this is perceived as a bad idea It would be appreciated.
Convert fully or partially to a NoSQL database.
** Honestly I have no experience with schemaless databases and don't really know how dynamic user defined fields on a per record basis would work ( although I know it's possible ). If someone could explain the implications of the switch or differences in queries and potential benefits that would be appreciated.
Create a JSON column in each table that requires extra fields. Then add the extra fields into that JSON object.
** The issue I have with this solution is that it is nearly impossible to filter data via the custom columns. You would not be able to report on these columns and until you have received and processed them you don't really know what is in them.
Finally if anyone has a solution not mentioned above or any thoughts or disagreements on any of my notes please tell me as this is all I have been able to find or figure out for myself.
A typical solution is to have a JSON (or XML) column that contains the user-defined fields. This would be an additional column in each table.
This is the most flexible. It allows:
New fields to be created at any time.
No modification to the existing table to do so.
Supports any reasonable type of field, including types not readily available in SQL (i.e. array).
On the downside,
There is no validation of the fields.
Some databases support JSON but do not support indexes on them.
JSON is not "known" to the database for things like foreign key constraints and table definitions.
When I create a view I can base it on multiple columns from different tables.
When I want to create a lookup table I need information from one table, for example the foreign key of an order table, to get customer details from another table. I can create a view having parameters to make sure it will get all data that I need. I could also - from what I have been reading - make a lookup table. What is the difference in this case and when should I choose for a lookup table?? I hope this ain't a bad question, I'm not very into db's yet ;).
Creating a view gives you a "live" representation of the data as it is at the time of querying. This comes at the cost of higher load on the server, because it has to determine the values for every query.
This can be expensive, depending on table sizes, database implementations and the complexity of the view definition.
A lookup table on the other hand is usually filled "manually", i. e. not every query against it will cause an expensive operation to fetch values from multiple tables. Instead your program has to take care of updating the lookup table should the underlying data change.
Usually lookup tables lend themselves to things that change seldomly, but are read often. Views on the other hand - while more expensive to execute - are more current.
I think your usage of "Lookup Table" is slightly awry. In normal parlance a lookup table is a code or reference data table. It might consist of a CODE and a DESCRIPTION or a code expansion. The purpose of such tables is to provide a lsit of permitted values for restricted columns, things like CUSTOMER_TYPE or PRIORITY_CODE. This category of table is often referred to as "standing data" because it changes very rarely if at all. The value of defining this data in Lookup tables is that they can be used in foreign keys and to populate Dropdowns and Lists Of Values.
What you are describing is a slightly different scenario:
I need information from one table, for
example the foreign key of an order
table, to get customer details from
another table
Both these tables are application data tables. Customer and Order records are dynamic. Now it is obviously valid to retrieve additional data from the Customer table to display along side the Order data, and in that sense Customer is a "lookup table". More pertinently it is the parent table of Order, because it has the primary key referenced by the foreign key on Order.
By all means build a view to capture the joining logic between Order and Customer. Such views can be quite helpful when building an application that uses the same joined tables in several places.
Here's an example of a lookup table. We have a system that tracks Jurors, one of the tables is JurorStatus. This table contains all the valid StatusCodes for Jurors:
Code: Value
WS : Will Serve
PP : Postponed
EM : Excuse Military
IF : Ineligible Felon
This is a lookup table for the valid codes.
A view is like a query.
Read this tutorial and you may find helpful info when a lookup table is needed:
SQL: Creating a Lookup Table
Just learn to write sql queries to get exactly what you need. No need to create a view! Views are not good to use in many instances, especially if you start to base them on other views, when they will kill performance. Do not use views just as a shorthand for query writing.
I want to design a table for items.
There are many types of items, all share several fields.
Each type of item has it's own fields.
I want to store the uncommon fields in a separate table.
I thought of something like :
----Items
+Item_id
+Item_Type_Id
+Item_Serial
...
----Item_types
+Item_Type_Id
+Item_Name
...
----Item_Fields
+Item_Field_Id
+Item_Type_Id
+Field_Name
...
----Field_Values
+Field_Value_Id
+Item_Field_Id
+Item_Id
+Value
...
The pro is having the ability to add fields and values without changing the tables.
The con is that i have to transpose the field names and values in order to see all info for an item.
Any better suggestions? Or perhaps a simple (not stored procedure) way to join the tables to get a flat info?
I tried to use PIVOT (I'm using SQL 2005) but with no luck.
Thanks.
I wrote a stored proc to make PIVOT more useful. Here is the source:
http://dot-dash-dot.com/files/pivot_query.sql
and some examples how to use it:
http://dot-dash-dot.com/files/pivot_query_examples.sql
For your data, the query would just be the raw data joining those tables above to produce a raw listing of:
set #myQuery = '
Select Item_Id, Item_Name, Field_Name, Value From ...
';
Then your call to pivot_query would be:
exec pivot_query #myQuery, 'Item_Id, Item_Name', 'Field_Name', 'max(Value)'
like that.
One other option is to store items in XML format in one single field. Depending on your usage scenario, it may work well. Or it may not.
I believe there has to be some grouping of values.
For example lets say your items are objects in a room. Then different types of objects have different attributes. For example books have publication date and number of pages, chairs have color pattern and height, etc.
In this example, you make an item table, a book table and a chair table.
You could make an "additional values" table that holds generic information as above, but what you really want to do is figure out the "types" of the different groups of attributes and then make every one of those types it's own table.
Is there a set of values that all items have? There has to be at least one which is a type field (this describes where the other information is stored. I expect every item will also have a name and a description. This is the information to go in the item table.
Then you make additional tables for the different types itembook, itemchair etc. There may even be some overlap. For example itembook, itemhardback, itempaperback would be 3 tables used to describe books.
I believe this is the best solution to your problem. It will still allow you to extend, but it does put a framework around your data.
Of course there are systems that do it the way you describe, but unless you are building a tool that others are going to reuse for many different projects, it makes sense to design the system for the task at hand. You end up falling into the over designing trap otherwise. (IMHO)
On the other hand, if you are going to go the totally generic direction I suggest you use one of the systems that already exist that work in this way (entity framework, app framework, etc) Use someone else's don't start from scratch.
I'm not too sure how you want to retrieve the info, but something like the below may work. (It's probably close to what Hogan mentioned.)
If you want to retrieve data for a type, you can just JOIN two tables.
If you want to retrieve data for all types (with all fields), you can LEFT JOIN all tables.
----Items
+Item_id
+Item_Type_Id
+Item_Common_Field1
+Item_Common_Field1
...
----Item_Type_A
+Item_id
+Item_Type_A_Specific_Field1
+Item_Type_A_Specific_Field2
...
----Item_Type_B
+Item_id
+Item_Type_B_Specific_Field1
...
If you add these columns to the table, you can make them sparse columns to avoid the space taken by unspecified uncommon fields.
But I would not call this a best practice. (see comments under your question)
I don't want to be accused of being the always-uses-the-latest-useless-technology guy, but depending on your use case, this might be a good case for a nosql database - Tokyo, Mongo, SimpleDB, etc. Or as Developer Art suggested, you could just serialize the different fields into a single column. It's not the worst thing in the world.
Database design question for y'all. I have a form (like, the paper kind) that has several entry points for data. This form has changed, and is expected to change over years. It is being turned into a computer app, so that we can, among other things, quit wasting paper. (And minor things, like have all the data in one central store that can be queried, etc.) I'd like to store all of the forms data in a database, and have it be pretty agnostic as to the changes.
Originally, I was just considering each field to be a string -- and I had a table something like this:
FormId int (FK)
FieldName nvarchar(64)
FieldValue nvarchar(128)
...something like that. It was actually a bit more 3NFy in that FieldName was in another table, associated with an artificial key, so that the field names weren't duplicated all over the place.
However, I'd like to extend this to numeric and drop-down data. I could just store numeric data as strings, but that seems like a pretty crappy idea. Same with drop downs.
I could stop using a table, and actually use columns on the main form table (the one that FormId above references), but that means adding a column for each new item as they come along, and older forms would just be null. (And, unless I stored it, I wouldn't know when that column was created. With the string table above, it's implicit.)
I could extend the table above to something like:
FormId int (FK)
FieldName nvarchar(64)
FieldValueType int -- enum as to which of the columns below are valid (or just let nulls imply that)
FieldValue nvarchar(128)
FieldValueInt int
Combos would have to be in a OTLT (one true lookup table), which I have reservations about, but perhaps it's needed here?
Any advice on StackOverflow? I'm using MSSQL, but this is really a more general question.
Use Nulls. Proper database design is a complicated subject; you may do well to pick up a good reference and do some research on the whole thing (I gather this is a good book on the topic). In general, it sounds like you would be well served by starting with a single table that encapsulates all the fields in your form, and then putting it through the normalization process. And yes, use nulls and do NOT use an int to enumerate which columns are set to valid values; that is exactly what nulls are for.
You could have a separate table for each datatype.
I.e. to fetch an entire form you'd do an N-way join using the form id where N is the number of distinct datatypes you support (+ perhaps extras depending on the info you want - e.g. dropdown values would probably be stored in another table / your fieldname lookup / etc.)
But the design should probably also depend on how you intend to use the data, which you've said nothing about. And it would also depend on just how fast the rate of change is for these forms . . .
By creating a table with a description of your forms, you are actually defining a metadata structure. That's daunting. You would need a lot of the infrastructure needed for proper table description. I think the vendors of your database system spent a lot of effort in doing all that.
At first I thought - what a nice idea! Build your own compatibility-aware table description system!
But then I thought - I'm too stupid to do that on my own. There must be a database system capable of doing that.
So I conclude, not being a db expert, define proper defaults for 'new fields' in new form versions. Handle the compatibility issue in your business logic.
I would strongly advise against having a "generic table" like you describe.
You are essentially reinventing the relational database, which is not a good idea: Queries and updates will be very painful with your structure, and you will not be able to use the more advanced features like foreign keys and triggers, should you need them.
Just make a table(s) with columns for the data fields, and if a form does not have a field, let it be null.
Or, probably even better, have a "base table" (field that are in every form), and give names/version numbers to updated forms, and have a new table for the new columns that this version adds, then use a synthetic PK to join these new tables to your base table.
I.e.:
base table: id(numeric,PK), name, birthday, town
addresstable1: street, number, postal code, country, base_table_id (foreign key)
addresstable2: po box no, po box code, base_table_id (FK)
and so on.
That way you avoid loads of null fields; your tables are not so wide (always desirable), and your records are implicitly versioned, because the list of tables that have a record belonging to a record in your base table tells you which fields the original form had, hence what kind of form was used originally.
My friend is building a product to be used by different independent medical units.
The database stores a vast collection of measurements taken at different times, like the temperature, blood pressure, etc...
Let us assume these are held in a table called exams with columns temperature, pressure, etc... (as well as id, patient_id and timestamp). Most of the measurements are stored as floats, but some are of other types (strings, integers...)
While many of these measurements are handled by their product, it needs to allow the different medical units to record and process other custom measurements. A very nifty UI allows the administrator to edit these customs fields, specify their name, type, possible range of values, etc...
He is unsure as to how to store these custom fields.
He is leaning towards a separate table (say a table custom_exam_data with fields like exam_id, custom_field_id, float_value, string_value, ...)
I worry that this will make searching both more difficult to achieve and less efficient.
I am leaning towards modifying the exam table directly (while avoiding conflicts on column names with some scheme like prefixing all custom fields with an underscore or naming them custom_1, ...)
He worries about modifying the database dynamically and having different schemas for each medical unit.
Hopefully some people which more experience can weigh in on this issue.
Notes:
he is using Ruby on Rails but I think this question is pretty much framework agnostic, except from the fact that he is only looking for solutions in SQL databases only.
I simplified the problem a bit since the custom fields need to be available for more than one table, but I believe this doesn`t really impact the direction to take.
(added) A very generic reporting module will need to search, sort, generate stats, etc.. of this data, so it is required that this data be stored in the columns of the appropriate type
(added) User inputs will be filtered, for the standard fields as well as for the custom fields. For example, numbers will be checked within a given range (can't have a temperature of -12 or +444), etc... Thus, conversion to the appropriate SQL type is not a problem.
I've had to deal with this situation many times over the years, and I agree with your initial idea of modifying the DB tables directly, and using dynamic SQL to generate statements.
Creating string UserAttribute or Key/Value columns sounds appealing at first, but it leads to the inner-platform effect where you end up having to re-implement foreign keys, data types, constraints, transactions, validation, sorting, grouping, calculations, et al. inside your RDBMS. You may as well just use flat files and not SQL at all.
SQL Server provides INFORMATION_SCHEMA tables that let you create, query, and modify table schemas at runtime. This has full type checking, constraints, transactions, calculations, and everything you need already built-in, don't reinvent it.
It's strange that so many people come up with ad-hoc solutions for this when there's a well-documented pattern for it:
Entity-Attribute-Value (EAV) Model
Two alternatives are XML and Nested Sets. XML is easier to manage but generally slow. Nested Sets usually require some type of proprietary database extension to do without making a mess, like CLR types in SQL Server 2005+. They violate first-normal form, but are nevertheless the fastest-performing solution.
Microsoft Dynamics CRM achieves this by altering the database design each time a change is made. Nasty, I think.
I would say a better option would be to consider an attribute table. Even though these are often frowned upon, it gives you the flexibility you need, and you can always create views using dynamic SQL to pivot the data out again. Just make sure you always use LEFT JOINs and FKs when creating these views, so that the Query Optimizer can do its job better.
I have seen a use of your friend's idea in a commercial accounting package. The table was split into two, first contained fields solely defined by the system, second contained fields like USER_STRING1, USER_STRING2, USER_FLOAT1 etc. The tables were linked by identity value (when a record is inserted into the main table, a record with same identity is inserted into the second one). Each table that needed user fields was split like that.
Well, whenever I need to store some unknown type in a database field, I usually store it as String, serializing it as needed, and also store the type of the data.
This way, you can have any kind of data, working with any type of database.
I would be inclined to store the measurement in the database as a string (varchar) with another column identifying the measurement type. My reasoning is that it will presumably, come from the UI as a string and casting to any other datatype may introduce a corruption before the user input get's stored.
The downside is that when you go to filter result-sets by some measurement metric you will still have to perform a casting but at least the storage and persistence mechanism is not introducing corruption.
I can't tell you the best way but I can tell you how Drupal achieves a sort of schemaless structure while still using the standard RDBMSs available today.
The general idea is that there's a schema table with a list of fields. Each row really only has two columns, the 'table':String column and the 'column':String column. For each of these columns it actually defines a whole table with just an id and the actual data for that column.
The trick really is that when you are working with the data it's never more than one join away from the bundle table that lists all the possible columns so you end up not losing as much speed as you might otherwise think. This will also allow you to expand much farther than just a few medical companies unlike the custom_ prefix you were proposing.
MySQL is very fast at returning row data for short rows with few columns. In this way this scheme ends up fairly quick while allowing you lots of flexibility.
As to search, my suggestion would be to index the page content instead of the database content. Use Solr to parse through rendered pages and hold links to the actual page instead of trying to search through the database using clever SQL.
Define two new tables: custom_exam_schema and custom_exam_data.
custom_exam_data has an exam_id column, plus an additional column for every custom attribute.
custom_exam_schema would have a row to describe how to interpret each of the columns of the custom_exam_data table. It would have columns like name, type, minValue, maxValue, etc.
So, for example, to create a custom field to track the number of fingers a person has, you would add ('fingerCount', 'number', 0, 10) to custom_exam_schema and then add a column named fingerCount to the exam table.
Someone might say it's bad to change the database schema at run time, but I'd argue that configuring these custom fields is part of set up and won't happen too often. Still, this method lets you handle changes at any time and doesn't risk messing around with your core table schemas.
lets say that your friend's database has to store data values from multiple sources such as demogrphic values, diagnosis, interventions, physionomic values, physiologic exam values, hospitalisation values etc.
He might have as well to define choices, lets say his database is missing the race and the unit staff need the race of the patient (different races are more unlikely to get some diseases), they might want to use a drop down with several choices.
I would propose to use an other table that would have these choices or would you just use a "Custom_field_choices" table, which at some point is exactly the same but with a different name.
Considering that the database :
- needs to be flexible
- that data from multiple tables can be added and be customized
- that you might want to keep the integrity of the main structure of your database for distribution and uniformity purpose
- that data MUST have a limit and alarms and warnings
- that data must have units ( 10 kg or 10 pounds) ?
- that data can have a selection of choices
- that data can be with different rights (from simple user to admin)
- that these data might be needed to generate reports without modifying the code (automation)
- that these data might be needed to make cross reference analysis within the system without modifying the code
the custom table would be my solution, modifying each table would end up being too risky.
I would store those custom fields in a table where each record ( dataType, dataValue, dataUnit ) would use in one row. So there would be a relation oneToMany from one sample to the data. You can also create a table to record all the kind of cutsom types you would use. For example:
create table DataType
(
id int primary key,
name varchar(100) not null unique
description text,
uri varchar(255) //<-- can be used for an ONTOLOGY
)
create table DataRecord
(
id int primary key,
sample_id int not null,//<-- reference to the sample
dataType_id int not null, //<-- references DataType
value varchar(100),//<-- the value as string
unit varchar(50)//<-- g, mg/ml, etc... but it could also be a link to a table describing the units just like DataType
)