i am trying to design a table which contains sections and each section contains tasks and each task contains sub tasks and so on. I would like to do it under one table. Please let me know the best single table approach which is scalable. I am pretty new to database design. Also please suggest if single table is not the best approach then what could be the best approach to do this. I am using db2.
Put quite simply, I would say use 1 table for tasks.
In addition to all its various other attributes, each task should have a primary identifier, and another column to optionally contain the identifier of its parent task.
If you are using DB2 for z/OS, then you will use a recursive query with a common table expression. Otherwise you you can use a hierarchical recursive query in DB2 for i, or possibly in DB2 for LUW (Linux, Unix, Windows).
Other designs requiring more tables, each specializing in a certain part of the task:subtask relationship, may needlessly introduce issues or limitations.
There are a few ways to do this.
One idea is to use two tables: Sections and Tasks
There could be a one to many relationship between the two. The Task table could be designed as a tree with a TaskId and a ParentTaksId which means you can have Tasks that go n-levels deep (sub tasks of sub tasks og sub tasks etc). Every Task except for the root task will have a parent.
I guess you can also solve this by using a single table where you just add a section column to the Task table I described above.
If you are going to put everything into one table although convenient will be inefficient in the long run. This would mean you will be storing unnecessary repeated groups of data in your database which would not be processor and memory friendly at all. It would in fact violate the Normalization rules and to be more specific the 1st Normal Form which says that there should be no repeating groups that could be found in your table. And it would actually also violate the 3rd Normal Form which means there will be no (transitional) dependency of a non-primary key to another non-primary key.
To give you an illustration, I will put your design into one table. Although I will be guessing on the possible fields but just bear with it because this is for the sake of discussion. Look at the graphics below:
If you look the graphics above (although this is rather small you could download the image and see it closer for yourself), the SectionName, Taskname, TaskInitiator, TaskStartDate and TaskEndDate are unnecessary repeated which as I mentioned earlier a violation of the 1st Normal Form.
Secondly, Taskname, TaskInitiator, TaskStartDate and TaskEndDate are functionally dependent on TaskID which is not a primary key instead of SectionID which in this case should be the primary key (if on a separate table). This is violation of 3rd Normal Form which says that there should be no Transitional Dependence or non-primary key should be dependent on
another non-primary key.
Although there are instances that you have to de-normalized but I believe this one should be normalized. In my own estimation there should be three tables involved in your design, namely, Sections,Tasks and SubTasks that would like the one below.
Section is related to Tasks, that is, a section could have many Tasks.
And Task is related to Sub-Tasks, that is, a Task could have many Sub-tasks.
If I understand correctly the original poster does not know, how many levels of hierarchy will be needed (hence "and so on"). His problem is to create a design that can hold a structure of any depth.
Imho that is a complex issue that does not have a single answer. When implementing such a design you need to count such factors as:
Will the structure be fairly constant? (How many writes?)
How often will this structure be read?
What operations will need to be possible? (Get all children objects of a given object? Get the parent object? Get the direct children?)
If the structure will be constant You could use the nested set model (http://en.wikipedia.org/wiki/Nested_set_model)
In this way the table has a 'left' and 'right' column. The parent object has its left and right column encompasing the values of any of its children object.
In that way you can list all the children of an object using a query like this:
SELECT child.id
FROM table AS parent
JOIN table AS child
ON child.left BETWEEN parent.left AND parent.right
AND child.right BETWEEN parent.left AND parent.right
WHERE
parent.id = #searchId
This design can be VERY fast to read, but is also EXTREMELY costly when the structure changes (for example when adding a child to any object You will have to update any object with a 'right' value that is higher than the inserted one).
If you need to be able to make changes to structure in real time you should probably use a design with two tables - one holding the objects, the second the structure (something like parentId, childId, differenceInHierarchyLevels).
Related
I'm designing a database from scratch and I'm wondering if the way I'm using one-to-one relationships is correct.
Imagine I have a table that needs the columns city and country_id, the first being alphanumeric and the second being a foreign key to another table. Should I place these in a locations table and use a one-to-one relationship?
Another example:
I have a table with the factory information of a device like the serial number and other fields. These will later be used to register a device in another table. Of course this is a one-to-one relationship, but should the columns of the first table be in the second table instead? Have in mind that the registrations table has another 4-5 columns.
I've read a lot of times that these relationships can often be omitted. However, I like the separation of concerns that creating a new table can give, in some cases.
Thanks in advance!
This may be a duplicate question, e.g. see:
SQL one to one relationship vs. single table
There's no perfect answer to this question as it depends on use case, but here's the rule of thumb I recommend abiding by: if you can already envision the potential need for separate tables, then I would err on the side of splitting them and using a 1:1 relationship. For example, imagine in the future that you want to have some kind of one-to-many relationship between some new table and the country table, or between some new table and the device table. In these cases you probably don't want city information mixed up with the former, and you probably don't want device registration information mixed up with the latter. By keeping your DB schema normalized, you can better future-proof it and you can mitigate the need for (likely extremely painful) updates that may have otherwise cropped up.
I am about to embark on a project for work that is very outside my normal scope of duties. As a SQL DBA, my initial inclination was to approach the project using a SQL database but the more I learn about NoSQL, the more I believe that it might be the better option. I was hoping that I could use this question to describe the project at a high level to get some feedback on the pros and cons of using each option.
The project is relatively straightforward. I have a set of objects that have various attributes. Some of these attributes are common to all objects whereas some are common only to a subset of the objects. What I am tasked with building is a service where the user chooses a series of filters that are based on the attributes of an object and then is returned a list of objects that matches all^ of the filters. When the user selects a filter, he or she may be filtering on a common or subset attribute but that is abstracted on the front end.
^ There is a chance, depending on user feedback, that the list of objects may match only some of the filters and the quality of the match will be displayed to the user through a score that indicates how many of the criteria were matched.
After watching this talk by Martin Folwler (http://www.youtube.com/watch?v=qI_g07C_Q5I), it would seem that a document-style NoSQL database should suit my needs but given that I have no experience with this approach, it is also possible that I am missing something obvious.
Some additional information - The database will initially have about 5,000 objects with each object containing 10 to 50 attributes but the number of objects will definitely grow over time and the number of attributes could grow depending on user feedback. In addition, I am hoping to have the ability to make rapid changes to the product as I get user feedback so flexibility is very important.
Any feedback would be very much appreciated and I would be happy to provide more information if I have left anything critical out of my discussion. Thanks.
This problem can be solved in by using two separate pieces of technology. The first is to use a relatively well designed database schema with a modern RDBMS. By modeling the application using the usual principles of normalization, you'll get really good response out of storage for individual CRUD statements.
Searching this schema, as you've surmised, is going to be a nightmare at scale. Don't do it. Instead look into using Solr/Lucene as your full text search engine. Solr's support for dynamic fields means you can add new properties to your documents/objects on the fly and immediately have the ability to search inside your data if you have designed your Solr schema correctly.
I'm not an expert in NoSQL, so I will not be advocating it. However, I have few points that can help you address your questions regarding the relational database structure.
First thing that I see right away is, you are talking about inheritance (at least conceptually). Your objects inherit from each-other, thus you have additional attributes for derived objects. Say you are adding a new type of object, first thing you need to do (conceptually) is to find a base/super (parent) object type for it, that has subset of the attributes and you are adding on top of them (extending base object type).
Once you get used to thinking like said above, next thing is about inheritance mapping patterns for relational databases. I'll steal terms from Martin Fowler to describe it here.
You can hold inheritance chain in the database by following one of the 3 ways:
1 - Single table inheritance: Whole inheritance chain is in one table. So, all new types of objects go into the same table.
Advantages: your search query has only one table to search, and it must be faster than a join for example.
Disadvantages: table grows faster than with option 2 for example; you have to add a type column that says what type of object is the row; some rows have empty columns because they belong to other types of objects.
2 - Concrete table inheritance: Separate table for each new type of object.
Advantages: if search affects only one type, you search only one table at a time; each table grows slower than in option 1 for example.
Disadvantages: you need to use union of queries if searching several types at the same time.
3 - Class table inheritance: One table for the base type object with its attributes only, additional tables with additional attributes for each child object type. So, child tables refer to the base table with PK/FK relations.
Advantages: all types are present in one table so easy to search all together using common attributes.
Disadvantages: base table grows fast because it contains part of child tables too; you need to use join to search all types of objects with all attributes.
Which one to choose?
It's a trade-off obviously. If you expect to have many types of objects added, I would go with Concrete table inheritance that gives reasonable query and scaling options. Class table inheritance seems to be not very friendly with fast queries and scalability. Single table inheritance seems to work with small number of types better.
Your call, my friend!
May as well make this an answer. I should comment that I'm not strong in NoSQL, so I tend to lean towards SQL.
I'd do this as a three table set. You will see it referred to as entity value pair logic on the web...it's a way of handling multiple dynamic attributes for items. Lets say you have a bunch of products and each one has a few attributes.
Prd 1 - a,b,c
Prd 2 - a,d,e,f
Prd 3 - a,b,d,g
Prd 4 - a,c,d,e,f
So here are 4 products and 6 attributes...same theory will work for hundreds of products and thousands of attributes. Standard way of holding this in one table requires the product info along with 6 columns to store the data (in this setup at least one third of them are null). New attribute added means altering the table to add another column to it and coming up with a script to populate existing or just leaving it null for all existing. Not the most fun, can be a head ache.
The alternative to this is a name value pair setup. You want a 'header' table to hold the common values amoungst your products (like name, or price...things that all rpoducts always have). In our example above, you will notice that attribute 'a' is being used on each record...this does mean attribute a can be a part of the header table as well. We'll call the key column here 'header_id'.
Second table is a reference table that is simply going to store the attributes that can be assigned to each product and assign an ID to it. We'll call the table attribute with atrr_id for a key. Rather straight forwards, each attribute above will be one row.
Quick example:
attr_id, attribute_name, notes
1,b, the length of time the product takes to install
2,c, spare part required
etc...
It's just a list of all of your attributes and what that attribute means. In the future, you will be adding a row to this table to open up a new attribute for each header.
Final table is a mapping table that actually holds the info. You will have your product id, the attribute id, and then the value. Normally called the detail table:
prd1, b, 5 mins
prd1, c, needs spare jack
prd2, d, 'misc text'
prd3, b, 15 mins
See how the data is stored as product key, value label, value? Any future product added can have any combination of any attributes stored in this table. Adding new attributes is adding a new line to the attribute table and then populating the details table as needed.
I beleive there is a wiki for it too... http://en.wikipedia.org/wiki/Entity-attribute-value_model
After this, it's simply figuring out the best methodology to pivot out your data (I'd recommend Postgres as an opensource db option here)
If I have a parent and a child table filled with data, is it trivial to add a new table between them?
For example, before introduction the relationship is:
Parent -> Child
Then:
Parent -> New Table -> Child
In this case I'm referring to SQLite3 so a Child in this schema has a Foreign Key which matches the Primary Key of the Parent Table.
Thanks!
This may be too obvious, but...
How trivial it is will be dependent on how much code has already been written that needs to change with this. If this is a new app, with little code written, and you're just beginning to work on the design, then yes it's trivial. If you have tons of functions (whether it's external code, or DB code like stored procedures and views) accessing these tables expecting the original relationship then it becomes less trivial.
Changing it in the database should be relatively non-trivial, assuming you know enough SQL to populate the new table and set up the relations.
As with all development challenges, you just need to look at what will be affected, how, and determine how you're going to account for those changes.
All of this is a really long-winded way of saying "it depends on your situaiton".
I am not disagreeing with David at all, just being precise re a couple of aspects of the change.
If you have implemented reasonable standards, then the only code affected with be code that addresses the changed columns in Child (not New_Table). If you have not, then an unknown amount of code, which should not need to change, will have to change.
The second consideration is the quality of the Primary Key in Child. If you have Natural Relational Keys, the addition of New_Table has less impact, not data changes required. If you have IDENTITY type keys, then you may need to reload, or worse, "re-factor" the keys.
Last, introducing New_Table is a correction to a Normalisation error, which is a good thing. Consequentially, certain Child.columns will become New_Table.columns, and New_Table can be loaded from the existing data. You need to do that correctly and completely, in order to realise the performance gain from the correction. That may mean changing a couple more code segments.
If you have ANSI SQL, all the tasks are fairly straight-forward and easy.
I have to add functionality to an existing application and I've run into a data situation that I'm not sure how to model. I am being restricted to the creation of new tables and code. If I need to alter the existing structure I think my client may reject the proposal.. although if its the only way to get it right this is what I will have to do.
I have an Item table that can me link to any number of tables, and these tables may increase over time. The Item can only me linked to one other table, but the record in the other table may have many items linked to it.
Examples of the tables/entities being linked to are Person, Vehicle, Building, Office. These are all separate tables.
Example of Items are Pen, Stapler, Cushion, Tyre, A4 Paper, Plastic Bag, Poster, Decoration"
For instance a Poster may be allocated to a Person or Office or Building. In the future if they add a Conference Room table it may also be added to that.
My intital thoughts are:
Item
{
ID,
Name
}
LinkedItem
{
ItemID,
LinkedToTableName,
LinkedToID
}
The LinkedToTableName field will then allow me to identify the correct table to link to in my code.
I'm not overly happy with this solution, but I can't quite think of anything else. Please help! :)
Thanks!
It is not a good practice to store table names as column values. This is a bad hack.
There are two standard ways of doing what you are trying to do. The first is called single-table inheritance. This is easily understood by ORM tools but trades off some normalization. The idea is, that all of these entities - Person, Vehicle, whatever - are stored in the same table, often with several unused columns per entry, along with a discriminator field that identifies what type the entity is.
The discriminator field is usually an integer type, that is mapped to some enumeration in your code. It may also be a foreign key to some lookup table in your database, identifying which numbers correspond to which types (not table names, just descriptions).
The other way to do this is multiple-table inheritance, which is better for your database but not as easy to map in code. You do this by having a base table which defines some common properties of all the objects - perhaps just an ID and a name - and all of your "specific" tables (Person etc.) use the base ID as a unique foreign key (usually also the primary key).
In the first case, the exclusivity is implicit, since all entities are in one table. In the second case, the relationship is between the Item and the base entity ID, which also guarantees uniqueness.
Note that with multiple-table inheritance, you have a different problem - you can't guarantee that a base ID is used by exactly one inheritance table. It could be used by several, or not used at all. That is why multiple-table inheritance schemes usually also have a discriminator column, to identify which table is "expected." Again, this discriminator doesn't hold a table name, it holds a lookup value which the consumer may (or may not) use to determine which other table to join to.
Multiple-table inheritance is a closer match to your current schema, so I would recommend going with that unless you need to use this with Linq to SQL or a similar ORM.
See here for a good detailed tutorial: Implementing Table Inheritance in SQL Server.
Find something common to Person, Vehicle, Building, Office. For the lack of a better term I have used Entity. Then implement super-type/sub-type relationship between the Entity and its sub-types. Note that the EntityID is a PK and a FK in all sub-type tables. Now, you can link the Item table to the Entity (owner).
In this model, one item can belong to only one Entity; one Entity can have (own) many items.
your link table is ok.
the trouble you will have is that you will need to generate dynamic sql at runtime. parameterized sql does not typically allow the objects inthe FROM list to be parameters.
i fyou want to avoid this, you may be able to denormalize a little - say by creating a table to hold the id (assuming the ids are unique across the other tables) and the type_id representing which table is the source, and a generated description - e.g. the name value from the inital record.
you would trigger the creation of this denormalized list when the base info is modified, and you could use that for generalized queries - and then resort to your dynamic queries when needed at runtime.
I am looking at quite a monstrosity of an application that uses several tables to represent a reporting hierarchy, but eacvh of these tables is identical. The table at the bottom of the hierarchy has the most records, each of which has a ParentID to the rollup table above it, eventually all adding up to only one total in the top rollup table.
I am plagued to insanity by gargantuan 'if' blocks of code with hard-coded joins and table names, and I am trying hard to recognise some sane reason for not using a single table, with a levelID in each row, instead of one table for each level, for all these levels, or at least several views on the same table. The latter because the database was designed to be used in MSAccess, which doesn't allow aliased sub-queries AFAIK.
Are the tables all the same in their semantics or just in their form? If the tables are identical in both form and semantics, then a single table solution is probably far superior, but I don't know enough about your case to say for sure.
Representing a hierarchy in an SQL table can be quite a challenge. Fortunately, reporting hierarchies are generally small enough and stable enough so that a variety of techniques will work.
The simplest technique goes by the name "adjacency list" model. In this model, there are two columns one of which refers to the other. I'll call them MyTable(ID, ParentID). In a real case, Mytable will have other columns. ParentID references ID in a different row of the same table. This is easy to implement, and easy to update. It can be a pain to do rollups.
Another technique goes by the name "nested sets". Call it MyTable (ID, lft, rgt, Level). (Level is redundant, and often omitted). Here we have two columns (lft and rgt) that show where the row fits into the hierarchy, because lgt and rgt are nested inside the lft and rgt of all the ancestors of the node in question. This technique is hard to update. It's easy to do rollups, and to find subtrees, and ancestor paths, and lots of other types of queries.
A third way to "flatten the hierarchy". In this technique, each level of the hierarchy has a named column of its own, and each row displays its entire ancestry all the way back to the apex of the hierarchy. Here we have MyTable (ID, Division, Department, Group, Team). Division, Department, Group and Team are all levels of the hierarchy. This is ultimately easy for users who access the data via a point and click drill down interface, because there's nothing for them to learn, if the column names are chosen well. It requires a name for each level. It does not adapt well to indefinite levels of hierarchy. It's got a lot of redundancy. In general flattened hiearachies are generated automatically from a table that stores hierarchies in adajency list form or nested set form.
Any one of these are a good alternative to separate tables for every level in the hierarchy.
excellent solutions are suggested here already. I would add one to use a hierarchical database such as hypergraph.