I'm building a small financial system. Because of double-entry accounting, transactions always come in batches of two or more, so I've got a batch table and a transaction table. (The transaction table has batch_id, account_id, and amount fields, and shared data like date and description are relegated to the batch table).
I've been using basic vo-type models for each table so far. Because of this table structure, though, transactions will almost always be selected with a join on the batch table.
So should I take the selected records and splice them into two separate vo objects, or should I create a "shared" vo that contains both batch and transaction data?
There are a few cases in which batch records and/or transaction records are loaded individually, so they will each also have their associated vo class. Are there possible pitfalls down the road if I have "overlapping" vo classes like this?
The best approach is to tie models not to database tables, but to your views. E.g. if view has date field, then use "shared " view object (ideally even specific-to-the-view object), if view has only transaction info, use another object etc. It can be tedious, but separation of concerns will be worthy. Too much duplication can be remedied with reusing/inheriting when appropriate.
Related
We have an audit table which we get from OLTP system, it records any activity done by the user including if he downloaded some attachment, or read some note or written some note , or any change for an incident etc.How do we include these audit table activity in our dimensional model for incident management system(IT service management)?
On a simple level, which is all I can provide based on the level of detail in the question, is to look at your audit table and decide which categories of audit you want to be a dimension. Perhaps there are audit_type, user_type, and audit_subtype fields or something like that? Also, typically you have another field called a "measure" or "quantity", which is typically used for stats on numerics, to support aggregate functions. For example, you might typically have store_id, product_cat as categorical dimensions, but roll up sales$ as min,max,avg,stdev grouped by different date types like month, quarter and other dimensions. If your data is purely categorical by date, then COUNT() is usually used as a calculated measure.
You really just need to decide how you want to be able to drill up and drill down though the data, which categories matter, and which quantities matter. Once you decide that, create a flat table with FKs to lookup tables. A star schema is simply a fat table with a bunch of lookup tables floating around it like a star.
Hope this helps
Is it possible, using an ADO.NET typed DataSet containing two tables in a parent/child relationship, to populate the DataSet with ONE trip to the d/b (query could return one or two tables; if one, then result set has columns from both tables, right?), and to update the d/b with ONE trip to the d/b (call to generated stored proc, I guess).
By "is it possible", I mean is it possible to have Visual Studio (2012) automagically generate the classes and SQL code to make this happen?
Or am I kind of on my own? It's looking an awful lot like VS really wants to generate one d/b server round trip for each table involved.
*I guess the update stored proc would have to take table-typed parameters from both parent and child, and perform inserts/updates/deletes appropriately.
Yes, one round trip per table is the way to go.
(- It's certainly possible to use a join query to populate a datatable but VS will then be reluctant to generate update etc SQL. This may or may not be a problem, depending on what you intend to do with the dataset.)
But if you have two tables in a dataset, lets say customers - orders, then you would typically use two queries, and two trips to the db:
SELECT * FROM customers WHERE customers.customerid=#customerid
and
SELECT * FROM orders WHERE orders.customerid=#customerid
Somewhat more counter-intuitive is the situation where you want all customers and orders for one country:
SELECT * FROM customers WHERE customers.countryid=#countryid
and
SELECT orders.* FROM orders INNER JOIN customers ON customers.customerid=orders.customerid WHERE customers.countryid=#countryid
Note how the join query returns data from only one table, but uses the join to identify which rows to return.
Then, once you have the data in your dataset, you can navigate it using the getparentrow and getchildrows methods. This is how ADO.Net manages hierarchical data.
You do need this one-table-at-a-time approach, because, assuming you have foreign key constraints in your db, you need to insert and update in reverse order from delete.
EDIT Yes, this does mean that in some circumstances, depending on the data you want and the structure of your primary keys, you could end up with a humungous set of JOINS that still only pull the data from the table at the end of the hierarchy. This might seem wrong in terms of traditional SQL, but actually it's fine. The time you have lost in the multiple, more complex queries is saved by the reduced amount of data you have to pull back across the wire, compared with one big join query that would be returning multiple copies of the parent data.
My question may seems more general. But only answer I got so far is from the SO itself. My question is, I have a table customer information. I have 47 fields in it. Some of the fields are optional. I would like to split that table into two customer_info and customer_additional_info. One of its column is storing a file in byte format. Is there any advantage by splitting the table. I saw that the JOIN will slow down the query execution. Can I have more PROs and CONs of splitting a table into two?
I don't see much advantage in splitting the table unless some of the columns are very infrequently accessed and fairly large. There's a theoretical advantage to keeping rows small as you're going to get more of them in a cached block, and you improve the efficiency of a full table scan and of the buffer cache. Based on that I'd be wary of storing this file column in the customer table if it was more than a very small size.
Other than that, I'd keep it in a single table.
I can think of only 2 arguments in favor of splitting the table:
If all the columns in Customer_Addition_info are related, you could potentially get the benefit of additional declarative data integrity that you couldn't get with a single table. For instance, lets say your addition table was CustomerAddress. Your business logic may dictate that a customer address is optional, but once you have a customer Zip code, the addressL1, City and State become required fields. You could set these columns to non null if they exist in a customerAddress table. You couldn't do that if they existed directly in the customer table.
If you were doing some Object-relational mapping and your had a customer class with many subclasses and you didn't want to use Single Table Inheritance. Sometimes STI creates problems when you have similar properties of various subclasses that require different storage layout. Being that all subclasses have to use the same table, you might have name clashes. The alternative is Class Table inheritance where you have a table for the superclass, and an addition table for each subclass. This is a similar scenario to the one you described in your question.
As for CONS, The join makes things harder and slower. You also run the risk of accidentally creating a 1 to many relationship. I.E. You create 2 addresses in the CustomerAddress table and now you don't know which one is valid.
EDIT:
Let me explain the declarative ref integrity point further.
If your business rules are such that a customer address is optional, and you embed addressL1, addressL2, City, State, and Zip in your customer table, you would need to make each of these fields Nullable. That would allow someone to insert a customer with a City but no state. You could write a table level check constraint to cover this situation. But that isn't as easy as simply setting the AddressL1, City, State and Zip columns in the CustomerAddress table not nullable. To be clear, I am NOT advocating using the multi-table approach. However you asked for Pros and Cons, and I'm just pointing out this aspect falls on the pro side of the ledger.
I second what David Aldridge said, I'd just like to add a point about the file column (presumably BLOB)...
BLOBs are stored up to approx. 4000 bytes in-line1. If a BLOB is used rarely, you can specify DISABLE STORAGE IN ROW to store it out-of-line, removing the "cache pollution" without the need to split the table.
But whatever you do, measure the effects on realistic amounts of data before you make the final decision.
1 That is, in the row itself.
I am Working on web application where i have 90 fields for a Person class which are divided in to family details,education details, personal details etc....
I want separate form for each, like for family details has-father name, mother name siblings etc... fields and so on for other
I want separate table for each detail with common reference id for all tables
My question is how many bean classes should i write? Is it with one bean class can i map from multiple forms to multiple tables?
class PersonRegister{
private Long iD;
private String emailID;
private String password;
.
.
}//for register.......
once logged in i need to maintain his/her details
Either
class person{
}
or
class PersonFamilyDetails{}
class PersonEducationDetails{}
etc
which way software developing standards specify to create?
Don't go overboard, I believe in your case single but very wide (i.e. with a lot of columns) table would be most efficient and simplest from maintenance perspective. Only thing to keep in mind is too query only for a necessary subset of columns/fields when loading lots of rows. Otherwise you'll be fetching kilobytes of unnecessary data, not needed for particular use case.
Unfortunately Hibernate doesn't have direct support for that, when designing a mapping for Person, you'll end up with huge class and even worse - Hibernate will always fetch all simple columns (and many-to-one relationships). You can however overcome this problem either by creating several views in the database containing only subset of columns or by having several Java classes mapping to the same table but only to subset of columns.
Splitting your database model into several tables is beneficial only if your schema is not normalized. E.g. when storing siblings first name and last name you may wish to have a separate Sibling table and next time some other family member is entered, you can reuse the same row. This makes database smaller and might be faster when searching by sibling.
Your question comes down to database normalization, as described in-depth by Boyce and Codd, see
http://en.wikipedia.org/wiki/Database_normalization.
The main advantage of database normalization is avoiding modification anomalies. In your case, if you got one table with for each person e.g. father-firstname and father-lastname, and you have multiple people with the same father, this data will be duplicated, and when you discover a typo in the father-lastname, you could modify it for one sibling, and not for the next.
In this simplified case, database design best practices would call for a first normalization into a separate table with father-id, father-firstname and father-lastname, and your person table having a one-to-many relation to it.
For one-to-one relations, e.g. person->personeducationdetails, there's some debate. In the original definition of 1st Normal Form, every optional field would be normalized by putting it's own table. This was later weakened by introducing 'null' in relational databases, see http://en.wikipedia.org/wiki/First_normal_form#cite_note-CoddRule-12. But still, if a whole set of columns could be null at the same time, you put them in a separate table with a one-to-one relation.
E.g. if you don't know a person's educationdetails, all of its related fields are null, so you better split them off in a separate table, and simply not have a personeducationdetails record for that person.
I am using Spring + Hibernate, and I will have a HTML from that has like 100+ fields and I must store all these values to database in a single table.
They are all used in one big massive calculation.
How should I handle this, I thought about creating an Entity with 100 fields and setters, getters, but is there a nicer solution for it?
EDIT:
Everytime when someone submits form, a new row will be added, so eventually there will be tens of thousands of rows.
I believe its not about an HTML but about the data modeling.
Think about your data, who are the consumers of it, how and in which business flows you're going to query the data.
In general an entity with 100 fields is not a good idea because it should be mapped to one single table with 100 columns. Its just not maintainable.
Maybe all the data should be normalized and you can store pieces of it in different tables in db with foreign keys?
Hope this helps or at least will give you some direction to think about
I think you could use a Map in this case, because:
You only want to store the fields as key-value elements.
It is more flexible to add/remove fields in the future.
So, instead of having a table with 100 fields you will end with a table with 2 fields (3 if you want to include the form identifier or something like that) and 100 rows.
If many of the form fields are empty (sparse data) you could also save some storage space (it depends on the database you are using).