How to easily access widely different subsets of fields of related objects/DB tables? - sql

Question

Imagine we have a number of related objects (equivalently DB tables), for example:
public class Person {
private String name;
private Date birthday;
private int height;
private Job job;
private House house;
..
}
public class Job {
private String company;
private int salary;
..
}
public class House {
private Address address;
private int age;
private int numRooms;
..
}
public class Address {
private String town;
private String street;
..
}
How to best design a system for easily defining and accessing widely varying subsets of data on these objects/tables? Design patterns, pros and cons, are very welcome. I'm using Java, but this is a more general problem.
For example, I want to easily say:
I'd like some object with (Person.name, Person.height, Job.company, Address.street)
I'd like some object with (Job.company, House.numRooms, Address.town)
Etc.
Other assumptions:
We can assume that we're always getting a known structure of objects on the input, e.g. a Person with its Job, House, and Address.
The resulting object doesn't necessarily need to know the names of the fields it was constructed from, i.e. for subset defined as (Person.name, Person.height, Job.company, Address.street) it can be the array of Objects {"Joe Doe", 180, "ACompany Inc.", "Main Street"}.
The object/table hierarchy is complex, so there are hundreds of data fields.
There may be hundreds of subsets that need to be defined.
A minority of fields to obtain may be computed from actual fields, e.g. I may want to get a person's age, computed as (now().getYear() - Person.birtday.getYear()).
Here are some options I see:
A SQL view for each subset.
Minuses:
They will be almost the same for similar subsets. This is OK just for field names, but not great for the joins part, which could ideally be refactored out to a common place.
Less testable than a solution in code.
Using a DTO assembler, e.g. http://www.genericdtoassembler.org/
This could be used to flatten the complex structure of input objects into a single DTO.
Minuses:
I'm not sure how I'd then proceed to easily define subsets of fields on this DTO. Perhaps if I could somehow set the ones irrelevant to the current subset to null? Not sure how.
Not sure if I can do computed fields easily in this way.
A custom mapper I came up with.
Relevant code:
// The enum has a value for each field in the Person objects hierarchy
// that we may be interested in.
public enum DataField {
PERSON_NAME(new PersonNameExtractor()),
..
PERSON_AGE(new PersonAgeExtractor()),
..
COMPANY(new CompanyExtractor()),
..
}
// This is the container for field-value pairs from a given instance of
// the object hierarchy.
public class Vector {
private Map<DataField, Object> fields;
..
}
// Extractors know how to get the value for a given DataField
// from the object hierarchy. There's one extractor per each field.
public interface Extractor<T> {
public T extract(Person person);
}
public class PersonNameExtractor implements Extractor<String> {
public String extract(Person person) {
return person.getName();
}
}
public class PersonAgeExtractor implements Extractor<Integer> {
public int extract(Person person) {
return now().getYear() - person.getBirthday().getYear();
}
}
public class CompanyExtractor implements Extractor<String> {
public String extract(Person person) {
return person.getJob().getCompany();
}
}
// Building the Vector using all the fields from the DataField enum
// and the extractors.
public class FullVectorBuilder {
public Vector buildVector(Person person) {
Vector vector = new Vector();
for (DataField field : DataField.values()) {
vector.addField(field, field.getExtractor().extract(person));
}
return vector;
}
}
// Definition of a subset of fields on the Vector.
public interface Selector {
public List<DataField> getFields();
}
public class SampleSubsetSelector implements Selector {
private List<DataField> fields = ImmutableList.of(PERSON_NAME, COMPANY);
...
}
// Finally, a builder for the subset Vector, choosing only
// fields pointed to by the selector.
public class SubsetVectorBuilder {
public Vector buildSubsetVector(Vector fullVector, Selector selector) {
Vector subsetVector = new Vector();
for (DataField field : selector.getFields()) {
subsetVector.addField(field, fullVector.getValue(field));
}
return subsetVector;
}
}
Minuses:
Need to create a tiny Extractor class for each of hundreds of data fields.
This is a custom solution that I came up with, seems to work and I like it, but I feel this problem must have been encountered and solved before, likely in a better way.. Has it?
Edit
Each object knows how to turn itself into a Map of fields, keyed on an enum of all fields.
E.g.
public enum DataField {
PERSON_NAME,
..
PERSON_AGE,
..
COMPANY,
..
}
public class Person {
private String name;
private Date birthday;
private int height;
private Job job;
private House house;
..
public Map<DataField, Object> toMap() {
return ImmutableMap
.add(DataField.PERSON_NAME, name)
.add(DataField.BIRTHDAY, birthday)
.add(DataField.HEIGHT, height)
.add(DataField.AGE, now().getYear() - birthday.getYear())
.build();
}
}
Then, I could build a Vector combining all the Maps, and select subsets from it like in 3.
Minuses:
Enum name clashes, e.g. if Job has an Address and House has an Address, then I want to be able to specify a subset taking street name of both. But how do I then define the toMap() method in the Address class?
No obvious place to put code doing computed fields requiring data from more than one object, e.g. physical distance from Address of House to Address of Company.
Many thanks!

Answer 1

Over in-memory object mapping in the application, I would favor database processing of the data for better performance. Views, or more elaborate OLAP/datawarehouse tooling could do the trick. If the calculated fields remain basic, as in "age = now - birth", I see nothing wrong with having that logic in the DB.
On the code side, given the large number of DTOs you have to deal with, you could use classless dynamic (available in some JVM languages) or JSON objects. The idea is that when a data structure changes, you only need to modify the DB and the UI, saving you the cost of changing a whole bunch of classes in between.