|By Kelvin Goodson, Geoffrey Winn||
|February 26, 2007 04:15 PM EST||
Service Data Objects (SDOs) simplify and unify Service Oriented Architecture (SOA) data access and code.
SDO complements the strength that SCA (Service Component Architecture) offers for simplifying development of SOA-based solutions. SCA handles the composition of service networks and SDO focuses on simplifying data handling. These technologies are getting significant support in the industry. The development of the SDO and SCA specifications is in the hands of the Open Service Oriented Architecture collaboration (www.osoa.org) and open source implementations of these specifications are being developed in the Apache Tuscany incubator project (http://incubator.apache.org/tuscany).
In this two-part article we use a scenario to demonstrate the value of many of the facets of SDO.
The first SDO specification was published in November 2004 as a result of collaborative between IBM and BEA. The Eclipse Foundation developed an open source implementation of this SDO 1 specification. SDO primarily addressed the lack of general applicability of the existing technologies such as JAXB and JDO. Around that time Microsoft entered this space with ADO.NET, offering a slightly different technical perspective. The SDO 2.0.1 specification appeared late in 2005 and is continuing to evolve, with wider industry involvement; at the time of writing revision 2.1 is imminent and revision 3.0 is in the pipeline.
The Advantages of SDO
SDO provides flexible data structures that allow data to be organized as graphs of objects (called data objects) that are composed of properties. Properties can be single or many valued and can have other data objects as their values. A data object can maintain a change summary of the alterations made to it, providing efficient communication of changes and a convenient way to update an original data source. SDO naturally permits disconnected data access patterns with an optimistic concurrency control model.
SDO offers a convenient way to work with XML documents. SDO implementations provide helpers to populate a data graph from both XML documents and relational databases and to read SDO metadata from an XML Schema Definition (XSD). Data objects can be serialized to XML and the metadata can be serialized to an XSD file (see Figure 1).
Data Objects can be introspected using the SDO metadata API to get information about types, relationships, and constraints.
SDO delivers unified and consistent access to data from heterogeneous sources. This provides both a simple programming model for the application programmer and lets tools and frameworks work consistently across those heterogeneous data sources.
SDO offers a single model for data across the enterprise.
The diagram below shows a WebUI client accessing data from a variety of sources, mediated by SDO. Web applications typically operate in a semi-connected fashion and rely on optimistic-concurrency. SDO is well suited to this environment, where data can be manipulated remotely and then a summary of the changes can be delivered back to the data sources (see Figure 2).
The following sections will introduce SDO in more detail.
This example is based on an imaginary project inspired by some real-world scenarios. A hypothetical group of universities, hospitals, and companies have embarked on a long-term collaboration to study some family of diseases that has both a genetic and environmental component. They will need to exchange the medical histories of the people they're treating and studying, and also exchange the medical histories of relatives. The data will likely come from disparate sources; basic patient data will probably be in a relational database; data from medical investigations conducted as part of this research project will be in XML documents; other medical data may come from less well known formats or custom sources. The amount of data about any given person will vary greatly. A long-standing patient may come with an extensive medical history. A relative might have little beyond name and relationship. This data has to be assembled into a coherent manageable whole, and SDO is an attractive option for representing a complicated mix of data about each person and potentially maintain a graph of such entities. For this example, we can't even assert that the graph is a (family) tree because with adoption, re-marriage, fertility treatment, and so on, one person's associations with others can be quite intricate.
The various institutions involved may not want to give unrestricted access to their data sources, although they've agreed to supply pieces of it as needed. A hospital may be willing to provide the medical data associated with one patient as part of an investigation, but they won't permit open access to their entire patient record database. Similarly, a company will want to limit access to commercially sensitive material. SDO provides a convenient way for the owner of the data to deliver to outsiders a subset of that data of their own choosing.
We'll now show some of the key values of SDO through this scenario.
To illustrate where an SDO feature helps, consider a scenario where a hospital refers a patient to a university for further investigation. Relevant data will have to flow from the hospital to the university, and it may well come from a variety of different sources. Assume that name, age, records of visits, and so forth comes from an SQL database, while specific medical data (the results of tests) are in XML documents. Using standard SDO features it's straightforward for the hospital to combine these various sources into a data object and send that, letting users of the data access it via SDO's unified API.
The university does whatever it does with the patient, and then updates the SDO and sends it back. The change history in the SDO lets the hospital apply the updates to its various data repositories without the university ever needing to know the detail of those repositories.
It's unlikely that these updates will clash with other updates made independently by the hospital, but if they do, the use of an SDO change summary ensures that this is detected and sorted out (probably manually in this case). The software component responsible for moving data between the data source (for example, a relational database in this case) and SDO is called a Data Access Service (DAS). A DAS can typically also handle conflicting updates.1
Using SDO as the data exchange format makes the system tolerant of the considerable variation to be expected in such a loosely coupled system. It's inevitable that, sooner or later, the versions of the applications that are sending and receiving data will get out-of-step. In fact, this may be usual. However, the fact that an SDO can arrive with its own metadata means that an older application can always retrieve what it wants from a newer (and presumably richer) input SDO - ignoring anything that it doesn't recognise. In the reverse case, a newer application can similarly recognise that the information it has received is from an older version and compensate accordingly.
In the previous scenarios, we've concentrated mostly on XML and SQL data sources. Now, let's suppose that in one hospital the results from the biochemistry lab are delivered in HL7 message format. This message format is widely used in the healthcare industry but is virtually unknown outside it, and so there's no off-the-shelf way to read such messages into an SDO. At this point there are several choices. We could use some broker-style product to reformat the HL7 into XML and then read it into an SDO or we could pay someone to write a new DAS that would populate an SDO directly from HL7. Since our collaborators are using an open source implementation of SDO, however, they opt to write their own DAS and donate it to the Apache Software Foundation's Tuscany project.
Other approaches exist to linking these various organisations, such as putting some software intermediary in the middle and using that to convert the data as needed. To do so though requires knowledge of all the possible input and output formats and how to convert between them. In such a loose collaboration there simply is no such central authority.
We now turn our attention to presenting the details of SDO using some code fragments.
In SDO data objects have a type so the first step in presenting our example is to construct the types we're going to use. We have several choices here. The first choice we face is whether to generate static Java classes that represent the types or whether to build them dynamically.
In a situation where the type system is stable and well understood then generating static types leads to simpler, more natural coding. For example, with generated types we'd be able to code something like...
as opposed to
Statically generated types also offer the possibility for the programmer to code to the generated interface without knowing the SDO API. The corollary of this is that when the type system isn't well known or might change then the dynamic SDO API may be more suitable. Choosing to use statically generated types has the advantage that the whole SDO dynamic API is still available to the programmer for handling less common operations.
We're going to focus on dynamically building types, since it naturally leads to exploring more of the SDO API, but bear in mind that if we were to use the option of generating static classes we have the power of SDO operating behind the scenes while using Java method calls that are no more than JavaBean getters and setters.
An option when defining types dynamically might be to use the facilities of an existing DAS, which, for example, could convert from a database schema; we could also use SDO's XSDHelper to read an XSD and build SDO types from it. The SDO specification provides a way to create types dynamically, however, it depends on knowing the SDO API, which we haven't seen yet! To simplify this example, we'll use an extension from Apache Tuscany, which lets type definitions be built without knowing the SDO API.
Type personType = SDOUtil.createType(
TypeHelper.INSTANCE, "www.example.org", "Person", false);
The net result of this line of code is the creation of an empty SDO type called "Person" scoped by the URI "www.example.org" and when completed, this type can be used to instantiate data objects. We can now add properties to the type and set its characteristics. Every property has a type, and we can make use of SDO's built-in types (in this case a string) to build our model.
Type stringType = TypeHelper.INSTANCE.getType("commonj.sdo", "string");
We use this type to add a "name" property to our "person" type.
SDOUtil.createProperty(personType, "name", stringType);
In our example scenario we can't know in advance all the information we might want to associate with a person. By making the type open we permit data objects having this type to carry additional properties that aren't defined as part of this type.
We could continue building this type in this way, however, it would rapidly become tedious. An alternative approach is to use SDO's XSDHelper to build a type system by reading XML schema definitions (see Figure 1).
The XSD for our type definitions is shown in Listing 1. Just as in our previous code example, we've made the Person type in the XSD open by using the "xsd:any." There are other interesting aspects of this schema that we'll develop as the example unfolds.
We can read this schema using SDO's XSDHelper and then we have three new types, Person, Relative, and PersonSet, available to us that can be used to create data objects.
File inputFile =
InputStream inputStream =
List schemaTypes = xsdHelper.define(
Building a Graph
These new types are all scoped within the URI www.example.org/people. Now that we have some types defined we're in good shape to create some data objects, so the first thing we do is to use the SDO DataFactory and our Person type to construct an SDO DataObject representing an instance of Person.
DataObject person1 = DataFactory.
We know from the XSD that the Person type has "id," "name," and "gender" properties so we can set values for these properties as follows.
person1.setString("name", "Joe Johnson Snr.");
We can begin building a graph by adding this person to a set of "referrals" in a test, i.e., the set of people who have been referred by a medical practitioner because they've exhibited symptoms or are related to an existing patient. We do this by creating a new DataObject of type PersonSet.
DataObject referrals = DataFactory.
The "people" property of the referrals DataObject is defined in the XSD as many valued and is therefore accessed via the getList method.
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