Xml Matters #9

Generating DTDs and XML Documents from SQL Queries

David Mertz, Ph.D.
Bricolateur, Gnosis Software, Inc.
March 2001

SQL queries that extract data from relational databases can also be used to provide very practical ad hoc document type information for the representation of query results in XML. This column discusses the public domain sql2dtd and sql2xml utilities that allow RDBMS-independent generation of portable XML result sets.


The previous XML Matters column discussed some of the advantages and theory underlying various data models. One conclusion of that column was that RDBMS' are here to stay (with good reasons), and that XML is best seen, in this context, as a means of transporting data between various DBMS', rather than as something to replace DBMS'. XPATH and XSLT are useful for certain "data querying" purposes, but their application is far less broad and general than RDBMS'--and SQL, in particular--is.

A number of recent RDBMS' include built-in (or at least optional) tools for exporting XML. These include DB2 and Oracle, and probably other RDBMS' also. However, the tools discussed in this column are intended to be generic to any particular RDBMS; in particular, the DTDs generated by the presented tools will remain identical for the same query performed against different RDBMS'. We hope this will further goals of data transparency.

Simplifying Too Much

What might strike you as the most obvious way of converting relational database data to XML is also generally a bad idea. That is, it would be simple enough--conceptually and practically--to do a table-by-table "dump" of all the contents of an RDBMS into corresponding XML documents. For example, a LIBRARY database (we will continue the simple example in the previous column) might have one table called BOOKPRICE, with contents like:

| ISBN       | Price |
| 2994927282 | 34.99 |
| 3920202049 | 47.50 |

We could straightforwardly convert this into a document BOOKPRICE.xml that looked like:

<?xml version="1.0"?>

Once we had created similar XML documents for every table within a database, we would have a complete snapshot of the database.

Simplifying Only Enough

There are two basic problems with the approach sketched above. The first problem is that our "XML-dump" is hugely inefficient. XML, as readers well know, is an extremely verbose format, and an "XML-dump" of a large database would be an even larger collection of XML documents. Futhermore, major DBMS' already provide compact and efficient flat-file or packed-record style dumps. The XML sketched provides no additional functionality to those simple formats, while simply multiplying the size of transport files.

The second problem is more interesting than the first, however. In a sense, "DASD is cheap," and bandwidth is also getting cheaper ("DASD" is an old IBM way of saying "hard disks"; and the phrase is a design cliche). So mere efficiency is not necessarily overriding. What is more important is that the data one wants to communicate with partners/departments/users/etc. is rarely the entire contents of a database. Sometimes some contents are private; and almost all the time, most contents are simply not relevant to a particular recipient.

What would be more interesting than dumping raw tables to XML would be dumping the results of useful SQL queries to XML. What would be still better would be to associate DTDs with these useful queries in order to regularize expectations about the exact parsing and processing required for XML transactions or feeds. These two interesting actions are precisely what the public domain Python utilities sql2dtd and sql2xml let you accomplish.

Suppose that A and B each have their own internal data storage strategies (e.g. in different RDBMS'). They each maintain all sort of related information which is not relevant to the interaction between A and B, but they also have some information they'd like to share. Suppose, on these lines, that A needs to communicate a particular kind of data set to B on a recurrent basis. One thing A and B can do is agree that A will periodically send to B a set of XML documents, each of which will conform to a DTD agreed to in advance. The specific data in one transmission will vary with time, but the validity rules have been specified in advance. Both A and B can carry out their programming, knowing what the protocol will look like.

Generating The Dtd's

One way to develop the communication between A and B contemplated above is to develop DTDs (or Schemas) that match the specific needs of A and B. Then A will need to develop custom code to export data into the agreed upon DTDs from A's current RDBMS; and B will need to develop custom code to import the same data (into a differently structured database). Then, finally, the communication channel can be opened.

There is likely to be a quicker way, however, and a way that is likely to leverage existing export/import procedures. The Standard Query Language (SQL) is a wonderfully compact and expressive means of expressing exactly what data within an RDBMS database you are interested in. Trying to bolt on XML native techniques like XPATH or XSLT to a relational model will probably feel unnatural, although they can certainly express querying functions within XML's basically hierarchical model.

Moreover, many organizations have already developed well-tested sets of SQL statements that are relevant to achieving known tasks. Often, in fact, RDBMS' provide means for optimizing stored queries. While there are certainly cases, as well, where designing rich DTDs for data exchanges makes sense, in many or most cases, a good solution can be to use the structuring information implicit in SQL queries as an (automatic) basis for XML data transmissions.

While SQL queries can combine table data in complex ways, the result from any SQL query is a rather simple row-and-column arrangement. Query output has a fixed number of fixed columns, with each row filling in values for every column. The potential of XML to represent complex nesting patterns of elements is just simply not going to be deeply exercised in representing SQL results. However, there are nonetheless several important aspects of an SQL query that can and should be represented in an XML DTD beyond simply row/column positions.

What To Represent From An Sql Query?

I would argue that in our contemplated data exchange between A and B, two aspects should be separated out. On the one hand, there is the internal organization of A's data--its normalization, and denormalized optimizations, for example. B does not, and need not, be concerned about the A-internal aspect. On the other hand, there is meta-data that importantly describes what is actually transmitted. Of course, separating these aspects is not necessarily easy.

In writing sql2dtd (and in helping plan Scott Hathaway's sql2xml), I made several decisions about what is part of a data transmission, and what is internal to the sender's setup (and need not be represented in the DTD). A sample XML (with the DTD as an internal set) output can help illustrate these decisions (this output is generated entirely from the SQL query contained as an attribute; when run against a suitable database, of course):

<?xml version="1.0"?>
<!ELEMENT SQL (row)*>
                      FROM AUTHGROUP GROUP BY AuthID
                      ORDER BY AuthID"
<!ELEMENT row (SSN, column2)>
<!ELEMENT column2 (#PCDATA)>

  <row num="1">
  <row num="2">
  <row num="3">

This simple XML document may actually contain more meta-data than one notices initially. Of course, by including the SQL itself at an attribute of the root node, one can reconstruct anything implicit in the SQL. But doing that requires re-parsing the SQL, which sql2dtd has represented in the document, so it is not generally necessary.

The fact that the XML contains calculated elements is contained in the specification of the CALC attribute for any such element. Since a calculated expression can be long, and contain characters illegal for XML tags, calculated columns are named simply by their position. However, the particular calculation that went into the element contents is contained as an attribute of the tag. In order to avoid repeating the attribute throughout the XML body, it is specified as #FIXED in the DTD.

Frequently, if calculated columns are used, the calculation reflects grouping of columns with the "GROUP BY" modifier. Any such groupings are listed in the GROUP_BY attribute of the root element.

Furthermore, if an "ORDER BY" clause is used, each <row> tag carries a num attribute that specifies the specific sequence of output data. However, if a result set is unordered, no num attribute is used.

Let us consider what is not represented within the DTD, and see that it really does pertain to A's internal data representation, not to the transmitted message.

Beyond the embedded original SQL query, no representation is kept of the table or tables that were queried for data (the "FROM" clause). The particular table organization is simply not something B needs to be interested in. In fact, A may very well modify their database design after the transmission protocol is in place; but B need not worry about that as long as the same fields (columns) are extracted by some means. In particular, since the "AS" clause overrides the actual table column-name, it is possible to continue sending a XML element that no longer has any direct literal meaning in A's database.

Most importantly in the design of sql2dtd, "WHERE" and "HAVING" clauses are ignored (and also JOIN, DISTINCT and ALL modifiers). As with table names the particular joins and filters necessary to get the data out of A's tables just is not something B should have to worry about. If A happens to need to join together a few tables to get some datum, that is simply a normalization strategy by A. B may or may not use any analogous strategy (for a different data subset), and either way doe not care what A does. Filters (mostly using the "WHERE" clause or "DISTINCT" modifier) are ignored for a related, but slightly different reason. If for whatever business reasons, A only needs to inform B about those woozles whose whatzit is more than 25, from B's perspective that is just in the nature of woozles. That is A may be interested in a subclass of woozles B does not care about, but the specific fact that A needed to filter to get the interesting ones (as opposed to not having them, or putting them in different tables) is not B's worry. Sub-selects, in this respect, are just another kind of filter.

Wrapping Up

We have not seen anything on the specific usage of sql2dtd and sql2xml. Not much is needed here, since both are well documented internally. In general, sql2dtd can generate the DTD from an SQL query, but does not itself query any database. sql2xml peforms queries via ODBC, and optionally utilizes sql2dtd to get a DTD (or it can generate DTD-less XML documents).

What these tools help with is only approximately half the process contemplated between A and B. They can quickly arrive at DTDs using these tools, and A can equally quickly generate the output XML documents conforming with these DTDs. But B, at its end, still needs to do all the work involved in parsing, storing and processing these received documents. Later columns will discuss B's job in some more detail.


My fellow XML Zone columnist, Uche Ogbuji has written an interesting article covering somewhat different elements of RDBMS/XML connections for LinuxWorld. As well as writing a good article, Uche includes an extensive list of relevant resources:


My sql2dtd module can be obtained at:


Scott Hathaway's related sql2xml can be found at:


Matt Sergeant's DBIx::XML_RDB is a Perl module whose purpose is substantially similar to sql2xml. However, the XML documents generated by DBIx::XML_RDB lack an accompanying DTD:


About The Author

Picture of Author David Mertz, as a child had a quite large collection of Legos (or at least so it seemed). He donated them therefrom to Goodwill, perhaps just a bit earlier in childhood than he actually bored of them. But therein arises his love of small programming components. David may be reached at [email protected]; his life pored over athttp://gnosis.cx/publish/. Suggestions and recommendations on this, past, or future, columns are welcomed.