NAME DBIx::DBStag - Relational Database to Hierarchical (Stag/XML) Mapping SYNOPSIS use DBIx::DBStag; my $dbh = DBIx::DBStag->connect("dbi:Pg:dbname=moviedb"); my $sql = q[ SELECT studio.*, movie.*, star.* FROM studio NATURAL JOIN movie NATURAL JOIN movie_to_star NATURAL JOIN star WHERE movie.genre = 'sci-fi' AND star.lastname = 'Fisher' USE NESTING (set(studio(movie(star)))) ]; my $dataset = $dbh->selectall_stag($sql); my @studios = $dataset->get_studio; # returns nested data that looks like this - # # (studio # (name "20th C Fox") # (movie # (name "star wars") (genre "sci-fi") # (star # (firstname "Carrie")(lastname "Fisher"))))) # iterate through result tree - foreach my $studio (@studios) { printf "STUDIO: %s\n", $studio->get_name; my @movies = $studio->get_movie; foreach my $movie (@movies) { printf " MOVIE: %s (genre:%s)\n", $movie->get_name, $movie->get_genre; my @stars = $movie->get_star; foreach my $star (@stars) { printf " STARRING: %s:%s\n", $star->get_firstname, $star->get_lastname; } } } # manipulate data then store it back in the database my @allstars = $dataset->get("movie/studio/star"); $_->set_fullname($_->get_firstname.' '.$_->get_lastname) foreach(@allstars); $dbh->storenode($dataset); Or from the command line: unix> selectall_xml -d 'dbi:Pg:dbname=spybase' 'SELECT * FROM studio NATURAL JOIN movie' DESCRIPTION This module is for mapping from databases to Stag objects (Structured Tags - see the Data::Stag manpage), which can also be represented as XML. It has two main uses: Querying This module can take the results of any SQL query and decompose the flattened results into a tree data structure which reflects the foreign keys in the underlying relational schema. It does this by looking at the SQL query and introspecting the database schema, rather than requiring metadata or an object model. In this respect, the module works just like a regular the DBI manpage handle, with some extra methods provided. Storing Data DBStag objects can store any tree-like datastructure (such as XML documents) into a database using normalized schema that reflects the structure of the tree being stored. This is done using little or no metadata. XML can also be imported, and a relational schema automatically generated. For a tutorial on using DBStag to build and query relational databases from XML sources, please see the DBIx::DBStag::Cookbook manpage HOW QUERYING WORKS This is a general overview of the rules for turning SQL query results into a tree like data structure. Relations Relations (i.e. tables and views) are elements (nodes) in the tree. The elements have the same name as the relation in the database. Columns Table and view columns of a relation are sub-elements of the table or view to which they belong. These elements will be data elements (i.e. terminal nodes). Only the columns selected in the SQL query will be present. For example, the following query SELECT name, job FROM person; will return a data structure that looks like this: (person (name "fred") (job "forklift driver")) (person (name "joe") (job "steamroller mechanic")) The data is shown as a lisp-style S-Expression - it can also be expressed as XML, or manipulated as an object within perl. Table aliases If an ALIAS is used in the FROM part of the SQL query, the relation element will be nested inside an element with the same name as the alias. For instance, the query SELECT name FROM person AS author WHERE job = 'author'; Will return a data structure like this: (author (person (name "Philip K Dick"))) The underlying assumption is that aliasing is used for a purpose in the original query; for instance, to determine the context of the relation where it may be ambiguous. SELECT * FROM person AS employee INNER JOIN person AS boss ON (employee.boss_id = boss.person_id) Will generate a nested result structure similar to this - (employee (person (person_id "...") (name "...") (foo "...") (boss (person (person_id "...") (name "...") (foo "..."))))) If we neglected the alias, we would have 'person' directly nested under 'person', and the meaning would not be obvious. Note how the contents of the SQL query dynamically modifies the schema/structure of the result tree. NOTE ON SQL SYNTAX Right now, DBStag is fussy about how you specify aliases; you must use AS - you must say SELECT name FROM person AS author; instead of SELECT name FROM person author; Nesting of relations The main utility of querying using this module is in retrieving the nested relation elements from the flattened query results. Given a query over relations A, B, C, D,... there are a number of possible tree structures. Not all of the tree structures are meaningful. Usually it will make no sense to nest A under B if there is no foreign key relationship linking either A to B, or B to A. This is not always the case - it may be desirable to nest A under B if there is an intermediate linking table that is required at the relational level but not required in the tree structure. DBStag will guess a structure/schema based on the ordering of the relations in your FROM clause. However, this guess can be over-ridden at either the SQL level (using DBStag specific SQL extensions) or at the API level. The default algorithm is to nest each relation element under the relation element preceeding it in the FROM clause; for instance: SELECT * FROM a NATURAL JOIN b NATURAL JOIN c If there are appropriately named foreign keys, the following data will be returned (assuming one row in each of a, b and c) (set (a (a_foo "...") (b (b_foo "...") (c (c_foo "..."))))) where 'x_foo' is a column in relation 'x' This is not always desirable. If both b and c have foreign keys into table a, DBStag will not detect this - you have to guide it. There are two ways of doing this - you can guide by bracketing your FROM clause like this: !!## !!## NOTE - THIS PART IS NOT SET IN STONE - THIS MAY CHANGE !!## SELECT * FROM (a NATURAL JOIN b) NATURAL JOIN c This will generate (set (a (a_foo "...") (b (b_foo "...")) (c (c_foo "...")))) Now b and c are siblings in the tree. The algorithm is similar to before: nest each relation element under the relation element preceeding it; or, if the preceeding item in the FROM clause is a bracketed structure, nest it under the first relational element in the bracketed structure. (Note that in MySQL you may not place brackets in the FROM clause in this way) Another way to achieve the same thing is to specify the desired tree structure using a DBStag specific SQL extension. The DBStag specific component is removed from the SQL before being presented to the DBMS. The extension is the USE NESTING clause, which should come at the end of the SQL query (and is subsequently removed before processing by the DBMS). SELECT * FROM a NATURAL JOIN b NATURAL JOIN c USE NESTING (set (a (b)(c))); This will generate the same tree as above (i.e. 'b' and 'c' are siblings). Notice how the nesting in the clause is the same as the nesting in the resulting tree structure. Note that 'set' is not a table in the underlying relational schema - the result data tree requires a named top level node to group all the 'a' relations under. You can call this top level element whatever you like. If you are using the DBStag API directly, you can pass in the nesting structure as an argument to the select call; for instance: my $seq = $dbh->selectall_xml(-sql=>q[SELECT * FROM a NATURAL JOIN b NATURAL JOIN c], -nesting=>'(set (a (b)(c)))'); or the equivalent - my $seq = $dbh->selectall_xml(q[SELECT * FROM a NATURAL JOIN b NATURAL JOIN c], '(set (a (b)(c)))'); If you like, you can also use XML here (only at the API level, not at the SQL level) - my $seq = $dbh->selectall_xml(-sql=>q[SELECT * FROM a NATURAL JOIN b NATURAL JOIN c], -nesting=>q[ ]); As you can see, this is a little more verbose. Most command line scripts that use this module should allow pass-through via the '-nesting' switch. Aliasing of functions and expressions If you alias a function or an expression, DBStag needs to know where to put the resulting column; the column must be aliased. This is inferred from the first named column in the function or expression; for example, in the SQL below SELECT blah.*, foo.*, foo.x - foo.y AS z The z element will be nested under the foo element You can force different nesting using a double underscore: SELECT blah.*, foo.*, foo.x - foo.y AS blah__z This will nest the z element under the blah element Conformance to DTD/XML-Schema DBStag returns the Data::Stag manpage structures that are equivalent to a simplified subset of XML (and also a simplified subset of lisp S-Expressions). These structures are examples of semi-structured data - a good reference is this book - Data on the Web: From Relations to Semistructured Data and XML Serge Abiteboul, Dan Suciu, Peter Buneman Morgan Kaufmann; 1st edition (January 2000) The schema for the resulting Stag structures can be seen to conform to a schema that is dynamically determined at query-time from the underlying relational schema and from the specification of the query itself. CLASS METHODS connect Usage - $dbh = DBIx::DBStag->connect($DSN); Returns - L Args - see the connect() method in L selectall_stag Usage - $stag = $dbh->selectall_stag($sql); $stag = $dbh->selectall_stag($sql, $nesting_clause); $stag = $dbh->selectall_stag(-template=>$template, -bind=>{%variable_bindinfs}); Returns - L Args - sql string, [nesting string], [bind hashref], [template DBIx::DBStag::SQLTemplate] Executes a query and returns a the Data::Stag manpage structure An optional nesting expression can be passed in to control how the relation is decomposed into a tree. The nesting expression can be XML or an S-Expression; see above for details selectall_xml Usage - $xml = $dbh->selectall_xml($sql); Returns - string Args - See selectall_stag() As selectall_stag(), but the results are transformed into an XML string selectall_sxpr Usage - $sxpr = $dbh->selectall_sxpr($sql); Returns - string Args - See selectall_stag() As selectall_stag(), but the results are transformed into an S-Expression string; see the Data::Stag manpage for more details. selectall_sax Usage - $dbh->selectall_sax(-sql=>$sql, -handler=>$sax_handler); Returns - string Args - sql string, [nesting string], handler SAX As selectall_stag(), but the results are transformed into SAX events [currently this is just a wrapper to selectall_xml but a genuine event generation model will later be used] selectall_rows Usage - $tbl = $dbh->selectall_rows($sql); Returns - arrayref of arrayref Args - See selectall_stag() As selectall_stag(), but the results of the SQL query are left undecomposed and unnested. The resulting structure is just a flat table; the first row is the column headings. This is similar to DBI->selectall_arrayref(). The main reason to use this over the direct DBI method is to take advantage of other stag functionality, such as templates prepare_stag SEMI-PRIVATE METHOD Usage - $prepare_h = $dbh->prepare_stag(-template=>$template); Returns - hashref (see below) Args - See selectall_stag() Returns a hashref { sth=>$sth, exec_args=>\@exec_args, cols=>\@cols, col_aliases_ordered=>\@col_aliases_ordered, alias=>$aliasstruct, nesting=>$nesting }; storenode Usage - $dbh->storenode($stag); Returns - Args - L Recursively stores a tree structure in the database SQL TEMPLATES DBStag comes with its own SQL templating system. This allows you to reuse the same canned SQL or similar SQL qeuries in different contexts. See the DBIx::DBStag::SQLTemplate manpage find_template Usage - $template = $dbh->find_template("my-template-name"); Returns - L Args - str Returns an object representing a canned paramterized SQL query. See the DBIx::DBStag::SQLTemplate manpage for documentation on templates list_templates Usage - $templates = $dbh->list_templates(); Returns - Arrayref of L Args - Returns a list of ALL defined templates - See the DBIx::DBStag::SQLTemplate manpage find_templates_by_schema Usage - $templates = $dbh->find_templates_by_schema($schema_name); Returns - Arrayref of L Args - str Returns a list of templates for a particular schema - See the DBIx::DBStag::SQLTemplate manpage find_templates_by_dbname Usage - $templates = $dbh->find_templates_by_dbname("mydb"); Returns - Arrayref of L Args - db name Returns a list of templates for a particular db Requires resources to be set up (see below) RESOURCES resources_list Usage - $rlist = $dbh->resources_list Returns - arrayref to a hashref Args - none Returns a list of resources; each resource is a hash {name=>"mydbname", type=>"rdb", schema=>"myschema", } SETTING UP RESOURCES The above methods rely on you having a file describing all the relational dbs available to you, and setting the env var DBSTAG_DBIMAP_FILE set (this is a : separated list of paths). This is alpha code - not fully documented, API may change Currently a resources file is a whitespace delimited text file - XML/Sxpr/IText definitions may be available later Here is an example of a resources file: # LOCAL mytestdb rdb Pg:mytestdb schema=test # SYSTEM worldfactbook rdb schema=wfb employees rdb schema=employees The first column is the nickname or logical name of the resource/db. This nickname can be used instead of the full DBI locator path (eg you can just use employees instead of dbi:Pg:dbname=employees; The second column is the resource type - rdb is for relational database. You can use the same file to track other system datasources available to you, but DBStag is only interested in relational dbs. The 3rd column is a way of locating the resource - driver:name@host The 4th column is a ; separated list of tag=value pairs; the most important tag is the schema tag. Multiple dbs may share the same schema, and hence share SQL Templates COMMAND LINE SCRIPTS DBStag is usable without writing any perl, you can use command line scripts and files that utilise tree structures (XML, S-Expressions) -d [-n ] Queries database and writes decomposed relation as XML Can also be used with templates: -d / ... -d [-n ] Queries database and writes decomposed relation as HTML with nested tables indicating the nested structures. -d Stores data from a file (Supported formats: XML, Sxpr, IText - see the Data::Stag manpage) in a normalized database. Gets it right most of the time. TODO - metadata help [-l ]* Takes data from a file (Supported formats: XML, Sxpr, IText - see the Data::Stag manpage) and generates a relational schema in the form of SQL CREATE TABLE statements. ENVIRONMENT VARIABLES DBSTAG_TRACE setting this environment will cause all SQL statements to be printed on STDERR BUGS This is alpha software! Probably several bugs. The SQL parsing can be quite particular - sometimes the SQL can be parsed by the DBMS but not by DBStag. The error messages are not always helpful. There are probably a few cases the SQL SELECT parsing grammar cannot deal with. If you want to select from views, you need to hack DBIx::DBSchema (as of v0.21) TODO Use SQL::Translator to make SQL DDL generation less Pg-specific; also for deducing foreign keys (right now foreign keys are guessed by the name of the column, eg table_id) Can we cache the grammar so that startup is not so slow? Improve algorithm so that events are fired rather than building up entire structure in-memory Tie in all DBI attributes accessible by hash, i.e.: $dbh->{...} Error handling WEBSITE AUTHOR Chris Mungall COPYRIGHT Copyright (c) 2004 Chris Mungall This module is free software. You may distribute this module under the same terms as perl itself