1. OEM and LORE Query Language Sanjay Madria Department of Computer Science University of Missouri-Rolla madrias@umr.edu

2. Source : http://WWW-DB.Stanford.EDU/lore/

3. Semistructured Data (SSD) No explicit schema; Irregular and incomplete data Schema may be hidden or mixed with data Examples: –Semi-structured data arises mainly from the integration of heterogeneous data sources; both structured and non- rigid structured Information sources change, or new sources added. semantic discrepancies among heterogeneous data sources –Data from the web Overall site structure may change often. – Biological data

4. Characteristics of SSD Missing or additional attributes Multiple attributes Different types in different objects Heterogeneous collections Self-describing Irregular, no priori structure

5. Object Exchange Model (OEM) Motivation Self-describing data model information exchange and extraction Handle incomplete and irregular data Why a new data model? … it not a new model.

6. LORE Lore : Lightweight Object Repository –Lightweight because Object Model supported is lightweight No multiuser or heavyweight DBMS features

7. Lore - motivation Relational data model has null values, and OO models have inheritance and complex objects. Both have difficulties in designing schemas to incorporate irregular data. To manage semi-structured data, as in such environment : –Difficult to decide in advance on a single, correct schema as structure of the data may evolve rapidly, or data elements may change types, or data not conforming to previous structure may be added

8. Thus: –Need for management of semi-structured data! Data managed by Lore is not confined to a schema and it may be irregular or incomplete. OEM is the Lore’s data model. Lorel is Lore’s query language.

9. Object Exchange Model (OEM) Data in this model can be thought of as a labeled directed graph. –Schema-less and self-describing. –nodes are objects and –edges are labeled with attribute names and, –leaf nodes have atomic values Object nesting. Vertices in graph are objects. –Each object has a unique object identifier (oid), such as &5. –Atomic objects have no outgoing edges and are of types such as int, real, string, gif, java, etc. –All other objects that have outgoing edges are called complex objects.

10. OEM (Cont.) Examples: –Object &3 is complex, and its subobjects are &8, &9, &10, and &11. –Object &7 is atomic and has value “Clark”. DBGroup is a name that denotes object &1. (Names are entry points into the database). Type and structure heterogeneity : Observe that members may have 0, 1 or more offices, office is a string and sometimes, also complex object, a room may be string and integer DbGroup.Member denotes all member-labeled subobjects

11. DBGroup &1 &2&3&4&5&6 &11&8 &9 &10&12&13&14&7&15&16 &17&18&19&20 Member Office Age NameProject Name Age Office RoomBuilding Room “Clark”“Smith ” 46“Gates 252” “Lore”“Tsimmis ” “Jones”28 An OEM Database “CIS”“411”“CIS”252

12. Object Exchange Model - OEM Each value exchanged is given an explicit label. Object  temp-in-Fahrenheit, integer, 80  -“temp-in-Fahrenheit” is the label. -Each object is self-describing, with a label, type and value.  set-of-temps, set, {cmpnt1, cmpnt2}  cmpnt1 is  temp-in-Fahrenheit, integer, 80  cmpnt2 is  temp-in-Celsius, integer, 20 

13. Labels Lables Play two roles – identifying an object (component) –identifying the meaning of an object (component) Person-name both identifies cmpnt1 and coveys its meaning.  person-record, set, {cmpnt1, cmpnt2, cmpnt3}  cmpnt1 is  person-name, string, ``Fred’’  cmpnt2 is  office-num-in-bldg-5, integer, 333  cmpnt3 is  department, string, ``toy’’  In relational data this corresponds to ….

14. Labels - Issues Labels are relative (more specific) to the source of the data object. Similar labels from different sources need to be resolved. Labels provide the flexibility in representing object structure

15. OEM - Specification Each object in OEM has the following structure: –Label: A variable character string describing what the object represents. –Type: The data type of the object’s value. Each is either an atom type, or type set. –Value: A variable-length value of the object. –Object-ID: A unique variable-length identifier for the object or null. LabelTypeValueObject-ID

16. OEM - Summary OEM is an information exchange model. It does not specify how objects are stored at source. OEM does specify how objects are received at a client, but after objects are received they can be stored in any way the client likes. Each source has a distinguished object with lexical identifier ``root’’.

17. Example doc1 is auths1 is auth11 is topic1 is call-no1 is doc2 is auths2 is auth21 is auth22 is auth23 is topic2 is call-no1 is docn is authsn is <auth,string, ``Crichton’’> topic1 is call-no1 is biblio is the root object.

18. OEM - QL SELECT Fetch-expression FROM Object WHERE Condition The result of this query is itself an object, with special label ``answer’’:  answer, set, {obj1, obj2, …, objn}  Each returned obji is a component of object specified in the From clause of the query, where the component is located by the Fetch- expression and satisfies the Condition.

19. Path The notion of path is used in both Fetch- Expression in the Select clause and the condition in the Where clause. Path describes traversals through an object using subobject structure and labels. Example: ``biblio.doc.auth’’ Paths are used in Fetch-Expression to specify which components are are returned in the answer object. Paths are used in the condition to qualify the fetched objects or other (related) components in the same object structure.

20. Queries - Simple Retrieve the topic of each document for which ``Ullman’’ is one of the authors: SELECT biblio.doc.topic FROM root WHERE biblio.doc.auth-set.auth-ln = ``Ullman’’ Intuitively, the query’s where clause finds all paths through subobject structure with the sequence of labels [biblio,doc,auth-set,auth-ln] such that the object at the end of the path has value ``Ullman.’’ obj1 is obj2 is

21. Queries - ``wild-cards’’ Retrieve all documents with internal call number: SELECT biblio.?.topic FROM root WHERE biblio.?.internal-call-no ``?’’ label matches any label. For this query, the doc labels can be replaced by any other strings and query would produce the same result. By convention, two occurrences of ? In the same query must match the same label unless variables are used. obj1 is

22. Queries - ``wild-paths’’ Retrieve all documents with internal call number: SELECT *.topic FROM root WHERE *.internal-call-no Symbol ``*’’ matches any path of length one or more. The use of * followed by a single label is a convenient and common way to locate objects with a certain label in complex structure. Similar to ?, two occurrences of * in the same query must match the same sequence of labels, unless variables are used. obj1 is

23. Queries - variables Retrieve each document for which both ``Hopcroft’’ and ``Aho’’ are co-authors: SELECT biblio.doc FROM root WHERE biblio.doc.auth-set.auth-ln=``Aho’’ and biblio.doc.auth-set.auth-ln=``Hopcroft’’ Here, the query finds all the paths with structure [biblio, doc, auth-set], and with two distinct path completions with label auth with values ``Aho’’ and ``Hopcroft’’ obj1 is the complete doc2

24. Lorel Query Language Need query language that supports path expressions for traversing graph data and handling of ‘typeless’ data. A simple path expression is a name followed by a sequence of labels. –DBGroup.Member.Office. –Set of objects that can be reached starting with the DBGroup object, following edges labeled as member and then office.

25. Lorel (cont.) Example: –select DBGroup.Member.Office where DBGroup.Member.Age < 30 Result: –Office “Gates 252” –Office Building “CIS” Room “411”

26. Lorel Query Rewrite Previous query rewritten to (OQL style) –select O from DBGroup.Member M, M.Office O where exists y in M.Age : y < 30

27. Lorel Query Features Explicitly handle coercion. Automatic type coercion 0.5 < “0.9” should return true Comparison on age transformed to existential condition. Since all properties are set-valued in OEM. A user can ask DBGroup.Member.Age < 30 regardless of whether Age is single valued, set valued, or unknown.

28. Path expression queries -specification for a set of possible paths through the graph –Example - * is a path expression that matches any number of labels Use of Data guides – Structural summary of the database

29. Lorel (cont.) General path expressions are loosely specified patterns for labels in the database. (‘|’ disjunction, ‘?’ label pattern optional) Example: –select DBGroup.Member.Name where DBGroup.Member.Office(.Room%|.Cubicle)? like “%252” Result: –Name “Jones” Name “Smith”

30. Lorel Queries - Simple Path Expression Retrieve the offices of members with age greater than 30 years: Query SELECT DBGroup.Member.Office WHERE DBGroup.Member.Age > 30 ResultOffice “Gates 252” Office Building “CIS” Room “411”

31. Queries - General Path Expression Query SELECT DBGroup.Member.Name WHERE DBGroup.Member.Office(.Room%|.Cubicle)? Like “%252” ResultName “Jones” Name “Smith” Room% matches all labels starting from Room, like Room68. “|” stands for disjunction. “?” indicates that the label pattern is optional. “like %252” specifies that the data value should end with string “252”.

32. Queries - SubQueries Retrieve Lore project members who work on other projects Query SELECT M.Name, ( SELECT M.Project.Title WHERE M.Project.Title != “Lore”) FROM DBGroup.Member M WHERE M.Project.Title = “Lore” ResultMember Name “Jones” Title “Tsimmis”

33. Lore - Summary Lore does facilitate query and updates on semi- structural databases There has been more work done on optimization using: data guides (vldb97). How is this related to WWW? XML-QL and related work provides the answer.