A Visual Query Language for Business Processes

1
A Visual Query Language for Business Processes

• Catriel Beeri Hebrew University
• Anat Eyal,
• Simon Kamenkovich, Tel Aviv University
• Tova Milo

2
Outline

• Introduction and motivation
• Overview by example
• System and query formal model
• Compact representation of query answers
• Implementation
• Summary

3
The Standard Example
Credit Service
Consolidate Results
PO Service
Client
Inventory Service
4
Web Services Meet Business Processes
Local to company A
Web Service 1
Web Service 4
Web Service 2
Web Service 5
Web Service 3
Web Service n
At company B
On the Web
Company A business process
5
Recent History of Business Process Standards
BPML (Intallio et al)
BPSS (ebXML)
WS-Choreography (W3C)
WSCI (Sun et al)
2000/05
2001/03
2001/05
2001/06
2002/03
2002/06
2003/01
2003/04
2002/08
XLang (Microsoft)
WSFL (IBM)
BPEL4WS 1.0 (IBM, Microsoft)
BPEL4WS 1.1(OASIS)
WSCL (HP)
BPEL
6
BPEL in a nutshell

• Business process -- control and data flow
• Actions
• atomic
• compound fork, join, while, procedure/process
  call,
• Process spec. represented in XML
• Commercial products
• design tools with conceptual model
• Application generators compile to executable code
• Application servers execute the code

7
Points to note

• Not just a modeling language applications
  are automatically generated from the (relatively
  declarative) specs.
• There will be plenty of such specs around
• Specs are data a lot of interest in querying
  them
• What kind of credit services are used
  (in)directly?
• How can I buy a plane ticket ?
• Can one get a price quote without giving
  first credit card info?
• ? motivation for developing a query facility

8
Can a QL be based on BPEL?

• NO!
• The BPEL XML representation is machine oriented,
• unfit for human consumption
• It decomposes the system diagram into a
  (XML-based) relational representation of
  nodes and edges
• ? loss of understanding queries will require
  lots of joins
• Need Similarity of system and query models

9
Why not XQuery?(on XML representation of
conceptual model)

• Additional requirements from query language
• Graphs rather than trees
• Queries about control data flow paths
• Need to query at different level of granularity
• Zoom-in/zoom-out
• P2P architecture Specs are distributed
• ? We use a home-brewed QL

10
Querying Specs, not Runs

• Not the same semantics
• Q does the spec contain these two operations ?
  
• V can there be a run that contains these two
  operations?
• Querying the specs is
• Cheaper (specs are data, not possible
  executions)
• Gives a reasonably good approximation for actual
  runs
• A (practical) problem with verification
• It needs a clear semantics...

11
Outline

• Introduction and motivation
• Overview by example
• System and query formal model
• Compact representation of query answers
• Implementation
• Summary

12
A system specification

• Property, data activity nodes
• Control and data flow edges
• A process is a di-graph of atomic and compound
  activities
• Compound activities can be zoomed-in (a-la
  statecharts)

13
Travel Agency Process
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Zoom In
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Queries

• Use process patterns (like tree patterns for
  xml)
• Single/double-headed edges (compare to / and //
  in XPath)
• edges
• paths of arbitrary length
• Single/double-bounded activities
• w/o zoom-in
• unbounded zoom-in
• Allow as node label
• Node label variables
• Mark requested nodes/edges by

16
Query1 provided operations?
17
Query2 used credit card services?
local
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Query3 search without login?
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Query4 data flow
Data elements affected by searchRequest and
affecting returnTripResults
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Outline

• Introduction and motivation
• Overview by example
• System and query formal model
• Compact representation of query answers
• Implementation
• Summary

21
Formal Model

• System
• Process graphs implementation function
• Graph refinement (graph rewriting)
• Query
• Process patterns implementation function

22
System example
implementation
23
Refinement (rewriting)
searchTrip
refined to
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Query

• Process patterns
• node labels, node variables
• Nodes / edges can be marked as transitive
• Transitive edges paths of arbitrary
  length
• Transitive node refinements of arbitrary
  depth
• Nodes / edges can be marked as output
• Patterns related by a query implementation
  function

25
Query semantics

• An embedding a mapping
• from query graphs (with uniquely identifiable
  nodes)
• to refinements of process graphs
• satisfying conditions
• (nodes) preserves nodes types and labels
• (edges) edge mapped to
• edge mapped
  to a path
• (imp) preserves implementation
  relationships
• A result image of query graph under an
  embedding
• Answer all results

26

• Examples

answer
system
query
A B C
A1 B2 B3 4
A1 B2 B3 C4
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• Examples

System
A B C D
A B C
Query
A1 B2 B3 4
A1 B2 D3
Answer
A1 B2 B3 C4
A1 B2 C B D3
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Outline

• Introduction and motivation
• Overview by example
• System and query formal model
• Compact representation of query answers
• Implementation
• Summary

29
Large or Infinite answers!

• Many fork/joins ? exponential number of paths

30

• Infinite answers can be generated by either
• Cycles in process graph (example seen previously)
• Cycles (recursion) in zoom-in relationships
  ? Infinite of refinements
• Path vars (double headed edges) cycles
• ? infinite of results

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Recursive zoom-in
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A query with an infinite answer
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Finite representation
34

• Systems and queries are essentially
• regular graph grammars
• Bad news ?
• not closed under intersection (general case)
• Good news ?
• Our systems and queries are sufficiently simple
  Psize representation (as a regular
  grammar) can be computed in Ptime (data
  complexity!)
• skip

35
Answer construction

• Observations
• Embeddings (results) can be composed of
• query pattern to system process embeddings
  (results)
• glue the constraint (imp)
• Multiple embeddings can be represented by
• a shared node mapping
• (that satisfies (nodes) and (edges) -- a
  homomorphism)
• ? Construction of node mappings is the core
  problem

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Node mapping/answer construction

• The simple case from pQ to pS (not into
  refinement)
• Find node mappings that satisfy (nodes), (edges)
• NP-complete in pQ (query) , Ptime in pS
  (data)
• Results are 1-1 images of mappings
• each query node is distinct,
• new nodes and edges for paths (images of
  )

A B C D
A1 B2 C B D3
A1 B2 D3
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• The complex case from pQ to refinement of
  pS
• A mapping may be split into parts
• into pS itself
• into implementation of a compound action of pS,
  and so on
• with double-headed edges to any depth,
  including cycles
• Observations
• Only sub-graphs of pQ with single entry/exit can
  be mapped to an implementation
• In one mapping, a disjoint set of such graphs can
  be mapped to an implementation

38

• The construction For each pQ and pS
• For disjoint set J of such sub-graphs, construct
  mappings for pQ/J (each member of J replaced by
  node) to pS
• Do same for also for these sub-graphs
• Glue together using by a regular grammar
• nodes (suitably labeled) are non-terminals
• Each node (for G) is associated with the mappings
  for G

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Query
System
A
D
A
A
B
E
B
B
C
F
C
C
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Extensions to QL

• OK extensions
• label predicates ,
• Regular path expressions (on node labels),
• Negation,
• Joins on node labels
• Not OK extensions
• Joins on path variables
• The result is not a regular graph grammar
• Emptiness is undecidable
• NP-hard even without cycles and recursion

41
Outline

• Introduction and motivation
• Overview by example
• System and query formal model
• Compact representation of query answers
• Implementation
• Summary

42

• Simple and intuitive query formulation
• similar to how processes are specified
• Operates in distributed environment
• System and queries modeled as graph grammars
• ? allows compact representation of
  large/infinite answers
• Ignores semantics of composite actions
• AXML as an implementation platform supports
• Transparent distribution
• Taking advantage of built-in optimizations

43
High Lights of Model QL

• Base system unit directed node-labeled graph
• QL primitives
• /, // (forward axis only)
• Node equality
• Node label equality
• Node label predicates
• Regular expressions on node labels in paths
• Negation on sub-patterns
• Can be seen as adaptation of XPath to di-graphs,
  but selection not restricted to one path

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• Advanced system structure an infinite family
  of directed node-labeled graphs, specified by
  a graph grammar
• Additional QL primitives
• double-headed node query on all graphs derived
  from a given graph
• Answer representation as a graph grammar

45
Future work

• Investigate queries on logs
• Does this pattern exist?
• Querying of runs essentially verification
• Marxist extensions to QL primitives