Monitoring of distributed applications (in P2P) Serge Abiteboul, Pierre Bourhis, Bogdan Marinoiu, INRIA Saclay and Universit

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Monitoring of distributed applications (in P2P)
Serge Abiteboul, Pierre Bourhis, Bogdan
Marinoiu, INRIA Saclay and Université Paris 11
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Organization

• The context the AXML program
• Motivation for monitoring
• The architecture
• Axlog
• Example
• Conclusion

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The context the AXML program
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Distributed data management with AXML

• Active XML XML document with embedded function
  calls
• Intentional dynamic information
• In pull or push mode
• Object Active data
• AXML store AXML peer/V2
• persistence, activation of local data
• AXML query processor and optimizer Optimax
• Distributed query plans
• AXML Business artifacts verification
• AXML monitor P2Pmonitor
• Distributed monitoring

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Motivation
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With the Web, more and more distribution

• Often distributed applications are very dynamic
• Content change rapidly
• Intense communications
• Complex and hard to control systems
• Many peers
• Peers are distributed
• Peers are autonomous
• Peers are sometimes unreliable and selfish
• Peers sometimes come and leave
• Goal monitor such systems
• support active features ala active databases

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Example Dell supply chain
Suppliers
Monitoring of distributed information
manufacturing system
Monitor
Revolver
Monitor
Shipping Co.
Shipping Co.
Plant
Monitor
Monitor
Webstore
Customer
Monitor
Bank
Bank
Global supervisor
Monitor
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More examples

• Business applications
• Gather information for billing, bug tracing
• Procurement
• Web Intelligence e.g., business intelligence and
  surveillance of competing companies
• Security surveillance against intrusion, spamming
• P2P applications
• Optimization and tuning e.g., gather statistics,
  control indexing
• Error management, detection, diagnosis

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The architecture
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Architecture
Alerters
Streams
actions
Stream processors
publishers
RSS
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Alerter monitor a single system

• Detect events at the peer level
• Depend on the peer that is monitored
• Monitor what?
• Database updates
• Events in RSS feed
• Web page changes
• WS calls (in/out)
• Each event is represented as an XML document
• Active stream

Active stream
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Active streams

• Monotone case
• Stream of XML documents (possibly Active XML)
• Nonmonotone case
• Think of the stream as defining a forest
• We can send updates to the previous data,
  typically deletions
• Insert 12,jean,1300, 11,marie,1555
• Insert 3,zoe,1333
• Delete Id12 Insert 5,noé,1111
• In the style of RSS feeds
• Streams are published as channel where it is
  possible to subscribe
• They are implement as Web service calls

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Stream processors

• Efficient Filter - can support a large number of
  selections simultaneously
• Binary operators union, join, etc.
• Operator with memory duplicate elimination
• Aggregation operator
• Publisher
• XML page, RSS, email, Web page
• Novelty axlog (axlog subscription axlog
  engine)

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Algebraic (monitoring) plans

• ActiveXML algebra same algebra as for
  distributed query processing
• Algebra over streams of (A)XML documents
• To send just some tree T T, eos
• From ActiveXML XML embedded service calls
• A service may be any query
• The algebraic glue send, receive, eval

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Axlog (axml datalog)
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Axlog principle Doc query
Q

• Incoming streams
• The outgoing stream is defined by a query Q (tree
  pattern join)
• Each time an incoming message arrives, it
  modifies the document
• Possibly the query result
• An outgoing message is generated
• Incremental view maintenance

Active XML document
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Axlog - continued

• We have implemented an axlog engine
• We use datalog to benefit from
• Incremental view maintenance in datalog ?
  technique
• Query optimization in datalog Magic set
• We have developed specific techniques
• 3-valued based (true, false, possibleInFuture)
• Avoid some derivation that Magic would do
  preprocessing
• Precompute in an optimistic manner
• Garbage collection

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Example
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Example

• Some process (e.g.,, BPEL workflow mailOrder)
  may be initiated at a webStore in US or France
• The last operation of the process (e.g.,
  shipping) occurs on Shipping we are interested
  in shipping from UK
• We want to detect when one mailOrder took more
  that 5 days to process when the customer is a
  Premium customer
• Easy case
• Monotone in-stream
• Monotone query
• No time constraint
• No aggregation

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Local alerter specifications

• On webStore US and webStore FR
• for call in(WS-outCall)
• where call/method mailOrder
• return ltstartgt ltIdgt call/ID ltIdgt
• lttimegt call/time lt/timegt lt/startgt
• On shipping UK
• for call in(WS-outCall)
• where call/method shipping
• return ltstartgt ltIdgt call/ID ltIdgt
• lttimegt call/time lt/timegt lt/startgt

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Axlog specification

• AXML monitor.axml
• ltxmlgt ltstartsgt mailOrder-Alert_at_webStore.del
  l.com()
• mailOrder-Alert_at_webStore.dell.fr()
  lt/startsgt
• ltendsgt shippping-Alert_at_shipping.dell.uk(
  ) lt/endsgt
• lt/xmlgt
• Query from supervisor in India
• For s in doc(monitor.axml)/starts/start,
• e in doc(monitor.axml)/ends/end
• Where s/Id e/Id and s//Premium
• and (e/time - s/time) gt 1800 and
• Return ltlong IDe/idgt s, e lt/longgt

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Monitoring task plan
wsAlert_at_FR
wsAlert_at_US
wsAlert_at_UK
s
s
s
?
?Join
Reporter
Publisher
Emai lto India
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Monitoring task plan localisation
Site UK
wsAlerter s
wsAlerter s
wsAlerter
Publish
s
?
Site FR
Publish
?Join
Site US
Reporter
channel
Publisher
Email to India
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Conclusion

• Prelim paper in International Workshop on Web
  Information and Data Management 2007
• Demo in ICDE08
• On going
• Temporal queries
• Negation in queries
• Deletion
• Related work on Mashups with Tel Aviv Univ. IBM
  Haifa
• Purely relational

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Merci
Merci