Peer-to-Peer Databases

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Peer-to-Peer Databases

• David Andersen
• Advanced Databases

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What is Peer-to-Peer?

• Shared Resources
• Each peer is a shares its resources with
  others, acting as both a client and server.
• Decentralization and Self-organization
• Peers coordinate their activities with other
  peers rather than with a centralized server.
• Autonomy
• Peers are free to come and go at will.

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Napster

• Hybrid P2P
• Data stored on peers, but a central server
  maintained index of file location.
• File sharing - not a DBMS system.

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Gnutella

• True P2P - Peer need only know one other peer to
  join.
• The Gnutella Protocol

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Gnutella

• Uses Flooding
• Queries hop from peer-to-peer. A TTL
  (time-to-live) sent with the query prevents
  eternal searching.
• Very High Bandwidth Usage.
• File Sharing Not DBMS

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P2P and Databases

• Advantages
• No Bottlenecks
• Vast Resources Available
• Improved Scalability
• Improved Robustness
• Less Management
• Access to a tremendous amount of data

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P2P and Databases

• Challenges
• Coordinating Semantics
• Query Processing Efficiency
• Topology/Bandwidth Considerations
• Indexing
• Replication
• Performing Updates and Avoiding Stale Data
• Security - Access Control and Peer Reputation

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Case Study Hyperion Project

• Peers have a own local DBMS.
• PeerDBMS layer augments the local DBMS to support
  peer-to-peer functionality.
• Peers can form acquaintances.
• Metadata is exchanged and the semantics of the
  peer acquaintance is mapped on the local system.
• Uses Pair-wise Mappings to resolve queries.

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The Hyperion PDBMS

• Query Service
• Handles Local Queries
• Uses Mapping Tables to Rewrite or Translate
  Queries destined for Remote Databases
• Peer Coordination Service
• Manages and Executes Updates
• Uses Event-Condition-Action Rules

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The Hyperion PDBMS

• P2P User Interface
• Local and Peer Queries are posed through the
  interface
• User is unaware of differing semantics at the
  peer
• Peer Manager
• Messaging system to communicate with peers
• Acquaintance Manager
• Manages exchange of schemas, mapping tables, and
  rules for updating data

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Hyperion Mapping Tables

• Table from Airline A
• Table from Airline B
• Mapping Tables

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Case Study The Piazza Project

• Project Goals
• Focus on developing query reformulation
  algorithms
• Assist in defining mappings
• Indexing
• Enforcing access control

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Piazza Schema Mappings

• Two types of mappings
• Peer Description
• Relates two or more peer schemas
• Example DBProjectsMember(pName, member)
• UWMember(mid, pid, member), UWProject(pid,
  pName)
• Storage Description
• Relates data stored in at a peer into peers view
  of the world.
• ExampleUPennstudent(sid, name, advisor)
  UPennStudent(sid, name),
• UPennAdvisor(sid, fid), UPennFaculty(fid,
  advisor)

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Piazza Querying Reformulation Example
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Piazza Indexing

• Challenge
• How to send a query to a peer most likely to
  have the answer and avoid flooding entire
  network.
• Piazza attempts to index schema and value
  mappings.
• Current implementation is centralized
• Peers upload summaries of differing granularity
  of data they possess
• Peers periodically refresh their data summaries
  at the index.

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Piazza Indexing

• Peers upload attribute value pairs.
• Index maintains a table of these pairs together
  with the object id of its origin.
• Users query to the index and are returned the
  object which contains at least a partial match.
• An example of an object that is indexed
• s2 name "Por", age IN 50, 70,
• disease "tuberculosis", type ""

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Update Management

• Data is often replicated with traditional
  distributed databases
• Problem is to avoid reading stale data
• Technique Use Read Consensus and Write
  Consensus
• Example Write to majority before performing
  update and/or read to a majority and accept
  newest version.

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Update Management

• Quorum Consensus can work with P2P too, but not
  with 100 guarantee because actual number of
  replications is not known, so setting a quorum
  very difficult.
• Allow user to set quorum thresholds and accept
  the consequences of their decisions.

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Update Management

• Trade-offs

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Questions?
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References

• Flexible Update Management in Peer-to-Peer
  Database Systems,David Del Vecchio and Sang H.
  Son, Department of Computer Science, University
  of Virginia
• An Overview on Peer-to-Peer Information Systems,
  Karl Aberer, Manfred Hauswirth, Swiss Federal
  Institute of Technology (EPFL), Switzerland
• Data Sharing in the Hyperion Peer Database
  System, Patricia Rodríguez-Gianolli et al,
  Proceedings of the 31st VLDB Conference,Trondheim,
  Norway, 2005
• The Hyperion ProjectFrom Data Integration to
  Data Coordination, Marcelo Arenas et al, SIGMOD
  Record, Vol. 32, No. 3, September 2003
• The Piazza Peer Data Management Project, Igor
  Tatarinov et al, SIGMOD Record, Vol. 32, No. 3,
  September 2003
• Distributed Query Processing in P2P Systems with
  incomplete schema information,
• Marcel Karnstedt, Katja Hose, Kai-Uwe Sattler,
  Department of Computer Science and Automation, TU
  Ilmenau P.O. Box 100565, D-98684 Ilmenau, Germany