Web Data Management

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Web Data Management

• Raghu Ramakrishnan

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QUIQ Lessons

• Structured data management powers scalable
  collaboration environments
• ASP
• Multi-tenancy
• Massively distributed
• Fine-grained permissions, hierarchical acls
• RDBMSs were a lousy fit

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Cloud Computing Computing as a Service
Packaged Software
Cloud Computing
CPU Intensive
Data Intensive
High-throughput E.g., Condor
Analytic E.g., SSDS, Hadoop
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Implications

• Data management as a service
• Scientists and others whove resisted
  (installing, maintaining, and) using DBMSs will
  find it much easier to reap the benefits
• Data centers and Computing Centers will come
  into vogue again
• Hosted back-ends and RAD tools will make Web
  application development accessible to all
• The Web is becoming open
• E.g., OpenSocial, OpenID
• Ideas will be the most valuable currency, not the
  wherewithal to build complex systems
• Paradigm shifts possible for how we do research
  in many fields
• Build applications that embed your algorithms and
  test them directly in the fieldComputer
  Scientists can interact directly with users
  (ironically, this would still be a breakthrough
  of sorts after four decades!)
• Many other disciplines (e.g., Sociology,
  microeconomics) can design and conduct online
  experiments involving unprecedented numbers of
  participants

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PNUTS DB in the Cloud
Indexes and views
CREATE TABLE Parts ( ID VARCHAR, StockNumber
INT, Status VARCHAR )
Geographic replication
Parallel database
Structured, flexible schema
Hosted, managed infrastructure
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Basic Consistency Model

• Goal
• Make it easier for applications to reason about
  updates and cope with asynchronyalternative to
  transactions in an asynchronous world
• What happens to a record with primary key
  Brian?
• Guarantees
• Every reader will always see some consistent, but
  possibly stale version
• Readers can request a more up-to-date version,
  but may pay extra latency
• Special case Critical read (writer/readers see
  their own writes)
• Writers can verify that the record is still at
  the version they expect

Record inserted
Record inserted
Update
Record inserted
Update
Update
Update
Delete
Delete
Update
Delete
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Time
Generation 1
Generation 2
Generation 3
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Lots of Issues to Re-think

• Massive distribution replication
• Asynchrony
• Availability
• Consistency
• DBA to the world
• Auto-tuning
• Multi-tenancy
• Access control (granularity, online ids)
• Encryption
• App-support
• Caching

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Querying the Web

• Search will become more semanticbest-effort
  match-making between
• Query intent (NLP, query logs )
• Interpreted web content
• Deep web has a lot of structured data
• How we get a handle on it is an interesting
  problem
• But this is only part of the problem lots of
  data not here
• Semantic web isnt working
• Site-wrapping doesnt scale
• Solutions?
• Domain-wrapping
• Mass collaboration
• ??