Approximate XML Query Answers

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• Approximate XML Query Answers

Authors N. polyzotis, M. Garofalakis, Y.
Ioannidis
Presenter Hongyu Guo
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Outline of this talk

• Motivation
• TreeSketch Approach
• Experimental Results
• Contributions and Limitations

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Outline

• Motivation
• TreeSketch Approach
• Experimental Results
• Contributions and Limitations

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Motivations
--Need fast feedback

• XML de-facto standard for data exchange
• Need to explore large XML data sets and get fast
  feedback from complex XML queries
• Conflict between fast on-line response and
  query execution cost

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XML Query Challenges

• Involve complex traversals of the XML data
  hierarchy
• Complex queries over massive tree-structured
  data--very expensive
• Approaches Optimize the query or optimize the
  data structure
• No need for accurate results, we can instead
  return approximate query answers

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Approximate Query answers
R
Query
.
R

• Obtain an approximation to the true result
• Currently employed in relational systems
  successfully
• Use approximate result to get timely feedback

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Outline
--A technique being used to return fast,
approximate results

• Motivation
• TreeSketch Approach
• Experimental Results
• Contributions and Limitations

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Data and Query Model
--Some background, XML document
a author n name b book p paper y year
k keyword t title
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Data and Query Process
--Twig Query, Query Tree, and Nested Result Tree
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Basic Query Scenario
Approximate Nesting Tree
True Nesting Tree

• Key idea is to return fast, accurate feedback

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Approximate Query Answers
-- Two key problems

• How to construct concise XML synopses, which
  capture the statistical traits of the true data
• How to produce approximate query answers over the
  synopsis efficiently

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TreeSketch Construction
--Construction Algorithm

• Step 1
• Given an XML tree T, build a graph synopsis each
  node represents a set of same tag elements, large
  tree
• Step2
• Compress synopsis by merging nodes with similar
  sub-structures (i.e. clustering of the XML
  elements)
• Step 3
• Repeat Step 2 until the predefined space budget
  constraint is met
• Step 4
• Return the TreeSketch Synopsis

Space Budget
Perfect
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More Discussions
--of the construction procedure

• Graph synopsis construction
• Use node to represent a set of same tag elements
• Query can be retrieved with zero-error
• The size can become very large-it can easily be
  in the order of the original document size
• TreeSketch synopsis construction
• Compress the synopsis by merging nodes
• Bottom-up merging clustering algorithm
• Key technique to compress ? Clustering
• Based on structure
• Model accuracy depends on quality of clustering
• Tight clusters ? Accurate synopsis, but large
  model
• Loose clusters ? Less accuracy, but small model

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Construction Example
--Count same tag elements
XML Document
(Graph Synopsis)

• Synopsis node ? Set of elements of the same tag
• Synopsis edge ? Document edge(s)

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Construction Example
--Calculate number of children per element

• Calculate the number of children for each edge
• Count r, p mean children in p per element in r

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Merging Nodes
--Less space budget
TreeSkech synopsis
R(1)
1
P(1)
More Concise Synopsis
2
S(2)
2
F(4)
1
0.5
C(4)
E(2)
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Compute Approximate Answers
--more like the traditional way

• Travel down the tree
• Match a pattern in the structure and return a
  sub-tree
• TreeSketch Fast response
• Concise synopsis
• Keep statistical information
• Node number of same tag elements
• Edge number of children per element

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Compute Approximate Answers
--Example
TreeSketch
Query
Approximate Nesting Tree
R
q0
//section
q1
.//caption
.//equation
q2
q3
Approximate results with structure 1) Take
advantage of the concise structure 2) and the
statistical data
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Outline

• Motivation
• TreeSketch Approach
• Experimental Results
• Contributions and Limitations

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Experimental Setup

• Focus on
• the quality of the approximate answers generated
• the efficiency of the construction process
• Data Set
• Data Sets XMark, DBLP, IMDB, SwissProt
• Workload 1000 random twig queries

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Evaluation Methods

• Error ? Distance between R and R
• Popular metric Tree-edit distance
• Min-cost sequence of operations that transform R
  to R
• Argument not capture the structure similarity
• New Evaluation metrics ESD (Element Simulation
  Distance)
• Calculate the number of children for each edge in
  the tree to capture the complete structure of the
  tree
• model how well the structure of two trees match
  from each other
• degree of simulation between two trees
• Average ESD for evaluation

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Experimental Results
--Approximate answers, compared with TwigXsketches
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Experimental Results
--Relative Errors
lt 5 i.e. 95 accuracy
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Outline
-Strengths and Weaknesses

• Motivation
• TreeSketch Approach
• Experimental Results
• Contributions and Limitations

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TreeSketch Approach
-In this paper

• Propose an effective XML-summarization mechanism
• Captures the complete tree structure of large XML
  data
• Experimental results produce fast and accurate
  approximate query answers
• Author claim The first work to address the
  timely problem of producing approximate
  tree-structured answers for complex XML queries
• Comparison with the related work 2 options
• Either compute the exact answer to a path query
  expensive
• Or use an approach such as twig-XSketch, which
  does not capture the complete tree structure of
  the underlying XML database

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Limitations
-Nice research, Next steps for further
investigation

• Difficult to optimize some pre-defined
  parameters, such as the space budget
• which directly related to the accuracy of the
  approximate query answers
• too large ? affect the efficiency, too small ?
  quality of the answers depends on the query,
  data set, and the computing resources
• Expecting incremental model construction process
• XML data always increase incrementally, we need
  to construct the synopsis model incrementally
• More experiments or some real applications are
  needed to justify the scalability of this
  technique

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Thank You / Merci