1. Early Profile Pruning on XML-aware Publish-Subscribe Systems
Mirella M. Moro, Petko Bakalov, Vassilis J. Tsotras
University of California, Riverside
2/2/2019

2. Overview Motivation Bottom-up Filtering FSM (BUFF)
Bounding-based XML Filtering (BoxFilter)
Core Modules
Filtering algorithms
Experimental results
Overview of the talk
2/2/2019

3. Motivation
Publish-subscribe systems: The message transmission is defined by the message content
Examples: notification websites hotwire.com or ticketmaster.com
Publisher
Publisher
Publisher
Publisher
Docu
ments
Docu
ments
Docu
ments
Docu
ments
Matching algorithm Re su l t Re su l t Re su l t Re su l t
Prof
ile
Prof
ile
Prof
ile
Prof
ile
Submit,
Update,
Delete
Submit,
Update,
Delete
Submit,
Update,
Delete
Submit,
Update,
Delete
Subscriber
Subscriber
Subscriber
Subscriber
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4. Publish-subscribe systems
The data is exchanged in XML format.
Nodes - correspond to elements, attributes or text values
Edges represent immediate element-subelement or element-value relationships
<Bib>
<article vol=“7” no=“11”>
<title>t1</title>
<author>
<last>DeWitt</last>
<mi>J</mi>
<first>David</first>
</author>
<journal>TPDS</journal>
<year>1996</year>
</article>
<article>
<title>t2</title>
<last>Florescu</last>
<first>Daniela</first>
<proceedings>SIGMOD
</proceedings>
<year>2006</year>
</Bib>
Bib
article
title
journal
author
last
first
David
DeWitt
TPDS t1
proceedings
Daniela
Florescu
SIGMOD t2 mi J
year
1996
2006 no 11
vol 7
Overview of the talk
(a) Document
(b) Tree representation
2/2/2019

5. Publish-subscribe systems (cont.)
The user profiles are expressed in XML query language (XPath, XQuery)
XML query contains
structural constraints
value-based constraints
Structural constraints:
Tree pattern:
article
author
proceedings
last
conf
Overview of the talk
2/2/2019

6. Related Work/Our Contribution
Current work
Construction of overlay network
Dissemination/indexing of profiles (queries)
Processing of stream of messages
We focus on the matching process that takes place within a broker
Improves the performance of regular FSM by using a bottom-up evaluation of the document
Develop index-based filtering technique that performs early pruning of the query profile
2/2/2019

7. Overview Motivation Bottom-up Filtering FSM (BUFF)
Bounding-based XML Filtering (BoxFilter)
Core Modules
Filtering algorithms
Experimental results
Overview of the talk
2/2/2019

8. Bottom-up vs. Top-down filtering
State machines are among the most common methods for the XML matching process
Top-down approach: (i.e. in-order traversal or depth first order): advancing the state machine for each XML element (or attribute) read.
Do not consider any form of early pruning
Bottom-up approach: This approach takes into consideration the (usual) fact that an XML document has its more selective elements located at its leaves
On this slide we have definition of the problem.
2/2/2019

9. Example
Top-down approach groups the queries according to their common prefixes
Bottom up: groups them according to their common suffixes.
root Q1 a b c d Q2 a Q3 a Q4 a e f h Q5 e Q6 e g h a a a a a a a a a a a b b b b b b b b b b b c e f c c c c c c c c c c c d f h d
(a) Document
(b) Queries c d a 2 3 4 b 3 4 b Q1 c 1 2 Q1 c d d a 1 5 6 5
On this slide we have definition of the problem. a e Q2 Q2 f h 7 8 9 f e a 6 7 8 Q3 Q4 h Q3 e f h 11 12 f e 10 11 a 12 10 Q5 9 Q5 Q4 g h g e 13 14 13 14 Q6 Q6
(c) Top-down
(d) Bottom up
2/2/2019

10. BUFF FSM-based Bottom-up approach for XML filtering.
BUFF avoids translating documents and queries to Prüfer sequences (as the other algorithms do), and employs a more direct evaluation algorithm.
The document is parsed through a SAX parser, which triggers events for specific marks (tags) in the XML document
The machine keeps a runtime stack that stores the current document path being processed.
Overview of the talk
2/2/2019

11. BUFF Example d4 a1 b2 c3 d7 b5 c6 e8 f10 e9 </e> a c d b 1Q1 f c b b a
<b> 5 6 7 8
<a> a Q2
(a) Document and BUFF
(b)‏
(c)‏
</d> a c b 2 1 a c b e
1,2
</f> 5
</e> a c b 1
1,2 5
</c> a b
3,6
1,2,5
Overview of the talk
(d)‏
(e)‏
(f)‏
(g)‏
2/2/2019

12. Overview Motivation Bottom-up Filtering FSM (BUFF)
Bounding-based XML Filtering (BoxFilter)
Core Modules
Filtering algorithms
Experimental results
Overview of the talk
2/2/2019

13. Bounding-based XML Filtering
Two major processes working asynchronously
Profile Management
Profile Matching
Profile Index
Profiles P1 P2 P3
Prüfer
Sequence
Profile
Manager
Matching
Algorithm
Overview of the talk
Matching
Module
Profiles
(queries)‏
Input
Documents
Matched
Documents
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14. Prüfer Sequence A unique sequential encoding of a labeled tree
Algorithm:
Iteratively removes nodes from the tree until all nodes but the last two have been removed.
At each iteration, the algorithm finds and removes the leaf with the smallest label and adds to the Prüfer sequence the label of that leaf's parent.
Theorem: If a query tree Q is a subgraph of a document tree D then the Prüfer sequence of Q is a subsequence of the Prüfer sequence of D
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15. Sequence Envelope
Assume a set of k Prüfer sequences representing user profiles S1,..,Sk
We can derive two new sequences
Upper bound U: for each position take largest element
Lower bound L: for each position take smallest element
L and U form the smallest possible bounding envelope that encompasses all members of the set of sequences from above and below.
Overview of the talk
2/2/2019

16. Example Assume 3 sequences with 11 symbols each abcabababcd
cdcdecdcdec
dedededebab
Overview of the talk
2/2/2019

17. Sequence Envelope (Cont.)
The sequence envelope structure is that it can be used as an aggregation of the sustaining set of sequences
Overview of the talk
2/2/2019

18. BoXFilter Tree Sequence envelopes can be nested forming BoXFilter tree
Overview of the talk
2/2/2019

19. Filtering algorithms
The profiles in the system are organized in BoXFilter tree. Documents are traversed thought the tree
There are two variations of the filtering algorithm
Sequential – documents are processed one by one
Batch processing – documents are organized in a tree like the queries and both trees are joined
After the traversal of the BoXFilter tree, there is a verification step
Overview of the talk
2/2/2019

20. Overview Motivation Bottom-up Filtering FSM (BUFF)
Bounding-based XML Filtering (BoxFilter)
Core Modules
Filtering algorithms
Experimental results
Overview of the talk
2/2/2019

21. Experimental Results
We have generated datasets with 1000, and small documents (with up to 8KB)
We generated up to queries with selectivity fixed to 50%
Overview of the talk
(a)‏
(b)‏
(c)‏
2/2/2019

22. Experimental Results (cont.)
In this set of experiments, we vary the number of documents that match any of the profile queries. (selectivity 1\% means that one percent of the documents satisfy \textit{any} of the queries.)
Overview of the talk
2/2/2019

23. Thank You!
2/2/2019