Prefetching for Visual Data Exploration

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Prefetching for Visual Data Exploration

• Punit R. Doshi, Elke A. Rundensteiner, Matthew O.
  Ward
• Computer Science Department
• Worcester Polytechnic Institute
• Support NSF grants IIS-9732897, EIA-9729878,
  and IIS-0119276.

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Overview

• Why visually explore data?
• Fact Increasing data set sizes
• Need Efficient techniques for exploring the data
• Possible solution Interactive Data Visualization
  -- humans can detect certain patterns better and
  faster than data mining tools
• Why cache and prefetch?
• Interactive data visualization tools do not scale
  well
• Interactive ? real-time response needed
• Caching and prefetching improve response time.
• Goal Propose and evaluate prefetching for
  visualization tools

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Example Visual Exploration Tool XmdvTool
Data Hierarchy
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Example Visual Exploration Tool XmdvTool
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Characteristics of a Visualization Environment
Move up/down

• Characteristics that can be exploited for caching
  and prefetching
• Locality of exploration
• Contiguity of user movements
• Idle time due to user viewing display

Move left/right
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Overview of Semantic Caching

• Purpose
• reduce response time and network traffic
• Issues
• visual query cannot directly translate into
  object IDs
• high-level cache specification to avoid complete
  scans
• Semantic Caching queries are cached rather than
  objects
• minimize cost of cache lookup
• dynamically adapt cached queries to patterns of
  queries

DB
GUI
cache
Server machine
Client machine
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In XmdvTool, caching reduced response time by 85
Prefetching can further improve response time.
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Prefetching

• Locality of exploration
• Contiguity of user movements
• Idle time due to user viewing display

Users next request can be predicted with high
accuracy
Time to prefetch
Fetching
New user query
Idle time
Cache
DB
Prefetching
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Prefetching Strategies
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XmdvTool Implementation

• Used
• C/C
• TCL/TK
• OpenGL
• Oracle 8i
• ProC

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Evaluation of Prefetching Strategies

• Setup
• Testbed XmdvTool freeware system for
  n-dimensional exploration
• User Traces
• Synthetic user traces with varying of hot
  regions, directionality, average delay
  between user requests
• Real user traces collected by a user study
• Study effect of different navigation patterns
• hot regions
• erratic vs. directional
• delay between user requests

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Focus strategy best as hot regions increases
Prefetching improves response time
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Random Strategy best for erratic
traces.Direction Strategy best for directional
traces.
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Prefetcher performance improves and plateaus as
delay between user operations increases.
Prefetcher performance improved up to 28.
Recall Caching improved response time by 85
over no caching.
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What Can We Conclude?

• Focus hot region calculation overhead
• Mean and EWA offers more than needed
• Direction simple, no prior knowledge required
• NOTE
• Our experiments on real user traces show that
  real users are highly directional
• ?If only one strategy can be chosen,
• select Directional Prefetching.

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Related Work

• Integrated visualization-database systems --
  Tioga, IDEA, DEVise
• have not used caching and prefetching
• Prefetching research -- mostly on (1) web
  prefetching, (2) prefetching for memory caches by
  OS, (3) I/O prefetching.
• no prefetching research for visualization
  apps

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Contributions

• Identified key characteristics of visualization
  tools exploitable for optimizing data access
  performance
• Developed, implemented and tested prefetching
  strategies in XmdvTool
• Shown that caching coupled with prefetching at
  client-side improves data access performance
• Caching reduces response time by 85 over
  no-caching.
• Prefetching further improves response time by 28
  over no-prefetching.

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Future Work

• No single prefetcher works best for all types of
  user navigation patterns
  
• ? Adaptive Prefetching
• (preliminary results show that this further
  improves response time and reduces prediction
  errors, at a minimal overhead cost).

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Thank You

• XmdvTool Homepage
• http//davis.wpi.edu/xmdv
• xmdv_at_cs.wpi.edu
• Code is free for research and education.
• Contact author rundenst_at_cs.wpi.edu