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MINERVA Infinity: A Scalable Efficient Peer-to-Peer Search Engine

MINERVA Infinity: A Scalable Efficient Peer-to-Peer Search Engine. Gerhard Weikum Max-Planck-Institut für Informatik Saarbrücken, Germany weikum@mpi-inf.mpg.de. Peter Triantafillou University of Patras Rio, Greece peter@ceid.upatras.gr. Sebastian Michel

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MINERVA Infinity: A Scalable Efficient Peer-to-Peer Search Engine

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  1. MINERVA Infinity: A Scalable Efficient Peer-to-Peer Search Engine Gerhard Weikum Max-Planck-Institut für Informatik Saarbrücken, Germany weikum@mpi-inf.mpg.de Peter Triantafillou University of Patras Rio, Greece peter@ceid.upatras.gr Sebastian Michel Max-Planck-Institut für Informatik Saarbrücken, Germany smichel@mpi-inf.mpg.de Middleware 2005 Grenoble, France

  2. Vision • Today: Web Search is dominated • by centralized engines (“to google”) • - censorship? • - single point of attack/abuse • - coverage of the web? • Ultimate goal: “Distributed Google” to • break information monopolies • P2P approach best suitable • large number of peers • exploit mostly idle resources • intellectual input of user community MINERVA Infinity: A Scalable Efficient P2P Search Engine

  3. Challenges • large scale networks • 100,000 to 10,000,000 users • large collections > 10^10 documents • 1,000,000 terms • high dynamics MINERVA Infinity: A Scalable Efficient P2P Search Engine

  4. Questions • Network Organization • structured? • hierarchical? • unstructured? • Data Placement • move data around? • data remains at the owner? • Scalability? • Query Routing/Execution • Routing indexes? • Message flooding? MINERVA Infinity: A Scalable Efficient P2P Search Engine

  5. Overview • Motivation (Vision/Challenges/Questions) • Introduction to IR and P2P Systems • P2P- IR • Minerva Infinity • Network Organization • Data Placement • Query Processing • Data Replication • Experiments • Conclusion MINERVA Infinity: A Scalable Efficient P2P Search Engine

  6. 5 x 7 x 4 x # of terms (term frequency) Information Retrieval Basics Document Terms MINERVA Infinity: A Scalable Efficient P2P Search Engine

  7. d28: 0.7 d53: 0.8 d51: 0.6 d11: 0.6 d55: 0.6 d12: 0.5 d17: 0.1 d44: 0.4 d14: 0.4 d17: 0.3 ... d52: 0.3 d52: 0.1 d44: 0.2 ... d28: 0.1 ... Information Retrieval Basics (2) Top-k Query Processing: find k documents with the highest total score Query Execution: Usually using some kind of threshold algorithm*: - sequential scans over the index lists (round-robin) - (random accesses to fetch missing scores) - aggregate scores - stop when the threshold is reached B+ tree on terms e.g. Fagin’s algorithm TA or a variant without random accesses index lists with (DocId: tf*idf) sorted by Score MINERVA Infinity: A Scalable Efficient P2P Search Engine

  8. P2P Systems • Peer: • “one that is of equal standing with another” (source: Merriam-Webster Online Dictionary ) • Benefits: • no single point of failure • resource/data sharing • Problems/Challenges: • authority/trust/incentives • high dynamics • … • Applications: • File Sharing • IP Telephony • Web Search • Digital Libraries MINERVA Infinity: A Scalable Efficient P2P Search Engine

  9. Structured P2P Systems based on Distributed Hash Tables (DHTs) • “structured” P2P networks • provide one simple method: lookup:key->peer • CAN [SIGCOMM 2001] • CHORD [SIGCOMM 2001] • Pastry [Middleware 2001] • P-Grid [CoopIS 2001] robustness to load skew, failures, dynamics MINERVA Infinity: A Scalable Efficient P2P Search Engine

  10. p1 p56 p8 k54 k10 p51 p48 p14 p21 p42 k24 p38 p32 k38 k30 Chord • Peers and keys are mapped to the same cyclic ID space using a hash function • Key k (e.g., hash(file name)) is assigned to the node with key p (e.g., hash(IP address)) such that k  p and there is no node p‘ with k  p‘ and p‘<p MINERVA Infinity: A Scalable Efficient P2P Search Engine

  11. Lookup(54) k54 Chord (2) • Using finger tables to speed up lookup process • Store pointers to few distant peers • Lookup in O(log n) steps p1 p56 Chord Ring p8 p51 p14 p42 p21 p38 p32 MINERVA Infinity: A Scalable Efficient P2P Search Engine

  12. Overview • Motivation (Vision/Challenges/Questions) • Introduction to IR and P2P Systems • P2P- IR • Minerva Infinity • Network Organization • Data Placement • Query Processing • Data Replication • Experiments • Conclusion MINERVA Infinity: A Scalable Efficient P2P Search Engine

  13. P2P - IR • Share documents (e.g. Web pages) in an efficient and scalable way • Ranked retrieval • simple DHT is insufficient MINERVA Infinity: A Scalable Efficient P2P Search Engine

  14. p1 p56 p8 p51 p48 p14 p21 p42 p38 p32 capacity overload of peers with highly frequent / popular terms (data load AND query load) Possible Approaches • Each peer is responsible for storing the COMPLETE index list for a subset of terms. Query Routing: DHT lookups Query Execution: Distributed Top-k [TPUT ’04, KLEE ‘05] MINERVA Infinity: A Scalable Efficient P2P Search Engine

  15. a: P1 P6 P4 b: P5 P3 P1 P6 ... P2 P1 P3 Distributed Directory Term List of Peers à P6 P4 P5 capacity overload of peers with - highly frequent terms - high-quality collections Possible Approaches (2) • Each peer has its own local index (e.g., created by web crawls) Query Routing: 1. DHT lookups 2. Retrieve Metadata 3. Find most promising peers Query Execution: - Send the complete Query and merge the incoming results MINERVA Infinity: A Scalable Efficient P2P Search Engine

  16. Overview • Motivation (Vision/Challenges/Questions) • Introduction to IR and P2P Systems • P2P- IR • Minerva Infinity • Network Organization • Data Placement • Query Processing • Data Replication • Experiments • Conclusion MINERVA Infinity: A Scalable Efficient P2P Search Engine

  17. low high low high high low Minerva Infinity • Idea: • assign (term, docId, score) triplets to the peers • order preserving • load balancing • hash(score)+ hash(term) as offset • guarantee 100% recall MINERVA Infinity: A Scalable Efficient P2P Search Engine

  18. Hash Function • Requirements: • Load balancing (to avoid overloading peers) • Order preserving (to make the QP work) • One without the other is trivial ... • Load balancing: apply a pseudo random hash function • Order preserving: • Both together is challenging … S-Smin ----------------- * N Smax - Smin MINERVA Infinity: A Scalable Efficient P2P Search Engine

  19. Hash Function (2) • Assume an exponential score distribution • Place the first half of the data to the first peer • The next quarter to the next peer • and so on … 1 … 0 MINERVA Infinity: A Scalable Efficient P2P Search Engine

  20. Term Index Networks (TINs) • Reduce # of hops during QP by reducing the number of peers that maintain the index list for a particular term  Only a small subset of peers is used to store an index list. 62 2 45 B 2 Global Network 45 24 7 41 41 7 62 A 12 C 12 37 15 16 24 24 16 20 MINERVA Infinity: A Scalable Efficient P2P Search Engine

  21. How to Create/Find a TIN • Use u Beacon-Peers to bootstrap the TIN for term T p = 1/u For i=0 to i<n‘ do id = hash(t, i*p) if (i>0) use hash(t,(i-1)*p) as a gateway to the TIN else node with id creates the TIN End for Global Network T Beacon nodes act as gateways to the TIN MINERVA Infinity: A Scalable Efficient P2P Search Engine

  22. Publish Data / Join a TIN • Peer with id = hash(t, score) not in the TIN for term t • Randomly select a beacon node (Beacon nodes act as gateways to the TIN) • Call the join method • Store the item (docId, t, score) MINERVA Infinity: A Scalable Efficient P2P Search Engine

  23. Query Processing Data Peers Coordinator 1 1 2-keyword Query Alternative: Collect data and send in one batch. MINERVA Infinity: A Scalable Efficient P2P Search Engine

  24. QP with Moving Coordinator Data Peers Coordinator 1 1 1 3-keyword Query MINERVA Infinity: A Scalable Efficient P2P Search Engine

  25. 41 41 7 7 62 62 A A 2 2 8 12 12 45 45 64 C C B B B B 16 16 24 24 20 28 55 11 57 1 50 7 B B B B C C 46 34 22 Data Replication • Vertical: Replicate data inside a TIN via a ‘reverse’ communication. • Horizontal: Replicate complete TINs 1 1 2 3 2 1 2 3 3 1 2 3 64 11 C C 24 24 31 1 49 5 A A A A 16 19 MINERVA Infinity: A Scalable Efficient P2P Search Engine

  26. Experiments Test bed: 10,000 peers Benchmarks: • GOV: TREC .GOV collection + 50 TREC-2003 Web queries, e.g. juvenile delinquency • XGOV: TREC .GOV collection + 50 manually expanded queries, e.g. juvenile delinquency youth minor crime law jurisdiction offense prevention • SCALABILITY: One query executed multiple times ………. MINERVA Infinity: A Scalable Efficient P2P Search Engine

  27. Experiments: Metrics Metrics • Network traffic (in KB) • Query response time (in s) - network cost (150ms RTT, 800Kb/s data transfer rate) - local I/O cost (8ms rotation latency + 8MB/s transfer delay) - processing cost • Number of Hops MINERVA Infinity: A Scalable Efficient P2P Search Engine

  28. Scalability Experiment • Measure time for a different query loads. • identical queries • inserted into a queue MINERVA Infinity: A Scalable Efficient P2P Search Engine

  29. Experiments: Results MINERVA Infinity: A Scalable Efficient P2P Search Engine

  30. Conclusion • Novel architecture for P2P web search. • High level of distribution both in data and processing. • Novel algorithms to create the networks, place data, and execute queries. • Support of two different data replication strategies. MINERVA Infinity: A Scalable Efficient P2P Search Engine

  31. Future Work • Support of different score distributions • Adapt TIN sizes to the actual load • Different top-k query processing algorithms MINERVA Infinity: A Scalable Efficient P2P Search Engine

  32. Thank you for your attention MINERVA Infinity: A Scalable Efficient P2P Search Engine

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