Tom Santero, Technical Evangelist, Basho Technologies delivered this presentation at a recent Big Data Warehousing Meetup that was held with Caserta Concepts. Full-text search capabilities have existed in Riak since 2010. Known simply as Riak Search, the implementation is a homegrown adaptation inspired by Lucene. While Riak Search has been used in production for many years now, Basho has been developing a replacement over the course of the past 12 months in a project codenamed 'Yokozuna'. In this talk, Tom discussed the motivation behind Yokozuna, how it works and why you want to run it in production. For more information, visit http://basho.com/ or http://www.casertaconcepts.com/.

1. Riak
Search
the next generation
Tuesday, September 17, 13

2. tsantero
@basho.com
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3. Tuesday, September 17, 13

4. Tuesday, September 17, 13

5. 2.0coming soon..
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6. the history of
Riak Search
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7. home grown
full-text search
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8. lucene
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9. SCALETuesday, September 17, 13

10. NODE # = HASH(KEY) % NUM_NODES
NH(Ka) = 0
NH(Kb) = 1
NH(Kc) = 2
NH(Kd) = 0
...
Naive Hashing
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11. NODE 0 NODE 1 NODE 2
Ka Kb KcKd Ke KfKg Kh Ki
Kj KkKm KlKp Kn KoKq Kr
Naive Hashing
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12. NODE 0 NODE 1 NODE 2
Ka Kb Kc KdKgKi
NODE 3
Ke Kf KhKj Kk Kl
Km Kn Ko KpKq Kr
Naive Hashing
Tuesday, September 17, 13

13. K * (NN - 1) / NN => K
• K = # OF KEYS
• NN = # OF NODES
• AS NN GROWS FACTOR ESSENTIALLY BECOMES 1, THUS
ALL KEYS MOVE
Naive Hashing
Tuesday, September 17, 13

14. PARTITION # = HASH(KEY) % PARTITIONS
• # PARTITIONS REMAINS CONSTANT
• KEY ALWAYS MAPS TO SAME PARTITION
• NODES OWN PARTITIONS
• PARTITIONS CONTAIN KEYS
• EXTRA LEVEL OF INDIRECTION
Consistent Hashing
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15. P9P6P3P8P5P2P7P4P1
NODE 0 NODE 1 NODE 2
Ka Kb KcKd Ke KfKg Kh Ki
Kj KkKm KlKp Kn KoKq Kr
Consistent Hashing
Tuesday, September 17, 13

16. P9P6P3P8 P5P2P7P4 P1
NODE 0 NODE 1 NODE 2
KaKb KcKd KeKfKg Kh Ki
KjKkKm KlKp KnKoKq Kr
NODE 3
Consistent Hashing
Tuesday, September 17, 13

17. NN * K/Q => K/Q
• K = # OF KEYS
• NN = # OF NODES
• Q = # OF PARTITIONS
• AS K GROWS NN BECOMES CONSTANT,THUS K/Q KEYS
MOVE
Consistent Hashing
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18. uniform distribution
Consistent
Hashing
{logical vs physical
partitioning scheme
even division of keys
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19. the future of
Riak Search
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20. Tuesday, September 17, 13

21. persistence
distributing Solr
querying
indexing
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22. Each Riak node runs an instance of Solr
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23. Solr index = riak bucket
document = RObj value
plaintext, JSON, XML
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24. Distributed Searching in Solr
query
faceting
highlighting
stats
spell check
term vectors
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25. SolrCloud
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26. SolrCloud
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27. Harvest vs Yield
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28. A better measure of
Availability
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29. Queries Issues
Queries OfferedYield =
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30. Harvest =
Data Available
Total Dataset
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31. Harvest
Yield
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32. Manage Harvest by storing Index Replicas
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33. Term vs Document
Partitioning Schemes
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34. Node 0
Node 1
Node 2
Term Based Partitioning
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35. Node 0
Node 1
Node 2
Document Based Partitioning
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36. Replicas
Node 0
Node 1
Node 2
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37. Quorums
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38. Concurrency
=>
Siblings
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39. Read Repair
(Anti-Entropy)
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40. replica replica replica
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41. replica replica replica
X
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42. replica replica replica
replica replica replica
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43. Active Anti-Entropy
(self healing clusters)
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44. real-time updates
persistent
non-blocking
disk-based
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45. Tuesday, September 17, 13

46. = hashes marked “dirty”
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47. Tuesday, September 17, 13

48. Tuesday, September 17, 13

49. Tuesday, September 17, 13

50. Tuesday, September 17, 13

51. = keys to read-repair
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52. Questions?
make it so!
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