Annis on MonetDB. Viktor Rosenfeld 14. January Advisors: Prof. Dr. Ulf Leser and Dr.

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1 Ais o MoetDB Viktor Rosefeld rosefel@iformatik.hu-berli.de 14. Jauary 2013 Advisors: Prof. Dr. Ulf Leser ad Dr. Stefa Maegold

2 2

3 1. What is Ais ad how is it used? 2. Curret implemetatio o PostgreSQL 3. What are Colum-Stores? How ca Ais beefit? 4. New implemetatio o MoetDB ad evaluatio 3

4 1. What is Ais ad how is it used? 4

5 What s a corpus? ay pricipled collectio of laguage 5

6 What s a aotatio? classificatio ad iterpretatio of the corpus data additioal data to erich the corpus Steilpass Märkische Allgemeie Zeitug, Potsdam Commetary Corpus (Stede, 2004) 6

7 What s a aotatio? classificatio ad iterpretatio of the corpus data additioal data to erich the corpus Steilpass Märkische Allgemeie Zeitug, Potsdam Commetary Corpus (Stede, 2004) 7

8 What s a aotatio? classificatio ad iterpretatio of the corpus data additioal data to erich the corpus Steilpass Märkische Allgemeie Zeitug, Potsdam Commetary Corpus (Stede, 2004) 8

9 What s a aotatio? classificatio ad iterpretatio of the corpus data additioal data to erich the corpus Steilpass Märkische Allgemeie Zeitug, Potsdam Commetary Corpus (Stede, 2004) 9

10 Ais 10

11 Ais Query Aotatios Corpus selectio 11

12 Ais Query Aotatios Export for statistical Corpus aalysis selectio 11

13 Ais query laguage cat="s" & fid a setece "Wuder" & ad fid the phrase Wuder #1 _i_ #2 the setece icludes the phrase Wuder 12

14 Ais query laguage cat="s" & fid a setece "Wuder" & ad fid the phrase Wuder #1 _i_ #2 the setece icludes the phrase Wuder SELECT id1, id2 FROM... RDBMS WHERE... 12

15 2. Curret implemetatio o PostgreSQL 13

16 Database schema ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace 14

17 Example 1: Text search ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace AQL: "Wuder" SQL: oden.spa = 'Wuder' 15

18 Example 2: Aotatio search ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace cat="s" ode_aotation.ame = 'cat' ode_aotation.value = 'S' 16

19 Example 3: Iclusio operator ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace #1 _i_ #2 ode1.text_ref = ode2.text_ref ode1.right <= ode2.right ode1.left >= ode2.left 17

20 May tables May jois ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace 18

21 May tables May jois Aotatio searches ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace 18

22 May tables May jois Aotatio searches ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace Edge aotatios Biary relatios o edges 18

23 May tables May jois Aotatio searches ode id amespace ame text_ref left right spa toke_idex left_toke right_toke corpus_ref toplevel_corpus ode_aotatio ode_ref amespace ame value rak pre post paret ode_ref compoet_ref root level edge_aotatio rak_ref amespace ame value compoet id type ame amespace Edge aotatios Biary relatios o edges Bad performace o PostgreSQL 18

24 Solutio 1: Oe big table id spa text_ref left right... ode ode_aotatio ode_ref amespace ame value id spa text_ref left right... a_ame a_value cat S 2 Wuder morph Acc.Pl.Neut 2 Wuder pos NN 2 Wuder lemma Wuder... 19

25 Solutio 1: Oe big table id spa text_ref left right... ode ode_aotatio ode_ref amespace ame value id spa text_ref left right... a_ame a_value cat S 2 Wuder morph Acc.Pl.Neut 2 Wuder pos NN 2 Wuder lemma Wuder... Pro: Fewer jois Cotra: Icreased redudacy, less extesible 19

26 Solutio 2: Combied idexes id spa text_ref left right... a_ame a_value cat S 2 Wuder morph Acc.Pl.Neut 2 Wuder pos NN 2 Wuder lemma Wuder... Oe idex over 4 colums Fid odes spaig a certai word, i a certai text, at a certai positio. cat="s" & "Wuder" & #1 _i_ #2 Pro: Potetially very fast Cotra: Uses lots of disk space 20

27 Disk usage i PostgreSQL TIGER Treebak 2.1 ca seteces, tokes, 3 millio aotatios, 1 millio edges 280 MB 525 MB 1.2 GB 7.7 GB Data files Normalized Materialized Materialized (may tables) (oe table) + Idexes Icrease by factor 15 (or almost 30) 21

28 3. What are Colum-Stores? How ca Ais beefit? 22

29 What's a Colum-Store? ode_ref ame value coceptual model pos VVINF 123 lemma esse table pos NN storage model 23

30 What's a Colum-Store? ode_ref ame value coceptual model pos VVINF 123 lemma esse table pos NN pos VVINF storage model lemma esse pos NN rows 23

31 What's a Colum-Store? ode_ref ame value coceptual model pos VVINF 123 lemma esse table pos NN pos VVINF ode_ref ame value storage model lemma esse pos lemma VVINF esse pos NN 456 pos NN rows colums 23

32 Why Colum-Stores? Why Databases? data data too slow! very big sequetial fast(er) too small! radom very fast job of the database (traditioally) 24

33 Why Colum-Stores? Why Databases? data fast(er) very fast 24

34 Caches betwee RAM ad CPU 48 GB 12 MB 256 kb 32 kb 33 s 5.4 s 1.7 s 1.4 s job of the database o a moder system (amog others) 25

35 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: 123 pos VVFIN 26

36 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN 1. load first row 26

37 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN load first row 2. locate ame attribute 26

38 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN load first row 2. locate ame attribute 3. test ame attribute 26

39 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse 1. load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 26

40 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 26

41 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 6. test ame attribute 26

42 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse pos NN 1. load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 6. test ame attribute 7. load third row 26

43 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse pos NN load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 6. test ame attribute 7. load third row 8. locate ame attribute 26

44 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse pos NN load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 6. test ame attribute 7. load third row 8. locate ame attribute 9. test ame attribute 26

45 Cache usage of row layout query: compare ame attribute with value 'lemma' data file: pos VVINF lemma esse pos NN L1 cache: pos VVFIN lemma esse pos NN load first row 2. locate ame attribute 3. test ame attribute 4. load secod row 5. locate ame attribute 6. test ame attribute 7. load third row 8. locate ame attribute 9. test ame attribute 26

46 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: pos lemma pos 27

47 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: 1. pos lemma pos 1. load ame colum 27

48 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: 1. pos lemma pos load ame colum 2. test first ame attribute 27

49 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: 1. pos lemma pos load ame colum 2. test first ame attribute 3. test secod ame attribute 27

50 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: 1. pos lemma pos load ame colum 2. test first ame attribute 3. test secod ame attribute 4. test third ame attribute 27

51 Cache usage of colum layout query: compare ame attribute with value 'lemma' ode_ref ame value data file: pos lemma VVINF esse 456 pos NN L1 cache: 1. pos lemma pos load ame colum 2. test first ame attribute 3. test secod ame attribute 4. test third ame attribute 27

52 Colum operatios i Ais Search terms ca be idexed "Wuder" Regular expressios ca ofte be idexed but ot always morph=/.*\.pl\.neut/ Biary operatios ca be idexed eed may idexes slow if there are may idex lookups _= i_ > id spa text_ref left right Wuder Wuder Wuder

53 4. New implemetatio o MoetDB ad evaluatio 29

54 Prototype implemetatio Supported COUNT queries Ais 2 Query Laguage Not supported Ais 3 laguage features corpus selectio ANNOTATE, MATRIX queries 30

55 Realistic test workload Corpus: TIGER Treebak 2.1 Queries: 3 moth query log of Ais istace at the SFB TIGER queries (224 uique) up to 4 search terms up to 6 biary operators Radom workload: queries origial distributio excluded PostgreSQL timeout 31

56 Workload of queries 6 MoetDB PostgreSQL 5 hours 47 miutes Hours miutes 1 hour 37 miutes Server (48 GB RAM) 29 miutes Laptop (4 GB RAM) factor MB Data files 396 MB MoetDB 7.7 GB PostgreSQL 32

57 Idividual query performace 60 MoetDB PostgreSQL DNC Secods (log)

58 Idividual query performace 60 MoetDB PostgreSQL DNC Secods (log)

59 Idividual query performace 60 MoetDB PostgreSQL DNC Secods (log)

60 Idividual query performace 60 MoetDB PostgreSQL DNC Secods (log)

61 Idividual query performace 60 MoetDB PostgreSQL DNC Secods (log)

62 Simple queries are fast 60 MoetDB PostgreSQL DNC Secods (log) Query MoetDB PostgreSQL ode 6.6 ms 2926 ms "der" /der.*/ cat="s" lemma="wasche"

63 Ifluece of result size 60 MoetDB PostgreSQL DNC Secods (log) Query Results MoetDB PostgreSQL pos="vvimp" ms 15 ms pos="vvpp" pos="vvfin" pos="adja"

64 Queries with millios of results 60 MoetDB PostgreSQL DNC Secods (log) Query Results Moet PSQL lemma="müsse" & pos= /VV.*/ & pos="$." & #1.* #2 & #2.* #3 4.5 M 2 s 35 s pos=/vm.*/ & pos= /VV.*/ & pos=/.*/ & #1.* #2 & #2.* #3 384 M 175 s > 1 h 40

65 Fast regular expressios regular expressio without a fixed prefix ca't use a idex, eed to sca the etire colum Query MoetDB PostgreSQL /.*sich.*/ 213 ms 4206 ms /[Kk]a.*/ pos="vvpp" & lemma=/(ge)?komme/ & #1 _=_ # pos=/n.*/ & /[12][09][0-9][0-9]/ & #1 _=_ # lemma=/[^äöü]+/ & /.+[äöü].+/ & pos="nn" & #1 _=_ #2 & #2 _=_ #

66 Advatages MoetDB better overall performace stable query performace fast regular expressios ormalized schema greatly reduced disk cosumptio PostgreSQL queries with highly selective search term complete implemetatio bug-free SQL processig better use of limited resources 42

67 Summary prototypical implemetatio of Ais o MoetDB test sceario from a Ais istallatio i service i-depth performace compariso of Ais o MoetDB ad PostgreSQL SELECT viele FROM dak; 43

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