Raiding the MongoDB Toolbox

Presented July 19, 2015 at NYC Camp: http://2015.nyccamp.org/MongoDB-day

Presented April 17, 2015 at Lone Star PHP: https://joind.in/talk/view/13557

Presented October 29, 2014 at ZendCon: https://joind.in/talk/view/12092

Reveal.js presentation published at: http://jmikola.github.io/slides/mongodb_toolbox/

Transcript

1. RAIDING THE MONGODB TOOLBOX Jeremy Mikola jmikola
2. Agenda Full-text Indexing Geospatial Queries Data Aggregation Creating a Job Queue Tailable Cursors
3. Full-text Indexing
4. You have an awesome PHP blog { " _ i d " : O b j e c t I d ( " 5 4 4 f d 6 3 8 6 0 d a b 3 b 1 2 5 2 1 3 7 9 b " ) , " t i t l e " : " T e n S e c r e t s A b o u t P S R - 7 Y o u W o n ' t B e l i e v e ! " , " c o n t e n t " : " P h i l S t u r g e o n c a u s e d q u i t e a s t i r o n t h e P H P - F I G m a i l i n g l i s t t h i s m o r n i n g w h e n h e u n a n i m o u s l y p a s s e d M a t t h e w W e i e r O ' P h i n n e y ' s c o n t r o v e r s i a l P S R - 7 s p e c i f i c a t i o n . P H P - F I G m e m b e r s w e r e o u t r a g e d a s t h e s e l f - p r o c l a i m e d G o r d o n R a m s a y o f P H P … " , " p u b l i s h e d " : t r u e , " c r e a t e d _ a t " : I S O D a t e ( " 2 0 1 4 - 1 0 - 2 8 T 1 7 : 4 6 : 3 6 . 0 6 5 Z " ) }
5. We’d like to search the content Store arrays of keyword strings Query with regular expressions Sync data to Solr, Elasticsearch, etc. Create a full-text index
6. Creating a full-text index $ c o l l e c t i o n - > c r e a t e I n d e x ( [ ' c o n t e n t ' = > ' t e x t ' ] ) ; Compound indexing with other fields $ c o l l e c t i o n - > c r e a t e I n d e x ( [ ' c o n t e n t ' = > ' t e x t ' , ' c r e a t e d _ a t ' = > 1 ] ) ; Indexing multiple string fields $ c o l l e c t i o n - > c r e a t e I n d e x ( [ ' c o n t e n t ' = > ' t e x t ' , ' t i t l e ' = > ' t e x t ' ] ) ;
7. Step 1: Tokenization [ P h i l , S t u r g e o n , c a u s e d , q u i t e , a , s t i r , o n , t h e , P H P - F I G , m a i l i n g , l i s t , t h i s , m o r n i n g , w h e n , h e , u n a n i m o u s l y , p a s s e d , … ]
8. Step 2: Trim stop-words [ P h i l , S t u r g e o n , c a u s e d , q u i t e , s t i r , P H P - F I G , m a i l i n g , l i s t , m o r n i n g , u n a n i m o u s l y , p a s s e d , … ]
9. Step 3: Stemming [ P h i l , S t u r g e o n , c a u s e , q u i t e , s t i r , P H P - F I G , m a i l , l i s t , m o r n i n g , u n a n i m o u s , p a s s , … ]
10. Step 4: Profit?
11. Querying a text index $ c u r s o r = $ c o l l e c t i o n - > f i n d ( [ ' $ t e x t ' = > [ ' $ s e a r c h ' = > ' P h i l S t u r g e o n ' ] ] ) ; f o r e a c h ( $ c u r s o r a s $ d o c u m e n t ) { e c h o $ d o c u m e n t [ ' c o n t e n t ' ] . " \ n \ n " ; } ↓ P h i l S t u r g e o n c a u s e d q u i t e a s t i r o n t h e P H P - F I G … P h i l J e r k s o n , b e t t e r k n o w n a s @ p h p j e r k o n T w i t t e r …
12. and Phrases negations $ c u r s o r = $ c o l l e c t i o n - > f i n d ( [ ' $ t e x t ' = > [ ' $ s e a r c h ' = > ' P H P - " P h i l S t u r g e o n " ' ] ] ) ; f o r e a c h ( $ c u r s o r a s $ d o c u m e n t ) { e c h o $ d o c u m e n t [ ' c o n t e n t ' ] . " \ n \ n " ; } ↓ B e p r e p a r e d f o r t h e l a t e s t a n d g r e a t e s t v e r s i o n o f P H P w i t h …
13. Sorting by the match score $ c u r s o r = $ c o l l e c t i o n - > f i n d ( [ ' $ t e x t ' = > [ ' $ s e a r c h ' = > ' P h i l S t u r g e o n ' ] ] , [ ' s c o r e ' = > [ ' $ m e t a ' = > ' t e x t S c o r e ' ] ] ) ; $ c u r s o r - > s o r t ( [ ' s c o r e ' = > [ ' $ m e t a ' = > ' t e x t S c o r e ' ] ] ) ; f o r e a c h ( $ c u r s o r a s $ d o c u m e n t ) { p r i n t f ( " % . 6 f : % s \ n \ n " , $ d o c u m e n t [ ' s c o r e ' ] , $ d o c u m e n t [ ' c o n t e n t ' ] ) ; } ↓ 1 . 0 3 5 7 1 4 : P h i l S t u r g e o n c a u s e d q u i t e a s t i r o n t h e P H P - F I G … 0 . 5 5 5 5 5 6 : P h i l J e r k s o n , b e t t e r k n o w n a s @ p h p j e r k o n T w i t t e r …
14. Supporting multiple languages $ c o l l e c t i o n - > c r e a t e I n d e x ( [ ' c o n t e n t ' = > ' t e x t ' ] , [ ' d e f a u l t _ l a n g u a g e ' = > ' e n ' ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o n t e n t ' = > ' W e a r e p l a n n i n g a h o t d o g c o n f e r e n c e ' , ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o n t e n t ' = > ' D i e K o n f e r e n z w i r d W u r s t C o n b e n a n n t w e r d e n ' , ' l a n g u a g e ' = > ' d e ' , ] ) ; $ c o l l e c t i o n - > f i n d ( [ ' $ t e x t ' = > [ ' $ s e a r c h ' = > ' s a u c i s s e ' , ' $ l a n g u a g e ' = > ' f r ' ] ] , ) ;
15. Geospatial Queries
16. Because some of us ❤ maps
17. Geospatial indexes , , and 2 d s p h e r e for earth-like geometry Supports objects 2 d for flat geometry Legacy point format: [ x , y ] Inclusion proximity intersection GeoJSON
18. in a nutshell GeoJSON { " t y p e " : " P o i n t " , " c o o r d i n a t e s " : [ 1 0 0 . 0 , 0 . 0 ] } { " t y p e " : " L i n e S t r i n g " , " c o o r d i n a t e s " : [ [ 1 0 0 . 0 , 0 . 0 ] , [ 1 0 1 . 0 , 1 . 0 ] ] } { " t y p e " : " P o l y g o n " , " c o o r d i n a t e s " : [ [ [ 1 0 0 . 0 , 0 . 0 ] , [ 1 0 1 . 0 , 0 . 0 ] , [ 1 0 1 . 0 , 1 . 0 ] , [ 1 0 0 . 0 , 1 . 0 ] , [ 1 0 0 . 0 , 0 . 0 ] ] , [ [ 1 0 0 . 2 , 0 . 2 ] , [ 1 0 0 . 8 , 0 . 2 ] , [ 1 0 0 . 8 , 0 . 8 ] , [ 1 0 0 . 2 , 0 . 8 ] , [ 1 0 0 . 2 , 0 . 2 ] ] ] } { " t y p e " : " M u l t i P o l y g o n " , " c o o r d i n a t e s " : [ [ [ [ 1 0 2 , 2 ] , [ 1 0 3 , 2 ] , [ 1 0 3 , 3 ] , [ 1 0 2 , 3 ] , [ 1 0 2 , 2 ] ] ] , [ [ [ 1 0 0 , 0 ] , [ 1 0 1 , 0 ] , [ 1 0 1 , 1 ] , [ 1 0 0 , 1 ] , [ 1 0 0 , 0 . 0 ] ] ] ] } { " t y p e " : " G e o m e t r y C o l l e c t i o n " , " g e o m e t r i e s " : [ { … } , { … } ] }
19. ARRAYS ARRAYS EVERYWHERE
21. Indexing some places of interest $ c o l l e c t i o n - > i n s e r t ( [ ' n a m e ' = > ' H y a t t R e g e n c y S a n t a C l a r a ' , ' t y p e ' = > ' h o t e l ' , ' l o c ' = > [ ' t y p e ' = > ' P o i n t ' , ' c o o r d i n a t e s ' = > [ - 1 2 1 . 9 7 6 5 5 7 , 3 7 . 4 0 4 9 7 7 ] , ] , ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' n a m e ' = > ' I n - N - O u t B u r g e r ' , ' t y p e ' = > ' r e s t a u r a n t ' , ' l o c ' = > [ ' t y p e ' = > ' P o i n t ' , ' c o o r d i n a t e s ' = > [ - 1 2 1 . 9 8 2 1 0 2 , 3 7 . 3 8 7 9 9 3 ] , ] ] ) ; $ c o l l e c t i o n - > e n s u r e I n d e x ( [ ' l o c ' = > ' 2 d s p h e r e ' ] ) ;
22. Inclusion queries / / D e f i n e a G e o J S O N p o l g y o n $ p o l y g o n = [ ' t y p e ' = > ' P o l y g o n ' , ' c o o r d i n a t e s ' = > [ [ [ - 1 2 1 . 9 7 6 5 5 7 , 3 7 . 4 0 4 9 7 7 ] , / / H y a t t R e g e n c y [ - 1 2 1 . 9 8 2 1 0 2 , 3 7 . 3 8 7 9 9 3 ] , / / I n - N - O u t B u r g e r [ - 1 2 1 . 9 9 2 3 1 1 , 3 7 . 4 0 4 3 8 5 ] , / / R a b b i t ' s F o o t M e a d e r y [ - 1 2 1 . 9 7 6 5 5 7 , 3 7 . 4 0 4 9 7 7 ] , ] , ] , ] ; / / F i n d d o c u m e n t s w i t h i n t h e p o l y g o n ' s b o u n d s $ c o l l e c t i o n - > f i n d ( [ ' l o c ' = > [ ' $ g e o W i t h i n ' = > $ p o l y g o n ] ] ) ; / / F i n d d o c u m e n t s w i t h i n c i r c u l a r b o u n d s $ c o l l e c t i o n - > f i n d ( [ ' l o c ' = > [ ' $ g e o W i t h i n ' = > [ ' $ c e n t e r S p h e r e ' = > [ [ - 1 2 1 . 9 7 6 5 5 7 , 3 7 . 4 0 4 9 7 7 ] , / / C e n t e r c o o r d i n a t e 5 / 3 9 5 9 , / / C o n v e r t m i l e s t o r a d i a n s ] ] ] ] ) ;
23. Sorted proximity queries $ p o i n t = [ ' t y p e ' = > ' P o i n t ' , ' c o o r d i n a t e s ' = > [ - 1 2 1 . 9 7 6 5 5 7 , 3 7 . 4 0 4 9 7 7 ] ] ; / / F i n d l o c a t i o n s n e a r e s t a p o i n t $ c o l l e c t i o n - > f i n d ( [ ' l o c ' = > [ ' $ n e a r ' = > $ p o i n t ] ] ) ; / / F i n d t h e n e a r e s t 5 0 r e s t a u r a n t s w i t h i n 5 k m $ c o l l e c t i o n - > f i n d ( [ ' l o c ' = > [ ' $ n e a r ' = > $ p o i n t , ' $ m a x D i s t a n c e ' = > 5 0 0 0 ] , ' t y p e ' = > ' r e s t u a r a n t ' , ] ) - > l i m i t ( 5 0 ) ;
25. Data Aggregation
26. We have some commands for this aggregate count distinct group mapReduce
27. Count $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 5 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 2 5 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' B 2 1 2 ' , ' n u m ' = > 2 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 3 0 0 ] ) ; $ c o l l e c t i o n - > c o u n t ( ) ; / / R e t u r n s 4 $ c o l l e c t i o n - > c o u n t ( [ ' n u m ' = > [ ' $ g t e ' = > 2 5 0 ] ] ) ; / / R e t u r n s 3
28. Distinct $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 5 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 2 5 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' B 2 1 2 ' , ' n u m ' = > 2 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 3 0 0 ] ) ; $ c o l l e c t i o n - > d i s t i n c t ( ' c o d e ' ) ; / / R e t u r n s [ " A 1 2 3 " , " B 2 1 2 " ]
29. Group $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 5 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 2 5 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' B 2 1 2 ' , ' n u m ' = > 2 0 0 ] ) ; $ c o l l e c t i o n - > i n s e r t ( [ ' c o d e ' = > ' A 1 2 3 ' , ' n u m ' = > 3 0 0 ] ) ; $ r e s u l t = $ c o l l e c t i o n - > g r o u p ( [ ' c o d e ' = > 1 ] , / / f i e l d ( s ) o n w h i c h t o g r o u p [ ' s u m ' = > 0 ] , / / i n i t i a l a g g r e g a t e v a l u e n e w M o n g o C o d e ( ' f u n c t i o n ( c u r , a g g ) { a g g . s u m + = c u r . n u m } ' ) ) ; f o r e a c h ( $ r e s u l t [ ' r e t v a l ' ] a s $ g r o u p e d ) { p r i n t f ( " % s : % d \ n " , $ g r o u p e d [ ' c o d e ' ] , $ g r o u p e d [ ' s u m ' ] ) ; } ↓ A 1 2 3 : 1 0 5 0 B 2 1 2 : 2 0 0
30. MapReduce Extremely versatile, powerful Intended for complex data analysis Overkill for simple aggregation tasks e.g. averages, summation, grouping Incremental data processing
31. Aggregating query profiler output { " o p " : " q u e r y " , " n s " : " d b . c o l l e c t i o n " , " q u e r y " : { " c o d e " : " A 1 2 3 " , " n u m " : { " $ g t " : 2 2 5 } } , " n t o r e t u r n " : 0 , " n t o s k i p " : 0 , " n s c a n n e d " : 1 1 4 2 6 , " l o c k S t a t s " : { … } , " n r e t u r n e d " : 0 , " r e s p o n s e L e n g t h " : 2 0 , " m i l l i s " : 1 2 , " t s " : I S O D a t e ( " 2 0 1 3 - 0 5 - 2 3 T 2 1 : 2 4 : 3 9 . 3 2 7 Z " ) , }
32. Constructing a query skeleton { " c o d e " : " A 1 2 3 " , " n u m " : { " $ g t " : 2 2 5 } } ↓ { " c o d e " : < s t r i n g > , " n u m " : { " $ g t " : < n u m b e r > } } Aggregate stats for similar queries (e.g. execution time, index performance)
34. Aggregation framework Process a stream of documents Original input is a collection Outputs one or more result documents Series of operators Filter or transform data Input/output chain p s a x | g r e p m o n g o d | h e a d - n 1
35. Executing an aggregation pipeline $ c o l l e c t i o n - > a g g r e g a t e C u r s o r ( [ [ ' $ m a t c h ' = > [ ' s t a t u s ' = > ' A ' ] ] , [ ' $ g r o u p ' = > [ ' _ i d ' = > ' $ c u s t _ i d ' , ' t o t a l ' = > [ ' $ s u m ' = > ' $ a m o u n t ' ] ] ] ] ) ;
36. Pipeline operators $ m a t c h $ g e o N e a r $ p r o j e c t $ g r o u p $ u n w i n d $ s o r t $ l i m i t $ s k i p $ r e d a c t $ o u t
37. Aggregating fractals
38. Solving symbolic equations and calculus
39. Creating a Job Queue
40. Things not to do in your controllers Send email messages Upload files to S3 Blocking API calls Heavy data processing Mining cryptocurrency
41. Creating a job $ c o l l e c t i o n - > i n s e r t ( [ ' d a t a ' = > [ … ] , ' p r o c e s s e d ' = > f a l s e , ' c r e a t e d A t ' = > n e w M o n g o D a t e , ] ) ; $ c o l l e c t i o n - > c r e a t e I n d e x ( [ ' p r o c e s s e d ' = > 1 , ' c r e a t e d A t ' = > 1 ] ) ;
42. Selecting a job $ j o b = $ c o l l e c t i o n - > f i n d A n d M o d i f y ( [ ' p r o c e s s e d ' = > f a l s e ] , [ ' $ s e t ' = > [ ' p r o c e s s e d ' = > t r u e , ' r e c e i v e d A t ' = > n e w M o n g o D a t e ] ] , n u l l , / / f i e l d p r o j e c t i o n ( i f a n y ) [ ' s o r t ' = > [ ' c r e a t e d A t ' = > 1 ] , ' n e w ' = > t r u e , ] ) ; ↓ { " _ i d " : O b j e c t I d ( " 5 4 5 1 5 e 1 6 b a 5 a 4 d a 1 b 1 5 a 1 7 6 6 " ) , " d a t a " : { … } , " p r o c e s s e d " : t r u e , " c r e a t e d A t " : I S O D a t e ( " 2 0 1 4 - 1 0 - 2 9 T 2 1 : 3 7 : 2 6 . 4 0 5 Z " ) , " r e c e i v e d A t " : I S O D a t e ( " 2 0 1 4 - 1 0 - 2 9 T 2 1 : 3 7 : 3 3 . 1 1 8 Z " ) }
43. Schedule jobs in the future $ c o l l e c t i o n - > i n s e r t ( [ ' d a t a ' = > [ … ] , ' p r o c e s s e d ' = > f a l s e , ' c r e a t e d A t ' = > n e w M o n g o D a t e , ' s c h e d u l e d A t ' = > n e w M o n g o D a t e ( s t r t o t i m e ( ' 1 h o u r ' ) ) , ] ) ; ↓ $ n o w = n e w M o n g o D a t e ; $ j o b = $ c o l l e c t i o n - > f i n d A n d M o d i f y ( [ ' p r o c e s s e d ' = > f a l s e , ' s c h e d u l e d A t ' = > [ ' $ l t ' = > $ n o w ] ] , [ ' $ s e t ' = > [ ' p r o c e s s e d ' = > t r u e , ' r e c e i v e d A t ' = > $ n o w ] ] , n u l l , [ ' s o r t ' = > [ ' c r e a t e d A t ' = > 1 ] , ' n e w ' = > t r u e , ] ) ;
44. Prioritize job selection $ c o l l e c t i o n - > i n s e r t ( [ ' d a t a ' = > [ … ] , ' p r o c e s s e d ' = > f a l s e , ' c r e a t e d A t ' = > n e w M o n g o D a t e , ' p r i o r i t y ' = > 0 , ] ) ; / / I n d e x : { " p r o c e s s e d " : 1 , " p r i o r i t y " : - 1 , " c r e a t e d A t " : 1 } ↓ $ n o w = n e w M o n g o D a t e ; $ j o b = $ c o l l e c t i o n - > f i n d A n d M o d i f y ( [ ' p r o c e s s e d ' = > f a l s e ] , [ ' $ s e t ' = > [ ' p r o c e s s e d ' = > t r u e , ' r e c e i v e d A t ' = > $ n o w ] ] , n u l l , [ ' s o r t ' = > [ ' p r i o r i t y ' = > - 1 , ' c r e a t e d A t ' = > 1 ] , ' n e w ' = > t r u e , ] ) ;
45. Gracefully handle failed jobs $ c o l l e c t i o n - > i n s e r t ( [ ' d a t a ' = > [ … ] , ' p r o c e s s e d ' = > f a l s e , ' c r e a t e d A t ' = > n e w M o n g o D a t e , ' a t t e m p t s ' = > 0 , ] ) ; ↓ $ n o w = n e w M o n g o D a t e ; $ j o b = $ c o l l e c t i o n - > f i n d A n d M o d i f y ( [ ' p r o c e s s e d ' = > f a l s e ] , [ ' $ s e t ' = > [ ' p r o c e s s e d ' = > t r u e , ' r e c e i v e d A t ' = > $ n o w ] , ' $ i n c ' = > [ ' a t t e m p t s ' = > 1 ] , ] , n u l l , [ ' s o r t ' = > [ ' c r e a t e d A t ' = > 1 ] , ' n e w ' = > t r u e , ] ) ;
46. Tailable Cursors
47. Capped collections $ d a t a b a s e - > c r e a t e C o l l e c t i o n ( ' t a i l m e ' , [ ' c a p p e d ' = > t r u e , ' s i z e ' = > 1 6 7 7 7 2 1 6 , / / 1 6 M i B ' m a x ' = > 1 0 0 0 , ] ) ;
48. Producer f o r ( $ i = 0 ; + + $ i ; ) { $ c o l l e c t i o n - > i n s e r t ( [ ' x ' = > $ i ] ) ; p r i n t f ( " I n s e r t e d : % d \ n " , $ i ) ; s l e e p ( 1 ) ; } ↓ I n s e r t e d : 1 I n s e r t e d : 2 I n s e r t e d : 3 I n s e r t e d : 4 I n s e r t e d : 5 …
49. Consumer $ c u r s o r = $ c o l l e c t i o n - > f i n d ( ) ; $ c u r s o r - > t a i l a b l e ( t r u e ) ; $ c u r s o r - > a w a i t D a t a ( t r u e ) ; w h i l e ( t r u e ) { i f ( $ c u r s o r - > d e a d ( ) ) { b r e a k ; } i f ( ! $ c u r s o r - > h a s N e x t ( ) ) { c o n t i n u e ; } p r i n t f ( " C o n s u m e d : % d \ n " , $ c u r s o r - > g e t N e x t ( ) [ ' x ' ] ) ; } ↓ C o n s u m e d : 1 C o n s u m e d : 2 …
50. Replica set oplog $ c o l l e c t i o n - > i n s e r t ( [ ' x ' = > 1 , ] ) ; ↓ { " t s " : T i m e s t a m p ( 1 4 1 4 6 2 4 9 2 9 , 1 ) , " h " : N u m b e r L o n g ( " 2 6 3 1 3 8 2 8 9 4 3 8 7 4 3 4 4 8 4 " ) , " v " : 2 , " o p " : " i " , " n s " : " t e s t . f o o " , " o " : { " _ i d " : O b j e c t I d ( " 5 4 5 1 7 6 a 1 4 a b 5 c 0 c 9 9 9 d a 7 0 f 0 " ) , " x " : 1 } }
51. Replica set oplog $ c o l l e c t i o n - > u p d a t e ( [ ' x ' = > 1 ] , [ ' $ i n c ' = > [ ' x ' = > 1 ] ] ) ; ↓ { " t s " : T i m e s t a m p ( 1 4 1 4 6 2 4 9 6 2 , 1 ) , " h " : N u m b e r L o n g ( " 5 0 7 9 4 2 5 1 0 6 8 5 0 5 5 0 7 0 1 " ) , " v " : 2 , " o p " : " u " , " n s " : " t e s t . f o o " , " o 2 " : { " _ i d " : O b j e c t I d ( " 5 4 5 1 7 6 a 1 4 a b 5 c 0 c 9 9 9 d a 7 0 f 0 " ) } , " o " : { " $ s e t " : { " x " : 2 } } }
52. Fun with MongoDB’s oplog Syncing MongoDB to Solr with PHP MongoDB river plugin for Elasticsearch Building real-time systems @ Stripe Scalable oplog tailing @ Meteor
53. THANKS! Questions?
54. Image Credits Books designed by from the Aggregator designed by from the Register designed by from the Ouroboros designed by from the Catherine Please Noun Project stuart mcmorris Noun Project Wilson Joseph Noun Project Silas Reeves Noun Project http://mariompittore.com/wp-content/uploads/2013/08/Social-Gnomes1.png