Redis Graph. A graph database built on top of redis

Transcription

1 Redis Graph A graph database built on top of redis

2 What s Redis? Open source in-memory database Key => Data Structure server Key features: Fast, Flexible, Simple

3 A Lego for your database Key "I'm a Plain Text String!" { A: foo, B: bar, C: baz } [ A B C D E ] { A, B, C, D, E } { A: 0.1, B: 0.3, C: 100, D: 1337 } { A: (51.5, 0.12), B: (32.1, 34.7) } Strings/Blobs/Bitmaps Hash Tables (objects!) Linked Lists Sets Sorted Sets Geo Sets HyperLogLog

4 Node Jerry Seinfeld Jerry Seinfeld : { First_Name: Jerry, Age: 62 }

5 Relations Jerry Visit Berlin

6 Hexastore S Subject P Predicate O Object SPO SOP OPS OSP PSO POS 6

7 Hexastore Triplets SPO:Jerry:Visit:Berlin SOP:Jerry:Berlin:Visit OPS:Berlin:Visit:Jerry OSP:Berlin:Jerry:Visit PSO:Visit:Jerry:Berlin POS:Visit:Berlin:Jerry Jerry S Visit P Berlin O

8 Hexastore Places Jerry been to? SPO:Jerry:Visit:* Who visited Berlin? OPS:Berlin:Visit:* Who travels and to where? PSO:Visit:* Jerry S Visit P Berlin O

9 Query language Cypher* MATCH (Jerry: Jerry Seinfeld )-[friend]->(f)-[visit]->(country) WHERE (F.age >= Jerry.age AND country.continent = Europe ) RETURN F.name, count(country.name) AS countriesvisited ORDER BY countriesvisited, F.age DESC LIMIT 2

10 Query language Tokenizer - Lex Parser - Lemon, SQLite LALR(1) parser generator for C opencypher

11 MATCH (Jerry: Jerry Seinfeld )-[friend]->(f)-[visit]->(country) WHERE F.age >= 50 AND Country.continent = Europe RETURN F.name, F.age, Country.name ORDER BY F.age DESC LIMIT 5

12 Query Lexer Parser AST

13 AST Root Match Where Return Order

14 MATCH (Jerry:"Jerry Seinfeld")-[friend]->(F)-[visit]->(Country) Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID:? visit Alias: Country ID:?

15 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID:? visit Alias: Country ID:? SPO:Jerry Seinfeld:friend:* SPO:Jerry Seinfeld:friend:Cosmo Kramer SPO:Jerry Seinfeld:friend:George Costanza

16 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID: Cosmo Kramer visit Alias: Country ID:?

17 WHERE F.age >= 50 AND Country.continent = Europe Filter tree AND age >= 50 continent = Europe

18 Cosmo Kramer: { Name: Cosmo Kramer, Age: 48 } AND Kramer.age >= 50 continent = Europe

19 Cosmo Kramer: { Name: Cosmo Kramer, Age: 48 } AND Kramer.age >= 50 F continent = Europe

20 Cosmo Kramer: { Name: Cosmo Kramer, Age: 48 } AND F Kramer.age >= 50 F continent = Europe

21 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID:? visit Alias: Country ID:? SPO:Jerry Seinfeld:friend:* SPO:Jerry Seinfeld:friend:Cosmo Kramer SPO:Jerry Seinfeld:friend:George Costanza

22 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID: George Costanza visit Alias: Country ID:?

23 George Costanza:{ Name: George Costanza, Age: 52 } AND George.age >= 50 continent = Europe

24 George Costanza:{ Name: George Costanza, Age: 52 } George.age >= 50 T AND continent = Europe

25 George Costanza:{ Name: George Costanza, Age: 52 } George.age >= 50 T AND T continent = Europe T

26 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID: George Costanza visit Alias: Country ID:? SPO:George Costanza:visit:* SPO:George Costanza:visit:Italy SPO:George Costanza:visit:Cuba

27 Alias: Jerry ID: Jerry Seinfeld friend Alias: F ID: George Costanza visit Alias: Country ID: Italy

28 George Costanza:{ Name: George Costanza, Age: 52 } Italy: { Continent: Europe, Population: 1000, Name: Italy } George.age >= 50 T AND T Italy.continent = Europe T

29 TOP K heap RETURN F.name, F.age, Country.name ORDER BY F.age DESC LIMIT 5 [ George Costanza, 52, Italy]

30 Features Multi hop, multi entry point (A)-[R1]->(C)<-[R2]-(B) (Nicolas: Nicolas Cage )-[act]->(movie)<-[act]-(actor) Aggregations, Group bys RETURN F.gender, AVG(F.age) AS average_age Order bys, Distinct

31 Benchmark 150K inserts per second 15K simple queries per second

32 There s still work to be done Single node query: MATCH (A) RETURN A OPTIONAL MATCH WITH, SKIP, UNION Curly brackets filters (john {name: John }) In place evaluations WHERE Me.age > F.age + X Shortest path between nodes (A)-[*]-(B) A number of aggregation functions: stdev, precentilecount

33 Roadmap Hexastore sorted-set -> Trie Indexed entities Single node query Python lib

34 Contribute/Contact