Neo4j Introduction - Game of Thrones
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The document provides an introduction and agenda for a Neo4j workshop about modeling Game of Thrones data. It discusses loading Game of Thrones character, episode and house data into Neo4j and demonstrates different Cypher queries to analyze relationships between these entities such as determining the most prominent characters or how houses are related. The workshop also covers more advanced topics like aggregation queries using the WITH clause and deleting or constraining data.
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Neo4j Introduction - Game of Thrones
- 1. Intro to Neo4j @praveenasekhar / @markneedham <3
- 2. Tweet us your pictures @neo4j @WomenWhoCode Welcome!
- 3. Logistics ‣ Wi-fi • network: LNVisitor • user/password: LNGuest / LNGuest ‣ Grab a USB key from one of the tables or download from neo4j.com/download ‣ Install Neo4j 3.0.3
- 7. They GoT the title wrong ... There maybe spoilers.. [Maybe]
- 8. Example
- 9. Game of Thrones Wiki
- 10. By the end you will help us work out ‣ Who is the most prominent character in a season? ‣ Which house features the most characters? ‣ How are Starks and Targaryens related?
- 11. A quick show of hands... How many people have used databases before?
- 12. A quick show of hands... How many people have used Neo4j before?
- 13. A quick show of hands... How many people have watched Game of Thrones?
- 14. Whiteboard / Post-It Exercise Everyone! List down different types of entities and relationships that tie them in the Game of Thrones universe! http://gameofthrones.wikia.com/wiki/Game_of_Thrones_Wiki
- 15. ‣ Actors ‣ Characters ‣ Allegiances ‣ Houses ‣ Episodes ‣ Locations What data do we have?
- 16. ‣ An introduction to Neo4j and the Cypher query language ‣ GoT characters and episodes ‣ GoT houses ‣ GoT family relationships Agenda
- 17. Example
- 18. A brief into to the graph data model
- 19. GoT graph model
- 20. Nodes
- 21. Labels
- 22. Properties
- 23. Relationships
- 25. What is Cypher? ‣ The graph query language ‣ Declarative and based on finding patterns ‣ ASCII Art + Query Language = Cypher
- 26. Nodes () or (n) ● Surrounded with parentheses ● Use an alias to refer to our node later (n:Label) ● Specify a Label - grouping nodes by roles or types ● Think of Labels like "Tables"++ (n:Label {prop: 'value'}) ● Nodes can have properties
- 27. Relationships --> or -[:TYPE]-> ● Hyphenated & encased in square brackets ● Like labels, a relationship type starts with a colon : ● < > Specify the direction of the relationship -[:TYPE {propertyName: "value"}]-> ● Relationships can have properties too!
- 28. Our first graph ‣ Navigate to http://localhost:7474 ‣ Type the following into the pane at the top: :play http://guides.neo4j.com/got
- 29. Follow Along Run the first guide with us
- 30. When there are slides to see
- 31. Continue Continue with the Guide
- 33. Unique constraints We create unique constraints to: ‣ ensure uniqueness ‣ allow fast lookup of nodes which match these (label,property) pairs.
- 34. Unique constraints We create unique constraints to: ‣ ensure uniqueness ‣ allow fast lookup of nodes which match these (label,property) pairs. CREATE CONSTRAINT ON (c:Character) ASSERT c.name IS UNIQUE
- 35. Continue Continue with the Guide
- 36. End of Section 1 Continue with the Guide
- 37. Follow Along Run the next guide with us
- 39. Deleting data The DELETE command allows us to delete nodes and relationships...but we can’t delete nodes if they still have relationships
- 40. Deleting data The DELETE command allows us to delete nodes and relationships...but we can’t delete nodes if they still have relationships MATCH (n) DELETE n org.neo4j.kernel.api.exceptions.ConstraintViolationTransactionFailureException: Cannot delete node<0>, because it still has relationships. To delete this node, you must first delete its relationships.
- 41. Deleting data The DETACH DELETE command is our friend when we want to delete a node and all relationships attached to it. MATCH (n) DETACH DELETE n
- 42. Deleting schema We can delete constraints as well by changing ‘CREATE’ to ‘DROP’ in the command CREATE CONSTRAINT ON (c:Character) ASSERT c.name IS UNIQUE; DROP CONSTRAINT ON (c:Character) ASSERT c.name IS UNIQUE;
- 43. Follow Along Continue with the guide
- 45. LOAD CSV ‣ Import data from a HTTP or file URI • LOAD CSV WITH HEADERS FROM "file://" AS row LOAD CSV WITH HEADERS FROM "http://" AS row ‣ Transform and convert CSV values • MATCH (node1:Label {property: row.propertyValue}) CREATE (node2:Label {property: row.propertyValue}) MERGE (node3:Label {property: row.propertyValue}) • CREATE (node1)-[:REL_TYPE]->(node2) MERGE (node1)-[:REL_TYPE]->(node2)
- 46. Continue Continue with the Guide
- 48. Aggregation queries We don’t specify a GROUP BY key when using aggregation functions. The key is all non aggregation fields in the RETURN statement.
- 49. Aggregation queries We don’t specify a GROUP BY key when using aggregation functions. The key is all non aggregation fields in the RETURN statement. MATCH (character:Character)-[:APPEARED_IN]->() RETURN character.name, COUNT(*) AS appearances ORDER BY appearances DESC
- 50. Follow Along Continue with the guide
- 51. End of Section 2 Let’s take a 5 minute break
- 52. Follow Along Onto the next guide
- 53. Take Note Advanced aggregation queries
- 54. Let’s talk about joins Houses Episodes Characters Houses Episodes Characters
- 55. Let’s talk about joins We can use the WITH clause to work around this problem
- 56. WITH The WITH clause allows query parts to be chained together, piping the results from one to be used as starting points or criteria in the next.
- 57. WITH It’s used to: ‣ limit the number of entries that are then passed on to other MATCH clauses. ‣ filter on aggregated values ‣ separate reading from updating of the graph
- 58. WITH MATCH (h:House)<-[:HAS_ALLEGIANCE_TO]-(c:Character)-[:APPEARED_IN]->() RETURN c.id, c.name, COLLECT(h.name) AS houses, COUNT(*) AS appearances ORDER BY appearances DESC MATCH (h:House)<-[:HAS_ALLEGIANCE_TO]-(c:Character) WITH c, COLLECT(h.name) as houses MATCH (c)-[:APPEARED_IN]->() RETURN c.id, c.name, houses, COUNT(*) AS appearances ORDER BY appearances DESC
- 59. Follow Along Continue with the guide
- 60. End of Section 3 One more to go
- 61. Tweet us your pictures @neo4j @WomenWhoCode Thanks for coming!
- 62. That’s all for today! Thanks for coming! <3
- 63. Resources HBO Game of Thrones Wikipedia Family Tree House Stark Game of Thones Wikia Cool Interactive Infographic http://www.fastcodesign.com/1671439/infographic-every- murder-in-game-of-thrones-in-just-90-seconds https://www.washingtonpost.com/graphics/entertainment/game- of-thrones/ http://winteriscoming.net/2016/04/18/infographic-shows-that- death-has-been-good-for-game-of-thrones-ratings/ 15 GoT Infographics http://hauteslides.com/2011/05/game-of-thrones-infographic- illustrated-guide-to-houses-and-character-relationships/ Social Media Infographics Betrayal Graph Impressive GoT Railroad Map Character Relationship Graph from Book 3 NLP Analytics