Warming Up to Graphs

From PyOhio 2014

Transcript

1. Warming up to Graphs
   Brad Montgomery
   

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2. What is a Graph?
   

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3. Nope.
   7%
   8%
   10%
   11%
   29%
   35%
   

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4. 0
   25
   50
   75
   100
   April May June July
   Nope.
   

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5. Nope.
   0
   25
   50
   75
   100
   April May June July
   

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6. Yes.
   A
   B
   C
   

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7. – paraphrasing Wikipedia
   “A set of objects…connected by links”
   

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8. Some Graph Theory
   

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9. Some Graph Theory
   Very Little
   

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10. http://en.wikipedia.org/wiki/Leonhard_Euler#mediaviewer/File:Leonhard_Euler_2.jpg
    Leonhard Euler
    

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11. http://en.wikipedia.org/wiki/Leonhard_Euler#mediaviewer/File:Konigsberg_bridges.png
    Seven Bridges of Königsberg
    

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12. C
    A
    B
    This is a Graph
    

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13. C
    A
    B
    These are Nodes
    (aka vertices or points)
    

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14. C
    A
    B
    These are Edges
    (aka lines or arcs)
    

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15. C
    A
    B
    Edges may have an explicit direction.
    

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16. C
    A
    B
    A Directed Graph (aka Digraph)
    

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17. C
    A
    B
    This is an Undirected Graph.
    

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18. C
    A
    B
    Edges may also have weights.
    This becomes a Weighted Graph.
    42
    37
    

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19. C
    A
    B
    You can traverse a graph.
    This is a Path.
    

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20. C
    A
    B
    This is a Cycle.
    

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21. C
    A
    B
    This Graph has no cycles.
    It’s acyclic.
    

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22. C
    A
    B
    A Directed Acyclic Graph (aka DAG)
    

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23. C
    A
    B
    This Graph is Connected.
    

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24. C
    A
    B
    This Graph is not Connected.
    E
    D
    

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25. C
    A
    B
    A complete graph.
    

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26. C
    A
    B
    A Tree
    D E
    

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27. Graph Algorithms
    

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28. Graph Algorithms
    Wikipedia has 94 pages
    categorized as “Graph Algorithms”
    

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29. Shortest Path
    Dijkstra’s Algorithm
    A* search algorithm
    

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30. Search
    Depth-first search
    Breadth-first search
    B-trees
    

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31. Minimal Spanning Tree
    Kruskal's algorithm
    Prim's algorithm
    

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32. Graph Tours
    Eulerian Path
    Hamiltonian path/
    Traveling Salesman
    

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33. networkx.github.io
    

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34. Why a
    Graph Database?
    

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35. C
    A
    B
    !=
    

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36. Neo4j
    • Commercial Software
    • Community Edition is Open Source (GPL/AGPL)
    • Written in Java
    • Has a RESTful API
    • ACID/Transactions/High Availability*
    • Supports Billions of Nodes & Relationships on a single
    machine.
    

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37. Neo4j
    https://github.com/neo4j/neo4j
    

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38. How to play with Neo4j
    1. Download the current version (2.1.2)
    2. Unpack the .tar.gz file.
    3. Install Java?
    4. ./neo4j-community-2.1.2/bin/neo4j start
    5. Visit http://localhost:7474/
    

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40. Modeling Data
    

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41. Modeling Data
    Still called a Node.
    ~ An Entity. With properties.
    

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42. Modeling Data
    name: Janet
    email: janet@example.com
    

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43. Modeling Data
    User!
    name: Janet
    email: janet@example.com
    Nodes can also have Labels.
    

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44. Modeling Data
    User!
    name: Janet
    email: janet@example.com
    Project!
    name: open-unicorn
    website: open-unicorn.org
    

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45. Modeling Data
    User!
    name: Janet
    email: janet@example.com
    Project!
    name: open-unicorn
    website: open-unicorn.org
    Edges are called “Relationships”
    

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46. Modeling Data
    User!
    name: Janet
    email: janet@example.com
    Project!
    name: open-unicorn
    website: open-unicorn.org
    CONTRIBUTES_TO
    

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47. Modeling Data
    User!
    name: Janet
    email: janet@example.com
    Project!
    name: open-unicorn
    website: open-unicorn.org
    CONTRIBUTES_TO
    !
    first_commit: 2014-07-27
    User!
    name: Rose
    email: rose@example.com
    OWNED_BY
    

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48. And now for some
    Python
    

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49. Several Python Wrappers.
    !
    I’m using py2neo 1.6.4
    

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50. from py2neo import neo4j!
    !
    # Connect to a DB.!
    db = neo4j.GraphDatabaseService(!
    ‘http://localhost:7474/db/data/'!
    )
    

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51. from py2neo import node!
    !
    # Create a Node!
    n = node(name="Janet", email="janet@example.com")!
    Properties
    

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52. from py2neo import node!
    !
    # Create a Node!
    n = node(name="Janet", email="janet@example.com")!
    An Abstract Node
    

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53. from py2neo import node, rel!
    !
    db.create(!
    node(name="Janet", email="janet@example.com"),!
    node(name="open-unicorn", website="open-unicorn.org"),!
    rel(0, "CONTRIBUTES_TO", 1),!
    )!
    

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54. from py2neo import node, rel!
    !
    db.create(!
    node(name="Janet", email="janet@example.com"),!
    node(name="open-unicorn", website="open-unicorn.org"),!
    rel(0, "CONTRIBUTES_TO", 1),!
    )!
    What?
    

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55. from py2neo import node, rel!
    !
    # Create some Users!
    user_data = [{'name': 'Janet', 'email': 'janet@example.com'}]!
    user_nodes = [node(d) for d in user_data] # Abstract Nodes!
    users = db.create(*user_nodes)!
    !
    !
    !
    !
    

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56. from py2neo import node, rel!
    !
    # Create some Users!
    user_data = [{'name': 'Janet', 'email': 'janet@example.com'}]!
    user_nodes = [node(d) for d in user_data] # Abstract Nodes!
    users = db.create(*user_nodes)!
    !
    for u in users:!
    u.add_labels("User")!
    !
    Now you can add Labels
    

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57. from py2neo import node, rel!
    !
    # Create some Projects.!
    project_data = [!
    {'name': 'open-unicorn', 'website': 'open-unicorn.org'}!
    ]!
    project_nodes = [node(d) for d in project_data]!
    projects = db.create(*project_nodes)!
    !
    # Every User contributes to every Project.!
    rels = []!
    for p in projects:!
    p.add_labels("Project")!
    for u in users:!
    rels.append(!
    rel(u, "CONTRIBUTES_TO", p)!
    )!
    !
    # Save the relationships!
    relationships = db.create(*rels)!
    

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58. # Find a User based on their email!
    users = db.find(!
    “User",!
    property_key=“email",!
    property_value=“janet@example.com"!
    )!
    !
    print(users[0])!
    # (1 {'name': ‘Janet',!
    ‘email': 'janet@example.com'})!
    

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59. # Find a User based on their email!
    users = db.find(!
    “User",!
    property_key=“email",!
    property_value=“janet@example.com"!
    )!
    !
    print(users[0])!
    # (1 {'name': ‘Janet',!
    ‘email': 'janet@example.com'})!
    Label
    

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60. # Find a User based on their email!
    users = db.find(!
    “User",!
    property_key=“email",!
    property_value=“janet@example.com"!
    )!
    !
    print(users[0])!
    # (1 {'name': ‘Janet',!
    ‘email': 'janet@example.com'})!
    Nodes get an ID, but don’t rely on it.
    

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61. # Accessing Node Attributes!
    users = db.find(…)!
    user = users[0]!
    print(user[‘name’]) !
    # Janet
    

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62. # Access Labels and additional properties!
    print user.get_labels()!
    # {'User'}!
    !
    print user.get_properties()!
    # {'name': 'Janet', 'email': 'janet@example.com'}
    

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63. # Accessing Relationships!
    for relationship in user.match_outgoing():!
    print(!
    relationship.type, !
    relationship.end_node[‘name']!
    )!
    # CONTRIBUTES_TO open-unicorn!
    

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64. # Accessing Relationships!
    for relationship in user.match_outgoing():!
    print(!
    relationship.type, !
    relationship.end_node[‘name']!
    )!
    # CONTRIBUTES_TO open-unicorn!
    User
    Project
    

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65. for relationship in user.match_incoming():!
    print(!
    relationship.type, !
    relationship.start_node[‘name']!
    )!
    # OWNED_BY open-unicorn
    

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66. for relationship in user.match_incoming():!
    print(!
    relationship.type, !
    relationship.start_node[‘name']!
    )!
    # OWNED_BY open-unicorn
    User
    Project
    

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67. for relationship in user.match():!
    print(!
    relationship.start_node['name'],!
    relationship.type,!
    relationship.end_node['name'],!
    )!
    # open-unicorn OWNED_BY Janet!
    # Janet CONTRIBUTES_TO open-unicorn
    

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68. for relationship in user.match():!
    print(!
    relationship.start_node['name'],!
    relationship.type,!
    relationship.end_node['name'],!
    )!
    # open-unicorn OWNED_BY Janet!
    # Janet CONTRIBUTES_TO open-unicorn
    User
    Project
    

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69. # Find a project's contributors.!
    # 1) get the project node!
    projects = db.find(!
    "Project",!
    property_key="name",!
    property_value="open-unicorn"!
    )!
    p = projects[0]!
    !
    # 2) list all contributors!
    for r in p.match_incoming(rel_type="CONTRIBUTES_TO"):!
    print(rel.start_node['name']) # Janet!
    

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70. More Interesting Queries
    • People that contribute to open-unicorn also
    contribute to … ?
    • Who contributes to similar projects as me?
    • Six degrees of Guido van Rossum?
    

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71. Cypher
    

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72. Cypher
    • Declarative
    • SQL-like
    • Sometimes *looks* like a graph.
    

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73. MATCH (n) RETURN n
    

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74. MATCH (n) RETURN n
    A Node
    

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75. MATCH (n:User) RETURN n
    

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76. MATCH (n:User) RETURN n
    A Label
    

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77. MATCH (n:User)
    WHERE n.name=“Janet”
    RETURN n
    

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78. MATCH (p)-[:OWNED_BY]->(u)
    RETURN p, u
    

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79. MATCH (p)-[:OWNED_BY]->(u)
    RETURN p, u
    A Relationship
    

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80. MATCH (p)-[:OWNED_BY]->(u)
    RETURN p, u
    

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81. View Slide

82. MATCH
    (u:User)-[:CONTRIBUTES_TO]->(p:Project)
    WHERE u.name="Janet"
    RETURN p.name
    ORDER BY p.name
    

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83. from py2neo import cypher!
    !
    # Create a Transaction.!
    session = cypher.Session(!
    ‘http://localhost:7474/db/data/'!
    )!
    tx = session.create_transaction()
    

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84. query = """!
    MATCH (n:User) !
    WHERE n.username={name} !
    RETURN n!
    """!
    tx.append(!
    query,!
    parameters={‘name’:‘Janet’}!
    )!
    results = tx.commit()
    

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85. query = """!
    MATCH (n:User) !
    WHERE n.username={name} !
    RETURN n!
    """!
    tx.append(!
    query,!
    parameters={‘name’:‘Janet’}!
    )!
    results = tx.commit()
    Parameter
    Substitution
    

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86. # Returns a list of Records for each query.!
    [!
    [!
    Record(!
    columns=('n',),!
    values=(Node(), )!
    )!
    ],!
    ]!
    

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87. # Returns a list of Records for each query.!
    [!
    [!
    Record(!
    columns=('n',),!
    values=(Node(), )!
    )!
    ],!
    ]!
    May contain Nodes and Relationships
    

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88. People that contribute
    to open-unicorn also
    contribute to…
    

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89. query = """!
    MATCH!
    (p:project)-[:CONTRIBUTES_TO]->(o:project)!
    WHERE p.name={name}!
    RETURN o.name, count(*)!
    ORDER BY count(*) DESC, o.name!
    LIMIT {limit}!
    """!
    # tx is a transaction object!
    tx.append(!
    query,!
    parameters={"name": "open-unicorn", "limit": 5}!
    )!
    results = tx.commit()!
    for record in results[0]:!
    name, count = record.values!
    print("({0}) {1}".format(count, name))!
    

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90. # o.name count(*)!
    # --------------------------!
    # open-jackrabbit 6!
    # flailing-jackrabbit 5!
    # secret-butterfly 5!
    # tiny-armyant 5!
    # flaming-butterfly 3
    

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91. Who contributes to
    similar projects?
    

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92. # People who contribute to similar projects as Janet!
    query = """!
    MATCH!
    (a:user)-[:CONTRIBUTES_TO]->(p:project)!
    -[:OWNED_BY]->(u)!
    -[:CONTRIBUTES_TO]->(x:project)!
    WHERE a.username={name} AND NOT a=people!
    RETURN people.name AS name, count(*) AS similar_contribs!
    ORDER BY similar_contribs DESC!
    """!
    # tx is a transaction object!
    tx.append(!
    query,!
    parameters={"name":"Janet", "limit": 5}!
    )!
    results = tx.commit()!
    for record in results[0]:!
    name, count = record.values!
    print("{0} {1}".format(name, count))
    

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93. # people.name count(*)!
    # ---------------------------!
    # Bridget Betty 33!
    # Donald Catherine 33!
    # Donald Bob 30!
    # Frank Chuck 28!
    # Bob Brad 27
    

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94. How am I connected to
    Guido Van Rossum?
    

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95. # Path between two Users!
    query = """!
    MATCH!
    (a:user), (b:user),!
    p=shortestPath((a)-[]->(b))!
    WHERE a.name={name_a} AND b.name={name_b}!
    RETURN LENGTH(p), p!
    """!
    params = {'name_a': 'Janet' 'name_b': 'Daisy'}!
    tx.append(query, parameters=params)!
    results = tx.commit()!
    for record in results[0]:!
    length, path = record.values!
    print("{0} hops".format(length))!
    for rel in path.relationships:!
    print("({0})-[:{1}]->({2})".format(!
    rel.start_node['name'],!
    rel.type,!
    rel.end_node['name']!
    ))
    

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96. # 6 hops.!
    # (Janet)-[:CONTRIBUTES_TO]->(enterprise-grasshopper)!
    # (enterprise-grasshopper)-[:OWNED_BY]->(Zoe)!
    # (Zoe)-[:CONTRIBUTES_TO]->(open-turtledove)!
    # (open-turtledove)-[:OWNED_BY]->(Delia)!
    # (Delia)-[:CONTRIBUTES_TO]->(flailing-sealion)!
    # (flailing-sealion)-[:OWNED_BY]->(Daisy)!
    

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97. Object-Graph
    Mapping (ogm)
    

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98. !
    class User(object):!
    !
    def __init__(self, name=None, email=None):!
    self.name = name!
    self.email = email!
    !
    !
    class Project(object):!
    !
    def __init__(self, name=None):!
    self.name = name!
    

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99. from py2neo import ogm!
    !
    # Create a User & Project!
    store = ogm.Store(db)!
    u = User("Janet", "janet@example.com")!
    p = Project(“open-unicorn")!
    !
    store.save_unique("User", "email", u.email, u)!
    store.save_unique("project", "name", p.name, p)!
    store.relate(u, ”CONTRIBUTES_TO”, p)!
    store.save(u)!
    

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100. # Retrieve a User!
     store = ogm.Store(db)!
     u = store.load_unique(!
     "User", "email","janet@example.com", User!
     )!
     p = store.load_unique(!
     "Project", "name", "massive-aardvark", Project!
     )!
     !
     # Get some relationships!
     contribs = store.load_related(!
     u, "CONTRIBUTES_TO", Project!
     )!
     

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101. # User!
     u.__node__!
     !
     # A Dictionary of Outgoing Relationships!
     u.__rel__!
     !
     

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102. Performance.
     

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103. Performance
     RDBMs Index Lookup: O(log n)
     Neo4j: Immediate Relationships: O(1)
     

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104. Performance
     RDBMs Traversals: O(m log n)
     Neo4j: Traversals: O(m)
     

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105. Scenarios
     When is a GraphDB the right tool?
     

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106. Social Graphs
     

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107. Fraud Detection
     

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108. Recommendations
     

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109. Dependencies
     

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110. Graph-Like Data
     (Trees)
     

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111. When is it a Bad Idea?
     

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112. Write-Heavy
     

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113. Tabular Data?
     

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114. When Postgres Works
     

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115. More Python!
     

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116. More Python
     • Neomodel - Neo4j Models for Django (build on
     py2neo)
     • neo4django - Neo4j Models for Django
     • bulbflow - Neo4j, OrientDB, Titan
     • neo4j-rest-client - Nice API. Active development.
     • py2neo - Undergoing a major rewrite.
     

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117. View Slide

118. (me)-[:THANKS]->(you)
     

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119. (you)-[:QUESTIONS]->(me)
     

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