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DSE Graph Schema Management Cheat Sheet in Gremlin Groovy

DSE Graph Schema Management Cheat Sheet in Gremlin Groovy

DSE Graph schema management examples taken from the excellent DS330: DataStax Enterprise Graph course.

Graph Definition

List all graph names:

system.graphs();  // => KillrVideo

Describe all graphs:

system.describe(); // => system.graph("KillrVideo").create()

Describe a specific graph:

system.graph("KillrVideo").describe();  // => system.graph("KillrVideo").create()

Create a graph:

system.graph("KillrVideo").create()
system.graph("KillrVideo").ifNotExists().create()

Create a graph with replication:

system
  .graph("KillrVideo")
  .option("graph.replication_config")
  .set("{'class' : 'NetworkTopologyStrategy','DC-East' : 3,'DC-West' : 5}")
  .option("graph.system_replication_config")
  .set("{'class' : 'NetworkTopologyStrategy','DC-East' : 3,'DC-West' : 3}")
  .ifNotExists()
  .create()

Create a graph in development mode:

system.graph("KillrVideo").create()
schema.config().option("graph.schema_mode").set("Development")

Check if a graph exists:

system.graph("KillrVideo").exists() // => true

Drop a specific graph:

system.graph("SomeGraph").drop();

Graph Schema Definition

Define a property key for a scalar integer:

// Property key with a single integer value
schema.propertyKey("year").Int().single().create();

// single() is assumed by default and can be omitted
schema.propertyKey("year").Int().create();

Defina a multi-property (note that multi-properties can only be associated with vertices):

// Property key that allows many text values for film production companies
schema.propertyKey("production").Text().multiple().create();

Define a meta-property (note that meta-properties can only be associated with vertex properties):

// Property key definitions
schema.propertyKey("source").Text().create();
schema.propertyKey("date").Timestamp().create();

// Multi-property key with two meta-properties
schema.propertyKey("budget").Text().multiple().properties("source","date").create();

Creating vertex labels:

// Vertex label with six associated property keys
schema
  .vertexLabel("movie")
  .properties("movieId","title","year", "duration","country","production")
  .create();
  
// Different vertex labels cna use the same property key

// Property key "name" definition
schema.propertyKey("name").Text().create();

// Property key "name" is associated with both vertex labels
schema.vertexLabel("genre").properties("genreId","name").create();
schema.vertexLabel("person").properties("personId","name").create();  

Creating Edge Labels

// A single cardinality edge label defintion
// A movie can be rated by a user at most once
schema
  .edgeLabel("rated")
  .single()
  .properties("rating")
  .connection("user","movie")
  .create();
  
// A multi-cardinality edge label definition
// Acting in a movie in multiple roles is possible
schema
  .edgeLabel("actor")
  .multiple()
  .connection("movie","person")
  .create();

// multiple() is assumed by default and can be omitted
schema
  .edgeLabel("actor")
  .connection("movie","person")
  .create();
  
// A multi-connection edge label definition
// Edge label with different domains and ranges
schema
  .edgeLabel("knows")
  .single()
  .connection("user","user")
  .connection("user","person")
  .connection("person","user")
  .create();

Dropping graph schemas:

// Dropping graph schema will also result in loosing all graph data!
schema.clear()

Retrieve vertext with a Default ID:

g.V().hasId("{~label=movie, member_id=0, community_id=63341568}")
// Sample output:
// v[{~label=movie, member_id=0, community_id=63341568}]

g.V("{~label=movie, member_id=0, community_id=63341568}")
// Sample output:
// v[{~label=movie, member_id=0, community_id=63341568}]

Defining Custom Vertex IDs

// Property keys
schema.propertyKey("username").Text().create();
schema.propertyKey("age").Int().create();
schema.propertyKey("gender").Text().create();

// Vertex label with a custom ID
schema
  .vertexLabel("user")
  .partitionKey("username")
  .properties("age","gender")
  .create();
  
// Property keys
schema.propertyKey("movieId").Text().create();
schema.propertyKey("title").Text().create();
schema.propertyKey("year").Int().create();
schema.propertyKey("duration").Int().create();
schema.propertyKey("country").Text().create();

// Vertex label with a custom ID
schema.vertexLabel("movie").
       partitionKey("year","country").
       clusteringKey("movieId").
       properties("title","duration").create();  

Retrieving a Vertex with a Custom ID

g.V("{~label=user, username=agent007}")   // or
g.V().hasId("{~label=user, username=agent007}")
// Sample output:
// v[{~label=user, username=agent007}]

g.V("{country=United States, movieId=m267, ~label=movie, year=2010}")   
// or
g.V().hasId("{country=United States, movieId=m267, ~label=movie, year=2010}")
// Sample output:
// v[{country=United States, movieId=m267, ~label=movie, year=2010}]

Graph Index Definition

Vertex Indexes

Create a materialized view index on a high cardinality property

// Indexing movies by movieId
schema.vertexLabel("movie").index("moviesById").materialized().by("movieId").add()

// Find a movie with a given movieId
// Both vertex label and property key-value must be 
// specified for a traversal to use an index.
g.V().hasLabel("movie").has("movieId","m267")
// or
g.V().has("movie","movieId","m267")

Create a secondary index on a low cardinality property

// Indexing movies by year
schema.vertexLabel("movie").index("moviesByYear").secondary().by("year").add()

// Find movies from a given year
g.V().hasLabel("movie").has("year",2010)
// or
g.V().has("movie","year",2010)
// Note: A traversal with no explicitly specified vertex label, 
// e.g., g.V().has("year",2010), cannot take advantage of a vertex index.

Create a full text search index on a text property

// Indexing movies by title
schema.vertexLabel("movie").index("search").search().by("title").asText().add()

// Find movies with words that start with "Wonder" in their titles
g.V().has("movie","title",Search.tokenRegex("Wonder.*"))
// Indexed properties can be queried using token(), tokenPrefix(), and tokenRegex().

Create a string search index on a text property

//Indexing movies by country
schema.vertexLabel("movie").index("search").search().by("country").asString().add()

//Find movies from countries that start with letter "U"
g.V().has("movie","country",Search.prefix("U"))
//Indexed properties can be queried using prefix(), regex(), eq() and neq().

Create additional specialized search index capabilities

// Spacial indexes: asCartesian() and asGeo()
// Other non-text indexes: no special index type
// One search index, many properties
// Indexing users by name, location, and age
schema
  .vertexLabel("user")
  .index("search")
  search()
  by("name").asText()
  by("location").asCartesian(0.0,0.0,100.0,100.0)
  by("age").add()

List vertex indexes

// Listing all graph schema information
schema.describe()

// Listing schema information for a particular vertex label
schema.vertexLabel("movie").describe()
// Sample output:
// schema.vertexLabel("movie").properties("movieId", "title", "year", "duration",
//                                                       "country", "production").create()
// schema.vertexLabel("movie").index("moviesById").materialized().by("movieId").add()
// schema.vertexLabel("movie").index("moviesByYear").secondary().by("year").add()
// schema.vertexLabel("movie").index("search").search().by("title").asText(),
//                                                     .by("country").asString().add()
// ...

Drop a vertex index

// Dropping a materialized view index
schema.vertexLabel("movie").index("moviesById").remove()

// Dropping a secondary index
schema.vertexLabel("movie").index("moviesByYear").remove()

// Dropping a specific search index property
schema.vertexLabel("user").index("search").
                           search().properties("location").remove()

// Dropping a search index
schema.vertexLabel("user").index("search").remove()

Property Indexes

Efficiently retrieve properties of a known vertex that have associated meta-properties whose values are known or fall into a known range using materialized views in Cassandra.

Create and use a Property Index

// Indexing movie budget estimates by source
schema.vertexLabel("movie").index("movieBudgetBySource")
  .property("budget").by("source").add()

// Querying movie budget estimates based on source
g.V().has("movie","movieId","m267").properties("budget")
  .has("source","Los Angeles Times").value()
      
// Indexing movie budget estimates by date
schema.vertexLabel("movie").index("movieBudgetByDate")
  .property("budget").by("date").add()

// Querying movie budget estimates based on date
g.V().has("movie","movieId","m267").properties("budget")
  .has("date", gt(Instant.now().minusSeconds(86400 * 365)))
  .value()

Edge Indexes

Efficiently traverse edges that are incident to a known vertex, have a known label, and have properties whose values are known or fall into a known range using a materialized view in Cassandra.

Create and use an Edge Index

// Find how many users rated a particular movie with an 8-star rating
schema.vertexLabel("movie")
  .index("toUsersByRating")
  .inE("rated").by("rating")
  .add();

g.V().has("movie","movieId","m267")
  .inE("rated").has("rating",8).count()
  
// Find movies rated with a greater-than-7 rating by a particular user
schema.vertexLabel("user")
  .index("toMoviesByRating")
  .outE("rated").by("rating")
  .add();

g.V().has("user","userId","u1")
  .outE("rated").has("rating",gt(7)).inV()
// Both incoming and outgoing edges of a vertex can be indexed by 
// specifying bothE() when creating an edge index.  

Production/Development Schema Modes

Change the schema mode for a graph:

schema.config().option("graph.schema_mode").get() // Production

schema.config().option("graph.schema_mode").set("Development")
schema.config().option("graph.schema_mode").get() // Development

Enabling graph scans in production mode

// This is OK for scanning small portions of data, but caution is advised
schema.config().option("graph.schema_mode").get() // Production
g.V().hasLabel("genre").values("name")
// Could not find a suitable index ... and graph scans are disabled

schema.config().option("graph.allow_scan").set(true)
g.V().hasLabel("genre").values("name")
// Action Adventure Animation Comedy ... 18 genres in total

Profiling Traversals

Executa a query and track profiling data

OLTP traversal example

g.V().has("person","name","Johnny Depp").in("actor").values("title").profile()

Traversal Metrics
Step                                              Count  Traversers       Time (ms)    % Dur
============================================================================================
DsegGraphStep([~label.eq(person), name.eq(Johnn...    1           1           1.103    16.25
  query-optimizer                                                             0.117
  query-setup                                                                 0.004
  index-query                                                                 0.330
DsegVertexStep(IN,[actor],vertex)                    14          14           1.312    19.33
  query-optimizer                                                             0.068
  query-setup                                                                 0.001
  vertex-query                                                                0.519
DsegPropertiesStep([title],value)                    14          14           4.373    64.43
  query-optimizer                                                             0.154
  query-setup                                                                 0.000
  vertex-query                                                                0.161
  query-setup                                                                 0.000
  vertex-query                                                                0.150
  query-setup                                                                 0.000
  vertex-query                                                                0.179
  query-setup                                                                 0.000
  vertex-query                                                                0.209
  query-setup                                                                 0.000
                           >TOTAL                     -           -           6.789        -

OLAP traversal example

g.E().groupCount().by(label).profile()

Traversal Metrics
Step                               Count  Traversers       Time (ms)    % Dur
=============================================================================
GraphStep(edge,[])                 69054       69054        4161.214    98.50
GroupCountStep(label)                  1           1          63.277     1.50
                        >TOTAL         -           -        4224.492        -

Switching to the OLTP traversal engine

:remote config alias g KillrVideo.g
g.V().has("person","name","Johnny Depp").in("actor").values("title")

Switching to the OLAP traversal engine

:remote config alias g KillrVideo.a
g.E().groupCount().by(label)
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