AWS IoT TwinMaker knowledge graph additional resources - AWS IoT TwinMaker

AWS IoT TwinMaker knowledge graph additional resources

This topic provides basic examples of the PartiQL syntax used to write queries in the knowledge graph, as well as links to PartiQL documentation that provide information on the knowledge graph data model.

This set of examples provides basic queries with responses. Use this as refrence to write your own queries.

Basic queries
  • Get all entities with a filter

    SELECT entity FROM EntityGraph MATCH (entity) WHERE entity.entityName = 'room_0'

    This query returns all the entities in a workspace with name room_0.

    FROM clause: EntityGraph in the is a graph collection that contains all the entities and their relationships in a workspace. This collection is automatically created and managed by AWS IoT TwinMaker based on the entities in your workspace.

    MATCH clause: specifies a pattern that matches a portion of the graph. In this case, the pattern () matches every node in the graph and is bound to the entity variable. The FROM clause must be followed by the MATCH clause.

    WHERE clause: specifies a filter on the entityName field of the node where the value must be room_0.

    SELECT clause: specifies the entity variable so the whole entity node is returned.


    { "columnDescriptions": [ { "name": "entity", "type": "NODE" } ], "rows": [ { "rowData": [ { "arn": "arn:aws:iottwinmaker:us-east-1: 577476956029: workspace / SmartBuilding8292022 / entity / room_18f3ef90 - 7197 - 53 d1 - abab - db9c9ad02781 ", "creationDate": 1661811123914, "entityId": "room_18f3ef90-7197-53d1-abab-db9c9ad02781", "entityName": "room_0", "lastUpdateDate": 1661811125072, "workspaceId": "SmartBuilding8292022", "description": "", "components": [ { "componentName": "RoomComponent", "componentTypeId": "", "properties": [ { "propertyName": "roomFunction", "propertyValue": "meeting" }, { "propertyName": "roomNumber", "propertyValue": 0 } ] } ] } ] } ] }

    The columnDescriptions returns metadata about the column such as the name and type. The type returned is NODE. This indicates that the whole node has been returned. Other values for type can be EDGE which would indicate a relationship or VALUE which would indicate a scalar value like integer or string.

    The rows returns a list of rows. As only one entity was matched, one rowData is returned which contains all the fields in an entity.


    Unlike SQL where you can only return scalar values, you can return an object (as JSON) using PartiQL.

    Each node contains all the entity-level fields such as entityId, arn and components, component-level fields such as componentName, componentTypeId and properties as well as property-level fields such as propertyName and propertyValue all as a nested JSON.

  • Get all relationships with a filter:

    SELECT relationship FROM EntityGraph MATCH (e1)-[relationship]->(e2) WHERE relationship.relationshipName = 'isLocationOf'

    This query returns all the relationships in a workspace with relationship name isLocationOf.

    The MATCH clause: specifies a pattern that matches two nodes, indicated by (), that are connected by a directed edge, indicated by -[]-> and bound to a variable called relationship.

    The WHERE clause: specifies a filter on the relationshipName field of the edge where the value is isLocationOf.

    The SELECT clause: specifies the relationship variable so the whole edge node is returned.


    { "columnDescriptions": [{ "name": "relationship", "type": "EDGE" }], "rows": [{ "rowData": [{ "relationshipName": "isLocationOf", "sourceEntityId": "floor_83faea7a-ea3b-56b7-8e22-562f0cf90c5a", "targetEntityId": "building_4ec7f9e9-e67e-543f-9d1b- 235df7e3f6a8", "sourceComponentName": "FloorComponent", "sourceComponentTypeId": "" }] }, ... //rest of the rows are omitted ] }

    The type of the column in columnDescriptions is an EDGE.

    Each rowData represents an edge with fields like relationshipName, this is the same as the relationship property name defined on the entity. The sourceEntityId, sourceComponentName and sourceComponentTypeId gives information about which entity and component the relationship property was defined on. The targetEntityId specified which entity this relationship is pointing towards.

  • Get all entities with a certain relationship to a certain entity

    SELECT e2.entityName FROM EntityGraph MATCH (e1)-[r]->(e2) WHERE relationship.relationshipName = 'isLocationOf' AND e1.entityName = 'room_0'

    This query returns all the entity names of all entities that have a isLocationOf relationship with room_0 entity.

    MATCH clause: specifies a pattern that matches any two nodes (e1, e2) that has a directed edge (r).

    The WHERE clause: specifies a filter on the relationship name and source entity’s name.

    The SELECT clause: return the entityName field within the e2 node.


    { "columnDescriptions": [ { "name": "entityName", "type": "VALUE" } ], "rows": [ { "rowData": [ "floor_0" ] } ] }


    In the columnDescriptions, the type of the column is VALUE since entityName is a string.

    One entity floor_0 is returned.


The following patterns are supported in a MATCH clause:

  • Matches node b pointing to node a:

    FROM EntityGraph MATCH (a)-[rel]-(b)
  • Matches node a pointing to node b:

    FROM EntityGraph MATCH (a)-[]->(b)

    There is no variable bound to relationship assuming a filter doesn’t need to be specified on the relationship.

  • Matches node a pointing to node b and node b pointing to node a:

    FROM EntityGraph MATCH (a)-[rel]-(b)

    This will return two matches: one from a to b and another from b to a so the recommendation is to use directed edges wherever possible.

  • The relationship name is also a label of the property graph EntityGraph so you can simply specify the relationship name following a : colon instead of specify a filter on rel.relationshipName in the WHERE clause.

    FROM EntityGraph MATCH (a)-[:isLocationOf]-(b)
  • Chaining: patterns can be chained to match on multiple relationships.

    FROM EntityGraph MATCH (a)-[rel1]->(b)-[rel2]-(c)
  • Variable hop patterns can span multiple nodes and edges as well:

    FROM EntityGraph MATCH (a)-[]->{1,5}(b)

    his query matches any pattern with outgoing edges from node a within 1 to 5 hops.The allowed quantifiers are:

    {m,n} - between m and n repetitions

    {m,} - m or more repetitions.


An entity node can contain nested data such as components which themselves contain further nested data such as properties. These can be accessed by unnesting the result of the MATCH pattern.

SELECT e FROM EntityGraph MATCH (e), e.components AS c, AS p WHERE c.componentTypeId = '', AND p.propertyName = 'roomFunction' AND p.propertyValue = 'meeting'

Access nested fields by dotting . into a variable. A comma , is used to unnest (or join) entities with the components inside and then the properties inside those components. AS is used to bind a variable to the unnested variables so that they can be used in the WHERE or SELECT clauses. This query returns all entities that contains a property named roomFunction with value meeting in a component with component type id

To access multiple nested fields of a field such as multiple components in an entity, use the comma notation to do a join.

SELECT e FROM EntityGraph MATCH (e), e.components AS c1, e.components AS c2
  • Return a node:

    SELECT e FROM EntityGraph MATCH (e)
  • Return an edge:

    SELECT r FROM EntityGraph MATCH (e1)-[r]->(e2)
  • Return a scalar value:

    SELECT floor.entityName, room.description, p.propertyValue AS roomfunction FROM EntityGraph MATCH (floor)-[:isLocationOf]-(room), room.components AS c, AS p

    Format the name of the output field by aliasing it using AS. Here, instead of propertyValue as column name in the response, roomfunction is returned.

  • Return aliases:

    SELECT floor.entityName AS floorName, luminaire.entityName as luminaireName FROM EntityGraph MATCH (floor)-[:isLocationOf]-(room)-[:hasPart]- (lightingZone)-[:feed]-(luminaire) WHERE floor.entityName = 'floor_0' AND luminaire.entityName like 'lumin%'

    Using aliases is highly recommended to be explicit, increase readability and avoid any ambiguities in your queries.

  • The supported logical operators are AND, NOT andOR.

  • The supported comparison operators are <, <=, >, =>,=, and !=.

  • Use the IN keyword if you want to specify multiple or conditions on the same field.

  • Filter on an entity, component or property field:

    FROM EntityGraph MATCH (e), e.components AS c, AS p WHERE e.entityName = 'room_0' AND c.componentTypeId = '', AND p.propertyName = 'roomFunction' AND NOT p.propertyValue = 'meeting' OR p.propertyValue = 'office'
  • Filter on property configuration. Here unit is the key in the configuration map and Celsius is the value.

    WHERE p.definition.configuration.unit = 'Celsius'
  • Check if a map property contains a given key and value:

    WHERE p.propertyValue.length = 20.0
  • Check if a map property contains a given key:

    WHERE NOT p.propertyValue.length IS MISSING
  • Check if a list property contains a given value:

    WHERE 10.0 IN p.propertyValue
  • Use the lower() function for case insensitive comparisons. By default, all comparisons are case sensitive.

    WHERE lower(p.propertyValue) = 'meeting'

Useful if you do not know the exact value for a field and can perform full text search on the specified field. % represents zero or more.

WHERE e.entityName LIKE '%room%'
  • Infix search: %room%

  • Prefix search: room%

  • Suffix search: %room

  • If you have % in your values, then put an escape character in LIKE and specify the character in ESCAPE.

WHERE e.entityName LIKE 'room\%' ESCAPE '\'
SELECT DISTINCT c.componentTypeId FROM EntityGraph MATCH (e), e.components AS c
  • The DISTINCT keyword eliminates duplicates from the final result.

  • DISTINCT is not supported on complex data types.

SELECT e.entityName FROM EntityGraph MATCH (e) WHERE e.entityName LIKE 'room_%' LIMIT 10 OFFSET 5

LIMIT specifies the number of results to be returned in the query, and OFFSET specifies the number of results to skip.

Listed below are the AWS IoT TwinMaker knowledge graph query limits:

Limit Name Quota Adjustable

Query execution timeout

10 seconds No

Maximum number of hops

10 Yes

Maximum number of self JOINs

20 Yes

Maximum number of projected fields

20 Yes

Maximum number of conditional expressions (AND, OR, NOT)

10 Yes

Maximum length of a LIKE expression pattern (including wildcards and escapes)

20 Yes
Maximum number of items that can be specified in an IN clause 10 Yes
Maximum value for OFFSET 3000 Yes

Maximum value for LIMIT

3000 Yes

Maximum value for traversals (OFFSET + LIMIT)

3000 Yes