How to query nested array with Cosmos DB - azure-cosmosdb

Given the following JSON
{
"Families": [
{ "Name": "Smith",
"Children": [
{ "Name": "Bob",
"Pets": [
{ "Name": "Oscar", "Type": "Cat"},
{ "Name": "Otto", "Type": "Dog"}
]
},
{ "Name": "Brittney",
"Pets": [
{ "Name": "Isolde", "Type": "Dog"},
{ "Name": "Ignatz", "Type": "Turtle"}
]
}
]
},
{ "Name": "Miller",
"Children": [
{ "Name": "Alex",
"Pets": [
{ "Name": "Elvis", "Type": "Horse"}
]
}
]
}
]
}
A) I'd like to create a query that yields the following structure
[
{ "FamilyName": "Smith",
"KidName": "Bob",
"Petname": "Oscar"
},
{ "FamilyName": "Smith",
"KidName": "Bob",
"Petname": "Otto"
},
{ "FamilyName": "Smith",
"KidName": "Brittney",
"Petname": "Isolde"
},
{ "FamilyName": "Smith",
"KidName": "Brittney",
"Petname": "Ignatz"
},
{ "FamilyName": "Miller",
"KidName": "Alex",
"Petname": "Elvis"
}
]
B) I'd like to create a query that yields this slightly different structure
[
{ "FamilyName": "Smith",
"KidName": "Bob",
"Petnames": ["Oscar", Otto"]
},
{ "FamilyName": "Smith",
"KidName": "Brittney",
"Petname": ["Isolde", "Ignatz"]
},
{ "FamilyName": "Miller",
"KidName": "Alex",
"Petname": ["Elvis"]
}
]
Your help is greatly appreciated
Robert

There is actually a really good doc for this here: https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-join and here: https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-object-array#arrays
For arrays, you want to utilize nested joins, like so:
Given:
{
"id": "so-test",
"Families": [
{
"Name": "Smith",
"Children": [
{
"Name": "Bob",
"Pets": [
{
"Name": "Oscar",
"Type": "Cat"
},
{
"Name": "Otto",
"Type": "Dog"
}
]
},
{
"Name": "Brittney",
"Pets": [
{
"Name": "Isolde",
"Type": "Dog"
},
{
"Name": "Ignatz",
"Type": "Turtle"
}
]
}
]
},
{
"Name": "Miller",
"Children": [
{
"Name": "Alex",
"Pets": [
{
"Name": "Elvis",
"Type": "Horse"
}
]
}
]
}
]
}
You can use this query for A:
SELECT
f.Name as FamilyName,
c.Name as KidName,
p.Name as Petname
FROM d
JOIN f IN d.Families
JOIN c IN f.Children
JOIN p IN c.Pets
WHERE d.id = "so-test"
and you'll get this result:
[
{
"FamilyName": "Smith",
"KidName": "Bob",
"Petname": "Oscar"
},
{
"FamilyName": "Smith",
"KidName": "Bob",
"Petname": "Otto"
},
{
"FamilyName": "Smith",
"KidName": "Brittney",
"Petname": "Isolde"
},
{
"FamilyName": "Smith",
"KidName": "Brittney",
"Petname": "Ignatz"
},
{
"FamilyName": "Miller",
"KidName": "Alex",
"Petname": "Elvis"
}
]
For B), use this query which adds the ARRAY method
SELECT
f.Name as FamilyName,
c.Name as KidName,
ARRAY(SELECT DISTINCT VALUE p.Name from p IN c.Pets) as Petname
FROM d
JOIN f IN d.Families
JOIN c IN f.Children
WHERE d.id = "so-test"
you'll get these results:
[
{
"FamilyName": "Smith",
"KidName": "Bob",
"Petname": [
"Oscar",
"Otto"
]
},
{
"FamilyName": "Smith",
"KidName": "Brittney",
"Petname": [
"Isolde",
"Ignatz"
]
},
{
"FamilyName": "Miller",
"KidName": "Alex",
"Petname": [
"Elvis"
]
}
]

Related

Here Waypoint Sequencing API Doesn't Honor Delivery Windows

I am experimenting with the HERE Waypoint Sequencing API using the new JSON request format, and it doesn't seem to take into account delivery windows specified in the times array within the plan object. I went back to the example provided in the documentation and found that the same thing was happening: Arrival and departure times are far from the specified delivery windows.
In my Example, Customer 1 has times:
"times": [["2020-07-04T08:00:00Z","2020-07-04T10:00:00Z"],["2020-07-04T16:00:00Z","2020-07-04T18:00:00Z"]]
However, the solution contains:
"time": {
"arrival": "2020-07-04T00:30:00.000+0000",
"departure": "2020-07-04T00:33:00.000+0000"
}
Which isn't even close.
Endpoint: https://wps.hereapi.com/v8/findsequence
Request:
{
"configuration": {
"optimizations": {
"traffic": "liveOrHistorical",
"waitingTime": {
"bufferTime": 15,
"reduce": false
}
}
},
"fleet": {
"profiles": [{"type":"car","name":"normal_car"}],
"types": [
{
"amount": 1,
"capacity": [10,5],
"costs": {
"distance": 0.0001,
"fixed": 22,
"time": 0.0048
},
"id": "string",
"limits": {
"maxDistance": 20000,
"shiftTime": 21600
},
"profile": "normal_car",
"shifts": [
{
"breaks": [
{
"duration": 180,
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"times": [["2020-07-04T08:00:00Z","2020-07-04T10:00:00Z"],["2020-07-04T16:00:00Z","2020-07-04T18:00:00Z"]]
}
],
"end": {
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"time": "2020-07-04T23:30:00Z"
},
"start": {
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"time": "2020-07-04T00:30:00Z"
}
}
],
"skills": ["fridge"]
}
]
},
"id": "7f3423c2-784a-4983-b472-e14107d5a54a",
"plan": {
"jobs": [
{
"id": "string",
"places": {
"deliveries": [
{
"demand": [10,5],
"duration": 180,
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"tag": "Customer 1",
"times": [["2020-07-04T08:00:00Z","2020-07-04T10:00:00Z"],["2020-07-04T16:00:00Z","2020-07-04T18:00:00Z"]]
},
{
"demand": [10,5],
"duration": 180,
"location": {
"lat": 53.53088,
"lng": 14.98471
},
"tag": "Customer 2",
"times": [["2020-07-04T08:00:00Z","2020-07-04T10:00:00Z"],["2020-07-04T16:00:00Z","2020-07-04T18:00:00Z"]]
}
],
"pickups": [
{
"demand": [10,5],
"duration": 180,
"location": {
"lat": 52.53088,
"lng": 13.98471
},
"tag": "some_tag",
"times": [["2020-07-04T08:00:00Z","2020-07-04T10:00:00Z"],["2020-07-04T16:00:00Z","2020-07-04T18:00:00Z"]]
}
]
},
"skills": ["fridge"]
}
],
"relations": [
{
"jobs": [
"string"
],
"type": "flexible",
"vehicleId": "7f3423c2-784a-4983-b472-e14107d5a54a"
}
]
}
}
Response:
{
"problemId": "7f3423c2-784a-4983-b472-e14107d5a54a",
"statistic": {
"cost": null,
"distance": 441655,
"duration": 20127,
"times": {
"break": 0,
"driving": 19587,
"serving": 540,
"waiting": 0
}
},
"tours": [
{
"vehicleId": "string",
"typeId": null,
"stops": [
{
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"time": {
"arrival": null,
"departure": "2020-07-04T00:30:00.000+0000"
},
"load": [
],
"activities": [
{
"jobId": "departure",
"jobTag": "departure",
"type": null,
"location": null,
"time": null
}
]
},
{
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"time": {
"arrival": "2020-07-04T00:30:00.000+0000",
"departure": "2020-07-04T00:33:00.000+0000"
},
"load": [
],
"activities": [
{
"jobId": "Customer 1",
"jobTag": "Customer 1",
"type": null,
"location": null,
"time": null
}
]
},
{
"location": {
"lat": 52.53088,
"lng": 13.98471
},
"time": {
"arrival": "2020-07-04T01:34:05.000+0000",
"departure": "2020-07-04T01:37:05.000+0000"
},
"load": [
],
"activities": [
{
"jobId": "some_tag",
"jobTag": "some_tag",
"type": null,
"location": null,
"time": null
}
]
},
{
"location": {
"lat": 53.53088,
"lng": 14.98471
},
"time": {
"arrival": "2020-07-04T03:53:37.000+0000",
"departure": "2020-07-04T03:56:37.000+0000"
},
"load": [
],
"activities": [
{
"jobId": "Customer 2",
"jobTag": "Customer 2",
"type": null,
"location": null,
"time": null
}
]
},
{
"location": {
"lat": 52.53088,
"lng": 13.38471
},
"time": {
"arrival": "2020-07-04T06:05:27.000+0000",
"departure": null
},
"load": [
],
"activities": [
{
"jobId": "arrival",
"jobTag": "arrival",
"type": null,
"location": null,
"time": null
}
]
}
],
"statistic": {
"cost": null,
"distance": 441655,
"duration": 20127,
"times": {
"break": 0,
"driving": 19587,
"serving": 540,
"waiting": 0
}
}
}
],
"unassigned": null
}
Am I missing something?

Address in autocomplete results

When I do an autosuggest request in the address response I only receive the label. The address object is not filled.
This is my request: https://autosuggest.search.hereapi.com/v1/autosuggest?at=48.8578817,2.2791249999999934&limit=5&q=stj&apikey=xxxx
I receive this:
"title": "Top Services (Stj)",
"id": "here:pds:place:250u09wj-afceace0a11b49bca950ea22d0f8e452",
"resultType": "place",
"address": {
"label": "********"
},
I will need to receive the formatted address without the name
How can I fix this?
thanks
We have tried to reproduce your query and it works for us, please see the following code.
Please review the documentation page for detailed information on autosuggest
Documentation link :
https://autosuggest.search.hereapi.com/v1/autosuggest?at=48.8578817,2.2791249999999934&limit=5&q=stj&apikey=XXXX.
Query Result:
{
"items": [
{
"title": "Top Services (Stj)",
"id": "here:pds:place:250u09wj-afceace0a11b49bca950ea22d0f8e452",
"resultType": "place",
"address": {
"label": "Top Services, 61 Rue du Faubourg Saint-Denis, 75010 Paris, France"
},
"position": {
"lat": 48.8721,
"lng": 2.35384
},
"access": [
{
"lat": 48.87208,
"lng": 2.35392
}
],
"distance": 5690,
"categories": [
{
"id": "700-7200-0254",
"name": "Construction",
"primary": true
},
{
"id": "700-7200-0264",
"name": "Services de conseil et de gestion"
},
{
"id": "700-7200-0277",
"name": "Entrepreneur de second œuvre"
}
],
"highlights": {
"title": [
{
"start": 14,
"end": 17
}
],
"address": {
"label": [
]
}
}
},
{
"title": "La Clinique du Scooter d'Occasion (Stj 2 Roues)",
"id": "here:pds:place:250u09tv-591de1b090c54199b11154a72f462c0d",
"resultType": "place",
"address": {
"label": "La Clinique du Scooter d'Occasion, 148 Boulevard du Montparnasse, 75014 Paris, France"
},
"position": {
"lat": 48.84039,
"lng": 2.33383
},
"access": [
{
"lat": 48.84052,
"lng": 2.33393
}
],
"distance": 4451,
"categories": [
{
"id": "400-4200-0241",
"name": "Services logistiques",
"primary": true
}
],
"highlights": {
"title": [
{
"start": 35,
"end": 38
}
],
"address": {
"label": [
]
}
}
},
{
"title": "Stjohn's",
"id": "here:pds:place:2501r4ve-43f913ba8f9b0e7046aaee61bcfe8b9b",
"resultType": "place",
"address": {
"label": "Stjohn's, 11 Rue Edmond Valentin, 75007 Paris, France"
},
"position": {
"lat": 48.85961,
"lng": 2.30159
},
"access": [
{
"lat": 48.85968,
"lng": 2.30157
}
],
"distance": 1655,
"categories": [
{
"id": "700-7400-0141",
"name": "Services aux entreprises",
"primary": true
},
{
"id": "700-7200-0252",
"name": "Publicité, marketing, communication et études de marché"
}
],
"highlights": {
"title": [
{
"start": 0,
"end": 3
}
],
"address": {
"label": [
{
"start": 0,
"end": 3
}
]
}
}
},
{
"title": "Stjohn S",
"id": "here:pds:place:250u09tv-0f38e06dd8634ab4a0d931dad94de24c",
"resultType": "place",
"address": {
"label": "Stjohn S, 4 Rue des Petits-Pères, 75002 Paris, France"
},
"position": {
"lat": 48.86601,
"lng": 2.34027
},
"access": [
{
"lat": 48.8662,
"lng": 2.34023
}
],
"distance": 4564,
"categories": [
{
"id": "700-7200-0252",
"name": "Publicité, marketing, communication et études de marché",
"primary": true
},
{
"id": "700-7200-0271",
"name": "Services financiers et d'assurance"
}
],
"highlights": {
"title": [
{
"start": 0,
"end": 3
}
],
"address": {
"label": [
{
"start": 0,
"end": 3
}
]
}
}
},
{
"title": "Espace St-Jo'",
"id": "here:pds:place:250u09te-220742c64e4a40a48b8772987e7f987c",
"resultType": "place",
"address": {
"label": "Espace St-Jo', 54 Rue du Moulin de Pierres, 92140 Clamart, France"
},
"position": {
"lat": 48.80865,
"lng": 2.26594
},
"access": [
{
"lat": 48.8087,
"lng": 2.2659
}
],
"distance": 5558,
"categories": [
{
"id": "200-2200-0000",
"name": "Théâtre, musique et culture",
"primary": true
},
{
"id": "200-2000-0015",
"name": "Salle de spectacle/concert"
},
{
"id": "550-5520-0000",
"name": "Aire de loisirs"
}
],
"references": [
{
"supplier": {
"id": "yelp"
},
"id": "xJtl5krT8OZ3QYXtMl6Leg"
}
],
"highlights": {
"title": [
{
"start": 7,
"end": 12
}
],
"address": {
"label": [
{
"start": 7,
"end": 12
}
]
}
}
}
],
"queryTerms": [
]
}

Optimize this query to get lineage diagram in graph using gremlin

I have my data set up in cosmos DB gremlin API. I am trying to write a query that can starting at a given vertex, gives all the edges with labels and properties in both directions, and the vertices with their properties, with a loop count of lets say 2. I am running the following queries.
Data to be setup
g.addV('item').property('id','1').property('name', 'item1')
g.addV('item').property('id','2').property('name', 'item2')
g.addV('item').property('id','3').property('name', 'item3')
g.addV('item').property('id','4').property('name', 'item4')
g.addV('item').property('id','5').property('name', 'item5')
g.addV('item').property('id','6').property('name', 'item6')
g.addV('item').property('id','7').property('name', 'item7')
g.addV('report').property('id','8').property('name', 'report1')
g.addV('report').property('id','9').property('name', 'report2')
g.addV('folder').property('id','10').property('name', 'folder1')
g.addV('server').property('id','11').property('name', 'server1')
g.V('1').addE('hasParent').to(g.V('2'))
g.V('1').addE('hasParent').to(g.V('3'))
g.V('2').addE('hasParent').to(g.V('4'))
g.V('5').addE('hasParent').to(g.V('6'))
g.V('4').addE('hasParent').to(g.V('5'))
g.V('7').addE('hasParent').to(g.V('5'))
g.V('8').addE('hasParent').to(g.V('9'))
g.V('8').addE('hasParent').to(g.V('9'))
g.V('8').addE('belongsTo').to(g.V('10'))
g.V('10').addE('belongsTo').to(g.V('11'))
query: g.V('id','1').repeat(bothE().dedup().otherV()).times(2).path()
response:
[
{
"labels": [
[],
[],
[],
[],
[]
],
"objects": [
{
"id": "1",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "1|name",
"value": "item1"
}
]
}
},
{
"id": "a6b02073-68f8-4d53-8af0-54739eaaeaa0",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "2",
"outV": "1"
},
{
"id": "2",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "2|name",
"value": "item2"
}
]
}
},
{
"id": "c8722748-3899-4a2c-afe4-6f13b6c1f8d5",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "4",
"outV": "2"
},
{
"id": "4",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "4|name",
"value": "item4"
}
]
}
}
]
},
{
"labels": [
[],
[],
[],
[],
[]
],
"objects": [
{
"id": "1",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "1|name",
"value": "item1"
}
]
}
},
{
"id": "a6b02073-68f8-4d53-8af0-54739eaaeaa0",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "2",
"outV": "1"
},
{
"id": "2",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "2|name",
"value": "item2"
}
]
}
},
{
"id": "a6b02073-68f8-4d53-8af0-54739eaaeaa0",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "2",
"outV": "1"
},
{
"id": "1",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "1|name",
"value": "item1"
}
]
}
}
]
},
{
"labels": [
[],
[],
[],
[],
[]
],
"objects": [
{
"id": "1",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "1|name",
"value": "item1"
}
]
}
},
{
"id": "2f0c5890-3fa5-4d7d-8ada-910e5419750f",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "3",
"outV": "1"
},
{
"id": "3",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "3|name",
"value": "item3"
}
]
}
},
{
"id": "2f0c5890-3fa5-4d7d-8ada-910e5419750f",
"label": "hasParent",
"type": "edge",
"inVLabel": "item",
"outVLabel": "item",
"inV": "3",
"outV": "1"
},
{
"id": "1",
"label": "item",
"type": "vertex",
"properties": {
"name": [
{
"id": "1|name",
"value": "item1"
}
]
}
}
]
}
]
This is giving me the desired output, but has a lot of repetitions, i am guessing because it prints the path as it traverses. How can I modify this query to return the smallest possible json output? Just return the vertices and edges once. I am using cosmosDB gremlin APIs if that makes any difference.
Response needed: just a list of vertices and edges needed for painting this graph.
Your example as-is doesn't produce the same output that I see in your question - I get just one path:
gremlin> g.V('id','1').repeat(bothE().dedup().otherV()).times(2).path()
==>[v[1],e[11][1-hasParent->2],v[2],e[13][2-hasParent->4],v[4]]
I'm not sure if that's some mistake in your data script but I think I get the gist of what you are asking from your output. I can recreate a situation of duplication by doing an emit() on the repeat() to include all paths in the output:
gremlin> g.V('id','1').repeat(bothE().dedup().otherV()).emit().times(2).path()
==>[v[1],e[11][1-hasParent->2],v[2]]
==>[v[1],e[12][1-hasParent->3],v[3]]
==>[v[1],e[11][1-hasParent->2],v[2],e[13][2-hasParent->4],v[4]]
Now I have some duplication of vertices/edges in the resulting output. If you just want a unique list of all those objects, just unfold() each Path and dedup():
gremlin> g.V('id','1').repeat(bothE().dedup().otherV()).emit().times(2).path().unfold().dedup()
==>v[1]
==>e[11][1-hasParent->2]
==>v[2]
==>e[12][1-hasParent->3]
==>v[3]
==>e[13][2-hasParent->4]
==>v[4]
This is a bit of an interesting pattern in a sense because it provides an easy way to produce a subgraph for Gremlin Language Variants and graph systems that don't support subgraph() step.

Why is averageRating always 0?

I am using the 'Explore Popular Places by Category' API and it always returns averageRating as 0 for all items in the result.
I made this call with various categories such as restaurants and sights-museums, but it always returns 0 for averageRating. Does HERE not provide this detail, and if so, why is it returned in the response?
Some details:
I am making a call to this url:
https://places.ls.hereapi.com/places/v1/discover/explore?at=52.5159%2C13.3777&cat=sights-museums&apiKey={api_key}
and it returns something like this:
{
"results": {
"next": "https://places.ls.hereapi.com/places/v1/discover/explore;context=Y2F0PXNpZ2h0cy1tdXNldW1zJmZsb3ctaWQ9Mjk0ZjU1NTgtMmY0Mi01Y2FiLWJlYWUtOGEyM2ViY2EzMzgzXzE1ODMyNjMyNjEwMzZfMF84NTcyJm9mZnNldD0yMCZzaXplPTIw?at=52.5159%2C13.3777&app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"items": [
{
"position": [
52.51629,
13.37817
],
"distance": 54,
"title": "Brandenburg Gate",
"averageRating": 0,
"category": {
"id": "landmark-attraction",
"title": "Landmark/Attraction",
"href": "https://places.ls.hereapi.com/places/v1/categories/places/landmark-attraction?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"type": "urn:nlp-types:category",
"system": "places"
},
"icon": "https://download.vcdn.data.here.com/p/d/places2/icons/categories/38.icon",
"vicinity": "Pariser Platz<br/>Mitte, 10117 Berlin",
"having": [],
"type": "urn:nlp-types:place",
"href": "https://places.ls.hereapi.com/places/v1/places/276u33db-8ee2e0de906e459cbade0593986debe9;context=Zmxvdy1pZD0yOTRmNTU1OC0yZjQyLTVjYWItYmVhZS04YTIzZWJjYTMzODNfMTU4MzI2MzI2MTAzNl8wXzg1NzImcmFuaz0w?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"id": "276u33db-8ee2e0de906e459cbade0593986debe9",
"alternativeNames": [
{
"name": "Brandenburger Tor",
"language": "de"
}
]
},
{
"position": [
52.51373,
13.37976
],
"distance": 279,
"title": "Holocaust Memorial",
"averageRating": 0,
"category": {
"id": "museum",
"title": "Museum",
"href": "https://places.ls.hereapi.com/places/v1/categories/places/museum?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"type": "urn:nlp-types:category",
"system": "places"
},
"icon": "https://download.vcdn.data.here.com/p/d/places2/icons/categories/10.icon",
"vicinity": "Cora-Berliner-Straße 1<br/>Mitte, 10117 Berlin",
"having": [],
"type": "urn:nlp-types:place",
"href": "https://places.ls.hereapi.com/places/v1/places/276u33de-df7d57fd38494a93b2018fe549a0fd75;context=Zmxvdy1pZD0yOTRmNTU1OC0yZjQyLTVjYWItYmVhZS04YTIzZWJjYTMzODNfMTU4MzI2MzI2MTAzNl8wXzg1NzImcmFuaz0x?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"id": "276u33de-df7d57fd38494a93b2018fe549a0fd75",
"openingHours": {
"text": "Tue-Sun: 10:00 - 20:00",
"label": "Opening hours",
"isOpen": false,
"structured": [
{
"start": "T100000",
"duration": "PT10H00M",
"recurrence": "FREQ:DAILY;BYDAY:TU,WE,TH,FR,SA,SU"
}
]
},
"alternativeNames": [
{
"name": "Memorial to the Murdered European Jews",
"language": "en"
},
{
"name": "Memorial to the Murdered Jews of Europe",
"language": "en"
},
{
"name": "Denkmal für die ermordeten Juden Europas",
"language": "de"
}
]
},
{
"position": [
52.51666,
13.40784
],
"distance": 2041,
"title": "Nicholas Quarter",
"averageRating": 0,
"category": {
"id": "museum",
"title": "Museum",
"href": "https://places.ls.hereapi.com/places/v1/categories/places/museum?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"type": "urn:nlp-types:category",
"system": "places"
},
"icon": "https://download.vcdn.data.here.com/p/d/places2/icons/categories/10.icon",
"vicinity": "Nikolaikirchplatz<br/>Mitte, 10178 Berlin",
"having": [],
"type": "urn:nlp-types:place",
"href": "https://places.ls.hereapi.com/places/v1/places/276u33dc-049683d3c6be4bdba823808678a1b164;context=Zmxvdy1pZD0yOTRmNTU1OC0yZjQyLTVjYWItYmVhZS04YTIzZWJjYTMzODNfMTU4MzI2MzI2MTAzNl8wXzg1NzImcmFuaz0xOQ?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q",
"id": "276u33dc-049683d3c6be4bdba823808678a1b164",
"alternativeNames": [
{
"name": "Nikolaiviertel",
"language": "en"
},
{
"name": "Nikolaiviertel",
"language": "de"
}
]
}
]
},
"search": {
"context": {
"location": {
"position": [
52.5159,
13.3777
],
"address": {
"text": "Ebertstraße 22<br/>Mitte, 10117 Berlin<br/>Germany",
"house": "22",
"street": "Ebertstraße",
"postalCode": "10117",
"district": "Mitte",
"city": "Berlin",
"county": "Berlin",
"stateCode": "Berlin",
"country": "Germany",
"countryCode": "DEU"
}
},
"type": "urn:nlp-types:place",
"href": "https://places.ls.hereapi.com/places/v1/places/loc-dmVyc2lvbj0xO3RpdGxlPUViZXJ0c3RyYSVDMyU5RmUrMjI7bGF0PTUyLjUxNTk7bG9uPTEzLjM3Nzc7c3RyZWV0PUViZXJ0c3RyYSVDMyU5RmU7aG91c2U9MjI7Y2l0eT1CZXJsaW47cG9zdGFsQ29kZT0xMDExNztjb3VudHJ5PURFVTtkaXN0cmljdD1NaXR0ZTtzdGF0ZUNvZGU9QmVybGluO2NvdW50eT1CZXJsaW47Y2F0ZWdvcnlJZD1idWlsZGluZztzb3VyY2VTeXN0ZW09aW50ZXJuYWw;context=c2VhcmNoQ29udGV4dD0x?app_id=LKO34glU2MBEVbcOD5mQ&app_code=A2ta_nQ8HRYwenju5HFG5Q"
}
}
}
Does HERE not provide the averageRatings of restaurants or sights-museums?
From the docs it appears if the place hasn't received a rating it'll be 0
Note: If the place has no ratings (yet), both the average and the count values are zero. But if the place cannot be rated (i.e. a street), the whole rating object is not present.
https://developer.here.com/documentation/places/dev_guide/topics/object-rating.html

Get the complete graph information (properties,id etc ) in hierarchical way under a particular node in gremlin

I am able to get all the child nodes and its related information under a parent node but in a array of objects format , for the query
g.V(4128).repeat(out()).emit()
[
{
"id": 4152.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "1l3-37c-1l1",
"value": "XYZ"
}
],
"description": [
{
"id": "1zb-37c-7wl",
"value": "XYZ World"
}
],
"shortName": [
{
"id": "16v-37c-745",
"value": "XYZ"
}
]
}
},
{
"id": 4176.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "1l6-380-1l1",
"value": "XYZ-XYZW"
}
],
"description": [
{
"id": "1ze-380-7wl",
"value": "XYZ West Campus"
}
],
"shortName": [
{
"id": "16y-380-745",
"value": "XYZW"
}
]
}
},
{
"id": 8344.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "3kj-6fs-1l1",
"value": "XYZ-XYZE"
}
],
"description": [
{
"id": "3yr-6fs-7wl",
"value": "XYZ East Campus"
}
],
"shortName": [
{
"id": "36b-6fs-745",
"value": "XYZE"
}
]
}
},
{
"id": 4104.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "1kx-360-1l1",
"value": "XYZ-XYZW-P1"
}
],
"description": [
{
"id": "1z5-360-7wl",
"value": "XYZ West Campus-Phase-1"
}
],
"shortName": [
{
"id": "16p-360-745",
"value": "P1"
}
]
}
},
{
"id": 4296.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "1ll-3bc-1l1",
"value": "XYZ-XYZW-P3"
}
],
"description": [
{
"id": "1zt-3bc-7wl",
"value": "XYZ West Campus-Phase-3"
}
],
"shortName": [
{
"id": "17d-3bc-745",
"value": "P3"
}
]
}
},
{
"id": 8200.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "3k1-6bs-1l1",
"value": "XYZ-XYZW-P2"
}
],
"description": [
{
"id": "3y9-6bs-7wl",
"value": "XYZ West Campus-Phase-2"
}
],
"shortName": [
{
"id": "35t-6bs-745",
"value": "P2"
}
]
}
},
{
"id": 8224.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "3yc-6cg-1l1",
"value": "XYZ-XYZE-P1"
}
],
"description": [
{
"id": "4ck-6cg-7wl",
"value": "XYZ East Campus-Phase-1"
}
],
"shortName": [
{
"id": "3k4-6cg-745",
"value": "P1"
}
]
}
},
{
"id": 8392.0,
"label": "location",
"type": "vertex",
"properties": {
"displayName": [
{
"id": "3kp-6h4-1l1",
"value": "XYZ-XYZE-P2"
}
],
"description": [
{
"id": "3yx-6h4-7wl",
"value": "XYZ East Campus-Phase-2"
}
],
"shortName": [
{
"id": "36h-6h4-745",
"value": "P2"
}
]
}
}
]
I need to get the same information in hierarchial way .
I tried the following query
g.V(4128).repeat(out()).emit().tree().by(__.valueMap(true))
but I don't get the valid json.
I need to get the above data but in hierarchical way
Updated
I tried the following query
g.V(4128).repeat(out()).emit().tree().by(__.valueMap(true))
And the response I received was
[
{
"{label = org, name = [XYZ], orgId = [00000000-0000-0000-0000-000000000001], desc = [XYZ Organization], id = 4128}": {
"{label = location, displayName = [hh], description = [hfds], shortName = [kk], id = 8272}": {
},
"{label = location, displayName = [XYZ], description = [XYZ World], shortName = [XYZ], id = 4152}": {
"{label = location, displayName = [XYZ-XYZW], description = [XYZ West Campus], shortName = [XYZW], id = 4176}": {
"{label = location, displayName = [XYZ-XYZW-P3], description = [XYZ West Campus-Phase-3], shortName = [P3], id = 4296}": {
},
"{label = location, displayName = [XYZ-XYZW-P2], description = [XYZ West Campus-Phase-2], shortName = [P2], id = 8200}": {
},
"{label = location, displayName = [XYZ-XYZW-P1], description = [XYZ West Campus-Phase-1], shortName = [P1], id = 4104}": {
}
},
"{label = location, displayName = [XYZ-XYZE], description = [XYZ East Campus], shortName = [XYZE], id = 8344}": {
"{label = location, displayName = [XYZ-XYZE-P1], description = [XYZ East Campus-Phase-1], shortName = [P1], id = 8224}": {
},
"{label = location, displayName = [XYZ-XYZE-P2], description = [XYZ East Campus-Phase-2], shortName = [P2], id = 8392}": {
}
}
},
"{label = location, displayName = [hh], description = [hfds], shortName = [kk], id = 8248}": {
},
"{label = location, displayName = [hh], description = [hfds], shortName = [kk], id = 12488}": {
}
}
}
]
Now as you can see the json so received is not appropriate because the key contains fields that are '=' separated .
Now as for the answer I also tried the folowing query
g.V(4128).repeat(out()).emit().tree().next()
but the response returned only ids and didnt resolve the vertex properties
[
{
"4128": {
"8272": {},
"4152": {
"4176": {
"4104": {},
"4296": {},
"8200": {}
},
"8344": {
"8224": {},
"8392": {}
}
},
"8248": {},
"12488": {}
}
}
]
For the context I am using the following configurations in my gremlin-server.yaml file
authentication: {className: org.apache.tinkerpop.gremlin.server.auth.AllowAllAuthenticator,
config: null}
channelizer: org.apache.tinkerpop.gremlin.server.channel.HttpChannelizer
graphs: {graph: 'D:/graph-data-access/src/test/resources/titan-inmemory.properties'}
gremlinPool: 8
host: localhost
maxAccumulationBufferComponents: 1024
maxChunkSize: 8192
maxContentLength: 65536
maxHeaderSize: 8192
maxInitialLineLength: 4096
metrics:
consoleReporter: null
csvReporter: null
gangliaReporter: null
graphiteReporter: null
jmxReporter: null
slf4jReporter: {enabled: true, interval: 180000, loggerName: org.apache.tinkerpop.gremlin.server.Settings$Slf4jReporterMetrics}
plugins: [aurelius.titan, tinkerpop.gephi]
port: 8182
processors: []
resultIterationBatchSize: 64
scriptEngines:
gremlin-groovy:
config: null
imports: [java.lang.Math]
scripts: ['D:/graph-data-access/src/test/resources/generate-locations.groovy']
staticImports: [java.lang.Math.PI]
scriptEvaluationTimeout: 30000
serializedResponseTimeout: 30000
serializers:
- className: org.apache.tinkerpop.gremlin.driver.ser.GryoMessageSerializerV1d0
config: {useMapperFromGraph: graph}
- className: org.apache.tinkerpop.gremlin.driver.ser.GryoMessageSerializerV1d0
config: {serializeResultToString: true}
- className: org.apache.tinkerpop.gremlin.driver.ser.GraphSONMessageSerializerV1d0
config: {useMapperFromGraph: graph}
- className: org.apache.tinkerpop.gremlin.driver.ser.GraphSONMessageSerializerGremlinV1d0
config: {useMapperFromGraph: graph}
ssl: {enabled: false, keyCertChainFile: null, keyFile: null, keyPassword: null, trustCertChainFile: null}
threadPoolBoss: 1
threadPoolWorker: 1
writeBufferHighWaterMark: 65536
writeBufferLowWaterMark: 32768
I am using Tinkerpop version 3.0.1 incubating as I am trying to use Titan 1.0.0 with DynamoDb as storage backend for the remote connection.
Not sure what you mean by "but i don't get valid json". You should be able to serialized a Tree in GraphSON 1.0 if you don't include by(valueMap(true)) and just serialize the full vertex. There is a failure if you try to do it as just maps as it makes some assumptions about there being a graph Element as the key (which is probably bad).
gremlin> mapper = graph.io(graphson()).mapper().version(GraphSONVersion.V1_0).create().createMapper()
==>org.apache.tinkerpop.shaded.jackson.databind.ObjectMapper#6b2e0f78
gremlin> mapper.writeValueAsString(g.V(1).repeat(out()).emit().tree().next())
==>{"1":{"key":{"id":1,"label":"vertex","type":"vertex","properties":{"name":[{"id":0,"value":"marko"}],"age":[{"id":2,"value":29}]}},"value":{"2":{"key":{"id":2,"label":"vertex","type":"vertex","properties":{"name":[{"id":3,"value":"vadas"}],"age":[{"id":4,"value":27}]}},"value":{}},"3":{"key":{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},"value":{}},"4":{"key":{"id":4,"label":"vertex","type":"vertex","properties":{"name":[{"id":7,"value":"josh"}],"age":[{"id":8,"value":32}]}},"value":{"3":{"key":{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},"value":{}},"5":{"key":{"id":5,"label":"vertex","type":"vertex","properties":{"name":[{"id":9,"value":"ripple"}],"lang":[{"id":10,"value":"java"}]}},"value":{}}}}}}}
That formats to:
{
"1": {
"key": {
"id": 1,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 0,
"value": "marko"
}],
"age": [{
"id": 2,
"value": 29
}]
}
},
"value": {
"2": {
"key": {
"id": 2,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 3,
"value": "vadas"
}],
"age": [{
"id": 4,
"value": 27
}]
}
},
"value": {}
},
"3": {
"key": {
"id": 3,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 5,
"value": "lop"
}],
"lang": [{
"id": 6,
"value": "java"
}]
}
},
"value": {}
},
"4": {
"key": {
"id": 4,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 7,
"value": "josh"
}],
"age": [{
"id": 8,
"value": 32
}]
}
},
"value": {
"3": {
"key": {
"id": 3,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 5,
"value": "lop"
}],
"lang": [{
"id": 6,
"value": "java"
}]
}
},
"value": {}
},
"5": {
"key": {
"id": 5,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 9,
"value": "ripple"
}],
"lang": [{
"id": 10,
"value": "java"
}]
}
},
"value": {}
}
}
}
}
}
}
In GraphSON 2.0 you get this:
gremlin> mapper = graph.io(graphson()).mapper().version(GraphSONVersion.V2_0).create().createMapper()
==>org.apache.tinkerpop.shaded.jackson.databind.ObjectMapper#3ffb3598
gremlin> mapper.writeValueAsString(g.V(1).repeat(out()).emit().tree().next())
==>{"#type":"g:Tree","#value":[{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":1},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":0},"value":"marko","label":"name"}}],"age":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":2},"value":{"#type":"g:Int32","#value":29},"label":"age"}}]}}},"value":{"#type":"g:Tree","#value":[{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":2},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":3},"value":"vadas","label":"name"}}],"age":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":4},"value":{"#type":"g:Int32","#value":27},"label":"age"}}]}}},"value":{"#type":"g:Tree","#value":[]}},{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":3},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":5},"value":"lop","label":"name"}}],"lang":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":6},"value":"java","label":"lang"}}]}}},"value":{"#type":"g:Tree","#value":[]}},{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":4},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":7},"value":"josh","label":"name"}}],"age":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":8},"value":{"#type":"g:Int32","#value":32},"label":"age"}}]}}},"value":{"#type":"g:Tree","#value":[{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":3},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":5},"value":"lop","label":"name"}}],"lang":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":6},"value":"java","label":"lang"}}]}}},"value":{"#type":"g:Tree","#value":[]}},{"key":{"#type":"g:Vertex","#value":{"id":{"#type":"g:Int32","#value":5},"label":"vertex","properties":{"name":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":9},"value":"ripple","label":"name"}}],"lang":[{"#type":"g:VertexProperty","#value":{"id":{"#type":"g:Int32","#value":10},"value":"java","label":"lang"}}]}}},"value":{"#type":"g:Tree","#value":[]}}]}}]}}]}
which formats as:
{
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["marko"],
"id": {
"#type": "g:Int32",
"#value": 1
},
"age": [{
"#type": "g:Int32",
"#value": 29
}]
},
"value": {
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["lop"],
"id": {
"#type": "g:Int32",
"#value": 3
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["vadas"],
"id": {
"#type": "g:Int32",
"#value": 2
},
"age": [{
"#type": "g:Int32",
"#value": 27
}]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["josh"],
"id": {
"#type": "g:Int32",
"#value": 4
},
"age": [{
"#type": "g:Int32",
"#value": 32
}]
},
"value": {
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["ripple"],
"id": {
"#type": "g:Int32",
"#value": 5
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["lop"],
"id": {
"#type": "g:Int32",
"#value": 3
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}]
}
}]
}
}]
}
Note that you can also use by(valueMap(true)) in the case of GraphSON 2.0:
gremlin> mapper.writeValueAsString(g.V(1).repeat(out()).emit().tree().by(valueMap(true)).next())
==>{"#type":"g:Tree","#value":[{"key":{"label":"vertex","name":["marko"],"id":{"#type":"g:Int32","#value":1},"age":[{"#type":"g:Int32","#value":29}]},"value":{"#type":"g:Tree","#value":[{"key":{"label":"vertex","name":["lop"],"id":{"#type":"g:Int32","#value":3},"lang":["java"]},"value":{"#type":"g:Tree","#value":[]}},{"key":{"label":"vertex","name":["vadas"],"id":{"#type":"g:Int32","#value":2},"age":[{"#type":"g:Int32","#value":27}]},"value":{"#type":"g:Tree","#value":[]}},{"key":{"label":"vertex","name":["josh"],"id":{"#type":"g:Int32","#value":4},"age":[{"#type":"g:Int32","#value":32}]},"value":{"#type":"g:Tree","#value":[{"key":{"label":"vertex","name":["ripple"],"id":{"#type":"g:Int32","#value":5},"lang":["java"]},"value":{"#type":"g:Tree","#value":[]}},{"key":{"label":"vertex","name":["lop"],"id":{"#type":"g:Int32","#value":3},"lang":["java"]},"value":{"#type":"g:Tree","#value":[]}}]}}]}}]}
which formats to:
{
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["marko"],
"id": {
"#type": "g:Int32",
"#value": 1
},
"age": [{
"#type": "g:Int32",
"#value": 29
}]
},
"value": {
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["lop"],
"id": {
"#type": "g:Int32",
"#value": 3
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["vadas"],
"id": {
"#type": "g:Int32",
"#value": 2
},
"age": [{
"#type": "g:Int32",
"#value": 27
}]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["josh"],
"id": {
"#type": "g:Int32",
"#value": 4
},
"age": [{
"#type": "g:Int32",
"#value": 32
}]
},
"value": {
"#type": "g:Tree",
"#value": [{
"key": {
"label": "vertex",
"name": ["ripple"],
"id": {
"#type": "g:Int32",
"#value": 5
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}, {
"key": {
"label": "vertex",
"name": ["lop"],
"id": {
"#type": "g:Int32",
"#value": 3
},
"lang": ["java"]
},
"value": {
"#type": "g:Tree",
"#value": []
}
}]
}
}]
}
}]
}
If you are on older version of TinkerPop going back to 3.0.x, then there are some limitations with tree that aren't easily worked around. The only approach is to take a raw tree and post-process it to get it to a form that is friendly to JSON. Here is one way to do that:
gremlin> convert = { it.collectEntries{ k,v -> [(k.id()): [k, v.isEmpty() ? v : convert(v)]] }}
==>groovysh_evaluate$_run_closure1#255e5e2e
gremlin> t = g.V(1).repeat(out()).emit().tree().next()
==>v[1]={v[2]={}, v[3]={}, v[4]={v[3]={}, v[5]={}}}
gremlin> convert(t)
==>1=[v[1], {2=[v[2], {}], 3=[v[3], {}], 4=[v[4], {3=[v[3], {}], 5=[v[5], {}]}]}]
gremlin> mapper.writeValueAsString(convert(t))
==>{"1":[{"id":1,"label":"vertex","type":"vertex","properties":{"name":[{"id":0,"value":"marko"}],"age":[{"id":2,"value":29}]}},{"2":[{"id":2,"label":"vertex","type":"vertex","properties":{"name":[{"id":3,"value":"vadas"}],"age":[{"id":4,"value":27}]}},{}],"3":[{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},{}],"4":[{"id":4,"label":"vertex","type":"vertex","properties":{"name":[{"id":7,"value":"josh"}],"age":[{"id":8,"value":32}]}},{"3":[{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},{}],"5":[{"id":5,"label":"vertex","type":"vertex","properties":{"name":[{"id":9,"value":"ripple"}],"lang":[{"id":10,"value":"java"}]}},{}]}]}]}
This formats in GraphSON 1.0 (which is what is used in 3.0.x) to:
{
"1": [{
"id": 1,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 0,
"value": "marko"
}],
"age": [{
"id": 2,
"value": 29
}]
}
}, {
"2": [{
"id": 2,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 3,
"value": "vadas"
}],
"age": [{
"id": 4,
"value": 27
}]
}
}, {}],
"3": [{
"id": 3,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 5,
"value": "lop"
}],
"lang": [{
"id": 6,
"value": "java"
}]
}
}, {}],
"4": [{
"id": 4,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 7,
"value": "josh"
}],
"age": [{
"id": 8,
"value": 32
}]
}
}, {
"3": [{
"id": 3,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 5,
"value": "lop"
}],
"lang": [{
"id": 6,
"value": "java"
}]
}
}, {}],
"5": [{
"id": 5,
"label": "vertex",
"type": "vertex",
"properties": {
"name": [{
"id": 9,
"value": "ripple"
}],
"lang": [{
"id": 10,
"value": "java"
}]
}
}, {}]
}]
}]
}
The convert() function i created just recursively iterates the tree and turns every [vertex: children] into [vertexId: [vertex,children]. You can convert to whatever format you like, so long as you build valid JSON where there is a usable String key field. I could have just as easily made the convert() function return [vertexId: [node: vertex, leaves: children]:
gremlin> convert = { it.collectEntries{ k,v -> [(k.id()): [node: k, leaves:v.isEmpty() ? v : convert(v)]] }}
==>groovysh_evaluate$_run_closure1#2ab5afc7
gremlin> mapper.writeValueAsString(convert(t))
==>{"1":{"node":{"id":1,"label":"vertex","type":"vertex","properties":{"name":[{"id":0,"value":"marko"}],"age":[{"id":2,"value":29}]}},"leaves":{"2":{"node":{"id":2,"label":"vertex","type":"vertex","properties":{"name":[{"id":3,"value":"vadas"}],"age":[{"id":4,"value":27}]}},"leaves":{}},"3":{"node":{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},"leaves":{}},"4":{"node":{"id":4,"label":"vertex","type":"vertex","properties":{"name":[{"id":7,"value":"josh"}],"age":[{"id":8,"value":32}]}},"leaves":{"3":{"node":{"id":3,"label":"vertex","type":"vertex","properties":{"name":[{"id":5,"value":"lop"}],"lang":[{"id":6,"value":"java"}]}},"leaves":{}},"5":{"node":{"id":5,"label":"vertex","type":"vertex","properties":{"name":[{"id":9,"value":"ripple"}],"lang":[{"id":10,"value":"java"}]}},"leaves":{}}}}}}}

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