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?
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": [
]
}
I'm learning How to use Algolia and I have a few questions.
I have the table FreightDriver, which has a relationship one to many with the table Truck
id: ID!
name: String!
email: String!
phoneNumber: String!
cities: [String!]!
state: String!
country: String!
picture: String
trucks: [Truck] #connection(keyName: "byFreightDriver", fields: ["id"])
Then, the table Truck, which has a relationship one to one with the table FreightDriver, and another table, which is Box one to one as well
id: ID!
freightDriverId: ID!
boxId: ID!
brand: String!
model: String!
yearModel: Int!
// and more fields
freightDriver: FreightDriver #connection(fields: ["freightDriverId"])
box: Box #connection(fields: ["boxId"])
and the table Box:
id: ID!
type: String!
width: Float!
height: Float!
depth: Float!
I want to find trucks based on the state and city of the FreightDrivers, and also (if the user needs it), find based on the type of box and brand or model of a truck (just as an example).
Example find by state and city of a FreightDriver:
{
"data": {
"freightDriversByState": {
"items": [
{
"name": "Andrés Montoya",
"cities": [
"GUADALAJARA"
],
"state": "JALISCO",
"country": "MX",
"trucks": {
"items": [
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Ganadera",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 12,
"height": 12,
"depth": 12
}
},
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 12,
"height": 12,
"depth": 12
}
},
{
"brand": "chevrolet",
"model": "Semi",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Volcadora",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "hola",
"model": "12",
"yearModel": 12,
"box": {
"type": "Plataforma",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "Ford",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 1,
"height": 2,
"depth": 1
}
},
{
"brand": "dasdas",
"model": "12",
"yearModel": 12231,
"box": {
"type": "Grúa",
"width": 1,
"height": 2,
"depth": 3
}
},
{
"brand": "Tesla",
"model": "Semi",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 4,
"height": 4,
"depth": 2
}
}
]
}
},
{
"name": "Roberto mendez",
"cities": [
"GUADALAJARA"
],
"state": "JALISCO",
"country": "MX",
"trucks": {
"items": []
}
},
{
"name": "Fletes Jalisco Sa de Cv ",
"cities": [
"GUADALAJARA"
],
"state": "JALISCO",
"country": "MX",
"trucks": {
"items": [
{
"brand": "Ford",
"model": "F-450",
"yearModel": 2018,
"box": {
"type": "Seca (cerrada)",
"width": 2.7,
"height": 2.5,
"depth": 4.5
}
},
{
"brand": "Hiundai",
"model": "H100",
"yearModel": 2009,
"box": {
"type": "Seca (abierta)",
"width": 2.3,
"height": 2,
"depth": 4
}
},
{
"brand": "Hiundai",
"model": "H100",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 2.35,
"height": 2,
"depth": 3
}
},
{
"brand": "Ford",
"model": "F-450",
"yearModel": 2018,
"box": {
"type": "Seca (cerrada)",
"width": 2.7,
"height": 2.2,
"depth": 3
}
},
{
"brand": "Ford",
"model": "F-450",
"yearModel": 2004,
"box": {
"type": "Seca (abierta)",
"width": 2.5,
"height": 2,
"depth": 3
}
}
]
}
},
{
"name": "Cotransport",
"cities": [
"GUADALAJARA"
],
"state": "JALISCO",
"country": "MX",
"trucks": {
"items": [
{
"brand": "Chevrolet",
"model": "CX-5",
"yearModel": 2019,
"box": {
"type": "Seca (cerrada)",
"width": 4,
"height": 3,
"depth": 4
}
}
]
}
},
{
"name": "Andrés",
"cities": [
"EL LIMÓN",
"MAGDALENA",
"SANTA MARÍA DEL ORO",
"GUADALAJARA",
"ETZATLÁN"
],
"state": "JALISCO",
"country": "MX",
"trucks": {
"items": [
{
"brand": "chevrolet",
"model": "12",
"yearModel": 2020,
"box": {
"type": "Seca (abierta)",
"width": 1,
"height": 2,
"depth": 3
}
}
]
}
}
]
}
}
}
But, if I want to find using the state and city of a freight driver, the type of box and the model or brand of a truck, that's where the problem comes, because I'm using Dynamodb and this one does not have relationships, so, it's a little bit tricky to get the exact data. That's why I'd like to use Algolia, but how do I format the data for Algolia in this case? What do I need to do? thanks!
If someone is interested, here's the answer https://discourse.algolia.com/t/how-to-format-data-to-algolia/10897
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
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":{}}}}}}}