I have a managed object of type “ABC” with a fragment “A”, that has sub-structure as following:
{
"type": "ABC",
"A": {
"value": ["B", "C"]
}
}
How would one create a filter/query that would check if "A" fragment contains “C” in the "value" array?
That query fails:
{{url}}/inventory/managedObjects?query=$filter=(type+eq+'ABC'+and+A.value+has+‘C‘)
With
{
"error": "inventory/Invalid Data",
"message": "Find by filter query failed : Query '$filter=(type eq 'ABC' and A.value has ‘C‘)' could not be understood. Please try again.",
"info": "https://www.cumulocity.com/guides/reference-guide/#error_reporting"
}
Cumulocity doc about querying REST API.
Solution:
Use eq instead of has:
{{url}}/inventory/managedObjects?query=$filter=(type+eq+'ABC'+and+A.value+eq+‘C‘)
I couldn't find a source but the following is working for me with the expected result:
{{url}}/inventory/managedObjects?query=$filter=(type+eq+'ABC'+and+A.value+eq+'C')
So basically you need to use the eq operator for your use case.
Related
Background:
I wish to locate the entire JSON document that has a condition where "state" = "new" and where length(Features.id) > 4
{
"id": "123"
"feedback": {
"Features": [
{
"state": "new"
"id": "12345"
}
]
}
}
This is what I have tried to do:
Since this is a nested document. My query looks like this:
A stackoverflow member has helped me to access the nested contents within the query, but is there a way to obtain the full document
I have used:
SELECT VALUE t.id FROM t IN f.feedback.Features where t.state = 'new' and length(t.id)>4
This will give me the ids.
My desire is to have access to the full document with this condition?
{
"id": "123"
"feedback": {
"Features": [
{
"state": "new"
"id": "12345"
}
]
}
}
Any help is appreciated
Try this
SELECT *
FROM f
WHERE
f.feedback.Features[0].state = 'new'
AND length(f.feedback.Features[0].id)>4
Here is the SELECT spec for CosmosDB for more details
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-select
Also, check out "working with JSON" in CosmosDB notes
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-working-with-json
If the Features array has more than 1 value, you can use EXISTS clause to search within them. See specs of EXISTS here with examples:
https://learn.microsoft.com/en-us/azure/cosmos-db/sql-query-subquery#exists-expression
My documents in cloudant have the following structure
{
"_id" : "1234",
"name" : "test",
"objects" : [
{
"type" : "TYPE1"
"time" : "1215
},
{
"type" : "TYPE2"
"time" : "1115"
}
]
}
Now I need to query my documents by a list of types.
Examples
1) If I would query with TYPE1 then all the documents where there is an object with this type would return. (The example doc would return)
2) If I would query with TYPE1 and TYPE3 it would return all documents which contain either of them (The example doc would return)
3) If I would query with TYPE3, TYPE4 and TYPE5 it would return all documents which contain either of them (The example doc would not return)
How would the code in the _design document look like and how would my API request look like?
One option is to use Cloudant Search.
Sample design document named types, which indexes each type property in your objects array
{
"_id": "_design/types",
"views": {},
"language": "javascript",
"indexes": {
"one-of": {
"analyzer": "standard",
"index": "function (doc) {\n for(var i in doc.objects) {\n index(\"type\", doc.objects[i].type); \n }\n}"
}
}
}
Query examples:
Search for one key (type=val)
GET https://$HOST/$DATABASE/_design/$DDOC/_search/one-of?q=type%3ATYPE1
Search for multiple keys (type=val1 OR type=val2)
GET https://$HOST/$DATABASE/_design/$DDOC/_search/one-of?q=type%3ATYPE1%20OR%20type%3ATYPE2
Search for multiple keys (type=val1 AND type=val2)
GET https://$HOST/$DATABASE/_design/$DDOC/_search/one-of?q=type%3ATYPE1%20AND%20type%3ATYPE2
To include the documents in the response append &include_docs=true.
Hi when working in Backand I try to run the following query:
{
"object": "dr_persons",
"q": {
"person_type" : "4"
},
"fields": ["first_name", "last_name"]
}
person_type is a table in mysql db with "4" as a value.
When I run it I get this error:
Errors in Query
Please fix the following errors in the query:
not a valid constant for field person_type of object dr_persons
The only thing I can see is that when I sync my db it makes it a "float" which I can't change. Can anyone give me some direction on this?
The error message is due to the constant "4" being a string. According to the field type, float, it should be a number. Hence your query should be:
{
"object": "dr_persons",
"q": {
"person_type" : 4
},
"fields": ["first_name", "last_name"]
}
The only thing I managed to do is this link:
https://www.wikidata.org/w/api.php?action=wbgetentities&ids=Q568&format=jsonfm
But this produces lots of useless data. What I need is to get all the statements for the given item, but I can't see any of the statements in the query above.
here it will be:
{ "instance of" : "chemical element",
"element symbol" : "Li",
"atomic number" : 3,
"oxidation state" : 1,
"subclass of" : ["chemical element", "alkali metal"]
// etc...
}
Is there an API for this or must I scrape the web page?
The information you want is in your query, except it's hard to decode. For example, this:
"P246": [
{
"id": "q568$E47B8CE7-C91D-484A-9DA4-6153F132997D",
"mainsnak": {
"snaktype": "value",
"property": "P246",
"datatype": "string",
"datavalue": {
"value": "Li",
"type": "string"
}
},
"type": "statement",
"rank": "normal",
"references": …
}
]
means that the “element symbol” (property P246) is “Li”. So, you will need to read all the properties from your query and then find out the name for each of the properties you found.
To get just the statements, you could also use action=wbgetclaims, but it's in the same format as above.
ElasticSearch Version: 0.90.2
Here's the problem: I want to find documents in the index so that they:
match all query tokens across multiple fields
fields own analyzers are used
So if there are 4 documents:
{ "_id" : 1, "name" : "Joe Doe", "mark" : "1", "message" : "Message First" }
{ "_id" : 2, "name" : "Ann", "mark" : "3", "message" : "Yesterday Joe Doe got 1 for the message First"}
{ "_id" : 3, "name" : "Joe Doe", "mark" : "2", "message" : "Message Second" }
{ "_id" : 4, "name" : "Dan Spencer", "mark" : "2", "message" : "Message Third" }
And the query is "Joe First 1" it should find ids 1 and 2. I.e., it should find documents which contain all the tokens from search query, no matter in which fields they are (maybe all tokens are in one field, or maybe each token is in its own field).
One solution would be to use elasticsearch "_all" field functionality: that way it will merge all the fields I need (name, mark, message) into one and I'll be able to query it with something like
"match": {
"_all": {
"query": "Joe First 1",
"operator": "and"
}
}
But this way I can specify analyzer for the "_all" field only. And I need "name" and "message" fields to have different set of tokenizers/token filters (let's say name will have phonetic analyzer and message will have some stemming token filter).
Is there a way to do this?
Thanks to guys at elasticsearch group, here's the solution... pretty simple need to say :)
All I needed to do is to use query_string query http://www.elasticsearch.org/guide/reference/query-dsl/query-string-query/ with default_operator = AND and it will do the trick:
{
"query": {
"query_string": {
"fields": [
"name",
"mark",
"message"
],
"query": "Joe First 1",
"default_operator": "AND"
}
}
}
I think using a multi match query makes sense here. Something like:
"multi_match": {
"query": "Joe First 1",
"operator": "and"
"fields": [ "name", "message", "mark"]
}
As you say, you can set the analyzer (or search_analyzer/index_analyzer) to be used on the _all field. It seems to me that should indeed be your first step to achieve the query results you're looking for.
From http://jontai.me/blog/2012/10/lucene-scoring-and-elasticsearch-_all-field/, we have this tasty quote:
... the _all field copies the text from the other fields and analyzes
them again; it doesn’t copy the pre-analyzed tokens. You can set a
separate analyzer for the _all field.
Which I interpret to mean that you should set your _all analyzer(s) as well as individual field analyzer(s). The _all field won't re-analyze the individual field data; it will grab the original field contents.