I can't find very much documentation on how to properly define the index function such that I can do a full text search on the information that I need.
I've used the Alchemy API to add "entities" json to my documents.
For instance, I have a document with the following:
"_id": "redacted",
"_rev": "redacted",
"session": "20152016",
"entities": [
{
"relevance": "0.797773",
"count": "3",
"type": "Organization",
"text": "California Constitution"
},
{
"relevance": "0.690092",
"count": "1",
"type": "Organization",
"text": "Governors Highway Safety Association"
}
]
I haven't been able to find any code snippets showing how to construct a search index function that looks at nested json.
My stab at indexing the whole object appears to be incorrect.
This is the full design document:
{
"_id": "_design/entities",
"_rev": "redacted",
"views": {},
"language": "javascript",
"indexes": {
"entities": {
"analyzer": "standard",
"index": "function (doc) {\n if (doc.entities.relevance > 0.5){\n index(\"default\", doc.entities.text, {\"store\":\"yes\"});\n }\n\n}"
}
}
}
And the search index formatted a little bit more clearly is
function (doc) {
if (doc.entities.relevance > 0.5){
index("default", doc.entities.text, {"store":"yes"});
}
}
Adding the for loop as suggested below makes a lot of sense.
However, I still am not able to return any results.
My query is
"https://user.cloudant.com/calbills/_design/entities/_search/entities?q=Governors"
Server response is:
{"total_rows":0,"bookmark":"g2o","rows":[]}
The "for..in" style loop doesn't seem to work.
However, I do get results using the more standard for loop loops.
function (doc) {
if(doc.entities){
var arrayLength = doc.entities.length;
for (var i = 0; i < arrayLength; i++) {
if (parseFloat(doc.entities[i].relevance) > 0.5)
index("default", doc.entities[i].text);
}
}
}
Cheers!
Your need to loop on the elements in the doc.entities array.
function (doc) {
for(entity in doc.entities){
if (parseFloat(entity.relevance) > 0.5){
index("default", entity.text, {"store":"yes"});
}
}
}
This is what I tried :
function(doc){
if(doc.entities){
for( var p in doc.entities ){
if (doc.entities[p].relevance > 0.5)
{
index("entitiestext", doc.entities[p].text, {"store":"yes"});
}
}
}
}
Query String used :"q=entitiestext:California Constitution&include_docs=true"
Result:
{
"total_rows": 1,
"bookmark": "xxxx",
"rows": [
{
"id": "redacted",
"order": [
0.03693288564682007,
1
],
"fields": {
"entitiestext": [
"Governors Highway Safety Association",
"California Constitution"
]
},
"doc": {
"_id": "redacted",
"_rev": "4-7f6e6db246abcf2f884dc0b91451272a",
"session": "20152016",
"entities": [
{
"relevance": "0.797773",
"count": "3",
"type": "Organization",
"text": "California Constitution"
},
{
"relevance": "0.690092",
"count": "1",
"type": "Organization",
"text": "Governors Highway Safety Association"
}
]
}
}
]
}
Query String used: q=entitiestext:California Constitution
Result:
{
"total_rows": 1,
"bookmark": "xxxx",
"rows": [
{
"id": "redacted",
"order": [
0.03693288564682007,
1
],
"fields": {
"entitiestext": [
"Governors Highway Safety Association",
"California Constitution"
]
}
}
]
}
Related
I faced with the issue when I try to search for several words including a special character (section sign "§").
Example: AB § 32.
I want all words "AB", "32" and symbol "§" to be included in found documents.
In some cases document can be found, in some not.
If my document contains the following text then search finds it:
Lagrum: 32 § 1 mom. första stycket a) kommunalskattelagen (1928:370) AB
But if document contains this text then search doesn't find:
Lagrum: 32 § 1 mom. första stycket AB
For symbol "§" I use UT8-encoding "\xc2\xa7".
Index uses "lucene.swedish" analyzer.
"Content": [
{
"analyzer": "lucene.swedish",
"minGrams": 4,
"tokenization": "nGram",
"type": "autocomplete"
},
{
"analyzer": "lucene.swedish",
"type": "string"
}
]
Query looks like:
{
"index": "test_index",
"compound": {
"filter": [
{
"text": {
"query": [
"111111111111"
],
"path": "ProductId"
}
},
],
"must": [
{
"autocomplete": {
"query": [
"AB"
],
"path": "Content"
}
},
{
"autocomplete": {
"query": [
"\xc2\xa7",
],
"path": "Content"
}
},
{
"autocomplete": {
"query": [
"32"
],
"path": "Content"
}
}
],
},
"count": {
"type": "lowerBound",
"threshold": 500
}
}
The question is what is wrong with the search and how can I get a correct result (return both above mentioned documents) ?
Focusing only on the content field, here is an index definition that should work for your requirements. The docs are here. Let me know if this works for you.
{
"mappings": {
"dynamic": false,
"fields": {
"content": [
{
"type": "autocomplete",
"tokenization": "nGram",
"minGrams": 4,
"maxGrams": 7,
"foldDiacritics": false,
"analyzer": "lucene.whitespace"
},
{
"analyzer": "lucene.swedish",
"type": "string"
}
]
}
}
}
I'm fairly new to JSONPath so this could be my fault but when I try this expression in an online evaluator (https://jsonpath.com/) it works but does not in Karate.
$..entry[?(#.resource.resourceType == 'AllergyIntolerance' && #.resource.category=='food')].resource.code.coding.*.system
If I use an index I am able to get the first element out but I want to grab all elements that match the expression regardless of their index in case there are more items in the array and not my specific data example.
Working JSONPath:
$..entry[?(#.resource.resourceType == 'AllergyIntolerance' && #.resource.category[0]=='food')].resource.code.coding.*.system
I've tried to use wildcards but that doesn't seem to work:
$..entry[?(#.resource.resourceType == 'AllergyIntolerance' && #.resource.category[*]=='food')].resource.code.coding.*.system
JSON snippit with relevant sections
{
"entry": [ {
"resource": {
"resourceType": "AllergyIntolerance",
"id": "allergyFood",
"category": [ "food" ],
"criticality": "high",
"code": {
"coding": [ {
"system": "http://snomed.info/sct",
"code": "91935009",
"display": "Allergy to peanuts"
} ],
"text": "Allergy to peanuts"
},
"reaction": [ {
"manifestation": [ {
"coding": [ {
"system": "http://snomed.info/sct",
"code": "271807003",
"display": "skin rash"
} ],
"text": "skin rash"
} ],
"severity": "mild"
} ]
}
}, {
"resource": {
"resourceType": "AllergyIntolerance",
"id": "allergyMed",
"verificationStatus": "unconfirmed",
"type": "allergy",
"category": [ "medication" ],
"criticality": "high",
"code": {
"coding": [ {
"system": "http://www.nlm.nih.gov/research/umls/rxnorm",
"code": "7980",
"display": "penicillin"
} ]
}
}
} ]
}
The JsonPath engine is known to have issues with such complex expressions. Please use karate.filter() instead which I am sure you will agree is much more readable: https://github.com/intuit/karate#json-transforms
* def resources = $..resource
* def fun = function(x){ return x.resourceType == 'AllergyIntolerance' && x.category[0] == 'food' }
* def temp = karate.filter(resources, fun)
I am using Cosmos DB and have a document with the following simplified structure:
{
"id1":"123",
"stuff": [
{
"id2": "stuff",
"a": {
"b": {
"c": {
"d": [
{
"e": [
{
"id3": "things",
"name": "animals",
"classes": [
{
"name": "ostrich",
"meta": 1
},
{
"name": "big ostrich",
"meta": 1
}
]
},
{
"id3": "default",
"name": "other",
"classes": [
{
"name": "green trees",
"meta": 1
},
{
"name": "trees",
"score": 1
}
]
}
]
}
]
}
}
}
}
]
}
My issue is - I have an array of these documents and need to search name to see if it matches my search word. For example I want both big trees and trees to return if a user types in trees.
So currently I push every document into an array and do the following:
For each document
for each stuff
for each a.b.c.d[0].e
for each classes
var splice = name.split(' ')
if (splice.includes(searchWord))
return id1, id2 and id3.
Using cosmosDB I am using SQL with the following code:
client.queryDocuments(
collection,
`SELECT * FROM root r`
).toArray((err, results) => {stuff});
This effectively brings every document in my collection into an array to perform the search manually above as mentioned.
This is going to cause issues when I have 1000s or 1,000,000s of documents in the array and I believe I should be leveraging the search mechanics available within Cosmos itself. Is anyone able to help me to work out what SQL query would be able to perform this type of function?
Having searched everything is it also possible to search the 5 latest documents?
Thanks for any insight in advance!
1.Is anyone able to help me to work out what SQL query would be able to
perform this type of function?
According to your sample and description, I suggest you using ARRAY_CONTAINS in cosmos db sql. Please refer to my sample:
sample documents:
[
{
"id1": "123",
"stuff": [
{
"id2": "stuff",
"a": {
"b": {
"c": {
"d": [
{
"e": [
{
"id3": "things",
"name": "animals",
"classes": [
{
"name": "ostrich",
"meta": 1
},
{
"name": "big ostrich",
"meta": 1
}
]
},
{
"id3": "default",
"name": "other",
"classes": [
{
"name": "green trees",
"meta": 1
},
{
"name": "trees",
"score": 1
}
]
}
]
}
]
}
}
}
}
]
},
{
"id1": "456",
"stuff": [
{
"id2": "stuff2",
"a": {
"b": {
"c": {
"d": [
{
"e": [
{
"id3": "things2",
"name": "animals",
"classes": [
{
"name": "ostrich",
"meta": 1
},
{
"name": "trees",
"meta": 1
}
]
},
{
"id3": "default2",
"name": "other",
"classes": [
{
"name": "green trees",
"meta": 1
},
{
"name": "trees",
"score": 1
}
]
}
]
}
]
}
}
}
}
]
},
{
"id1": "789",
"stuff": [
{
"id2": "stuff3",
"a": {
"b": {
"c": {
"d": [
{
"e": [
{
"id3": "things3",
"name": "animals",
"classes": [
{
"name": "ostrich",
"meta": 1
},
{
"name": "big",
"meta": 1
}
]
},
{
"id3": "default3",
"name": "other",
"classes": [
{
"name": "big trees",
"meta": 1
}
]
}
]
}
]
}
}
}
}
]
}
]
query :
SELECT distinct c.id1,stuff.id2,e.id3 FROM c
join stuff in c.stuff
join d in stuff.a.b.c.d
join e in d.e
where ARRAY_CONTAINS(e.classes,{name:"trees"},true)
or ARRAY_CONTAINS(e.classes,{name:"big trees"},true)
output:
2.Having searched everything is it also possible to search the 5 latest
documents?
Per my research, features like LIMIT is not supported in cosmos so far. However , TOP is supported by cosmos db. So if you could add sort field(such as date or id), then you could use sql:
select top 5 from c order by c.sort desc
I am new to Elastic Search APIs. I have a requirement where i need to query and list the documents which compulsorily contains following properties, say
"request: "/v3?id=100000" & "type: "GET"
Result should contains list of documents containing both the above. I have tried the following and it gets either of the above.
{
"query": {
"match": {
"type": "GET"
}
}
}
I tried
{
"query": {
"match": {
"type": "GET",
"request: "/v3/id=100000"
}
}
}
It fails...
Can someone suggest me a query to list all the docs with both the properties set as above ? Not sure how to use filters, if I try it shows failures - parse exceptions.
My example document:
{
"_index": "logstash-2016.04.22",
"_type": "endpoint-access",
"_id": "fAhTQkDRQTiHKlzuleNA",
"_score": null,
"_source": {
"#version": "1",
"#timestamp": "2016-04-22T15:26:35.153Z",
"offset": "43714176",
"ident": "-",
"auth": "-",
"timestamp": "22/Apr/2016:15:26:35 +0000",
"type": "GET",
"request": "/v3?id=1b32e833-b521",
"httpversion": "1.1",
"response": "500",
"bytes": "265",
"referrer": "-",
"agent": "-",
"x_forwarded_for": "\"101.2.123.24\""
"host": "101.123.115.167"
},
"sort": [
1461338795153,
1461338795153
]
}
You may use "must" to get the result:
{
"query": {
"bool": {
"must": [
{
"match": {
"type": "GET"
}
},
{
"match": {
"request": "/v3/id=100000"
}
}
]
}
}
}
i am doing aggregations on "location" field in my document ,where there is also a "city" field in the same document.I am querying the document on city field and aggregating the documents on location field.
{
"aggs": {
"locations": {
"terms": {
"field": "location",
"min_doc_count": 0
}
}
},
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"city": "mumbai",
"_cache": true
}
}
]
}
}
}
}
}
Now the count and aggregations come fine and along with the hits.but my problem is that i want to do aggregation with 'doc-count' set to 0 and the aggregation bucket returns me all the lcoations with 0 count which even falls in other city.I want to get 0 count locations only for that city.want to scope the context of 0 count location to city.
I tried achieving this by nested aggregation placing location inside nested city and then doing aggs, or combining the filter aggs with terms agg but still getting the same result.Is there any way to achieve this or elasticsearch is inherently build to work like this.
ES Version - 1.6
My mapping looks like this:
{
"service": {
"_source": {
"enabled": true
},
"properties": {
"name": {
"type": "string",
"index": "not_analyzed"
},
"location": {
"type": "string",
"index": "not_analyzed"
},
"city": {
"type": "string",
"index": "not_analyzed"
}
}
}
}
Sample docs to index
{
"name": "a",
"location": "x",
"city": "mumbai"
}
{
"name": "b",
"location": "x",
"city": "mumbai"
}
{
"name": "c",
"location": "y"
"city": "chennai"
}
You should try to sort your terms aggregation (embedded into a filter aggregation) by ascending doc count and you'll get all the terms with 0 doc count first. Note that by default, you'll only get the first 10 terms, if you have less terms with 0 doc count, you'll see them all, otherwise you might need to increase the size parameter to something higher than 10.
{
"aggs": {
"city_filter": {
"filter": {
"term": {
"city": "mumbai"
}
},
"aggs": {
"locations": {
"terms": {
"field": "location",
"min_doc_count": 0,
"size": 20, <----- add this if you have more than ten 0-doc-count terms
"order": { <----- add this to see 0-doc-count first
"_count": "asc"
}
}
}
}
}
},
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"city": "mumbai",
"_cache": true
}
}
]
}
}
}
}
}