_attribute not valorised and hops not executed
licenziato opened this issue · comments
We are trying to use Zentity 1.5.1 with Elasticsearch 7.3.2. for a pilot project. we're not able to make working a chain of resolvers most probably for the problem reported in the title.
I report here the index mapping of the data:
{
"obj-person": {
"aliases": {},
"mappings": {
"dynamic": "strict",
"properties": {
"completeName": {
"type": "text",
"fields": {
"phonetic": {
"type": "text",
"analyzer": "phonetic_analyzer"
}
}
},
"entry": {
"properties": {
"createdBy": {
"type": "keyword"
},
"createdDate": {
"type": "date"
},
"infoObject": {
"properties": {
"dateOfBirth": {
"properties": {
"originalValue": {
"type": "text",
"copy_to": [
"search"
]
},
"value": {
"type": "text",
"copy_to": [
"search"
]
}
}
},
"firstName": {
"properties": {
"originalValue": {
"type": "text",
"copy_to": [
"search"
]
},
"value": {
"type": "text",
"fields": {
"phonetic": {
"type": "text",
"analyzer": "phonetic_analyzer"
}
},
"copy_to": [
"search",
"completeName"
]
}
}
},
"lastName": {
"properties": {
"originalValue": {
"type": "text",
"copy_to": [
"search"
]
},
"value": {
"type": "text",
"fields": {
"phonetic": {
"type": "text",
"analyzer": "phonetic_analyzer"
}
},
"copy_to": [
"search",
"completeName"
]
}
}
}
}
}
}
},
"search": {
"type": "text",
"fields": {
"graphically_similar": {
"type": "text",
"analyzer": "normalize_graphically_similar_analyzer"
},
"normalized": {
"type": "text",
"analyzer": "normalize_alphanum_analyzer"
},
"phonetic": {
"type": "text",
"analyzer": "phonetic_analyzer"
}
}
},
"search_sensitive": {
"type": "text"
},
"type": {
"type": "keyword"
}
}
},
"settings": {
"index": {
"number_of_shards": "1",
"auto_expand_replicas": "1-5",
"provided_name": "obj-person",
"creation_date": "1582637094035",
"analysis": {
"filter": {
"phonetic_filter": {
"replace": "true",
"type": "phonetic",
"encoder": "double_metaphone"
}
},
"analyzer": {
"phonetic_analyzer": {
"filter": [
"phonetic_filter"
],
"tokenizer": "standard"
},
"normalize_graphically_similar_analyzer": {
"filter": [
"uppercase"
],
"char_filter": [
"strip_special_chars",
"replace_graphically_similar"
],
"type": "custom",
"tokenizer": "keyword"
},
"normalize_alphanum_analyzer": {
"filter": [
"uppercase",
"reverse"
],
"char_filter": "strip_special_chars",
"type": "custom",
"tokenizer": "keyword"
}
},
"char_filter": {
"replace_graphically_similar": {
"type": "mapping",
"mappings": [
"O => 0",
"D => 0",
"I => 1",
"B => 8",
"S => 5",
"Z => 2",
"G => 6",
"E => 3",
"o => 0",
"d => 0",
"i => 1",
"b => 8",
"s => 5",
"z => 2",
"g => 6",
"e => 3"
]
},
"strip_special_chars": {
"pattern": "[^\\w]",
"type": "pattern_replace",
"replacement": ""
}
}
},
"number_of_replicas": "1",
"uuid": "JFGNOU6xR4i_BHM8e0nB5Q",
"version": {
"created": "7030199"
}
}
}
}
}
Creating a zentity model like this:
PUT _zentity/models/zentity_test_resolution_person
{
"attributes" : {
"first_name" : {
"type" : "string"
},
"last_name" : {
"type" : "string"
},
"dob" : {
"type" : "string"
}
},
"resolvers" : {
"name_only" : {
"attributes" : [
"first_name",
"last_name"
]
},
"dob" : {
"attributes" : [
"dob"
]
}
},
"matchers" : {
"simple" : {
"clause" : {
"match" : {
"{{ field }}" : "{{ value }}"
}
}
},
"fuzzy" : {
"clause" : {
"match" : {
"{{ field }}" : {
"query" : "{{ value }}",
"fuzziness" : "{{ params.fuzziness }}"
}
}
},
"params" : {
"fuzziness" : "auto"
}
}
},
"indices" : {
"obj-person" : {
"fields" : {
"entry.infoObject.firstName.value" : {
"attribute" : "first_name",
"matcher" : "fuzzy"
},
"entry.infoObject.lastName.value" : {
"attribute" : "last_name",
"matcher" : "fuzzy"
},
"entry.infoObject.dateOfBirth.value" : {
"attribute" : "dob",
"matcher" : "simple"
}
}
}
}
}
Using three objects which the core data is:
Person1:
"firstName" : {
"value" : "Nolan"
},
"lastName" : {
"value" : "Hendricks"
},
"dateOfBirth" : {
"value" : "633-9242"
}
Person2:
"firstName" : {
"value" : "Nolan"
},
"lastName" : {
"value" : "Hendricks"
},
"dateOfBirth" : {
"value" : "677-9999"
}
Person3:
"firstName" : {
"value" : "Noln"
},
"lastName" : {
"value" : "Hendricks"
},
"dateOfBirth" : {
"value" : "677-9999"
}
If we execute this resolution:
POST _zentity/resolution/zentity_test_resolution_person?_source=false&_explanation=false
{
"attributes": {
"first_name": {
"values": ["Nolan"],
"params": {
"fuzziness": "0"
}
},
"last_name": ["Hendricks"]
}
}
the result is this:
{
"took" : 2,
"hits" : {
"total" : 2,
"hits" : [ {
"_index" : "obj-person",
"_type" : "_doc",
"_id" : "2D6F8CCF-227B-4FBF-A749-16C098BB0C0A",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"dob" : [ ],
"first_name" : [ ],
"last_name" : [ ]
}
}, {
"_index" : "obj-person",
"_type" : "_doc",
"_id" : "1CE639AD-B3FD-4FAB-9D9B-A469DE75C943",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"dob" : [ ],
"first_name" : [ ],
"last_name" : [ ]
}
} ]
}
}
How you can see _attributes are not valorized at all and no all the hops has been performed: I'll expect to see the third result based on the "dob" field.
Can you point me in the right direction?
@licenziato I'm sure this response comes far too late for your needs and I apologize for that. I'll answer it anyway for the record.
I wasn't able to reproduce your issue. I reproduced your setup (zentity 1.5.1, Elasticsearch 7.3.2) and configurations, and my resolution job included the third document which was matched by the "dob" resolver (see below). If I had to guess, the issue may have been rooted in the mapping, data, or other configuration in your environment.
POST _zentity/resolution/zentity_test_resolution_person?_source=false&_explanation=true
{
"took" : 65,
"hits" : {
"total" : 3,
"hits" : [ {
"_index" : "obj-person",
"_type" : "_doc",
"_id" : "1",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"dob" : [ "633-9242" ],
"first_name" : [ "Nolan" ],
"last_name" : [ "Hendricks" ]
},
"_explanation" : {
"resolvers" : {
"name_only" : {
"attributes" : [ "first_name", "last_name" ]
}
},
"matches" : [ {
"attribute" : "first_name",
"target_field" : "entry.infoObject.firstName.value",
"target_value" : "Nolan",
"input_value" : "Nolan",
"input_matcher" : "fuzzy",
"input_matcher_params" : {
"fuzziness" : "0"
}
}, {
"attribute" : "last_name",
"target_field" : "entry.infoObject.lastName.value",
"target_value" : "Hendricks",
"input_value" : "Hendricks",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
}
}, {
"_index" : "obj-person",
"_type" : "_doc",
"_id" : "2",
"_hop" : 0,
"_query" : 0,
"_attributes" : {
"dob" : [ "677-9999" ],
"first_name" : [ "Nolan" ],
"last_name" : [ "Hendricks" ]
},
"_explanation" : {
"resolvers" : {
"name_only" : {
"attributes" : [ "first_name", "last_name" ]
}
},
"matches" : [ {
"attribute" : "first_name",
"target_field" : "entry.infoObject.firstName.value",
"target_value" : "Nolan",
"input_value" : "Nolan",
"input_matcher" : "fuzzy",
"input_matcher_params" : {
"fuzziness" : "0"
}
}, {
"attribute" : "last_name",
"target_field" : "entry.infoObject.lastName.value",
"target_value" : "Hendricks",
"input_value" : "Hendricks",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
}
}, {
"_index" : "obj-person",
"_type" : "_doc",
"_id" : "3",
"_hop" : 1,
"_query" : 0,
"_attributes" : {
"dob" : [ "677-9999" ],
"first_name" : [ "Noln" ],
"last_name" : [ "Hendricks" ]
},
"_explanation" : {
"resolvers" : {
"dob" : {
"attributes" : [ "dob" ]
}
},
"matches" : [ {
"attribute" : "dob",
"target_field" : "entry.infoObject.dateOfBirth.value",
"target_value" : "677-9999",
"input_value" : "677-9999",
"input_matcher" : "simple",
"input_matcher_params" : { }
}, {
"attribute" : "last_name",
"target_field" : "entry.infoObject.lastName.value",
"target_value" : "Hendricks",
"input_value" : "Hendricks",
"input_matcher" : "fuzzy",
"input_matcher_params" : { }
} ]
}
} ]
}
}