Place an Analyzer on a a specific array item in a nested object - elasticsearch

I have the following mapping
"mappings":{
"properties":{
"name": {
"type": "text"
},
"age": {
"type": "integer"
},
"customProps":{
"type" : "nested",
"properties": {
"key":{
"type": "keyword"
},
"value": {
"type" : "keyword"
}
}
}
}
}
example data
{
"name" : "person1",
"age" : 10,
"customProps":[
{"hairColor":"blue"},
{"height":"120"}
]
},
{
"name" : "person2",
"age" : 30,
"customProps":[
{"jobTitle" : "software engineer"},
{"salaryAccount" : "AvGhj90AAb"}
]
}
so i want to be able to search for document by salary account case insensitive, i am also searching using wild card
example query is
{
"query": {
"bool": {
"should": [
{
"nested": {
"path": "customProps",
"query": {
"bool": {
"must": [
{ "match": { "customProps.key": "salaryAccount" } },
{ "wildcard": { "customProps.value": "*AvG*"
}
}
]}}}}]}}}
i tried adding analyzer with PUT using the following syntax
{
"settings":{
"index":{
"analysis":{
"analyzer":{
"analyzer_case_insensitive" : {
"tokenizer":"keyword",
"filter":"lowercase"
}
}
}
}
},
"mappings":{
"people":{
"properties":{
"customProps":{
"properties":{
"value":{
"type": "keyword",
"analyzer": "analyzer_case_insensitive"
}
}
}
}
}
}
}
im getting the following error
"type" : "mapper_parsing_exception",
"reason" : "Root mapping definition has unsupported parameters: [people: {properties={customProps={properties={value={analyzer=analyzer_case_insensitive, type=keyword}}}}}]"
any idea how to do the analyzer for the salary account object in the array when it exists?

Your use case is quite clear, that you want to search on the value of salaryAccount only when this key exists in customProps array.
There are some issues with your mapping definition :
You cannot define a custom analyzer for keyword type field, instead you can use a normalizer
Based on the mapping definition you added at the beginning of the question, it seems that you are using elasticsearch version 7.x. But the second mapping definition that you provided, in that you have added mapping type also (i.e people), which is deprecated in 7.x
There is no need to add the key and value fields in the index mapping.
Adding a working example with index mapping, search query, and search result
Index Mapping:
PUT myidx
{
"mappings": {
"properties": {
"customProps": {
"type": "nested"
}
}
}
}
Search Query:
You need to use exists query, to check whether a field exists or not. And case_insensitive param in Wildcard query is available since elasticsearch version 7.10. If you are using a version below this, then you need to use a normalizer, to achieve case insensitive scenarios.
POST myidx/_search
{
"query": {
"bool": {
"should": [
{
"nested": {
"path": "customProps",
"query": {
"bool": {
"must": [
{
"exists": {
"field": "customProps.salaryAccount"
}
},
{
"wildcard": {
"customProps.salaryAccount.keyword": {
"value": "*aVg*",
"case_insensitive": true
}
}
}
]
}
}
}
}
]
}
}
}
Search Result:
"hits" : [
{
"_index" : "myidx",
"_type" : "_doc",
"_id" : "2",
"_score" : 2.0,
"_source" : {
"name" : "person2",
"age" : 30,
"customProps" : [
{
"jobTitle" : "software engineer"
},
{
"salaryAccount" : "AvGhj90AAb"
}
]
}
}
]

Related

How can I use query_string to match both nested and non-nested fields at the same time?

I have an index with a mapping something like this:
"email" : {
"type" : "nested",
"properties" : {
"from" : {
"type" : "text",
"analyzer" : "lowercase_keyword",
"fielddata" : true
},
"subject" : {
"type" : "text",
"analyzer" : "lowercase_keyword",
"fielddata" : true
},
"to" : {
"type" : "text",
"analyzer" : "lowercase_keyword",
"fielddata" : true
}
}
},
"textExact" : {
"type" : "text",
"analyzer" : "lowercase_standard",
"fielddata" : true
}
I want to use query_string to search for matches in both the nested and the non-nested field at the same time, e.g.
email.to:foo#example.com AND textExact:bar
But I can't figure out how to write a query that will search both fields at once. The following doesn't work, because query_string searches do not return nested documents:
"query": {
"query_string": {
"fields": [
"textExact",
"email.to"
],
"query": "email.to:foo#example.com AND textExact:bar"
}
}
I can write a separate nested query, but that will only search against nested fields. Is there any way I can use query_string to match both nested and non-nested fields at the same time?
I am using Elasticsearch 6.8. Cross-posted on the Elasticsearch forums.
Nested documents can only be queried with the nested query.
You can follow below two approaches.
1. You can combine nested and normal query in must clause, which works like "and" for different queries.
{
"query": {
"bool": {
"must": [
{
"nested": {
"path": "email",
"query": {
"term": {
"email.to": "foo#example.com"
}
}
}
},
{
"match": {
"textExact": "bar"
}
}
]
}
}
}
2. copy-to
The copy_to parameter allows you to copy the values of multiple fields into a group field, which can then be queried as a single field.
{
"mappings": {
"properties": {
"textExact":{
"type": "text"
},
"to_email":{
"type": "keyword"
},
"email":{
"type": "nested",
"properties": {
"to":{
"type":"keyword",
"copy_to": "to_email" --> copies to non-nested field
},
"from":{
"type":"keyword"
}
}
}
}
}
}
Query
{
"query": {
"query_string": {
"fields": [
"textExact",
"to_email"
],
"query": "to_email:foo#example.com AND textExact:bar"
}
}
}
Result
"_source" : {
"textExact" : "bar",
"email" : [
{
"to" : "sdfsd#example.com",
"from" : "a#example.com"
},
{
"to" : "foo#example.com",
"from" : "sdfds#example.com"
}
]
}

How to Query elasticsearch index with nested and non nested fields

I have an elastic search index with the following mapping:
PUT /student_detail
{
"mappings" : {
"properties" : {
"id" : { "type" : "long" },
"name" : { "type" : "text" },
"email" : { "type" : "text" },
"age" : { "type" : "text" },
"status" : { "type" : "text" },
"tests":{ "type" : "nested" }
}
}
}
Data stored is in form below:
{
"id": 123,
"name": "Schwarb",
"email": "abc#gmail.com",
"status": "current",
"age": 14,
"tests": [
{
"test_id": 587,
"test_score": 10
},
{
"test_id": 588,
"test_score": 6
}
]
}
I want to be able to query the students where name like '%warb%' AND email like '%gmail.com%' AND test with id 587 have score > 5 etc. The high level of what is needed can be put something like below, dont know what would be the actual query, apologize for this messy query below
GET developer_search/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "abc"
}
},
{
"nested": {
"path": "tests",
"query": {
"bool": {
"must": [
{
"term": {
"tests.test_id": IN [587]
}
},
{
"term": {
"tests.test_score": >= some value
}
}
]
}
}
}
}
]
}
}
}
The query must be flexible so that we can enter dynamic test Ids and their respective score filters along with the fields out of nested fields like age, name, status
Something like that?
GET student_detail/_search
{
"query": {
"bool": {
"must": [
{
"wildcard": {
"name": {
"value": "*warb*"
}
}
},
{
"wildcard": {
"email": {
"value": "*gmail.com*"
}
}
},
{
"nested": {
"path": "tests",
"query": {
"bool": {
"must": [
{
"term": {
"tests.test_id": 587
}
},
{
"range": {
"tests.test_score": {
"gte": 5
}
}
}
]
}
},
"inner_hits": {}
}
}
]
}
}
}
Inner hits is what you are looking for.
You must make use of Ngram Tokenizer as wildcard search must not be used for performance reasons and I wouldn't recommend using it.
Change your mapping to the below where you can create your own Analyzer which I've done in the below mapping.
How elasticsearch (albiet lucene) indexes a statement is, first it breaks the statement or paragraph into words or tokens, then indexes these words in the inverted index for that particular field. This process is called Analysis and that this would only be applicable on text datatype.
So now you only get the documents if these tokens are available in inverted index.
By default, standard analyzer would be applied. What I've done is I've created my own analyzer and used Ngram Tokenizer which would be creating many more tokens than just simply words.
Default Analyzer on Life is beautiful would be life, is, beautiful.
However using Ngrams, the tokens for Life would be lif, ife & life
Mapping:
PUT student_detail
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "ngram",
"min_gram": 3,
"max_gram": 4,
"token_chars": [
"letter",
"digit"
]
}
}
}
},
"mappings" : {
"properties" : {
"id" : {
"type" : "long"
},
"name" : {
"type" : "text",
"analyzer": "my_analyzer",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"email" : {
"type" : "text",
"analyzer": "my_analyzer",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"age" : {
"type" : "text" <--- I am not sure why this is text. Change it to long or int. Would leave this to you
},
"status" : {
"type" : "text",
"analyzer": "my_analyzer",
"fields": {
"keyword": {
"type": "keyword"
}
}
},
"tests":{
"type" : "nested"
}
}
}
}
Note that in the above mapping I've created a sibling field in the form of keyword for name, email and status as below:
"name":{
"type":"text",
"analyzer":"my_analyzer",
"fields":{
"keyword":{
"type":"keyword"
}
}
}
Now your query could be as simple as below.
Query:
POST student_detail/_search
{
"query": {
"bool": {
"must": [
{
"match": {
"name": "war" <---- Note this. This would even return documents having "Schwarb"
}
},
{
"match": {
"email": "gmail" <---- Note this
}
},
{
"nested": {
"path": "tests",
"query": {
"bool": {
"must": [
{
"term": {
"tests.test_id": 587
}
},
{
"range": {
"tests.test_score": {
"gte": 5
}
}
}
]
}
}
}
}
]
}
}
}
Note that for exact matches I would make use of Term Queries on keyword fields while for normal searches or LIKE in SQL I would make use of simple Match Queries on text Fields provided they make use of Ngram Tokenizer.
Also note that for >= and <= you would need to make use of Range Query.
Response:
{
"took" : 233,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 3.7260926,
"hits" : [
{
"_index" : "student_detail",
"_type" : "_doc",
"_id" : "1",
"_score" : 3.7260926,
"_source" : {
"id" : 123,
"name" : "Schwarb",
"email" : "abc#gmail.com",
"status" : "current",
"age" : 14,
"tests" : [
{
"test_id" : 587,
"test_score" : 10
},
{
"test_id" : 588,
"test_score" : 6
}
]
}
}
]
}
}
Note that I observe the document you've mentioned in your question, in my response when I run the query.
Please do read the links I've shared. It is vital that you understand the concepts. Hope this helps!

Elasticsearch nested geo-shape query

Suppose I have the following mapping:
"mappings": {
"doc": {
"properties": {
"name": {
"type": "text"
},
"location": {
"type": "nested",
"properties": {
"point": {
"type": "geo_shape"
}
}
}
}
}
}
}
There is one document in the index:
POST /example/doc?refresh
{
"name": "Wind & Wetter, Berlin, Germany",
"location": {
"type": "point",
"coordinates": [13.400544, 52.530286]
}
}
How can I make a nested geo-shape query?
Example of usual geo-shape query from the documentation (the "bool" block can be skipped):
{
"query":{
"bool": {
"must": {
"match_all": {}
},
"filter": {
"geo_shape": {
"location": {
"shape": {
"type": "envelope",
"coordinates" : [[13.0, 53.0], [14.0, 52.0]]
},
"relation": "within"
}
}
}
}
}
}
Example of a nested query is:
{
"query": {
"nested" : {
"path" : "obj1",
"score_mode" : "avg",
"query" : {
"bool" : {
"must" : [
{ "match" : {"obj1.name" : "blue"} },
{ "range" : {"obj1.count" : {"gt" : 5}} }
]
}
}
}
}
}
Now how to combine them? In the documentation it is mentioned that nested filter has been replaced by nested query. And that it behaves as a query in “query context” and as a filter in “filter context”.
If I try query for intersect with the point:
{
"query": {
"nested": {
"path": "location",
"query": {
"geo_shape": {
"location.point": {
"shape": {
"type": "point",
"coordinates": [
13.400544,
52.530286
]
},
"relation": "disjoint"
}
}
}
}
}
}
I still get back the document even if relation is "disjoint", so it's not correct. I tried different combinations, with "bool" and "filter", etc. but query is ignored, returning the whole index. Maybe it's impossible with this type of mapping?
Clearly I am missing something here. Can somebody help me out with that, please? Any help is greatly appreciated.

Elasticsearch: How to get an exact match in a nested field

The mapping contains nested fields which shouldn't be analyzed (not sure if the 'not_analyzed' value is accurate). Is it possible to do an exact match on a nested field? In the query below the "metadata.value": "2014.NWJSD.47" still gets analyzed. Elasticsearch breaks up the string into several terms ("2014", "NWJSD", "47"). I tried to use "term" instead of "match" but this didn't return any result.
"mappings" : {
"metadata" : {
"type" : "nested",
"properties" : {
"name" : {
"type" : "text",
"index" : "not_analyzed"
},
"value" : {
"type" : "text",
"index" : "not_analyzed"
}
}
}
}
The Query:
"query": {
"bool": {
"must": [
{
"nested": {
"path": "metadata",
"query": {
"bool": {
"must": [
{
"match": {
"metadata.name": "number"
}
},
{
"match": {
"metadata.value": "2014.NWJSD.47"
}
}
]
}
}
}
}
]
}
}
Try to use keyword instead of text in your mapping like:
{
"mappings": {
"your_type_name": {
"properties": {
"metadata" : {
"type" : "nested",
"properties" : {
"name" : {
"type" : "keyword"
},
"value" : {
"type" :"keyword"
}
}
}
}
}
}
}
These fields won't be analyzed. Then you should reindex your data and to query your data you should replace match (which is analyzed query) with term.
{
"query": {
"bool": {
"must": [
{
"nested": {
"path": "metadata",
"query": {
"bool": {
"must": [
{
"term": {
"metadata.name": "number"
}
},
{
"term": {
"metadata.value": "2014.NWJSD.47"
}
}
]
}
}
}
}
]
}
}
}
I think you are looking for a query string query.
You can freely disable "analyze" option for that field in mapping option and reindex everything again but you could also check this query out:
as written here:
GET /_search
{
"query": {
"query_string" : {
"query" : "your string"
}
}
}

Highlighting on has_child query

In some of our types, we have a parent child setup and we want to search on parent fields and also on the child fields (and return parent) and we do query like below. When there is a has_child match is there any way to get highlighting information from the child match even though the parent is being returned. As an example, if we have mapping like the following:
PUT nested2
{
"mappings":{
"discussion":{
"properties" : {
"title":{
"type":"string"
}
}
},
"discussionPost":{
"_parent":{
"type" : "discussion"
},
"properties" : {
"post" : {
"type" : "string"
}
}
}
}
}
And we issue a query like below, highlight information is returned if there is a match on parent field but not if the parent is being returned due to a has_child match:
POST nested2/discussion/_search
{
"query": {
"bool": {
"should": [
{
"prefix": {
"_all" : "cat"
}
},
{
"has_child" : {
"type" : "discussionPost",
"score_mode" : "sum",
"query" : {
"prefix": {
"_all" : "cat"
}
}
}
}
],
"minimum_should_match": 1
}
},
"highlight":{
"fields":{
"*":{}
}
}
}
Is it possible to get highlight information on what matched in the child when has_child query is being issued on the parent?
Regards
LT
It is possible to do this using inner_hits inside the has_child query clause:
{
"query": {
"bool": {
"should": [
{
"has_child" : {
"inner_hits": {
"_source": false,
"highlight":{
"order": "score",
"fields": {"*":{}}
}
},
"type" : "discussionPost",
"score_mode" : "sum",
"query" : {
"prefix": {
"_all" : "cat"
}
}
}
}
],
"minimum_should_match": 1
}
}
}

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