elasticsearch - Return the tokens of a field - java

How can I have the tokens of a particular field returned in the result
For example, A GET request
curl -XGET 'http://localhost:9200/twitter/tweet/1'
returns
{
"_index" : "twitter",
"_type" : "tweet",
"_id" : "1",
"_source" : {
"user" : "kimchy",
"postDate" : "2009-11-15T14:12:12",
"message" : "trying out Elastic Search"
}
}
I would like to have the tokens of '_source.message' field included in the result

There is also another way to do it using the following script_fields script:
curl -H 'Content-Type: application/json' -XPOST 'http://localhost:9200/test-idx/_search?pretty=true' -d '{
"query" : {
"match_all" : { }
},
"script_fields": {
"terms" : {
"script": "doc[field].values",
"params": {
"field": "message"
}
}
}
}'
It's important to note that while this script returns the actual terms that were indexed, it also caches all field values and on large indices can use a lot of memory. So, on large indices, it might be more useful to retrieve field values from stored fields or source and reparse them again on the fly using the following MVEL script:
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;
import java.io.StringReader;
// Cache analyzer for further use
cachedAnalyzer=(isdef cachedAnalyzer)?cachedAnalyzer:doc.mapperService().documentMapper(doc._type.value).mappers().indexAnalyzer();
terms=[];
// Get value from Fields Lookup
//val=_fields[field].values;
// Get value from Source Lookup
val=_source[field];
if(val != null) {
tokenStream=cachedAnalyzer.tokenStream(field, new StringReader(val));
CharTermAttribute termAttribute = tokenStream.addAttribute(CharTermAttribute);
while(tokenStream.incrementToken()) {
terms.add(termAttribute.toString())
};
tokenStream.close();
}
terms
This MVEL script can be stored as config/scripts/analyze.mvel and used with the following query:
curl 'http://localhost:9200/test-idx/_search?pretty=true' -d '{
"query" : {
"match_all" : { }
},
"script_fields": {
"terms" : {
"script": "analyze",
"params": {
"field": "message"
}
}
}
}'

If you mean the tokens that have been indexed you can make a terms facet on the message field. Increase the size value in order to get more entries back, or set to 0 to get all terms.
Lucene provides the ability to store the term vectors, but there's no way to have access to it with elasticsearch by now (as far as I know).
Why do you need that? If you only want to check what you're indexing you can have a look at the analyze api.

Nowadays, it's possible with the Term vectors API:
curl http://localhost:9200/twitter/_termvectors/1?fields=message
Result:
{
"_index": "twitter",
"_id": "1",
"_version": 1,
"found": true,
"took": 0,
"term_vectors": {
"message": {
"field_statistics": {
"sum_doc_freq": 4,
"doc_count": 1,
"sum_ttf": 4
},
"terms": {
"elastic": {
"term_freq": 1,
"tokens": [
{
"position": 2,
"start_offset": 11,
"end_offset": 18
}
]
},
"out": {
"term_freq": 1,
"tokens": [
{
"position": 1,
"start_offset": 7,
"end_offset": 10
}
]
},
"search": {
"term_freq": 1,
"tokens": [
{
"position": 3,
"start_offset": 19,
"end_offset": 25
}
]
},
"trying": {
"term_freq": 1,
"tokens": [
{
"position": 0,
"start_offset": 0,
"end_offset": 6
}
]
}
}
}
}
}
Note: Mapping types (here: tweets) have been removed in Elasticsearch 8.x (see migration guide).

Related

ElasticSearch range query in a paragraph

I have a field called Description which is a text field and has data like:
This is a good thing for versions before 3.2 but bad for 3.5 and later
I want to run range query on this type of text. I know that for a field containing only Dates/Age(Numbers) or even String Ids, we can use queries like
{
"query": {
"range" : {
"age" : {
"gte" : 10,
"lte" : 20,
"boost" : 2.0
}
}
}
}
But i have a mixed field like mentioned above and I need to perform range query on that. Also, i cannot change the index structure. I can only perform queries or do some post processing after retrieving results. So anyone has any idea how to run this type of query, or even obtain my goal after getting results in the post processing? I am using Java.
I hope i fully understand what you are looking for.
I've managed to create a simple working example.
Mappings
Using char_group tokenizer:
The char_group tokenizer breaks text into terms whenever it encounters a character which is in a defined set. It is mostly useful for cases where a simple custom tokenization is desired, and the overhead of use of the pattern tokenizer is not acceptable.
Char Group Tokenizer
PUT my_index
{
"settings": {
"analysis": {
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "my_tokenizer"
}
},
"tokenizer": {
"my_tokenizer": {
"type": "char_group",
"tokenize_on_chars": [
"letter",
"whitespace"
]
}
}
}
},
"mappings": {
"properties": {
"text": {
"type": "text",
"fields": {
"digit": {
"type": "text",
"analyzer": "my_analyzer"
}
}
}
}
}
}
Post a few documents
PUT my_index/_doc/1
{
"text": "This is a good thing for versions before 3.2 but bad for 3.5 and later"
}
PUT my_index/_doc/2
{
"text": "This is a good thing for versions before 5 but bad for 6 and later"
}
Search Query
GET my_index/_search
{
"query": {
"range": {
"text.digit": {
"gte": 3.2,
"lte": 3.5
}
}
}
}
Results
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "1",
"_score" : 1.0,
"_source" : {
"text" : "This is a good thing for versions before 3.2 but bad for 3.5 and later"
}
}
]
}
Another Search Query
GET my_index/_search
{
"query": {
"range": {
"text.digit": {
"gt": 3.5
}
}
}
}
Results
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 1.0,
"hits" : [
{
"_index" : "my_index",
"_type" : "_doc",
"_id" : "2",
"_score" : 1.0,
"_source" : {
"text" : "This is a good thing for versions before 5 but bad for 6 and later"
}
}
]
}
Analyze Query
Play with the following query till you get the desired results.
It is already compatible to your example.
This is a good thing for versions before 3.2 but bad for 3.5 and later
POST _analyze
{
"tokenizer": {
"type": "char_group",
"tokenize_on_chars": [
"letter",
"whitespace"
]
},
"text": "This is a good thing for versions before 3.2 but bad for 3.5 and later"
}
Hope this helps

ElasticSearch - fuzzy search java api results are not proper

I have indexed sample documents in elasticsearch and trying to search using fuzzy query. But am not getting any results when am search by using Java fuzzy query api.
Please find my below mapping script :
PUT productcatalog
{
"settings": {
"analysis": {
"analyzer": {
"attr_analyzer": {
"type": "custom",
"tokenizer": "letter",
"char_filter": [
"html_strip"
],
"filter": ["lowercase", "asciifolding", "stemmer_minimal_english"]
}
},
"filter" : {
"stemmer_minimal_english" : {
"type" : "stemmer",
"name" : "minimal_english"
}
}
}
},
"mappings": {
"doc": {
"properties": {
"values": {
"type": "text",
"analyzer": "attr_analyzer"
},
"catalog_type": {
"type": "text"
},
"catalog_id":{
"type": "long"
}
}
}
}
}
Please find my sample data.
PUT productcatalog/doc/1
{
"catalog_id" : "343",
"catalog_type" : "series",
"values" : "Activa Rooftop, valves, VG3000, VG3000FS, butterfly, ball"
}
PUT productcatalog/doc/2
{
"catalog_id" : "12717",
"catalog_type" : "product",
"values" : "Activa Rooftop, valves"
}
Please find my search script :
GET productcatalog/_search
{
"query": {
"match" : {
"values" : {
"query" : " activa rooftop VG3000",
"operator" : "and",
"boost": 1.0,
"fuzziness": 2,
"prefix_length": 0,
"max_expansions": 100
}
}
}
}
Am getting the below results for the above query :
{
"took": 239,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 1,
"max_score": 0.970927,
"hits": [
{
"_index": "productcatalog",
"_type": "doc",
"_id": "1",
"_score": 0.970927,
"_source": {
"catalog_id": "343",
"catalog_type": "series",
"values": "Activa Rooftop, valves, VG3000, VG3000FS, butterfly, ball"
}
}
]
}
}
But if i use the below Java API for the same fuzzy search am not getting any results out of it.
Please find my below Java API query for fuzzy search :
QueryBuilder qb = QueryBuilders.boolQuery()
.must(QueryBuilders.fuzzyQuery("values", keyword).boost(1.0f).prefixLength(0).maxExpansions(100));
Update 1
I have tried with the below query
QueryBuilder qb = QueryBuilders.matchQuery(QueryBuilders.fuzzyQuery("values", keyword).boost(1.0f).prefixLength(0).maxExpansions(100));
But am not able to pass QueryBuilders inside matchQuery. Am getting this suggestion while am writing this query The method matchQuery(String, Object) in the type QueryBuilders is not applicable for the arguments (FuzzyQueryBuilder)
The mentioned java query is not a match query. It's a must query. you should use matchQuery instead of boolQuery().must(QueryBuilders.fuzzyQuery())
Update 1:
fuzzy query is a term query while match query is a full text query.
Also don't forget that in match query the default Operator is or operator which you should change it to and like your dsl query.

Completion Suggester in elasticsearch in mutifield

I'm using elasticsearch for the first time. I'm trying to use completion suggester in multi-field key, although I don't see any error but I don't get the response.
Mapping creation:
PUT /products5/
{
"mappings":{
"products" : {
"properties" : {
"name" : {
"type":"text",
"fields":{
"text":{
"type":"keyword"
},
"suggest":{
"type" : "completion"
}
}
}
}
}
}
}
Indexing:
PUT /products5/product/1
{
"name": "Apple iphone 5"
}
PUT /products5/product/2
{
"name": "iphone 4 16GB"
}
PUT /products5/product/3
{
"name": "iphone 3 SS 16GB black"
}
PUT /products5/product/4
{
"name": "Apple iphone 4 S 16 GB white"
}
PUT /products5/product/5
{
"name": "Apple iphone case"
}
Query:
POST /products5/product/_search
{
"suggest":{
"my-suggestion":{
"prefix":"i",
"completion":{
"field":"name.suggest"
}
}
}
}
Output:
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 0,
"max_score": 0,
"hits": []
},
"suggest": {
"my-suggestion": [
{
"text": "i",
"offset": 0,
"length": 1,
"options": []
}
]
}
}
Please guide me what is the mistake, I tried every possible options.
From the first perspective this looks accurate. Probably the reason why you don't have correct response is that you added documents in the index before you created mapping in the index. And documents are not indexed according to the mapping you specified
I have found an issue in your mapping name. There is an inconsistency between name of the mapping and value which you specifies in the url when you're creating new documents. You create a mapping in the index with the name products. And when you add new documents you're specifying product as a name of the mapping of your index and it doesn't end with s. You have a typo.

Unable to get data from elastic search SearchResponse

I am trying to retrieve the data from SearchResponse class with the above code:
SearchHits searchHits = searchResponse.getHits();
for (SearchHit searchHit : searchHits) {
SearchHitField title = searchHit.field("title");
System.out.println(title.getValue().toString());
}
But I get a null pointer exception in title.getValue() function. The "title" field is definitely there and I can verify that by printing the search response which gives the following output:
{
"took" : 13,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 1,
"max_score" : 1.0,
"hits" : [ {
"_index" : "myIndex",
"_type" : "myTye",
"_id" : "5c849b0f-d72d-4cc9-9b8c-e1201f888f94",
"_score" : 2.4181843,
"_source":{"esId":"100200153", "title":"Book 1"}
}
}
I know that I can retrieve the data with searchHit.getSource() but I am wondering why the above solution isn't working as well.
I think you have to specify .fields(fields) in the request to be able to access the fields part.
For example, if you have a query like this:
{
"query": {
"match_all": {}
}
}
you get in the hits section of the result some fields (_id, _type..., _source).
But, if you have something like this:
{
"query": {
"match_all": {}
},
"fields": ["my_field"]
}
you get back a different result:
"hits": {
"total": 2,
"max_score": 1,
"hits": [
{
"_index": "test_malformed",
"_type": "test",
"_id": "1",
"_score": 1,
"fields": {
"my_field": [
"whatever"
]
}
},
...
You notice there, in the hits you have fields where the field specified in the search request is being returned.
It looks like you are almost there. On each hit, instead of getting the title, get the _source object, then the title field from that source object.

Elastic search tokenizer &filter for Split the given data

I am so tied for split the data for my expectation output. But i could not able to got it. I tried all the Filter and Tokenizer.
I Have Updated setting in elastic search as give below.
{
"settings": {
"analysis": {
"filter": {
"filter_word_delimiter": {
"preserve_original": "true",
"type": "word_delimiter"
}
},
"analyzer": {
"en_us": {
"tokenizer": "keyword",
"filter": [ "filter_word_delimiter","lowercase" ]
}
}
}
}
}
Executed Queries
curl -XGET "XX.XX.XX.XX:9200/keyword/_analyze?pretty=1&analyzer=en_us" -d 'DataGridControl'
Hits value
{
"tokens" : [ {
"token" : "datagridcontrol"
"start_offset" : 0,
"end_offset" : 16,
"type" : "word",
"position" : 1
}, {
"token" : "data",
"start_offset" : 0,
"end_offset" : 4,
"type" : "word",
"position" : 1
}, {
"token" : "grid",
"start_offset" : 4,
"end_offset" : 8,
"type" : "word",
"position" : 2
}, {
"token" : "control",
"start_offset" : 9,
"end_offset" : 16,
"type" : "word",
"position" : 3
} ]
}
Expectation Result like ->
DataGridControl
DataGrid
DataControl
Data
grid
control
What type of tokenizer and Filter add to index setting.
Any help ?
Try this:
{
"settings": {
"analysis": {
"filter": {
"filter_word_delimiter": {
"type": "word_delimiter"
},
"custom_shingle": {
"type": "shingle",
"token_separator":"",
"max_shingle_size":3
}
},
"analyzer": {
"en_us": {
"tokenizer": "keyword",
"filter": [
"filter_word_delimiter",
"custom_shingle",
"lowercase"
]
}
}
}
}
}
and let me know if it gets you any closer.

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