ElasticSearch - Organize search by priority with/without spaces - elasticsearch

Question

I am using elastic 7.15.0.
I want to organize search by priority with/without spaces.
What does it mean?
query - "surf coff"
I want to see records contains or startswith "surf coff" - (SURF COFFEE, SURF CAFFETERIA, SURFCOFFEE MAN)
When records contains or startswith "surf" - (SURF, SURF LOVE, ENDLESS SURF)
When records contains or startswith "coff" - (LOVE COFFEE, COFFEE MAN)
query - "surfcoff"
i want to see records contains or startswith "surfcoff" - (SURF COFFEE, SURF CAFFETERIA, SURFCOFFEE MAN) only.
I created the analyzer with filters:
lowercase
word_delimiter_graph
shingle
edge n gram
pattern replace for spaces
{
"settings":{
"index": {
"max_shingle_diff" : 9,
"max_ngram_diff": 9
},
"analysis":{
"analyzer":{
"word_join_analyzer":{
"tokenizer":"standard",
"filter":[
"lowercase",
"word_delimiter_graph",
"my_shingle",
"my_edge_ngram",
"my_char_filter"
]
}
},
"filter":{
"my_shingle":{
"type":"shingle",
"min_shingle_size": 2,
"max_shingle_size": 10
},
"my_edge_ngram": {
"type": "edge_ngram",
"min_gram": 2,
"max_gram": 10,
"token_chars": ["letter", "digit"]
},
"my_char_filter": {
"type": "pattern_replace",
"pattern": " ",
"replacement": ""
}
}
}
}
}
So when i analyzed text = "SURF COFFEE", i got this result
{
"tokens": [
{
"token": "su",
"start_offset": 0,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "sur",
"start_offset": 0,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "surf",
"start_offset": 0,
"end_offset": 4,
"type": "<ALPHANUM>",
"position": 0
},
{
"token": "su",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "sur",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surf",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surf",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surfc",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surfco",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surfcof",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surfcoff",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "surfcoffe",
"start_offset": 0,
"end_offset": 11,
"type": "shingle",
"position": 0,
"positionLength": 2
},
{
"token": "co",
"start_offset": 5,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "cof",
"start_offset": 5,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "coff",
"start_offset": 5,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "coffe",
"start_offset": 5,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 1
},
{
"token": "coffee",
"start_offset": 5,
"end_offset": 11,
"type": "<ALPHANUM>",
"position": 1
}
]
}
As you can see, there is token "surfcoff".
How my search should be organized?
I've tried to combine approaches by bool should query with -
query_string, match_phrase_prefix, match_prefix and others.
But none of them gave correct results.
Can you please, help me.
How my query should be built?
Or maybe i should try other analyzer filters.
For example query
{
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "surf coff",
"default_field": "text",
"default_operator": "AND"
}
},
{
"query_string": {
"query": "surf",
"default_field": "text"
}
},
{
"query_string": {
"query": "coff",
"default_field": "text"
}
}
]
}
}
}
or this query
{
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "(surf coff) OR (surf) OR (coff)",
"default_field": "text"
}
}
]
}
}
}
or this query
{
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "((surf AND coff)^3 OR (surf)^2 OR (coff)^1)",
"default_field": "text"
}
}
]
}
}
}
or
{
"query": {
"match_bool_prefix" : {
"text" : "surf coff"
}
}
}
gives
SURF COFFEE SURFING NEVER ALONE
CONOSUR COLCHAGUA CONO SUR
SUNRISE CONCHA TORO SUNRISE 300 DAYS
SUN COFFEE
SURF COFFEE PROPAGANDA
....
but its strange for me, i think i misunderstand something.

Answer 1

{
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "(surf* AND coff*)^3 OR (surf*)^2 OR (coff*)^1",
"default_field": "text"
}
}
]
}
}
}
{
"settings":{
"index": {
"max_shingle_diff" : 9,
"max_ngram_diff": 9
},
"analysis":{
"analyzer":{
"word_join_analyzer":{
"tokenizer":"standard",
"filter":[
"lowercase",
"word_delimiter_graph",
"my_shingle",
"my_char_filter"
]
}
},
"filter":{
"my_shingle":{
"type":"shingle",
"min_shingle_size": 2,
"max_shingle_size": 10
},
"my_char_filter": {
"type": "pattern_replace",
"pattern": " ",
"replacement": ""
}
}
}
}
}
removing edge-n-gram and adding wilcard query with priority resolved my question.
But I still don't understand why edge n gram didn't work.

Answer 2

Finally resolved with
"filter":[
"lowercase",
"word_delimiter_graph",
"my_shingle",
"my_edge_ngram",
"my_char_filter"
]
the problem was with search_analyzer, because docs said " Sometimes, though, it can make sense to use a different analyzer at search time, such as when using the edge_ngram tokenizer for autocomplete or when using search-time synonyms."
So i added standard search_analyzer to my text field:
"text": { "type": "text", "analyzer": "word_join_analyzer", "search_analyzer": "standard" }
Search query:
{
"query": {
"bool": {
"should": [
{
"query_string": {
"query": "surf coff",
"default_field": "text"
}
}
]
}
}
}