问题
My database is sync with an Elasticsearch to optimize our search results and request faster.
I have an issue querying the users, I want with a query therm look for my users, it can be part of a name, phone, ip, ...
My actual query is
query_string: { fields: ['id', 'email', 'firstName', 'lastName', 'phone', 'ip'], query: `*${escapeElastic(req.query.search.toString().toLowerCase())}*`}
Where req.query.search
is my search and escapeElastic comes from the node module elasticsearch-sanitize
because I had issues with some symbols.
I have some issue for example if I query for an ipv6, I will have query: '*2001\\:0db8*'
but it will not find anything in the database and it should
Other issue if I have someone with firstName john-doe my query will be query: '*john\\-doe*'
and it will not find any result.
Seems that the escape prevent query errors but create some issues in my case.
I do not know if query_string
is the better way to do my request, I am open to suggestions to optimize this query
Thanks
回答1:
I suspect the analyzer on your fields is standard or similar. This means chars like :
and -
were stripped:
GET _analyze
{
"text": "John-Doe",
"analyzer": "standard"
}
showing
{
"tokens" : [
{
"token" : "john",
"start_offset" : 0,
"end_offset" : 4,
"type" : "<ALPHANUM>",
"position" : 0
},
{
"token" : "doe",
"start_offset" : 5,
"end_offset" : 8,
"type" : "<ALPHANUM>",
"position" : 1
}
]
}
Let's create our own analyzer which is going to keep the special chars but lowercase them all other chars the same time:
PUT multisearch
{
"settings": {
"analysis": {
"analyzer": {
"with_special_chars": {
"tokenizer": "whitespace",
"filter": [
"lowercase"
]
}
}
}
},
"mappings": {
"properties": {
"firstName": {
"type": "text",
"fields": {
"with_special_chars": {
"type": "text",
"analyzer": "with_special_chars"
}
}
},
"ip": {
"type": "ip",
"fields": {
"with_special_chars": {
"type": "text",
"analyzer": "with_special_chars"
}
}
}
}
}
}
Ingesting 2 sample docs:
POST multisearch/_doc
{
"ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334"
}
POST multisearch/_doc
{
"firstName": "John-Doe"
}
and applying your query from above:
GET multisearch/_search
{
"query": {
"query_string": {
"fields": [
"id",
"email",
"firstName.with_special_chars",
"lastName",
"phone",
"ip.with_special_chars"
],
"query": "2001\\:0db8* OR john-*"
}
}
}
both hits are returned.
Two remarks: 1) note that we were searching .with_special_chars
instead of the main fields and 2) I've removed the leading wildcard from the ip -- those are highly inefficient.
Final tips since you asked for optimization suggestions: the query could be rewritten as
GET multisearch/_search
{
"query": {
"bool": {
"should": [
{
"term": {
"id": "tegO63EBG_KW3EFnvQF8"
}
},
{
"match": {
"email": "john@doe.com"
}
},
{
"match_phrase_prefix": {
"firstName.with_special_chars": "john-d"
}
},
{
"match_phrase_prefix": {
"firstName.with_special_chars": "john-d"
}
},
{
"match": {
"phone.with_special_chars": "+151351"
}
},
{
"wildcard": {
"ip.with_special_chars": {
"value": "2001\\:0db8*"
}
}
}
]
}
}
}
- Partial
id
matching is probably an overkill -- either theterm
catches it or not email
can be simplymatch
edfirst-
&lastName
: I suspectmatch_phrase_prefix
is more performant thanwildcard
orregexp
so I'd go with that (as long as you don't need the leading*
)phone
can bematch
ed but do make sure special chars can be matched too (if you use the int'l format)- use
wildcard
for theip
-- same syntax as in the query string
Try the above and see if you notice any speed improvements!
来源:https://stackoverflow.com/questions/61640936/elasticsearch-query-string-handle-special-characters