I'm new to elasticsearch. What my business needs is that I should also do a partial matching on searchable fields I ended up with wildcard queries. my query is like this :
{
"query" : {
"wildcard" : "*search_text_here*"
}
}
Suppose that I'm searching for Red Flowers before the above query I was using an analyzed match query which provided me with both results for Red and Flowers lonely. but now my query only works when both Red Flowers are present together.
Use match phrase query as shown below for more information refer the ES doc:
GET /my_index/my_type/_search
{
"query": {
"match_phrase": {
"title": "red floewers"
}
}
}
Related
Hi i have a model which contains OrderNumber:540. I have to add partial search in params like if i send 5 in params it should shows all the results where OrderNumber started with 5. i found the solution with $where but i am getting an error of error MongoError: $where not allowed in this atlas tier
i have an api like /getPurchaseOrdersBySupplierId/:id/:po if po is 5 then it must show all the results that is starting with 5...
OrderNumber: req.params.po})```
please suggest me the method for partial search by int. $where is not working in my case. need some other suggestion
You can use $toString to parse values to string and then search using $regex like this:
db.collection.aggregate([
{
"$addFields": {
"key": {
"$toString": "$key"
}
}
},
{
"$match": {
"key": {
"$regex": "^"+req.params.po
}
}
}
])
Example here
Working on Elasticsearch, my use case is very straight forward. When a user types in a search box I want to search all of my data set irrespective of field or column or any condition (search all data and provide all occurrences of searched word in documents).
This might be available in their documentation but I'm not able to understand it. Can somebody explain on this?
The easiest way to search across all fields in an index is to use the _all field.
The _all field is a catch-all field which concatenates the values of all of the other fields into one big string, using space as a delimiter, which is then analyzed and indexed, but not stored.
For example:
PUT my_index/user/1
{
"first_name": "John",
"last_name": "Smith",
"date_of_birth": "1970-10-24"
}
GET my_index/_search
{
"query": {
"match": {
"_all": "john smith 1970"
}
}
}
Highlighting is supported so matching occurrences can be returned in your search results.
Drawbacks
There are two main drawbacks to this approach:
Additional disk space and memory are needed to store the _all field
You lose flexibility in how the data and search terms are analysed
A better approach is to disable the _all field and instead list out the fields you are interested in:
GET /_search
{
"query": {
"query_string" : {
"query" : "this AND that OR thus",
"fields":[
"name",
"addressline1",
"dob",
"telephone",
"country",
"zipcode"
]
}
}
}
Query_string (link) can do this job for u .
It support partial search effectively , here is my analysis https://stackoverflow.com/a/43321606/2357869 .
Query_string is more powerful than match , term and wildcard query .
Scenario 1 - Suppose u want to search "Hello" :-
Then go with :-
{
"query": {
"query_string": {"query": "*Hello*" }
}
}
It will search all words like ABCHello , HelloABC , ABCHeloABC
By default it will search hello in all fields (_all)
2) Scenario 2 - Suppose u want to search "Hello" or "World" :-
Then go with :-
{
"query": {
"query_string": {"query": "*Hello* *World*" }
}
}
It will search all words like ABCHello , HelloABC , ABCHelloABC , ABCWorldABC ,ABChello ,ABCworldABC etc.
it will search like Hello OR World , so whichever word having Hello Or world , it wiil give .
By default query_string (link) use default operator OR , u can change that .
I am new to ES. I am having trouble finding exact phrase matches.
Let's assume my index has a field called movie_name.
Let's assume I have 3 documents with the following values
movie_name = Mad Max
movie_name = mad max
movie_name = mad max 3d
If my search query is Mad Max, I want the first 2 documents to be returned but not the 3rd.
If I do the "not_analyzed" solution I will get only document 1 but not 2.
What am I missing?
I was able to do it using the following commands, basically create a custom analyzer, use the keyword tokenizer to prevent tokenization. Then use the analyzer in the "mappings" for the desired field, in this case "movie_name".
PUT /movie
{
"settings":{
"index":{
"analysis":{
"analyzer":{
"keylower":{
"tokenizer":"keyword",
"filter":"lowercase"
}
}
}
}
},
"mappings" : {
"search" : {
"properties" : {
"movie_name" : { "type" : "string", "analyzer":"keylower" }
}
}
}
}
Use Phrase matching like this :
{
"query": {
"match_phrase": {
"movie_name": "a"
}
}
}
I have a index document structure like below;
{
"term":"some term",
"inlang":"some lang"
"translations" : {
{
"translation":"some translation",
"outlang":"some lang",
"translations" : {
{
"translation":"some translation 1"
"outlang": "some lang 1"
"translations" : {...}
}
}
},
...
}
}
I want to find a translation in such documents. However, this translation can exists at any level of this document. Is it possible to search term dynamically by using elasticsearch?
For example,
{
"query": {
"*.translation":"searchterm"
}
}
Thanks in advance
I have managed to do that with following query;
{
"query": {
"query_string": {
"query": "someterm",
"fields": ["*.translation"]
}
}
}
or
{
"query": {
"multi_match": {
"query": "someterm",
"fields": ["*.translation"]
}
}
}
You can see elasticsearch google group conversation here
No, I do not believe this functionality is built into ElasticSearch at the moment. This answer suggests you could build the functionality with a script, but it would be super slow.
In general, ES doesn't play nicely with nested data. It supports nested fields, but many of the more advanced search functionality isn't capable of operating on complex nested data. My suggestion is to denormalize your data so that every translation is represented by a single item in the index, and link between them with ID numbers.
Let's say that I store documents like this in ElasticSearch:
{
'name':'user name',
'age':43,
'location':'CA, USA',
'bio':'into java, scala, python ..etc.',
'tags':['java','scala','python','django','lift']
}
And let's say that I search using location=CA, how can I sort the results according to the number of the items in 'tags'?
I would like to list the people with the most number of tag in the first page.
You can do it indexing an additional field which contains the number of tags, on which you can then easily sort your results. Otherwise, if you are willing to pay a little performance cost at query time there's a nice solution that doesn't require to reindex your data: you can sort based on a script like this:
{
"query" : {
"match_all" : {}
},
"sort" : {
"_script" : {
"script" : "doc['tags'].values.length",
"type" : "number",
"order" : "asc"
}
}
}
As you can read from the script based sorting section:
Note, it is recommended, for single custom based script based sorting,
to use custom_score query instead as sorting based on score is faster.
That means that it'd be better to use a custom score query to influence your score, and then sort by score, like this:
{
"query" : {
"custom_score" : {
"query" : {
"match_all" : {}
},
"script" : "_score * doc['tags'].values.length"
}
}
}