elasticsearch combine multiple queries - elasticsearch

I have an elasticsearch index for storing information about people.
To find specific persons I have some queries, each of them works alone but when I combine them using Bool Query I get an error.
One of the queries is a fuzzy search for the name
{
"query": {
"fuzzy_like_this": {
"fields": [
"firstname",
"lastname"
],
"like_text": "Peter"
}
}
}
Another query is for searching people who are born in a specific date range
{
"query": {
"range": {
"birthdate": {
"from": "1988-12-30",
"to": "1993-12-30"
}
}
}
}
Now I want to combine these two queries. My bool query:
{
"query": {
"bool": {
"must": [
{
"query": {
"fuzzy_like_this": {
"fields": [
"firstname",
"lastname"
],
"like_text": "Peter"
}
}
},
{
"query": {
"range": {
"birthdate": {
"from": "1988-12-30",
"to": "1993-12-30"
}
}
}
}
]
}
}
}
Although both queries work fine when I use them separately, when combining them I get an error.
There are people in my index whose firstname is Peter AND are born in this date range, but even if there were no people found I should get 0 results instead of an error.
The error says:
"error": "SearchPhaseExecutionException[Failed to execute phase [query], all shards failed;
nested: QueryParsingException[[indexname] No query registered for [query]]
Is combining queries the way I want to not possible with a bool query or did I just use the wrong syntax?

I think that you have a syntax error, the keyword query is not needed for queries that belong to must. In other words, it should be as follows:
{
"query": {
"bool": {
"must": [
{
"fuzzy_like_this": {
"fields": [
"firstname",
"lastname"
],
"like_text": "Peter"
}
},
{
"range": {
"birthdate": {
"from": "1988-12-30",
"to": "1993-12-30"
}
}
}
]
}
}
}
More info about boolean queries here

Related

Multi match query with terms lookup searching multiple indices elasticsearch 6.x

All,
I am working on building a NEST 6.x query that takes a serach term and looks in different fields in different indices.
This is the one I got so far but is not returning any results that I am expecting.
Please see the details below
Indices used
dev-sample-search
user-agents-search
The way the search should work is as follows.
The value in the query field(27921093) is searched against the
fields agentNumber, customerName, fileNumber, documentid(These are all
analyzed fileds).
The search should limit the documents to the agentNumbers the user
sampleuser#gmail.com has access to( sample data for
user-agents-search) is added below.
agentNumber, customerName, fileNumber, documentid and status are
part of the index dev-sample-search.
status field is defined as a keyword.
The fields in the user-agents-search index are all keywords
Sample user-agents-search index data:
{
"id": "sampleuser#gmail.com"",
"user": "sampleuser#gmail.com"",
"agentNumber": [
"123.456.789",
"1011.12.13.14"
]
}
Sample dev-sample-search index data:
{
"agentNumber": "123.456.789",
"customerName": "Bank of america",
"fileNumber":"test_file_1123",
"documentid":"1234456789"
}
GET dev-sample-search/_search
{
"from": 0,
"size": 10,
"query": {
"bool": {
"must": [
{
"multi_match": {
"type": "best_fields",
"query": "27921093",
"operator": "and",
"fields": [
"agentNumber",
"customerName",
"fileNumber",
"documentid^10"
]
}
}
],
"filter": [
{
"bool": {
"must": [
{
"terms": {
"agentNumber": {
"index": "user-agents-search",
"type": "_doc",
"user": "sampleuser#gmail.com",
"path": "agentNumber"
}
}
},
{
"bool": {
"must_not": [
{
"terms": {
"status": {
"value": "pending"
}
}
},
{
"term": {
"status": {
"value": "cancelled"
}
}
},
{
"term": {
"status": {
"value": "app cancelled"
}
}
}
],
"should": [
{
"term": {
"status": {
"value": "active"
}
}
},
{
"term": {
"status": {
"value": "terminated"
}
}
}
]
}
}
]
}
}
]
}
}
}
I see a couple of things that you may want to look at:
In the terms lookup query, "user": "sampleuser#gmail.com", should be "id": "sampleuser#gmail.com",.
If at least one should clause in the filter clause should match, set "minimum_should_match" : 1 on the bool query containing the should clause

elasticsearch multi field query is not working as expected

I've been facing some issues with multi field elasticsearch query. I am trying to query all the documents which matches the field called func_name to two hard coded strings, even though my index has documents with both these function names, but the query result is always fetching only one func_name. So far I have tried following queries.
1) Following returns only one function match, even though the documents have another function as well
GET /_search
{
"query": {
"multi_match": {
"query": "FEM_DS_GetTunerStatusInfo MDM_TunerStatusPrint",
"operator": "OR",
"fields": [
"func_name"
]
}
}
}
2) following intermittently gives me both the functions.
GET /_search
{
"query": {
"match": {
"func_name": {
"query": "MDM_TunerStatusPrint FEM_DS_GetTunerStatusInfo",
"operator": "or"
}
}
}
}
3) Following returns only one function match, even though the documents have another function as well
{
"query": {
"bool": {
"should": [
{ "match": { "func_name": "FEM_DS_GetTunerStatusInfo" }},
{ "match": { "func_name": "MDM_TunerStatusPrint" }}
]
}
}
}
Any help is much appreciated.
Thanks for your reply. Lets assume that I have following kind of documents in my elasticsearch. I want my search to return first two documents out of all as they matches my func_name.
{
"_index": "diag-178999",
"_source": {
"severity": "MIL",
"t_id": "03468500",
"p_id": "000007c6",
"func_name": "MDM_TunerStatusPrint",
"timestamp": "2017-06-01T02:04:51.000Z"
}
},
{
"_index": "diag-344563",
"_source": {
"t_id": "03468500",
"p_id": "000007c6",
"func_name": "FEM_DS_GetTunerStatusInfo",
"timestamp": "2017-07-20T02:04:51.000Z"
}
},
{
"_index": "diag-101010",
"_source": {
"severity": "MIL",
"t_id": "03468500",
"p_id": "000007c6",
"func_name": "some_func",
"timestamp": "2017-09-15T02:04:51.000Z"
}
The "two best ways" to request your ES is to filter by terms on a particular field or to aggregate your queries so that you can rename the field, apply multiple rules, and give a more understandable format to your response
See : https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html and the other doc page is here, very useful :
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations.html
In your case, you should do :
{
"from" : 0, "size" : 2,
"query": {
"filter": {
"bool": {
"must": {
"term": {
"func_name" : "FEM_DS_GetTunerStatusInfo OR MDM_TunerStatusPrint",
}
}
}
}
}
}
OR
"aggs": {
"aggregationName": {
"terms": {
"func_name" : "FEM_DS_GetTunerStatusInfo OR MDM_TunerStatusPrint"
}
}
}
}
The aggregation at the end is just here to show you how to do the same thing as your query filter. Let me know if it's working :)
Best regards
As I understand, you should use filtered query to match any document with one of the values of func_name mentioned above:
{
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"terms": {
"func_name": [
"FEM_DS_GetTunerStatusInfo",
"MDM_TunerStatusPrint"
]
}
}
]
}
}
}
}
}
See:
Filtered Query, Temrs Query
UPDATE in ES 5.0:
{
"query": {
"bool": {
"must": [
{
"terms": {
"func_name": [
"FEM_DS_GetTunerStatusInfo",
"MDM_TunerStatusPrint"
]
}
}
]
}
}
}
See: this answer

Elastic search bool query

My objective is to find out most recent 10 documents which match message id as MSG-1013 and Severity field must be info. Both conditions should satisfied and match text should be exact. I have tried with search query below but it does not give me expected results. What am I doing wrong here ?
{
"size": 10,
"query": {
"bool": {
"must": [
{
"match": { "messageId": "MSG-1013" }
},
{
"match": { "Severity": "Info" }
}
]
}
}
}
If I have understood you correctly, you want to find the top 10 (recent) documents having exactly fields "messageId" and "Severity". I assume, you don't need a score because your score seems to be the the document timestamp or something else like a date field. For this purpose, you could use the bool filter in combination with a sort query.
{
"query": {
"bool": {
"filter": [
{ "term": { "messageId": "MSG-1013" } },
{ "term": { "Severity": "Info" } }
]
}
},
"sort" : [
{ "documentTimestamp" : {"order" : "desc"}}
],
"size": 10
}

Elasticsearch - Aggregations on part of bool query

Say I have this bool query:
"bool" : {
"should" : [
{ "term" : { "FirstName" : "Sandra" } },
{ "term" : { "LastName" : "Jones" } }
],
"minimum_should_match" : 1
}
meaning I want to match all the people with first name Sandra OR last name Jones.
Now, is there any way that I can get perform an aggregation on all the documents that matched the first term only?
For example, I want to get all of the unique values of "Prizes" that anybody named Sandra has. Normally I'd just do:
"query": {
"match": {
"FirstName": "Sandra"
}
},
"aggs": {
"Prizes": {
"terms": {
"field": "Prizes"
}
}
}
Is there any way to combine the two so I only have to perform a single query which returns all of the people with first name Sandra or last name Jones, AND an aggregation only on the people with first name Sandra?
Thanks alot!
Use post_filter.
Please refer the following query. Post_filter will make sure that your bool should clause don't effect your aggregation scope.
Aggregations are filtered based on main query as well, but they are unaffected by post_filter. Please refer to the link
{
"from": 0,
"size": 20,
"aggs": {
"filtered_lastname": {
"filter": {
"query": {
"match": {
"FirstName": "sandra"
}
}
},
"aggs": {
"prizes": {
"terms": {
"field": "Prizes",
"size": 10
}
}
}
}
},
"post_filter": {
"bool": {
"should": [{
"term": {
"FirstName": "Sandra"
}
}, {
"term": {
"LastName": "Jones"
}
}],
"minimum_should_match": 1
}
}
}
Running a filter inside the aggs before aggregating on prizes can help you achieve your desired usecase.
Thanks
Hope this helps

Elastic Search : Match Query not working in Nested Bool Filters

I am able to get data for the following elastic search query :
{
"query": {
"filtered": {
"query": [],
"filter": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"term": {
"gender": "malE"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
]
}
}
}
}
}
However, If I query using "match" - I get error message with 400 status response
{
"query": {
"filtered": {
"query": [],
"filter": {
"bool": {
"must": [
{
"bool": {
"should": [
{
"match": {
"gender": "malE"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
]
}
}
}
}
}
Is match query not supported in nested bool filters ?
Since the term query looks for the exact term in the field’s inverted index and I want to query gender data as case_insensitive field - Which approach shall I try ?
Settings of the index :
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"analyzer_keyword": {
"tokenizer": "keyword",
"filter": "lowercase"
}
}
}
}
}
}
Mapping for field Gender:
{"type":"string","analyzer":"analyzer_keyword"}
The reason you're getting an error 400 is because there is no match filter, only match queries, even though there are both term queries and term filters.
Your query can be as simple as this, i.e. no need for a filtered query, simply put your term and match queries into a bool/should:
{
"query": {
"bool": {
"should": [
{
"match": {
"gender": "male"
}
},
{
"term": {
"sentiment": "positive"
}
}
]
}
}
}
This answer is for ElasticSearch 7.x. As I understand from the question, you would like to use a match query for the gender field and a term query for the sentiment field. The mappings for each of these field should look like below:
"sentiment": {
"type": "keyword"
},
"gender": {
"type": "text"
}
The corresponding search API would be:
"query": {
"bool": {
"must": [
{
"terms": {
"sentiment": [
"very positive", "positive"
]
}
},
{
"match": {
"gender": "malE"
}
}
]
}
}
This search API returns all the documents where gender is "Male"/"MALE"/"mALe" etc. So, you may have indexed the gender field holding "mALe", but, the match query for "gender": "malE" will still be able to retrieve it. In the latest version of ElasticSearch, if the query is a match type, the value (which is "gender": "malE") will be automatically lower cased internally before search begins. But, it should not be that tough for a client of the API to pass a lowercase to the match query at the onset itself. Coming to the sentiment field, since, its a keyword field, you can search for values that contain spaces too like very positive.

Resources