Combining and with or conditions - elasticsearch

I stuck with a query which has to combine some conditions.
this properties of the catalog are the following
_id:integer
parentID: integer
path: string
level: integer
i have absolutely no clue how to combine them, so that the query returns what I need.
a) _id has to be one of a given list ("_id": ["7","10"]) OR
b) parentID has to be of a given integer ("_parentID": "1") OR
c) path has to match a special pattern ("regexp": {"path": "/foobar.*"}) AND level has be between two integer ("range": {"level": {"gte": 2, "lte": 3 } })
Additionaly all entries have to be from one defined catalog
I will not write down all my attempts. I tried to use bool query with must and should, but this does not apply c):
{
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"type": {
"value": "category"
}
}
],
"should": [
{
"regexp": {
"path": "/foobar.*"
}
},
{
"range": {
"level": {
"gte": 2,
"lte": 3
}
}
},
{
"term": {
"_id": [
"7",
"10"
]
}
}
]
}
}
}
}
}
what is the best way to combine and and or conditions? i am kind of lost.

I think this should be pretty darn close to what you need.
GET devdev/alert/_search
{
"filter": {
"or": {
"filters": [
{
"terms": {
"_id": [
"eee75eJpRua4HasVzz0PeA",
"VALUE2"
]
}
},
{
"term": {
"_parentID": "SE.SE.0000"
}
},
{
"and": {
"filters": [
{
"term": {
"regexp": "foobar"
}
},
{
"range": {
"level": {
"from": 2,
"to": 3
}
}
}
]
}
}
]
}
}
}

Related

Elasticsearch Add additional condition if type is different

GET test/_search
{
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"bool": {
"must": [
{
"term": {
"fragmentId": "1"
}
},
{
"term": {
"type": "fragment"
}
}
]
}
},
{
"bool": {
"must": [
{
"term": {
"fragmentId": "1"
}
},
{
"term": {
"type": "cf"
}
},
{
"range" :{
"start": {
"gte": 1,
"lte": 5
}
}
}
]
}
}
]
}
}
}
I am looking for two documents, one which has fragment id = 1, and type = fragment, whereas another where fragment id = 1, type = "cf" and start between 1 and 5.
The above query is doing the job, but I need to write type and fragment id twice. Is there a way I can add range condition only when the type is cf, basically clubbing both bools in one ?
This is the query you're looking for:
{
"query": {
"bool": {
"filter": [
{
"term": {
"fragmentId": "1"
}
}
],
"minimum_should_match": 1,
"should": [
{
"term": {
"type": "fragment"
}
},
{
"bool": {
"filter": [
{
"term": {
"type": "cf"
}
},
{
"range": {
"start": {
"gte": 1,
"lte": 5
}
}
}
]
}
}
]
}
}
}

If Else Elasticsearch

I have two sets of documents, which are joined by fragmentId. I have written a query that pulls both documents, but I am thinking is there any other way to write it.
first set Document - There could be only one document which has type = fragment and fragmentId = 1
{
"fragmentId": "1",
"type" : "fragment"
}
The second kind of documents - There could be multiple such documents, separated by start and end values. In the query, I will be passing a value and only document inside that range should come.
Doc-1
{
"fragmentId" : "1",
"type": "cf",
"start": 1,
"end": 5
}
Doc- 2
{
"fragmentId" : "1",
"type": "cf",
"start": 6,
"end": 10
}
In the result, I want the first set document, then from the second set only the document which has a specific start and end values.
Here is the query, which is working for me-
GET test/_search
{
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"bool": {
"must": [
{
"term": {
"fragmentId": "1"
}
},
{
"term": {
"type": "fragment"
}
}
]
}
},
{
"bool": {
"must": [
{
"term": {
"fragmentId": "1"
}
},
{
"term": {
"type": "cf"
}
},
{
"range" :{
"start": {
"gte": 1,
"lte": 5
}
}
}
]
}
}
]
}
}
}
Is there a way to re-write this query in more simple form, so that first document is always picked, with the range matching document from the second set, basically a join operation on fragmentId?
Are you looking for something like this?
GET test/_search
{
"query": {
"bool": {
"must": [
{
"term": {
"fragmentId": "1"
}
},
{
"bool": {
"minimum_should_match": 1,
"should": [
{
"term": {
"type": "fragment"
}
},
{
"bool": {
"must": [
{
"term": {
"type": "cf"
}
},
{
"range": {
"start": {
"gte": 1,
"lte": 5
}
}
}
]
}
}
]
}
}
]
}
}
}
This query translates to :
(fragmentId = 1 AND (type = fragment OR (type = cf AND start is within 1 and 5)))

Using multiple Should queries

I want to get docs that are similar to multiple "groups" but separately. Each group has it's own rules (terms).
When I try to use more than one Should query inside a "bool" I get items that are a mix of both Should's terms.
I want to use 1 query total and not msearch for example.
Can someone please help me with that?
{
"explain": true,
"query": {
"filtered": {
"filter": {
"bool": {
"must_not": [
{
"term": {
"p_id": "123"
}
},
{
"term": {
"p_id": "124"
}
}
]
}
},
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"bool": {
"minimum_should_match": 1,
"should": [
{
"term": {
"cat": "1"
}
},
{
"term": {
"cat": "2"
}
},
{
"term": {
"keys": "a"
}
},
{
"term": {
"keys": "b"
}
}
]
}
},
{
"bool": {
"minimum_should_match": 1,
"should": [
{
"term": {
"cat": "6"
}
},
{
"term": {
"cat": "7"
}
},
{
"term": {
"keys": "r"
}
},
{
"term": {
"keys": "u"
}
}
]
}
}
]
}
}
}
},
"from": 0,
"size": 3
}
You can try using a terms aggregation on multiple fields with scripting and add a top hits aggregation as a sub-aggregation. Be warned this will be pretty slow. Add this after the query/filter and adjust the size parameter as needed
"aggs": {
"Cat_and_Keys": {
"terms": {
"script": "doc['cat'].values + doc['keys'].values"
},
"aggs":{ "separate_docs": {"top_hits":{"size":1 }} }
}
}

Filtered bool vs Bool query : elasticsearch

I have two queries in ES. Both have different turnaround time on the same set of documents. Both are doing the same thing conceptually. I have few doubts
1- What is the difference between these two?
2- Which one is better to use?
3- If both are same why they are performing differently?
1. Filtered bool
{
"from": 0,
"size": 5,
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"called_party_address_number": "1987112602"
}
},
{
"term": {
"original_sender_address_number": "6870340319"
}
},
{
"range": {
"x_event_timestamp": {
"gte": "2016-07-01T00:00:00.000Z",
"lte": "2016-07-30T00:00:00.000Z"
}
}
}
]
}
}
}
},
"sort": [
{
"x_event_timestamp": {
"order": "desc",
"ignore_unmapped": true
}
}
]
}
2. Simple Bool
{
"query": {
"bool": {
"must": [
{
"term": {
"called_party_address_number": "1277478699"
}
},
{
"term": {
"original_sender_address_number": "8020564722"
}
},
{
"term": {
"cause_code": "573"
}
},
{
"range": {
"x_event_timestamp": {
"gt": "2016-07-13T13:51:03.749Z",
"lt": "2016-07-16T13:51:03.749Z"
}
}
}
]
}
},
"from": 0,
"size": 10,
"sort": [
{
"x_event_timestamp": {
"order": "desc",
"ignore_unmapped": true
}
}
]
}
Mapping:
{
"ccp": {
"mappings": {
"type1": {
"properties": {
"original_sender_address_number": {
"type": "string"
},
"called_party_address_number": {
"type": "string"
},
"cause_code": {
"type": "string"
},
"x_event_timestamp": {
"type": "date",
"format": "strict_date_optional_time||epoch_millis"
},
.
.
.
}
}
}
}
}
Update 1:
I tried bool/must query and bool/filter query on same set of data,but I found the strange behaviour
1-
bool/must query is able to search the desired document
{
"query": {
"bool": {
"must": [
{
"term": {
"called_party_address_number": "8701662243"
}
},
{
"term": {
"cause_code": "401"
}
}
]
}
}
}
2-
While bool/filter is not able to search the document. If I remove the second field condition it searches the same record with field2's value as 401.
{
"query": {
"bool": {
"filter": [
{
"term": {
"called_party_address_number": "8701662243"
}
},
{
"term": {
"cause_code": "401"
}
}
]
}
}
}
Update2:
Found a solution of suppressing scoring phase with bool/must query by wrapping it within "constant_score".
{
"query": {
"constant_score": {
"filter": {
"bool": {
"must": [
{
"term": {
"called_party_address_number": "1235235757"
}
},
{
"term": {
"cause_code": "304"
}
}
]
}
}
}
}
}
Record we are trying to match have "called_party_address_number": "1235235757" and "cause_code": "304".
The first one uses the old 1.x query/filter syntax (i.e. filtered queries have been deprecated in favor of bool/filter).
The second one uses the new 2.x syntax but not in a filter context (i.e. you're using bool/must instead of bool/filter). The query with 2.x syntax which is equivalent to your first query (i.e. which runs in a filter context without score calculation = faster) would be this one:
{
"query": {
"bool": {
"filter": [
{
"term": {
"called_party_address_number": "1277478699"
}
},
{
"term": {
"original_sender_address_number": "8020564722"
}
},
{
"term": {
"cause_code": "573"
}
},
{
"range": {
"x_event_timestamp": {
"gt": "2016-07-13T13:51:03.749Z",
"lt": "2016-07-16T13:51:03.749Z"
}
}
}
]
}
},
"from": 0,
"size": 10,
"sort": [
{
"x_event_timestamp": {
"order": "desc",
"ignore_unmapped": true
}
}
]
}

Elasticsearch must_not filter not works with a big bunch of values

I have the next query that include some filters:
{
"from": 0,
"query": {
"function_score": {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"idpais": [
115
]
}
},
{
"term": {
"tipo": [
1
]
}
}
],
"must_not": [
{
"term": {
"idregistro": [
5912471,
3433876,
9814443,
11703069,
6333176,
8288242,
9924922,
6677850,
11852501,
12530205,
4703469,
12776479,
12287659,
11823679,
12456304,
12777457,
10977614,
...
]
}
}
]
}
},
"query": {
"bool": {
"should": [
{
"match_phrase": {
"area": "Coordinator"
}
},
{
"match_phrase": {
"company": {
"boost": 5,
"query": "IBM"
}
}
},
{
"match_phrase": {
"topic": "IT and internet stuff"
}
},
{
"match_phrase": {
"institution": {
"boost": 5,
"query": "University of my city"
}
}
}
]
}
}
}
},
"script_score": {
"params": {
"idpais": 115,
"idprovincia": 0,
"relationships": []
},
"script_id": "ScoreUsuarios"
}
}
},
"size": 24,
"sort": [
{
"_script": {
"order": "desc",
"script_id": "SortUsuarios",
"type": "number"
}
}
]
}
The must_not filter has a big bunch of values to exclude (around 200 values), but it looks like elasticsearch ignores those values and it includes on the result set. If I try to set only a few values (10 to 20 values) then elasticsearch applies the must_not filter.
Exists some restriction a bout the amount of values in the filters? Exists some way to remove a big amount of results from the query?
terms query is used for passing a list of values not term query.You have to use it like below in your must filter.
{
"query": {
"terms": {
"field_name": [
"VALUE1",
"VALUE2"
]
}
}
}

Resources