I have two indices Users and User Appointments, each Appointment has a userID field and appointmentDate.
I want to select all Users that have an appointment for a particular date using a single query. Currently, I do this using two search boolean requests, but it takes too much time for a large number of entries.
First query - get all appointments by date range:
https://opensearchhost:443/user_appointments_index/_search?_source_includes=userIds,appointmentDates
// selects userIDs for appointmentDates
{
"query": {
"bool": {
"must": [
{
"exists": {
"field": "appointmentDates"
}
}
],
"must": [
{
"range": {
"appointmentDates": {
"gte": "2023-02-10",
"lte": "2023-02-11",
"format": "yyyy-MM-dd",
"relation": "within"
}
}
}
]
}
}
// Response returns userIds that participate within the next request:
// selects users by userIds
https://opensearchhost:443/users_index/_search
{
"query": {
"match": {
"terms": {
"userIds.keyword": ["98765", "12345"]
}
}
}
}
}
Any ideas on how to use a multi-search request by combining two queries and having a query similar to RDBMS JOIN between two tables?
Related
I have a situation where I need to do elastic search based on multi-field. For Example: I have multiple fields in my postindex and I want to apply condition on four these fields (i.e. userid, channelid, createat, teamid) to meet my search requirement. When value of all these fields matched then search query displays results and if one of these is not match with values in postindex then it display no result.
I am trying to make a multifield search query for go-elasticsearch to search data from my post index. For the searcquery result four field must match otherwise it display 0 hit/no-result.
So, I think you need to write a following query :
GET postindex/_search
{
"query": {
"bool": {
"minimum_should_match": 1,
"should": [
{
"bool": {
"must": [
{
"term": {
"userid": {
"value": "mcqmycxpyjrddkie9mr13txaqe"
}
}
},
{
"term": {
"channelid": {
"value": "dnoihmrinins3qrm6bb9175ume"
}
}
},
{
"range": {
"createat": {
"gt": 1672909114890
}
}
}
]
}
},
{
"term": {
"teamid": {
"value": "qomrg11o8b8ijxoy8hrcnweoay"
}
}
}
]
}
}
}
In here, there is a bool query with should in parent scope, which is like OR. And inside the should there is another bool query with must which is like AND. We can also write the query shorter, but this will be better for you to understand.
Let says I have an index where I save a million of tweets (original object). I want to get the 90th percentile users based on the number of followers.
I know there is the aggregation "percentile" to do this, but my problem is that ElasticSearch use all documents so I have some users that tweet a lot who noise my calculation.
I want to isolate all unique user then compute the 90th.
The other constraint is that I want to do this in only one or two requests to keep the response lower than 500ms.
I have tried a lot of things and I was able to do this with "scripted_metric" but when my dataset exceed 100k of tweets the performances go down criticaly.
Any advice ?
Additionnal infos :
My index store orginal tweets & retweets based on user search queries
The index is mapped with a dynamic template mapping (No problem with this)
The index contains approximatly 100M
Unfortunately, "top hits" aggregation doesn't accept sub-aggs.
The request I try to achieve is :
{
"collapse": {
"field": "user.id" <--- I want this effect on aggregation
},
"query": {
"bool": {
"must": [
{
"term": {
"metadatas.clientId": {
"value": projectId
}
}
},
{
"match": {
"metadatas.blacklisted": false
}
}
],
"filter": [
{
"range": {
"publishedAt": {
"gte": "now-90d/d"
}
}
}
]
}
},
"aggs":{
"twitter": {
"percentiles": {
"field": "user.followers_count",
"percents": [95]
}
}
},
"size": 0
}
Finally, I figure out to find a workaround.
In percentile aggregation, I can use a script. I use params variable to hold unique keys then return preceding _score.
Without the complete explanation of the computation, I cannot fine tune the behavior of my script. But the result is good enough for me.
"aggs": {
"unique":{
"cardinality": {
"field": "collapse_profile"
}
},
"thresholds":{
"percentiles": {
"field": "user.followers_count",
"percents": [90],
"script": {
"source": """
if(params.keys == null){
params.keys = new HashMap();
}
def key = doc['user.id'].value;
def value = doc['user.followers_count'].value;
if(params.keys[key] == null){
params.keys[key] = _score;
return value;
}
return _score;
""",
"lang": "painless"
}
}
}
}
I'm using Elasticsearch 6.6, trying to extract multiple results/records based on multiple values (email_address) passed to the query (Bool) on a date range. For ex: I want to extract information about few employees based on their email_address (annie#test.com, charles#test.com, heman#test.com) and from the period i.e project_date (2019-01-01).
I did use should expression but unfortunately it's pulling all the records from elasticsearch based on the date range i.e. it's even pulling other employees information from project_date 2019-01-01.
{
"query": {
"bool": {
"should": [
{ "match": { "email_address": "annie#test.com" }},
{ "match": { "email_address": "chalavadi#test.com" }}
],
"filter": [
{ "range": { "project_date": { "gte": "2019-08-01" }}}
]
}
}
}
I also tried must expression but getting no result. Could you please help me on finding employees using their email_address with the date range?
Thanks in advance.
Should(Or) clauses are optional
Quoting from this article.
"In a query, if must and filter queries are present, the should query occurrence then helps to influence the score. However, if bool query is in a filter context or has neither must nor filter queries, then at least one of the should queries must match a document."
So in your query should is only influencing the score and not actually filtering the document. You must wrap should in must, or move it in filter(if scoring not required).
GET employeeindex/_search
{
"query": {
"bool": {
"filter": {
"range": {
"projectdate": {
"gte": "2019-01-01"
}
}
},
"must": [
{
"bool": {
"should": [
{
"term": {
"email.raw": "abc#text.com"
}
},
{
"term": {
"email.raw": "efg#text.com"
}
}
]
}
}
]
}
}
}
You can also replace should clause with terms clause as in #AlwaysSunny's answer.
You can do it with terms and range along with your existing query inside filter in more shorter way. Your existing query doesn't work as expected because of should clause, it makes your filter weaker. Read more here:
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
{
"query": {
"bool": {
"filter": [
{
"terms": {
"email_address.keyword": [
"annie#test.com", "chalavedi#test.com"
]
}
},
{
"range": {
"project_date": {
"gte": "2019-08-01"
}
}
}
]
}
}
}
I have an index in Elasticsearch with users' posts. I want to retrieve user_id from this index, if for given date range, there are at least X posts. Otherwise to skip such posts.
Anyway I can achieve it in ES or I have to get all entities and handle them later?
Trawa ;)
To answer your question I'll assume you have the fields user and datetime in your mapping.
You can get the requested data like so:
Get the list of users who have more then X (i.e X=100) posts by given date range - aggregate by user name for specific date range:
{
"size": 0,
"query": {
"bool": {
"must": [
{
"range": {
"datetime": {
"gte": "2017-05-01",
"lt": "2017-06-01"
}
}
}
]
}
},
"aggregations": {
"users": {
"terms": {
"field": "user",
"min_doc_count": 100
}
}
}
}
Edit the query to match your date range (and its format) and min_doc_count to the minimum X posts per user.
EDIT:
There is no way to avoid terms_aggregation to get all distinct values.
50k values do seems to be to much data to retrieve - but it also depends on your cluster.
My suggestion is to add another filter, lets say, alphabetically filter so instead of getting 50k results at once you can do it in other several queries:
"must": [
{
"range": {
"datetime": {
"gte": "2017-05-01",
"lt": "2017-06-01"
}
}
},
{
"wildcard": {
"user": "a*"
}
},
{
"wildcard": {
"user": "b*"
}
}
]
See Wildcard
Unfortunately, scrolling on aggregation results is not available. Manually dividing the data to pieces is the best thing I can see right now.
right now I have a query like this:
{
"query": {
"bool": {
"must": [
{
"match": {
"uuid": "xxxxxxx-xxxx-xxxx-xxxxx-xxxxxxxxxxxxx"
}
},
{
"range": {
"date": {
"from": "now-12h",
"to": "now"
}
}
}
]
}
},
"aggs": {
"query": {
"terms": [
{
"field": "query",
"size": 3
}
]
}
}
}
The aggregation works perfectly well, but I can't seem to find a way to control the hit data that is returned, I can use the size parameter at the top of the dsl, but the hits that are returned are not returned in the same order as the bucket so the bucket results do not line up with the hit results. Is there any way to correct this or do I have to issue 2 separate queries?
To expand on Filipe's answer, it seems like the top_hits aggregation is what you are looking for, e.g.
{
"query": {
... snip ...
},
"aggs": {
"query": {
"terms": {
"field": "query",
"size": 3
},
"aggs": {
"top": {
"top_hits": {
"size": 42
}
}
}
}
}
}
Your query uses exact matches (match and range) and binary logic (must, bool) and thus should probably be converted to use filters instead:
"filtered": {
"filter": {
"bool": {
"must": [
{
"term": {
"uuid": "xxxxxxx-xxxx-xxxx-xxxxx-xxxxxxxxxxxxx"
}
},
{
"range": {
"date": {
"from": "now-12h",
"to": "now"
}
}
}
]
}
}
As for the aggregations,
The hits that are returned do not represent all the buckets that were returned. so if have buckets for terms 'a', 'b', and 'c' I want to have hits that represent those buckets as well
Perhaps you are looking to control the scope of the buckets? You can make an aggregation bucket global so that it will not be influenced by the query or filter.
Keep in mind that Elasticsearch will not "group" hits in any way -- it is always a flat list ordered according to score and additional sorting options.
Aggregations can be organized in a nested structure and return computed or extracted values, in a specific order. In the case of terms aggregation, it is in descending count (highest number of hits first). The hits section of the response is never influenced by your choice of aggregations. Similarly, you cannot find hits in the aggregation sections.
If your goal is to group documents by a certain field, yes, you will need to run multiple queries in the current Elasticsearch release.
I'm not 100% sure, but I think there's no way to do that in the current version of Elasticsearch (1.2.x). The good news is that there will be when version 1.3.x gets released:
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations-metrics-top-hits-aggregation.html