Here are example documents:
{
"player": "Jim",
"score" : 5
"timestamp": 1459492890000
}
{
"player": "Jim",
"score" : 7
"timestamp": 1459492895000
}
{
"player": "Dave",
"score" : 9
"timestamp": 1459492894000
}
{
"player": "Dave",
"score" : 4
"timestamp": 1459492898000
}
I want to get the latest score for each player and then get the average of all those scores. So the answer would be 5.5. Jim's latest score is 7 and Dave's latest score is 4. The average between those two is 5.5
The only way I found to get the "latest" document of a player was to use the top_hits aggregation. However, it does not seem that I am able to do another aggregation after I get the latest document.
This is the best I came up with:
{
"aggs": {
"last_score": {
"terms": { "field": "player" },
"aggs": {
"last_score_hits": {
"top_hits": {
"sort": [ { "timestamp": { "order": "desc" } } ],
"size": 1
},
"aggs": {
"avg_score": {
"avg": { "field": "score" }
}
}
}
}
}
}
}
However, this gives me this error:
Aggregator [last_score_hits] of type [top_hits] cannot accept
sub-aggregations
If there is another way to accomplish this search without using top_hits as well, then I would be all for it.
You're trying to put avg_score as a sub-aggregation of last_score_hits.
To get success you have to put avg_score as a sub-aggregation of last_score. See an example bellow:
{
"aggs": {
"last_score": {
"terms": {
"field": "player"
},
"aggs": {
"last_score_hits": {
"top_hits": {
"sort": [
{
"timestamp": {
"order": "desc"
}
}
],
"size": 1
}
},
"avg_score": {
"avg": {
"field": "score"
}
}
}
}
}
}
You can have other aggregation on a parallel level of top_hit but you cannot have any sub_aggregation below top_hit. It is not supported by ElasticSearch. here is the link to Github issue
You can have a parallel level aggregation like:
"aggs": {
"top_hits_agg": {
"top_hits": {
"size": 10,
"_source": {
"includes": ["score"]
}
}
},
"avg_agg": {
"avg": {
"field": "score"
}
}
}
Related
I have a data structure in Elasticsearch that looks like:
{
"name": "abc",
"date": "2022-10-08T21:30:40.000Z",
"rank": 3
}
I want to get, for each unique name, the rank of the document (or the whole document) with the most recent date.
I currently have this:
"aggs": {
"group-by-name": {
"terms": {
"field": "name"
},
"aggs": {
"max-date": {
"max": {
"field": "date"
}
}
}
}
}
How can I get the rank (or the whole document) for each result, and if possible, in 1 request ?
You can use below options
Collapse
"collapse": {
"field": "name"
},
"sort": [
{
"date": {
"order": "desc"
}
}
]
Top hits aggregation
{
"aggs": {
"group-by-name": {
"terms": {
"field": "name",
"size": 100
},
"aggs": {
"top_doc": {
"top_hits": {
"sort": [
{
"date": {
"order": "desc"
}
}
],
"size": 1
}
}
}
}
}
}
I have a search query that returns all items matching users that have type manager or lead.
{
"from": 0,
"size": 20,
"query": {
"bool": {
"should": [
{
"terms": {
"type": ["manager", "lead"]
}
}
]
}
}
}
Is there a way to define what percentage of the results should be of type "manager"?
In other words, I want the results to have 80% of users with type manager and 20% with type lead.
I want to make a suggestion to use bucket_path aggregation. As I know this aggregation needs to be run in sub-aggs of a histogram aggregation. As you have such field in your mapping so I think this query should work for you:
{
"size": 0,
"aggs": {
"NAME": {
"date_histogram": {
"field": "my_datetime",
"interval": "month"
},
"aggs": {
"role_type": {
"terms": {
"field": "type",
"size": 10
},
"aggs": {
"count": {
"value_count": {
"field": "_id"
}
}
}
},
"role_1_ratio": {
"bucket_script": {
"buckets_path": {
"role_1": "role_type['manager']>count",
"role_2": "role_type['lead']>count"
},
"script": "params.role_1 / (params.role_1+params.role_2)*100"
}
},
"role_2_ratio": {
"bucket_script": {
"buckets_path": {
"role_1": "role_type['manager']>count",
"role_2": "role_type['lead']>count"
},
"script": "params.role_2 / (params.role_1+params.role_2)*100"
}
}
}
}
}
}
Please let me know if it didn't work well for you.
I'm trying to count # of logs grouped by user agent.
This is what I have.
GET /myindex/_search
{
"size": 30,
"stored_fields": ["req.headers.user-agent.keyword"],
"aggs": {
"group_by_userAgent": {
"terms": {
"field": "req.headers.user-agent.keyword"
}
}
}
}
I wanted to add "Query last 15 mins" feature. I've tried to add 'range' query and I ended up the following query, which does not work.
GET /myindex/_search
{
"size": 30,
"stored_fields": ["req.headers.user-agent.keyword"],
"aggs": {
"group_by_userAgent": {
"terms": {
"field": "req.headers.user-agent.keyword"
},
"range": {
"timestamp": {
"gt": "now-15m"
}
}
}
}
}
How do I query terms aggregation with range with "now-x15min" syntax?
The range should go inside the query section, not aggs. The time range is good as it is
I think what you're looking for is this, the number of docs in the first 30 user-agent buckets, i.e. the top 30 user agents producing the most logs
GET /myindex/_search
{
"size": 0,
"query": {
"range": {
"#timestamp": {
"gt": "now-15m"
}
}
},
"aggs": {
"group_by_userAgent": {
"terms": {
"field": "req.headers.user-agent.keyword",
"size": 30
}
}
}
}
you can do this in two ways to achieve aggregation results for user-agent.
POST phrase_index/_search
{
"aggs": {
"date_range_filtered_agg": {
"filter": {
"range": {
"timestamp": {
"gte": "now-15m/m"
}
}
},
"aggs": {
"group_by_userAgent": {
"terms": {
"field": "req.headers.user-agent.keyword",
"size": 10
}
}
}
}
},
"size": 30,
"stored_fields": ["req.headers.user-agent.keyword"]
}
POST phrase_index/_search
{
"query": {
"range": {
"timestamp": {
"gte": "now-15m/m"
}
}
},
"aggs": {
"group_by_userAgent": {
"terms": {
"field": "req.headers.user-agent.keyword",
"size": 10
}
}
},
"size": 30,
"stored_fields": ["req.headers.user-agent.keyword"]
}
You need a filter aggregation first to apply the range query, then add a terms sub-aggregation.
See: https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-filter-aggregation.html
I'm trying to find a way to only return the results of one aggregation in an Elasticsearch query. I have a max bucket aggregation (the one that I want to see) that is calculated from a sum bucket aggregation based on a date histogram aggregation. Right now, I have to go through 1,440 results to get to the one I want to see. I've already removed the results of the base query with the size: 0 modifier, but is there a way to do something similar with the aggregations as well? I've tried slipping the same thing into a few places with no luck.
Here's the query:
{
"size": 0,
"query": {
"range": {
"timestamp": {
"gte": "2018-11-28",
"lte": "2018-11-28"
}
}
},
"aggs": {
"hits_per_minute": {
"date_histogram": {
"field": "timestamp",
"interval": "minute"
},
"aggs": {
"total_hits": {
"sum": {
"field": "hits_count"
}
}
}
},
"max_transactions_per_minute": {
"max_bucket": {
"buckets_path": "hits_per_minute>total_hits"
}
}
}
}
Fortunately enough, you can do that with bucket_sort aggregation, which was added in Elasticsearch 6.4.
Do it with bucket_sort
POST my_index/doc/_search
{
"size": 0,
"query": {
"range": {
"timestamp": {
"gte": "2018-11-28",
"lte": "2018-11-28"
}
}
},
"aggs": {
"hits_per_minute": {
"date_histogram": {
"field": "timestamp",
"interval": "minute"
},
"aggs": {
"total_hits": {
"sum": {
"field": "hits_count"
}
},
"max_transactions_per_minute": {
"bucket_sort": {
"sort": [
{"total_hits": {"order": "desc"}}
],
"size": 1
}
}
}
}
}
}
This will give you a response like this:
{
...
"aggregations": {
"hits_per_minute": {
"buckets": [
{
"key_as_string": "2018-11-28T21:10:00.000Z",
"key": 1543957800000,
"doc_count": 3,
"total_hits": {
"value": 11
}
}
]
}
}
}
Note that there is no extra aggregation in the output and the output of hits_per_minute is truncated (because we asked to give exactly one, topmost bucket).
Do it with filter_path
There is also a generic way to filter the output of Elasticsearch: Response filtering, as this answer suggests.
In this case it will be enough to just do the following query:
POST my_index/doc/_search?filter_path=aggregations.max_transactions_per_minute
{ ... (original query) ... }
That would give the response:
{
"aggregations": {
"max_transactions_per_minute": {
"value": 11,
"keys": [
"2018-12-04T21:10:00.000Z"
]
}
}
}
I would like to plot a cumulative sum of some events, per day. The cumulative sum aggregation seems to be the way to go so I tried to reuse the example given in the docs.
The first aggregation works fine, the following query
{
"aggs": {
"vulns_day" : {
"date_histogram" :{
"field": "HOST_START_iso",
"interval": "day"
}
}
}
}
gives replies such as
(...)
{
"key_as_string": "2016-09-08T00:00:00.000Z",
"key": 1473292800000,
"doc_count": 76330
},
{
"key_as_string": "2016-09-09T00:00:00.000Z",
"key": 1473379200000,
"doc_count": 37712
},
(...)
I then wanted to query the cumulative sum of doc_count above via
{
"aggs": {
"vulns_day" : {
"date_histogram" :{
"field": "HOST_START_iso",
"interval": "day"
}
},
"aggs": {
"vulns_cumulated": {
"cumulative_sum": {
"buckets_path": "doc_count"
}
}
}
}
}
but it gives an error:
"reason": {
"type": "search_parse_exception",
"reason": "Could not find aggregator type [vulns_cumulated] in [aggs]",
I see that bucket_path should point to the elements to be summed and the example for cumulative aggregations created a specific intermediate sum but I do not have anything to sum (beside doc_count).
I guess, you should change your query like this:
{
"aggs": {
"vulns_day": {
"date_histogram": {
"field": "HOST_START_iso",
"interval": "day"
},
"aggs": {
"document_count": {
"value_count": {
"field": "HOST_START_iso"
}
},
"vulns_cumulated": {
"cumulative_sum": {
"buckets_path": "document_count"
}
}
}
}
}
}
I found the solution. Since doc_count did not seem to be available, I tried to retrieve stats for the time parameter, and use its count value. It worked:
{
"size": 0,
"aggs": {
"vulns_day": {
"date_histogram": {
"field": "HOST_START_iso",
"interval": "day"
},
"aggs": {
"dates_stats": {
"stats": {
"field": "HOST_START_iso"
}
},
"vulns_cumulated": {
"cumulative_sum": {
"buckets_path": "dates_stats.count"
}
}
}
}
}
}