I would like to compute the ratio of fields that have a value in my index.
I managed to count how many documents miss the field:
GET profiles/_search
{
"aggs": {
"profiles_wo_country": {
"missing": {
"field": "country"
}
}
},
"size": 0
}
I also managed to count how many documents have the filed:
GET profiles/_search
{
"query": {
"filtered": {
"query": {"match_all": {}},
"filter": {
"exists": {
"field": "country"
}
}
}
},
"size": 0
}
Naturally I can also get the total number of documents in the index. How can I compute the ratio?
An easy way to get the numbers you need out of a query is using the following query
POST profiles/_search?filter_path=hits.total,aggregations.existing.doc_count
{
"size": 0,
"aggs": {
"existing": {
"filter": {
"exists": {
"field": "tag"
}
}
}
}
}
You'll get an response like this one:
{
"hits": {
"total": 37258601
},
"aggregations": {
"existing": {
"doc_count": 9287160
}
}
}
And then in your client code, you can simply do
fill_rate = (aggregations.existing.doc_count / hits.total) * 100
And you're good to go.
Related
ElasticSearch 7.10.1 nested aggregations.
Can anyone point me to why the doc_count on my 2nd nested aggregation is not correct?
The count on the first aggregation is accurate but the 2nd isnt (both are keyword fields).
{
"size": 0,
"_source": false,
"query": {
"match_all": {}
},
"aggs": {
"products": {
"nested": {
"path": "productsImpacted"
},
"aggs": {
"field1": {
"terms": {
"field": "productsImpacted.product.keyword",
"size": 1000
},
"aggs": {
"resellers": {
"nested": {
"path": "requestType"
},
"aggs": {
"field2": {
"terms": {
"field": "requestType.type.keyword",
"size": 1000
}
}
}
}
}
}
}
}
}
}
Thanks,
ES’agg is inaccurate.
you cna use size and shard_size to improve accuracy means a decline in performance，You can refer to the official documents：
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html#search-aggregations-bucket-terms-aggregation-shard-size
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 have written a query to get the buckets based on id and then sort it. This works fine. But how to make it return buckets from position 100 till 200 for aggregation_by_id rule?
{
"query": {
"match_all": {}
},
"size": 0,
"aggregations": {
"aggregation_by_id": {
"terms": {
"field": "id.keyword"
"size" : 200
},
"aggs": {
"sort_timestamp": {
"top_hits": {
"sort": [{
"timestamp": {
"order": "desc",
"unmapped_type": "long"
}
}],
"size": 1
}
}
}
}
}
}
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 am interested to know how can I add a range for a significant terms aggregations query. For example:
{
"query": {
"terms": {
"text_content": [
"searchTerm"
]
},
"range": {
"dateField": {
"from": "date1",
"to": "date2"
}
}
},
"aggregations": {
"significantQTypes": {
"significant_terms": {
"field": "field1",
"size": 10
}
}
},
"size": 0
}
will not work. Any suggestions on how to specify the range?
Instead of using a range query, use a range filter as the relevance/score doesn't seem to matter in your case.
Then, in order to combine your query with a range filter, you should use a filtered query (see documentation).
Try something like this :
{
"query": {
"filtered": {
"query": {
"terms": {
"text_content": [
"searchTerm"
]
}
},
"filter": {
"range": {
"dateField": {
"from": "date1",
"to": "date2"
}
}
}
}
},
"aggs": {
"significantQTypes": {
"significant_terms": {
"field": "field1",
"size": 10
}
}
},
"size": 0
}
Hope this helps!