# Multiple Index Step by step query **URL:** \ **Category:** Elasticsearch\ **Created:** [May 25, 2020, 7:42am UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096 "2020-05-25T07:42:08Z")\ **Posts on this page:** 6\ **Page:** 1
**Author:** ![ivgenik](https://avatars.discourse-cdn.com/v4/letter/i/ce73a5/32.png) [@ivgenik](https://discuss.elastic.co/u/ivgenik)\ **Post date:** [May 25, 2020, 7:42am UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/1 "2020-05-25T07:42:08Z")
Hello, I probably need to create a multi step multi index query and I am not sure if such a thing is supported or if it is the right approach at all. Example Data: 2 indexes , 1 for orders, 1 for invoices I made a simple query that scans the invoices index and counts the amount of referenced orders like so : ``` { "aggs":{ "reference":{ "terms":{ "field":"References.DocType.SysName.keyword" } } }, "query":{ "bool":{ "filter":[ { "range":{ "MessageDate":{ "gte":"2015-05-24T00:00:00+03:00" } } } ] } } } ``` I am holding this information inside the invoice index so it is quite simple, by grouping by the docType of the references I can see how many references I got of type "order", also I needed to use a date in the query. My problem is that later on I will also going to need to query for the actual orders data and not just the orders amount which located in a different index(orders). But in order to determine which orders to return I first need to run something like the query above to determine which orders qualifies. From the first query I got access to the order Ids with which I can find the actual orders in the orders index. But I dont think it is very practical to make a second separate query by _XXXXX_ amount of ids. So I was wondering if it is possible to somehow make a merged query that finds all the order ids by the needed terms against the invoices index and then finds the actual orders from the orders index and retrieves those. ---
**Author:** ![warkolm](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/warkolm/32/39224_2.png) [@warkolm](https://discuss.elastic.co/u/warkolm)\ **Post date:** [May 25, 2020, 7:45am UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/2 "2020-05-25T07:45:32Z")
You're after a join, which Elasticsearch doesn't do sorry. Are the documents similar in structure? ---
**Author:** ![ivgenik](https://avatars.discourse-cdn.com/v4/letter/i/ce73a5/32.png) [@ivgenik](https://discuss.elastic.co/u/ivgenik)\ **Post date:** [May 25, 2020, 7:47am UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/3 "2020-05-25T07:47:12Z")
Yes they are built from the same base structure ---
**Author:** ![warkolm](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/warkolm/32/39224_2.png) [@warkolm](https://discuss.elastic.co/u/warkolm)\ **Post date:** [May 25, 2020, 7:57am UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/4 "2020-05-25T07:57:36Z")
It might be easier to put them into the same index then? ---
**Author:** ![ivgenik](https://avatars.discourse-cdn.com/v4/letter/i/ce73a5/32.png) [@ivgenik](https://discuss.elastic.co/u/ivgenik)\ **Post date:** [June 15, 2020, 3:09pm UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/7 "2020-06-15T15:09:46Z")
Thank you for the replay, In the end I ended up adding 2 new fields for my MongoDB collections (which ends up in the elastic DB indexes via an ETL process). This allowed me to create a pretty straight forward flow of 2 queries against the elastic engine which solved my problem. ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [July 13, 2020, 3:11pm UTC](https://discuss.elastic.co/t/multiple-index-step-by-step-query/234096/8 "2020-07-13T15:11:59Z")
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