Use query result as parameter for another query in Elasticsearch DSL - elasticsearch

Question

I'm using Elasticsearch DSL, I'm trying to use a query result as a parameter for another query like below:
{
"query": {
"bool": {
"must_not": {
"terms": {
"request_id": {
"query": {
"match": {
"processing.message": "OUT Followup Synthesis"
}
},
"fields": [
"request_id"
],
"_source": false
}
}
}
}
}
}
As you can see above I'm trying to search for sources that their request_id is not one of the request_idswith processing.message equals to OUT Followup Synthesis.
I'm getting an error with this query:
Error loading data [x_content_parse_exception] [1:1660] [terms_lookup] unknown field [query]
How can I achieve my goal using Elasticsearch DSL?

Answer 1

Original question extracted from the comments
I'm trying to fetch data with processing.message equals to 'IN Followup Sythesis' with their request_id doesn't appear in data with processing.message equals to 'OUT Followup Sythesis'. In SQL language:
SELECT d FROM data d
WHERE d.processing.message = 'IN Followup Sythesis'
AND d.request_id NOT IN (SELECT request_id FROM data WHERE processing.message = 'OUT Followup Sythesis');
Answer: generally speaking, neither application-side joins nor subqueries are supported in Elasticsearch.
So you'll have to run your first query, take the retrieved IDs and put them into a second query — ideally a terms query.
Of course, this limitation can be overcome by "hijacking" a scripted metric aggregation.
Taking these 3 documents as examples:
POST reqs/_doc
{"request_id":"abc","processing":{"message":"OUT Followup Synthesis"}}
POST reqs/_doc
{"request_id":"abc","processing":{"message":"IN Followup Sythesis"}}
POST reqs/_doc
{"request_id":"xyz","processing":{"message":"IN Followup Sythesis"}}
you could run
POST reqs/_search
{
"size": 0,
"query": {
"match": {
"processing.message": "IN Followup Sythesis"
}
},
"aggs": {
"subquery_mock": {
"scripted_metric": {
"params": {
"disallowed_msg": "OUT Followup Synthesis"
},
"init_script": "state.by_request_ids = [:]; state.disallowed_request_ids = [];",
"map_script": """
def req_id = params._source.request_id;
def msg = params._source.processing.message;
if (msg.contains(params.disallowed_msg)) {
state.disallowed_request_ids.add(req_id);
// won't need this particular doc so continue looping
return;
}
if (state.by_request_ids.containsKey(req_id)) {
// there may be multiple docs under the same ID
// so concatenate them
state.by_request_ids[req_id].add(params._source);
} else {
// initialize an appendable arraylist
state.by_request_ids[req_id] = [params._source];
}
""",
"combine_script": """
state.by_request_ids.entrySet()
.removeIf(entry -> state.disallowed_request_ids.contains(entry.getKey()));
return state.by_request_ids
""",
"reduce_script": "return states"
}
}
}
}
which'd return only the correct request:
"aggregations" : {
"subquery_mock" : {
"value" : [
{
"xyz" : [
{
"processing" : { "message" : "IN Followup Sythesis" },
"request_id" : "xyz"
}
]
}
]
}
}
⚠️ This is almost guaranteed to be slow and goes against the suggested guidance of not accessing the _source field. But it also goes to show that subqueries can be "emulated".
💡 I'd recommend to test this script on a smaller set of documents before letting it target your whole index — maybe restrict it through a date range query or similar.
FYI Elasticsearch exposes an SQL API, though it's only offered through X-Pack, a paid offering.