Fetching unique data in Elasticsearch - elasticsearch

Question

I have following data
ID: 1, fldname: pawan
ID: 1, fldname: pawan1
ID: 1, fldname: pawan2
ID: 2, fldname: pawan3
ID: 3, fldname: pawan4
ID: 4, fldname: pawan5
I am trying to get unique data based on ID field, similar to what we get in MySQL while firing group by queries like:
select * from table_name where fldname like 'pawan%' group by ID
This will return unique values. Same works in sphinx search when we use group by function.
Is there any way to get unique values in elasticsearch..?
Below is my sample mapping:
"mappings": {
"my_type": {
"properties": {
"docid": {
"type": "keyword"
},
"flgname": {
"type": "text"
}
}
}
}

Answer 1

I suggest that you slightly modify your mapping:
{
"record" : {
"dynamic" : "false",
"_all" : {
"enabled" : false
},
"properties" : {
"docid" : {
"type" : "long"
},
"flgname" : {
"type" : "text"
}
}
}
}
so that docid is a long
Then you could try fuzzy queries for filtering, together with aggregations, like this one here which retrieves the minimum, maximum, average and count of docid's:
{
"from" : 0,
"size" : 10,
"_source" : true,
"query" : {
"bool" : {
"must" : [ {
"match" : {
"flgname" : {
"query" : "pawan",
"operator" : "OR",
"fuzziness" : "1",
"prefix_length" : 1,
"max_expansions" : 50,
"fuzzy_transpositions" : true,
"lenient" : false,
"zero_terms_query" : "NONE",
"boost" : 1.0
}
}
} ]
}
},
"aggs" : {
"my_cardinality" : {
"cardinality" : {
"field" : "docid"
}
},
"my_avg" : {
"avg" : {
"field" : "docid"
}
},
"my_min" : {
"min" : {
"field" : "docid"
}
},
"my_max" : {
"max" : {
"field" : "docid"
}
}
}
}
By the way this is the result of the above query on the data you proposed:
{
"took" : 47,
"timed_out" : false,
"_shards" : {
"total" : 3,
"successful" : 3,
"failed" : 0
},
"hits" : {
"total" : 6,
"max_score" : 0.9808292,
"hits" : [ {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "40b5eac0-743b-4a6a-a06d-3ae4d56f4aca",
"_score" : 0.9808292,
"_source" : {
"docid" : "1",
"flgname" : "pawan"
}
}, {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "27821c39-e722-4361-bc07-0dcd5181a1ad",
"_score" : 0.7846634,
"_source" : {
"docid" : "2",
"flgname" : "pawan3"
}
}, {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "86fcd9c1-a688-4a6a-9c45-e91791a8b902",
"_score" : 0.7846634,
"_source" : {
"docid" : "4",
"flgname" : "pawan5"
}
}, {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "fb00a3cc-f1b8-4073-8808-f2ddbc4979e2",
"_score" : 0.55451775,
"_source" : {
"docid" : "1",
"flgname" : "pawan1"
}
}, {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "18e5e20d-17a7-4d59-b2f1-7bf325a4c4df",
"_score" : 0.55451775,
"_source" : {
"docid" : "3",
"flgname" : "pawan4"
}
}, {
"_index" : "stack_overflow1",
"_type" : "record",
"_id" : "fbf49af6-f574-4ad2-8686-cbbedc5e70c4",
"_score" : 0.23014566,
"_source" : {
"docid" : "1",
"flgname" : "pawan2"
}
} ]
},
"aggregations" : {
"my_cardinality" : {
"value" : 4
},
"my_max" : {
"value" : 4.0
},
"my_avg" : {
"value" : 2.0
},
"my_min" : {
"value" : 1.0
}
}
}

Answer 2

If you make flgname also a keyword, then you can use sub-aggregation to aggregate over docID and subaggregate over flgname. Result will be similar to the SQL query you mentioned.
Query would look like:
{ "size": 0,
"query": {
"regexp":{
"flgname": "pawa.*"
}
},
"aggs" : {
"docids": {
"terms": {"field": "docid"},
"aggs": { "flgnam": { "terms": {"field": "flgname"}}}}
}
}