In the previous blog we searched for a match_all, and sorted it by age. In this we will improve upon the query we are writing and look for other options.
GET profile/_search
{
"query": {
"match": {
"title": "Mr. Ms."
}
},
"sort": [
{
"age": "asc"
}
],
"size": 3
}The command executed above, uses match which allows to search for specific terms within a field title and the terms we are looking for are Mr. or Mrs.
The response as received is as under
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 10,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "4",
"_score" : null,
"_source" : {
"name" : "Deepa G",
"age" : 22,
"title" : "Ms.",
"role" : "QA",
"org" : "Security"
},
"sort" : [
22
]
},
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "6",
"_score" : null,
"_source" : {
"name" : "Smdie G",
"age" : 24,
"title" : "Mr.",
"role" : "Program management",
"org" : "Security"
},
"sort" : [
24
]
},
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "7",
"_score" : null,
"_source" : {
"name" : "Amdie G",
"age" : 24,
"title" : "Mr.",
"role" : "Program management",
"org" : "Security"
},
"sort" : [
24
]
}
]
}
}match_phrase#
GET profile/_search
{
"query": {
"match_phrase": {
"name": "G"
}
},
"sort": [
{
"age": "asc"
}
],
"size": 2
}In the example above I am trying to look for a phrase G rather than individual term.
{
"took" : 0,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 8,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "4",
"_score" : null,
"_source" : {
"name" : "Deepa G",
"age" : 22,
"title" : "Ms.",
"role" : "QA",
"org" : "Security"
},
"sort" : [
22
]
},
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "5",
"_score" : null,
"_source" : {
"name" : "Reepa G",
"age" : 24,
"title" : "Mrs.",
"role" : "QA",
"org" : "Security"
},
"sort" : [
24
]
}
]
}
}I have limited the size to 2 and hence even though it matched more than 2 documents, the result size was limited to 2.
Complex Query#
Creating a complex query is equally intuitive.
Bool – Query#
Let’s look for all the users who are between the age group of >= 30 && <= 50.
GET profile/_search
{
"query": {
"bool": {
"must": [
{ "range": {
"age": {
"gte": 30,
"lte": 50
}
}}
]
}
},
"sort": [
{
"age": "asc"
}
],
"size": 2
}The response as expected is
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 3,
"relation" : "eq"
},
"max_score" : null,
"hits" : [
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "11",
"_score" : null,
"_source" : {
"name" : "Veronica G",
"age" : 37,
"title" : "Ms.",
"role" : "Engineering",
"org" : "Security"
},
"sort" : [
37
]
},
{
"_index" : "profile",
"_type" : "_doc",
"_id" : "10",
"_score" : null,
"_source" : {
"name" : "Pranav G",
"age" : 47,
"title" : "Mr.",
"role" : "Engineering",
"org" : "Security"
},
"sort" : [
47
]
}
]
}
}A simple modifications to exclude Veronica is as under.
must_not clause is more of a filter.
GET profile/_search
{
"query": {
"bool": {
"must": [
{ "range": {
"age": {
"gte": 30,
"lte": 50
}
}}
],
"must_not": [
{
"match": {
"name": "Veronica G"
}
}
]
}
},
"sort": [
{
"age": "asc"
}
],
"size": 2
}Aggregating#
Let’s show aggregation
GET profile/_search
{
"aggs": {
"Group-By-Age": {
"terms": {
"field": "title.keyword"
}
}
},
"size": 0
}and the results are
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 11,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"Group-By-Age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Mr.",
"doc_count" : 8
},
{
"key" : "Ms.",
"doc_count" : 2
},
{
"key" : "Mrs.",
"doc_count" : 1
}
]
}
}
}What are these buckets?
"buckets" : []In our example we are aggregating for title.keyword and the key shows the unique values found and the doc_count is the total matches.
So for our response we have 8 Mr. , 2 Ms. and 1 Mrs.
If the size is not zero in the query all the responses that matched will also be returned in the hits[]
Complexity increased#
A little modifications to further aggregate and group by role.
GET profile/_search
{
"aggs": {
"Group-By-Age": {
"terms": {
"field": "title.keyword"
},
"aggs": {
"Group-By-Role": {
"terms": {
"field": "role.keyword"
}
}
}
}
},
"size": 0
}{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 11,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"Group-By-Age" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Mr.",
"doc_count" : 8,
"Group-By-Role" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Program management",
"doc_count" : 2
},
{
"key" : "Engineering",
"doc_count" : 1
},
{
"key" : "Engineering management",
"doc_count" : 1
},
{
"key" : "Lead",
"doc_count" : 1
},
{
"key" : "Lead Engr",
"doc_count" : 1
},
{
"key" : "Manager",
"doc_count" : 1
},
{
"key" : "Product management",
"doc_count" : 1
}
]
}
},
{
"key" : "Ms.",
"doc_count" : 2,
"Group-By-Role" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "Engineering",
"doc_count" : 1
},
{
"key" : "QA",
"doc_count" : 1
}
]
}
},
{
"key" : "Mrs.",
"doc_count" : 1,
"Group-By-Role" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "QA",
"doc_count" : 1
}
]
}
}
]
}
}
}
