[
]
Elastic Search Query Generator
what is Elastic Search Query Generator ?
-
While i was working with Elastic Search i found it very difficult to write complex queries as most of query are deep Nested
-
Thats the reason i decided to make a helper class that can generate complex Elastic Search query in Seconds
-
Library can be used to generate complex aggregation Query , Geo location Query (AND | OR | NOT ) any set of combination is possible
-
in addition to all mentioned above you can also generate auto complete query in matter of seconds
-
please see examples below on how to use this module.
-
if you have any questions or suggestion please drop me an email at shahsoumil519@gmail.com
-
Learn More : https://www.youtube.com/watch?v=C-JKcMM6IXE&t=2548s
documentation :
- UML Diagram
-
Constructor:
- Size: How Many Documents should the Query Return
- BucketName: is optional pass a name for Aggregation
- Source: Basically what fields you want to return takes a List Argument source= [“f1”, “f2”, …..]
- Min_score: used for filtering large documents average threshold is set to 0.5
-
Field:
- This is column or field you would like to search
-
Boost:
- If you want to Boost certain field pass a integer value
-
Operation
- There are four main operation you can pass * Should ( OR Operation) * Must (AND operation) * Filter (FILTER Result ) * Must_not (NOT Operation )
-
Analyzer:
- you can specify various analyzer such as stop etc
Installation
pip install elasticsearchquerygeneratorUsage
from elasticsearchquerygenerator.elasticsearchquerygenerator import ElasticSearchQuery
import json
def main():
helper = ElasticSearchQuery(size=100, BucketName="MyBuckets")
# match phrase
query=helper.match_phrase(field="myfeild", value="myvalue", operation='must')
# terms
query=helper.terms(field="myfeild", value="myvalue", operation='must')
# Feild Exists
query = helper.exists(field='comp feild', operation="must")
#Match
query=helper.match(field="MMMMM", value="myvalue", operation='must')
# Geo Queires
query = helper.add_geoqueries(radius="100", lat="22", lon="33")
# Aggreation
helper.add_aggreation(aggregate_name="FirstName", field="field1",type='terms',sort='desc', size=3)
helper.add_aggreation(aggregate_name="SecondName", field="field2",type='terms',sort='desc', size=3)
helper.add_aggreation(aggregate_name="ThirdName", field="field3",type='terms',sort='desc', size=3)
query = helper.complete_aggreation()
query = helper.query_string(default_field="DEFAULT",query="X OR Y",operation='must')
query = helper.add_geo_aggreation(field="AAAA", lat="22", lon="43",aggregate_name="my_distance")
print(json.dumps(query, indent=3))
if __name__ == "__main__":
main()
{
"_source": [],
"size": 100,
"min_score": 0.5,
"query": {
"bool": {
"must": [
{
"match_phrase": {
"myfeild": {
"query": "myvalue"
}
}
},
{
"match_phrase": {
"myfeild": {
"query": "myvalue"
}
}
},
{
"term": {
"myfeild": "myvalue"
}
},
{
"exists": {
"field": "comp feild"
}
},
{
"match": {
"MMMMM": {
"query": "myvalue"
}
}
},
{
"match": {
"MMMMM": {
"query": "myvalue"
}
}
},
{
"query_string": {
"default_field": "DEFAULT",
"query": "X OR Y"
}
}
],
"filter": [
{
"geo_distance": {
"distance": "100mi",
"null": {
"lat": "22",
"lon": "33"
}
}
}
],
"should": [],
"must_not": []
}
},
"aggs": {
"FirstName": {
"terms": {
"field": "field1",
"order": {
"_count": "desc"
},
"size": 3
}
},
"SecondName": {
"terms": {
"field": "field2",
"order": {
"_count": "desc"
},
"size": 3
}
},
"ThirdName": {
"terms": {
"field": "field3",
"order": {
"_count": "desc"
},
"size": 3
}
},
"my_distance": {
"geo_distance": {
"field": "AAAA",
"origin": "22,43",
"unit": "mi",
"ranges": [
{
"to": 0
},
{
"from": 0,
"to": 25
},
{
"from": 25,
"to": 50
},
{
"from": 50,
"to": 75
},
{
"from": 75,
"to": 100
},
{
"from": 100
}
]
}
}
}
}
Example 2
from elasticsearchquerygenerator.elasticsearchquerygenerator import ElasticSearchQuery
import json
def autocomplete():
helper = ElasticSearchQuery(size=0, BucketName="MyBuckets")
query = helper.autocomplete_1(field="title",value="n", size=25,sort='desc')
print(json.dumps(query, indent=3))
if __name__ == "__main__":
main(autocomplete{
"_source": [],
"size": 0,
"min_score": 0.5,
"query": {
"bool": {
"must": [
{
"match_phrase_prefix": {
"title": {
"query": "n"
}
}
}
],
"filter": [],
"should": [],
"must_not": []
}
},
"aggs": {
"auto_complete": {
"terms": {
"field": "title",
"order": {
"_count": "desc"
},
"size": 25
}
}
}
}i would be adding more examples and making it better and better
Authors
Soumil Nitin Shah
- Excellent experience of building scalable and high-performance Software Applications combining distinctive skill sets in Internet of Things (IoT), Machine Learning and Full Stack Web Development in Python.
Bachelor in Electronic Engineering | Masters in Electrical Engineering | Master in Computer Engineering |
- Website : https://soumilshah.herokuapp.com
- Github: https://github.com/soumilshah1995
- Linkedin: https://www.linkedin.com/in/shah-soumil/
- Blog: https://soumilshah1995.blogspot.com/
- Youtube : https://www.youtube.com/channel/UC_eOodxvwS_H7x2uLQa-svw?view_as=subscriber
- Facebook Page : https://www.facebook.com/soumilshah1995/
- Email : shahsoumil519@gmail.com
License
This project is licensed under the MIT License - see the LICENSE.md file for details
