There is a simple way, using RESTful client to create Index and Mappings in ElasticSearch, for example, with ElasticSearch Head plugin.
Create Index in ElasticSearch with Settings JSON file. URL: http://localhost:9200/orders/, Method: PUT
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| {
"settings": {
"index": {
"number_of_shards": 1,
"number_of_replicas": 0,
"analysis": {
"filter": {
"partial_matching_filter": {
"type": "edge_ngram",
"min_gram": 1,
"max_gram": 40
}
},
"normalizer": {
"lowercase_normalizer": {
"type": "custom",
"filter": ["lowercase"]
}
},
"analyzer": {
"partial_matcher": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"partial_matching_filter"
]
}
}
}
}
}
}
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Create Mappings in ElasticSearch with Mappings JSON file. URL: http://localhost:9200/orders/_mapping/order, Method: PUT
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| {
"dynamic": "false",
"_all": { "enabled": false},
"properties": {
"customer_id": {
"type": "keyword"
},
"encryption_key_id": {
"type": "keyword",
"index": "false"
},
"metadata_tags": {
"type": "text",
"analyzer": "whitespace"
},
"category": {
"type": "keyword"
},
"order_creation_date": {
"type": "date",
"format": "date_optional_time"
},
"order_reference": {
"type": "text"
},
"order_id": {
"type": "keyword",
"normalizer": "lowercase_normalizer"
},
"to_name": {
"type": "text",
"analyzer": "partial_matcher",
"search_analyzer": "standard"
},
"to_suburb": {
"type": "text",
"analyzer": "whitespace"
},
"to_state": {
"type": "text",
"analyzer": "whitespace"
},
"to_postcode": {
"type": "text",
"analyzer": "whitespace"
},
"to_email": {
"type": "text",
"analyzer": "whitespace"
}
}
}
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To add a new fields to ElasticSearch, while dynamic mapping is off:
Run with additional fields JSON file, with URL: http://localhost:9200/orders/_mapping/order, Method: PUT
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| {
"properties": {
"from_name": {
"type": "text",
"analyzer": "partial_matcher",
"search_analyzer": "standard"
},
"from_business_name": {
"type": "text",
"analyzer": "partial_matcher",
"search_analyzer": "standard"
},
"from_suburb": {
"type": "text",
"analyzer": "whitespace"
},
"from_state": {
"type": "text",
"analyzer": "whitespace"
},
"from_postcode": {
"type": "text",
"analyzer": "whitespace"
},
"from_country": {
"type": "text",
"analyzer": "whitespace"
},
"from_email": {
"type": "text",
"analyzer": "whitespace"
},
"from_phone": {
"type": "text",
"analyzer": "whitespace"
}
}
}
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An ElasticSearch query example, with URL: http://localhost:9200/orders/_search, Method: POST
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| {
"query": {
"bool": {
"must": [
{"match": {"customer_id": "1234567890"} },
{"simple_query_string": {
"query": "unlabelled+unmanifested",
"fields": ["metadata_tags"]
} },
{
"bool": {
"should": [
{
"multi_match": {
"query": "TerrenceMiao",
"fields": [
"name", "business_name", "order_id", "shipment_id", "sender_references", "article_ids"
]
}
},
{"match": {"phone": "abracadbravvv5/vv70qBu+/ve+/ve6EuA7vv70g77+9Su+/ve+/vX5y77+95JuV"} },
{
"multi_match": {
"query": "gdgdggddvvv75/vv70qBu+/ve+/ve6EuA7vv70g77+9Su+/ve+/vX5y77+95JuV",
"fields": [
"suburb", "state", "country", "postcode", "email"
]
}
}
]
}
},
{"simple_query_string": {
"query": "DESPATCH",
"fields": ["movement_type"]
} }
]
}
},
"sort": [
{"order_creation_date": {"order": "desc", "unmapped_type": "date"} },
{"shipment_creation_date": {"order": "desc"} }
],
"from": "0","size": "1"
}
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An example query with date/time type in a range:
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| {
"query": {
"range": {
"shipment_creation_date": {
"gte": "2018-04-19T15:30:00",
"lte": "now",
"time_zone": "+10:00"
}
}
},
"from": 0,
"size": 10,
"sort": [],
"aggs": {}
}
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