Datenbanken_II/elasticsearch_nested.py
2023-03-07 14:35:47 +01:00

52 lines
1.8 KiB
Python

from elasticsearch import Elasticsearch
# Create a connection to Elasticsearch
es = Elasticsearch("http://localhost:9200")
# Define an index mapping
mapping = {
"mappings": {
"properties": {
"customer_name": {"type": "keyword"},
"orders": {
"type": "nested",
"properties": {
"order_id": {"type": "integer"},
"product_name": {"type": "keyword"},
"quantity": {"type": "integer"},
"price": {"type": "float"}
}
}
}
}
}
# Create an index with the mapping
es.indices.create(index="customers", body=mapping)
# Insert some documents
es.index(index="customers", body={"customer_name": "Alice", "orders": [
{"order_id": 1, "product_name": "Apple", "quantity": 2, "price": 1.00},
{"order_id": 4, "product_name": "Banana", "quantity": 1, "price": 0.50}
]})
es.index(index="customers", body={"customer_name": "Bob", "orders": [
{"order_id": 2, "product_name": "Banana", "quantity": 3, "price": 0.50}
]})
es.index(index="customers", body={"customer_name": "Charlie", "orders": [
{"order_id": 3, "product_name": "Cherry", "quantity": 1, "price": 2.00},
{"order_id": 5, "product_name": "Durian", "quantity": 2, "price": 3.00}
]})
# Search for documents
query = {"query": {"nested": {"path": "orders", "query": {"match": {"orders.product_name": "Banana"}}}}}
result = es.search(index="customers", body=query)
# Print the search results
for hit in result['hits']['hits']:
print(hit['_source'])
# OUTPUT
'''
{'customer_name': 'Alice', 'orders': [{'order_id': 4, 'product_name': 'Banana', 'quantity': 1, 'price': 0.5}]}
{'customer_name': 'Bob', 'orders': [{'order_id': 2, 'product_name': 'Banana', 'quantity': 3, 'price': 0.5}]}
'''