如何在我的索引下面生成
在你的本地创建一个环境
使用 pip 安装必要的库(elasticsearch、requests、requests_aws4auth、boto3)
使用 lambda_function.py在里面创建文件env\Lib\site-packages\
并添加以下代码
压缩上述文件夹并将其命名为 lambda_function.zip 并上传到 lambda 函数,您可以在其中创建具有必要 IAM 角色的函数
import boto3
from requests_aws4auth import AWS4Auth
from elasticsearch import Elasticsearch, RequestsHttpConnection
session = boto3.session.Session()
credentials = session.get_credentials()
awsauth = AWS4Auth(credentials.access_key,
credentials.secret_key,
session.region_name, 'es',
session_token=credentials.token)
es = Elasticsearch(
['https://search-testelastic-2276kyz2u4l3basec63onfq73a.us-east-1.es.amazonaws.com'],
http_auth=awsauth,
use_ssl=True,
verify_certs=True,
connection_class=RequestsHttpConnection
)
def lambda_handler(event, context):
es.cluster.health()
es.indices.create(index='my-index', ignore=400)
r = [{'Name': 'Dr. Christopher DeSimone', 'Specialised and Location': 'Health'},
{'Name': 'Dr. Tajwar Aamir (Aamir)', 'Specialised and Location': 'Health'}]
for e in enumerate(r):
es.index(index="my-index", body=e[1])
回复如下
{"took":2,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":3,"relation":"eq"},"max_score":1.0,"hits":[{"_index":"my-index_1","_type":"_doc","_id":"elqrJHMB10jKFvejVaNM","_score":1.0,"_source":{"Name":"Dr. Christopher DeSimone","Specialised and Location":"Health"}},{"_index":"my-index_1","_type":"_doc","_id":"e1qrJHMB10jKFvejVqMK","_score":1.0,"_source":{"Name":"Dr. Tajwar Aamir (Aamir)","Specialised and Location":"Health"}},{"_index":"my-index_1","_type":"_doc","_id":"fFqrJHMB10jKFvejVqMR","_score":1.0,"_source":{"Name":"Dr. Bernard M. Aaron","Specialised and Location":"Health"}}]}}
如何将上述响应保存为 s3 存储桶中文件夹中的 json
存储桶名称 = test20220elastic
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