elasticsearch是经常用到的文档索引工具，使用方便快捷。
之前介绍了如何创建和查询索引结构
https://blog.csdn.net/liliang199/article/details/154641939
这里进一步示例在创建索引后，如何增加、删除、以及修改数据。
所用示例代码参考和修改自网络资料。
1 es索引管理
这里简单示例如何创建、和修改索引。
1.1 创建连接
首先连接es，示例如下
from elasticsearch.helpers import bulk
import elasticsearch
class ElasticSearchClient(object):
@staticmethod
def get_es_servers():
es_host = "http://localhost:9200"
es_client = elasticsearch.Elasticsearch(hosts=es_host)
return es_client
es_client = ElasticSearchClient().get_es_servers()
print(es_client.info())输出如下
{'name': 'a2e27d00bb95', 'cluster_name': 'docker-cluster', 'cluster_uuid': 'fXhGBstXTKmI3dd0JBq_mw', 'version': {'number': '8.11.3', 'build_flavor': 'default', 'build_type': 'docker', 'build_hash': '64cf052f3b56b1fd4449f5454cb88aca7e739d9a', 'build_date': '2023-12-08T11:33:53.634979452Z', 'build_snapshot': False, 'lucene_version': '9.8.0', 'minimum_wire_compatibility_version': '7.17.0', 'minimum_index_compatibility_version': '7.0.0'}, 'tagline': 'You Know, for Search'}
1.2 索引创建
创建名称为es_index_test的索引，包含document_id, title字段。
index = "es_index_test"
mapping = {
"properties": {
"document_id": {
"type": "text"
},
"title": {
"type": "text"
},
}
}
print(es_client.indices.exists(index=index))
res = es_client.indices.create(
index=index,
mappings=mapping
)
print(res)输出如下
False
{'acknowledged': True, 'shards_acknowledged': True, 'index': 'es_index_test'}
1.3 索引修改
这里在不重建索引前提下，新增content字段，示例如下。
# 添加新字段 "new_field" 为 keyword 类型
es_client.indices.put_mapping(
index=index,
body={
"properties": {
"content": {"type": "text"}
}
}
)
# 查看修改后的索引
res2 = es_client.indices.get(index=index)
print(res2)输出示例如下
{'es_index_test': {'aliases': {}, 'mappings': {'properties': {'content': {'type': 'text'}, 'document_id': {'type': 'text'}, 'title': {'type': 'text'}}}, 'settings': {'index': {'routing': {'allocation': {'include': {'_tier_preference': 'data_content'}}}, 'number_of_shards': '1', 'provided_name': 'es_index_test', 'creation_date': '1764842498013', 'number_of_replicas': '1', 'uuid': 'OP22_lHLQvCidVxzPyApyA', 'version': {'created': '8500003'}}}}}
1.4 删除索引
这里示例如何删除索引
if es_client.indices.exists(index=index):
print('test_index索引存在，即将删除')
es_client.indices.delete(index=index)
else:
print('test_index索引不存在！')2 es数据操作
这里示例如何导入、修改和删除索引的具体数据项。
2.1 单条导入
单条数据导入示例如下
obj1 = {
"document_id": "news_1",
"title": u"The Ten Best Science Books of 2025",
"content": u"In 2025, our science reporters followed the first confirmed glimpse of a colossal squid and a rare look at dinosaur blood vessels. We watched the odds of a future asteroid impact climb to higher-than-normal levels---then drop back down to zero. We parsed headlines on a blood test to detect cancer and a beloved pair of coyotes in New York City's Central Park. Throughout it all, many of us read extended works of science nonfiction, pulling back the curtain on tuberculosis, evolution and the Arctic....",
}
obj2 = {
"document_id": "news_2",
"title": u"The 7 Most Groundbreaking NASA Discoveries of 2025",
"content": u"In 2025, NASA faced unprecedented uncertainty as it grappled with sweeping layoffs, looming budget cuts, and leadership switch-ups. Despite all of that, the agency somehow still managed to do some seriously astonishing science.....",
}
_id1 = 1
es_client.index(index=index, body=obj1, id=_id1)
_id2 = 2
es_client.index(index=index, body=obj2, id=_id2)输出如下
ObjectApiResponse({'_index': 'es_index_test', '_id': '2', '_version': 4, 'result': 'updated', '_shards': {'total': 2, 'successful': 1, 'failed': 0}, '_seq_no': 8, '_primary_term': 1})
2.2 批量导入
批量插入数据示例如下
from elasticsearch.helpers import bulk
def add_date_bulk(es_client, index, row_obj_list):
"""
批量插入ES
"""
load_data = []
i = 1
bulk_num = 2000 # 2000条为一批
for row_obj in row_obj_list:
action = {
"_index": index,
"_id": row_obj.get('_id', 'None'),
"_source": {
'document_id': row_obj.get('document_id', None),
'title': row_obj.get('title', None),
'content': row_obj.get('content', None),
}
}
load_data.append(action)
i += 1
# 批量处理
if len(load_data) == bulk_num:
print('插入', i / bulk_num, '批数据')
print(len(load_data))
success, failed = bulk(es_client, load_data, index=index, raise_on_error=True)
del load_data[0:len(load_data)]
print(success, failed)
if len(load_data) > 0:
success, failed = bulk(es_client, load_data, index=index, raise_on_error=True)
del load_data[0:len(load_data)]
print(success, failed)
write_obj = {
"_id": 1,
"document_id": 1,
"title": u"Elasticsearch 完全指南：原理、优势与应用场景",
"content": u"Elasticsearch 是一个基于 Apache Lucene 构建的开源、分布式、RESTful 搜索和分析引擎。它是 Elastic Stack（ELK Stack）的核心组件，由 Elastic 公司开发和维护。",
}
row_obj_list = [write_obj]
for i in range(2, 2200):
temp_obj = write_obj.copy()
temp_obj["_id"] = i
temp_obj["document_id"] = str(i)
row_obj_list.append(temp_obj)
add_date_bulk(es_client, index, row_obj_list)输出如下
插入 1.0005 批数据
2000
2000 \[\]
199 \[\]
2.3 数据修改
单条数据修改更细示例如下，需要先获取到id，然后依据id更新对应的文档。
def update_by_id(es_client, index, row_obj):
"""
根据给定的_id,更新ES文档
:return:
"""
_id = row_obj.get("_id", 1)
row_obj.pop("_id")
es_client.update(index=index, body={"doc": row_obj}, id=_id)
row_obj = {
"_id": 1,
"document_id": 6,
"title": u"20个必知的PyTorch概念简单解释,带你快速入门",
"content": u"PyTorch是当今最重要且最受欢迎的深度学习框架之一。它基于Meta的Lua语言Torch库构建，并于2017年开源。自发布以来，该库已被用于构建几乎所有重要的现代AI创新，从特斯拉的自动驾驶汽车到OpenAI的ChatGPT。本文将从基础出发，系统阐述20个最重要的概念，以深化对PyTorch的理解。",
}
update_by_id(es_client, index, row_obj)2.4 数据删除
依据id删除文档示例如下。
先获取到id，然后依据id删除对应的文档。
def delete_by_id(es_client, index, _id):
"""
根据给定的id,删除文档
:return:
"""
es_client.delete(index=index, id=_id)
_id = 8
delete_by_id(es_client, index, _id)reference
elasticsearch创建和查询索引结构示例
https://blog.csdn.net/liliang199/article/details/154641939
ElasticSearch 数据增删改实现