Elasticsearch集群管理在分布式环境中的应用

from elasticsearch import Elasticsearch
 
# 假设ES服务器地址列表
es_servers = [
    {"host": "es-node1", "port": 9200},
    {"host": "es-node2", "port": 9200},
    {"host": "es-node3", "port": 9200}
]
 
# 连接Elasticsearch集群
es = Elasticsearch(es_servers)
 
# 检查集群健康状态
health_status = es.cluster.health()
print(f"Cluster Health: {health_status['status']}")
 
# 获取集群状态信息
cluster_state = es.cluster.state()
print(f"Number of Nodes in the Cluster: {len(cluster_state['nodes'])}")
 
# 更新集群设置
new_settings = {
    "transient": {
        "cluster.max_shards_per_node": 10000
    }
}
es.cluster.put_settings(body=new_settings)
 
# 获取并打印更新后的集群设置
updated_settings = es.cluster.get_settings()
print(f"Updated Cluster Settings: {updated_settings['transient']['cluster.max_shards_per_node']}")
 
# 关闭集群
# es.shutdown()

这段代码展示了如何使用Elasticsearch Python API连接到Elasticsearch集群，检查集群健康状况、获取集群状态信息，并更新集群设置。最后，代码中包含了一个关闭集群的注释命令，实际使用时应该取消注释以确保不会误操作。