一次ES從5.2版本升級到7.13測試生產完全實操記錄(Elasticsearch upgrade)

一次ES從5.2版本升級到7.13測試生產完全實操記錄

目前正在使用的elasticsearch 版本是5.2 ，使用Java Transport Client + Springbooot 構建的項目 ,
升級es引擎到最新版本7.13，需要代碼層面的改動。由於項目Springboot 版本是1.4.2,即選用Java REST Client[7.13]
因為是跨大版本升級，ES官網給出升級方案

If you are running a version prior to 6.0, upgrade to 6.8 and reindex your old indices or bring up a new 7.13.4 cluster and reindex from remote.

數據遷移方式：新建集群重建索引(bring up a new 7.13.4 cluster and reindex from remote)

測試環境ES實踐

1. 部署ES集群

  測試環境2台節點的集群，啟動2台虛擬機，
  ip分別位192.169.10.167、192.169.10.168

• 下載tag包，選擇自己需要的版本，並下載相應版本的kibana
• 解壓Es 到/usr/local/es,
  tar -zxvf elasticsearch-7.13.0-linux-x86_64.tar.gz -C /usr/local/es
  但是由於安全的考慮，elasticsearch不允許使用root用戶來啟動，所以需要創建一個新的用戶，並為這個賬戶賦予相應的權限來啟動elasticsearch集群。

useradd es
passwd es 

#創建文件夾用於存放數據和日志
mkdir -p /var/data/elasticsearch
mkdir -p /var/log/elasticsearch

# 改變文件的擁有者為es
chown -R es /usr/local/es/
chown -R es /var/log/elasticsearch
chown -R es /var/data/elasticsearch

• 配置
  JDK配置
  新版本自帶適應的JDK，這里直接采用修改啟動文件./bin/elasticsearch

#vim ./bin/elasticsearch添加如下配置
export JAVA_HOME=/usr/local/es/elasticsearch-7.13.0/jdk
export PATH=$JAVA_HOME/bin:$PATH

ES 配置文件主要位於 $ES_HOME/config 目錄下

最新版本 Elasticsearch 主要有三個配置文件：
elasticsearch.yml ES 的配置，more
jvm.options ES JVM 配置，more
log4j2.properties ES 日志配置，more

復制5.2版本的配置 注意參數名版本之間的變化
elasticsearch.yml 配置如下

#集群名
cluster.name:  microants-es-004
#節點名
node.name: node-01

# 數據目錄
path.data: /var/data/elasticsearch
# 日志目錄
path.logs: /var/log/elasticsearch

#網絡配置
network.host: 192.168.10.167
http.port: 9200
#遷移地址白名單
reindex.remote.whitelist: ["192.168.10.154:9200","192.168.10.155:9200"]

discovery.seed_hosts: ["192.168.10.167", "192.168.10.168"]
cluster.initial_master_nodes: ["node-01", "node-02"]

jvm.options

-Xms2g
-Xmx2g

其他可能需要的配置
1.修改文件描述符數目 2.最大映射數量MMP

#編輯 /etc/security/limits.conf，追加以下內容；
* soft nofile 65536
* hard nofile 65536

#/etc/sysctl.conf文件最后添加一行
vm.max_map_count=262144
#執行/sbin/sysctl -p 立即生效

• 啟動

#切換es 啟動 否則會失敗 
su es
./bin/elasticsearch -d

• 驗證啟動 http://192.168.10.167:9200/

{
"name": "node-01",
"cluster_name": "microants-es-004",
"cluster_uuid": "_na_",
"version": {
"number": "7.13.0",
"build_flavor": "default",
"build_type": "tar",
"build_hash": "5ca8591c6fcdb1260ce95b08a8e023559635c6f3",
"build_date": "2021-05-19T22:22:26.081971330Z",
"build_snapshot": false,
"lucene_version": "8.8.2",
"minimum_wire_compatibility_version": "6.8.0",
"minimum_index_compatibility_version": "6.0.0-beta1"
},
"tagline": "You Know, for Search"
}

至此 啟動第二台 192.169.10.168 ,設置elasticsearch.yml 時 集群名保持一致
驗證 http://192.168.10.167:9200/_cat/nodes 返回集群節點

192.168.10.168 19 45 15 0.43 0.19 0.11 cdfhilmrstw - node-02
192.168.10.167 23 49  0 0.24 0.11 0.07 cdfhilmrstw * node-01

• 部署kibana
  • 下載找到對應版本 https://www.elastic.co/cn/downloads/past-releases#kibana
  • 解壓

tar -zxvf kibana-7.13.0-linux-x86_64.tar.gz -C /opt/soft

配置 vim ./config/kibana.yml

server.port: 5601
server.host: "192.168.10.167"

elasticsearch.hosts: ["http://192.168.10.167:9200"]

i18n.locale: "zh-CN"

啟動 (最好添加kibana 用戶)

nohup ./bin/kibana &

集群安全設置

• 最低安全設置 https://www.elastic.co/guide/en/elasticsearch/reference/7.13/security-minimal-setup.html
  1.在每個節點 elasticsearch.yml 文件下加入
  xpack.security.transport.ssl.enabled: true xpack.security.transport.ssl.verification_mode: certificate xpack.security.transport.ssl.client_authentication: required xpack.security.transport.ssl.keystore.path: elastic-certificates.p12 xpack.security.transport.ssl.truststore.path: elastic-certificates.p12

2. 啟動
   ./bin/elasticsearch
3. 生成用戶和密碼采用走動生成
   ./bin/elasticsearch-setup-passwords auto
   結果會打印再控制台 保存 如：

hanged password for user apm_system
PASSWORD apm_system = IywjBT4YDU86NDw7ox

Changed password for user kibana_system
PASSWORD kibana_system = SQmORp23LcZyPZU48l

Changed password for user kibana
PASSWORD kibana = SQmORp2Nb3LcPZU48l

Changed password for user logstash_system
PASSWORD logstash_system = cEtJPTbzktxc7aPuQx

Changed password for user beats_system
PASSWORD beats_system = 5wDk7jQNu4iP5J7eLg

Changed password for user remote_monitoring_user
PASSWORD remote_monitoring_user = p1HkCWzYVtt8SPGEtN

Changed password for user elastic
PASSWORD elastic = PRmId87ogKerJboyLw

4. 任何節點生成ca證書
   ./bin/elasticsearch-certutil ca
   會生成一個elastic-stack-ca.p12 文件
   ./bin/elasticsearch-certutil cert --ca elastic-stack-ca.p12
   生成elastic-certificates.p12 文件
5. 復制文件 elastic-certificates.p12 到所有節點的conf目錄下
6. 如果證書有密碼 執行 ./bin/elasticsearch-keystore add xpack.security.transport.ssl.keystore.secure_password
   7.重啟es ,驗證查看節點是否可以通信

2.數據遷移

• 插件適配

查看老版本使用的插件
http://192.168.10.154:9200/_cat/plugins
返回：
node-0001 analysis-icu      5.2.0 
node-0001 analysis-ik       5.2.0 
node-0001 analysis-kuromoji 5.2.0 
node-0001 analysis-pinyin   5.2.1
 
node-0002 analysis-icu      5.2.0 
node-0002 analysis-ik       5.2.0 
node-0002 analysis-pinyin   5.2.1     

先官網查看[插件文檔](https://www.elastic.co/guide/en/elasticsearch/plugins/7.13/installation.html) 

https://www.elastic.co/guide/en/elasticsearch/plugins/7.13/installation.html

# 安裝插件格式
sudo bin/elasticsearch-plugin install [plugin_name]

• 安裝icu

[root@localhost elasticsearch-7.13.0]# sudo bin/elasticsearch-plugin install analysis-icu
-> Installing analysis-icu
-> Downloading analysis-icu from elastic
[=================================================] 100%   
-> Installed analysis-icu
-> Please restart Elasticsearch to activate any plugins installed

• 安裝ik 、pinyin

./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v6.3.0/elasticsearch-analysis-ik-7.13.0.zip
#網速慢 下載 了幾次失敗
#github手動下載download https://github.com/medcl/elasticsearch-analysis-ik/releases
#create plugin folder cd your-es-root/plugins/ && mkdir ik
yum install -y unzip zip
#unzip plugin to folder your-es-root/plugins/ik
#解壓二者到plugins下
unzip elasticsearch-analysis-ik-7.13.0.zip -d /usr/local/es/elasticsearch-7.13.0/plugins/ik/
unzip elasticsearch-analysis-pinyin-7.13.0.zip -d /usr/local/es/elasticsearch-7.13.0/plugins/pinyin/
#重啟es
ps -ef | grep elastic
kill 9 4093
su es
./bin/elasticsearch -d

查看結果 ：http://192.168.10.167:9200/_cat/plugins

node-01 analysis-icu    7.13.0
node-01 analysis-ik     7.13.0
node-01 analysis-pinyin 7.13.0

node-02 analysis-ik     7.13.0
node-02 analysis-pinyin 7.13.0

• 開始數據遷移 官網建議 https://www.elastic.co/guide/en/elasticsearch/reference/7.13/reindex-upgrade-inplace.html

To manually reindex your old indices in place:
1. Create an index with 7.x compatible mappings.
2. Set the refresh_interval to -1 and the number_of_replicas to 0 for efficient reindexing.
3. Use the reindexAPI to copy documents from the 5.x index into the new index. You can use a script to perform any necessary modifications to the document data and metadata during reindexing.
4. Reset the refresh_interval and number_of_replicas to the values used in the old index.
5. Wait for the index status to change to green.
6. In a single update aliases request:
Delete the old index.
Add an alias with the old index name to the new index.
Add any aliases that existed on the old index to the new index.

• 老數據5.2數據需要遷移的索引 http://192.168.10.156:9200/_cat/indices

green  open  seller_subject_index_v1     efIwSm31QAiNwEdus0BVNg 5 1   6002    23     3mb   1.5mb
green  open  search_keyword_index_v1     BTalZTHlRrCTaxgFrcH-jA 5 1   3415     0   2.1mb     1mb
green  open  platform_coupon_index_v1    lD15Hyl6TtSWV2GP79aX8Q 5 1     57     0 192.4kb  96.2kb
	.
	.
	.
	.
green  open  syscate_index_v1            dEWSZp1sSq-lA9TINGyt0A 5 1   4660    15     9mb   4.5mb
green  open  cars                        gSqMCkN-SSa3EhH6Vm1nCw 5 1      8     0  47.3kb  23.6kb
green  open  product_keyword_hint_v1     ubQgLk4FRVaAciEHP7imQw 1 1    280     0 324.5kb 162.2kb
green  open  subject_index_v1            u-M6le0JSxmuxLxGLkNCUQ 5 1   1445    79  17.1mb   8.5mb

此處以seller_subject_index_v1索引例子演示

Create an index with 7.x compatible mappings.

• es.5.2的seting、mapping

點擊查看代碼

#kibana 管理工具
get seller_subject_index_v1/_settings
{
  "seller_subject_index_v1": {
    "settings": {
      "index": {
        "number_of_shards": "5",
        "provided_name": "seller_subject_index_v1",
        "creation_date": "1557301817602",
        "analysis": {
          "analyzer": {
            "keyword_analyzer": {
              "filter": [
                "lowercase"
              ],
              "type": "custom",
              "tokenizer": "keyword"
            },
            "comma_analyzer": {
              "filter": [
                "lowercase"
              ],
              "pattern": ",",
              "type": "pattern"
            },
            "semicolon_analyzer": {
              "filter": [
                "lowercase"
              ],
              "pattern": ";",
              "type": "pattern"
            }
          }
        },
        "number_of_replicas": "1",
        "uuid": "efIwSm31QAiNwEdus0BVNg",
        "version": {
          "created": "5020199"
        }
      }
    }
  }
}
get seller_subject_index_v1/_mapping
{
  "seller_subject_index_v1": {
    "mappings": {
      "seller_subject": {
        "_all": {
          "enabled": false
        },
        "_routing": {
          "required": true
        },
        "properties": {
          "buyer_uid": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "check_time": {
            "type": "long"
          },
          "create_time": {
            "type": "long"
          },
          "modify_time": {
            "type": "long"
          },
          "origin": {
            "type": "byte",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "publish_type": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "seller_uid": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "sort_time": {
            "type": "long"
          },
          "status": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "status_reason": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "subject_id": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          }
        }
      }
    }
  }
}

- es7.13 setings、mapping

點擊查看代碼

	put seller_subject_index_v1
{
  "settings": {
      "index": {
        "refresh_interval":-1,
        "number_of_shards": "5",
        "analysis": {
          "analyzer": {
            "keyword_analyzer": {
              "filter": [
                "lowercase"
              ],
              "type": "custom",
              "tokenizer": "keyword"
            },
            "comma_analyzer": {
              "filter": [
                "lowercase"
              ],
              "pattern": ",",
              "type": "pattern"
            },
            "semicolon_analyzer": {
              "filter": [
                "lowercase"
              ],
              "pattern": ";",
              "type": "pattern"
            }
          }
        },
        "number_of_replicas": "1"
      }
  },
  "mappings": {
        "_routing": {
          "required": true
        },
        "properties": {
          "buyer_uid": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "check_time": {
            "type": "long"
          },
          "create_time": {
            "type": "long"
          },
          "modify_time": {
            "type": "long"
          },
          "origin": {
            "type": "byte",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "publish_type": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "seller_uid": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "sort_time": {
            "type": "long"
          },
          "status": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "status_reason": {
            "type": "short",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          },
          "subject_id": {
            "type": "long",
            "fields": {
              "comma": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "comma_analyzer"
              }
            }
          }
        }
      }
}



post /_aliases
{
    "actions":[
      { "add":{ "index":"seller_subject_index_v1","alias":"seller_subject_index"}
  }]
}

最后別忘了 別名映射

• _reindex API https://www.elastic.co/guide/en/elasticsearch/reference/7.13/docs-reindex.html

##遷移數據seller_subject_index_v1  再kibana 工具執行
##

Post _reindex
{
  "source":{
    "remote":{
      "host":"http://192.168.10.154:9200",
      "socket_timeout": "1m",
      "connect_timeout": "10s"
    },
   "index":"seller_subject_index_v1"
  },
  "dest":{
    "index":"seller_subject_index_v1"
  }
}

put /seller_subject_index_v1/_settings
{
  "index":{
    "refresh_interval": "1s"
  }
}

• 繼續執行其他索引
• 小結及重要的點
  1.出現{"statusCode":502,"error":"Bad Gateway","message":"Client request timeout"} ，加上參數wait_for_completion=false
  2. 一個索引有多個doc時需要拆分 加type參數

應用層代碼修改

官方文檔https://www.elastic.co/guide/en/elasticsearch/client/java-rest/current/java-rest-high.html

This section describes how to migrate existing code from the TransportClient to the Java High Level REST Client released with the version 5.6.0 of Elasticsearch.

• 如何遷移

Adapting existing code to use the RestHighLevelClient instead of the TransportClient requires the following steps:
1. Update dependencies
2.Update client initialization
3.Update application code

調整現有代碼以使用RestHighLevelClient代替TransportClient 需要以下步驟：
- 更新依賴
- 更新客戶端初始化
- 更新應用代碼

Since the Java High Level REST Client does not support request builders, applications that use them must be changed to use requests constructors instead

**代碼層面的改**變就是TransportClient的請求構建器不支持使用 如：

IndexRequestBuilder indexRequestBuilder   = transportClient.prepareIndex();  
DeleteRequestBuilder deleteRequestBuilder = transportClient.prepareDelete(); 
SearchRequestBuilder searchRequestBuilder = transportClient.prepareSearch(); 

用Java High Level REST 構造器替換 如：

IndexRequest request = new IndexRequest("index").id("id"); 
request.source("{\"field\":\"value\"}", XContentType.JSON);