elasticsearch使用脚本 滚动关闭索引，更新index setting

一 问题

     在旧的索引中更新mapping时，新增了分词器（分词器已经在模板中添加），但是在更新mapping时报错：

查看elasticsearch官网，发现不允许在已经存在的索引中动态更新分词器，只能先将索引close,更新分词器，然后再打开

Update index settings API | Elasticsearch Guide [8.3] | Elastic

You can only define new analyzers on closed indices.

To add an analyzer, you must close the index, define the analyzer, and reopen the index.

二 问题解决方式步骤（已经验证）

2.1 由暂停数据写入&关闭分片分配

    暂停数据写入，可以避免恢复阶段translog中大量数据回放，提升索引恢复速度。

关闭分片分配

 PUT _cluster/settings
  { "persistent" : { "cluster.routing.rebalance.enable": "none" } }

2.2 对所有需要进行更新分词器的索引执行flush操作。

    作用是将内存buffer flush到硬盘中，避免恢复阶段translog中大量数据回放，提升索引恢复速度。

   （1）获取所有索引

          GET /_cat/indices

 （2）获取指定索引对应的setting

         GET /prod_candidatev2_chunk_{i}/_settings

        根据setting内容判断索引是否包含分词器 back_edge_ngram_analyzer word_analyzer 作为更新索引判断依据

  （3）对指定索引进行flush操作以及sync操作，加速恢复，避免从主分片全量拉取数据同步至副本。

     POST /index{i}/_flush

    POST /index{i}/_flush/synced

2.3 对索引进行关闭操作

  POST /index{i}/_close

2.4 更新索引分词器

PUT index{i}/_settings
{
    
    "analysis": {
      "filter":{
        "back_edge_ngram_filter": {
          "min_gram": "1",
          "side": "back",
          "type": "edgeNGram",
          "max_gram": "256"
        }
      },
      "analyzer": {
        "back_edge_ngram_analyzer": {
          "filter": [
            "standard",
            "lowercase",
            "back_edge_ngram_filter"
          ],
          "tokenizer": "keyword"
        },
        "word_analyzer": {
          "filter": [
            "standard",
            "lowercase"
          ],
          "tokenizer": "keyword"
        },
        "mk_edge2": { 
              "type": "mk_edge",
              "extra_prarm": "cb,3,-1"
            },
            "mk_edge1": {  
              "type": "mk_edge",
              "extra_prarm": "wb,1,-1"
            }
      }
    }
  }

2.5 轮询等待集群恢复green状态

GET  _cluster/health

2.6 重复2.2至2.5步骤，直至所有索引恢复

python处理脚本：

import time
 
from tqdm import trange
 
from elasticsearch import Elasticsearch
 
ES_HOST = ["http://elastic:"]
 
client = Elasticsearch(ES_HOST)
 
# index_pattern = "thoth_candidatev2_chunk_*"
index_pattern = "prod_candidatev2_chunk_*"
# index_pattern = "test_candidatev2_chunk_*"
 
put_all_index = False
 
def main():
    all_indices = get_all_indices()
    print("Number of indices: ", len(all_indices))
    all_indices = [index for index in all_indices if not is_updated_index_settings(index) ]
    print("Number of not updated indices: ", len(all_indices))
    for index in all_indices:
        if put_all_index or select():
            print(f"Start put {index} settings")
            put_index_settings(index)
            check_cluster_health(index)
        else:
            break
    print('Finished')
 
def select():
    global put_all_index
 
    text = input("continue(all/y/n): ")
    if text == 'y':
        return True
    elif text == 'n':
        return False
    elif text == 'all':
        put_all_index = True
        return True
        
    
def is_updated_index_settings(index):
    settings = client.indices.get_settings(index=index)
    analysis = settings[index]["settings"]["index"]["analysis"]
    if "word_analyzer" in analysis["analyzer"] and "back_edge_ngram_analyzer" in analysis["analyzer"] and "back_edge_ngram_filter" in analysis["filter"]:
        print(f"{index} done")
        return True
    else:
        return False
 
def put_index_settings(index):
    
    if client.cat.indices(index=index,params={"h": "status"}).strip() != 'close':
        print(f"flush {index}")
        client.indices.flush(index=index)
        print(f"flush {index} done")
    
    close_index(index)
 
    body = '{"analysis":{"filter":{"back_edge_ngram_filter":{"min_gram":"1","side":"back","type":"edgeNGram","max_gram":"256"}},"analyzer":{"back_edge_ngram_analyzer":{"filter":["standard","lowercase","back_edge_ngram_filter"],"tokenizer":"keyword"},"word_analyzer":{"filter":["standard","lowercase"],"tokenizer":"keyword"},"mk_edge2":{"type":"mk_edge","extra_prarm":"cb,3,-1"},"mk_edge1":{"type":"mk_edge","extra_prarm":"wb,1,-1"}}}}'
    client.indices.put_settings(index=index, body=body)
    
    if not is_updated_index_settings(index):
        print(f"put index error: {index}")
        put_index_settings(index)
    
    open_index(index)
 
def close_index(index):
    print(f"{index} status: ", client.cat.indices(index=index,params={"h": "status"}).strip())
    client.indices.close(index)
    print(f"{index} status: ", client.cat.indices(index=index,params={"h": "status"}).strip())
 
def open_index(index):
    print(f"{index} status: ", client.cat.indices(index=index,params={"h": "status"}).strip())
    client.indices.open(index)
    print(f"{index} status: ", client.cat.indices(index=index,params={"h": "status"}).strip())
 
 
def check_cluster_health(index):
    t = trange(100, desc="recover: ", leave=True)
    last_progress = 0
    while client.cluster.health()["status"] != "green":
        t.set_description(client.cluster.health()["status"])
        current_progress = client.cluster.health()["active_shards_percent_as_number"]
        t.update(current_progress - last_progress)
        last_progress = current_progress
        recovery_status = client.cat.recovery(index=index, params={"h": "index,shard,translog_ops_percent,files_percent,stage", "v": "true"})
        output = []
        for idx, item in enumerate(recovery_status.split('\n')):
            if idx == 0:
                output.append(item)
            else:
                output.append(item) if not item.endswith('done') else None
        if len(output) > 1:
            print('\n'.join(output))
        time.sleep(2)
    t.set_description(client.cluster.health()["status"])
    t.update(100 - last_progress)
    t.close()
 
def get_all_indices():
    return client.indices.get_alias(index_pattern) 
 
def test_put_index():
    index = "test_candidatev2_chunk_{chunk}"
    body = ''
    for chunk in range(0, 10):
        client.indices.create(index=index.format(chunk=chunk), body=body)
 
 
if __name__ == "__main__":
    # test_put_index()
    main()