ELK系列(十三)、在Hive中操作ES的索引数据，创建/查询/更新/插入

- 日理万妓 2023-02-15 03:42 23阅读 0赞

本篇介绍如何在hive中查询、更新、插入ES数据，以及把数据从hive导入到es中。本方案适用于任何hive可以挂外表的数据库类型。

[ELK系列(一)、安装ElasticSearch+Logstash+Kibana+Filebeat-v7.7.0][ELK_ElasticSearch_Logstash_Kibana_Filebeat-v7.7.0]

[ELK系列(二)、在Kibana中使用RESTful操作ES库][ELK_Kibana_RESTful_ES]

[ELK系列(三)、安装Logstash插件及打包离线安装包][ELK_Logstash]

[ELK系列(四)、Logstash读取nginx日志写入ES中][ELK_Logstash_nginx_ES]

[ELK系列(五)、Logstash修改@timestamp时间为日志的产生时间][ELK_Logstash_timestamp]

[ELK系列(六)、修改Nginx日志为Json格式并使用Logstash导入至ES][ELK_Nginx_Json_Logstash_ES]

[ELK系列(七)、Filebeat+Logstash采集多个日志文件并写入不同的ES索引中][ELK_Filebeat_Logstash_ES]

[ELK系列(八)、使用Filebeat+Redis+Logstash收集日志数据][ELK_Filebeat_Redis_Logstash]

[ELK系列(九)、配置ES和Kibana的用户密码][ELK_ES_Kibana]

[ELK系列(十)、ES中文分词器IK插件安装和配置远程词库热加载][ELK_ES_IK]

[ELK系列(十一)、ElasticSearch7.7.0插件es-head安装及使用][ELK_ElasticSearch7.7.0_es-head]

[ELK系列(十二)、使用SQL查询ElasticSearch7.7.0][ELK_SQL_ElasticSearch7.7.0]

\-----------------------------------------------在HIVE中操作ES----------------------------------------------

官方文档：[https://www.elastic.co/guide/en/elasticsearch/hadoop/current/hive.html][https_www.elastic.co_guide_en_elasticsearch_hadoop_current_hive.html]

下载：[https://www.elastic.co/cn/downloads/past-releases\#es-hadoop][https_www.elastic.co_cn_downloads_past-releases_es-hadoop]

参数：[https://www.elastic.co/guide/en/elasticsearch/hadoop/current/configuration.html][https_www.elastic.co_guide_en_elasticsearch_hadoop_current_configuration.html]

# 环境 #

CDH-6.3.1
    
    hive-2.1.1
    
    ElasticSearch-6.6.2  (ES7.7一样的，因为之前用的ES6没升级，修改配置需要重启HIVE所以我就不用ES7演示了)

# 依赖 #

要在hive中查询操作ES需要先将ES的jar包放在hive的依赖环境中，这里有几种方式，首先下载jar包，到上面的链接中下载对应ES版本的elasticsearch-hadoop-hive-6.6.2.jar，然后到hive的lib下【/opt/cloudera/parcels/CDH/jars/commons-httpclient-3.1.jar】找到commons-httpclient-3.1.jar，待会讲为什么需要它。

在hive中添加外部jar包，hive中加载外部jar包的方式有几种：

### 1. hive shell中add jar ###

session级别的配置，只在hive命令行生效，不需要重启服务。

#在hive shell中：
    #本地jar
    add jar /home/tools/wyk/elasticsearch-hadoop-hive-6.6.2.jar;
    add jar /home/tools/wyk/commons-httpclient-3.1.jar;
    #或hdfs的jar包
    add jar  hdfs://nameservice1/tmp/hive/elasticsearch-hadoop-hive-6.6.2.jar;
    add jar  hdfs://nameservice1/tmp/hive/commons-httpclient-3.1.jar;

![20200604145819686.png][]

### 2. 启动hive shell时添加配置 ###

session级别的配置，只在hive命令行生效，不需要重启服务。

hive -hiveconf hive.aux.jars.path=/home/tools/wyk/elasticsearch-hadoop-hive-6.6.2.jar

### 3. 在hive-site.xml中添加配置 ###

服务级别的配置，在hive-shell和hiveserver2都可以生效，需要重启Hive。

*vim hive-site.xml*

<property>
      <name>hive.aux.jars.path</name>
      <value>/path/elasticsearch-hadoop.jar</value>
      <description>A comma separated list (with no spaces) of the jar files</description>
    </property>

### 4. 将jar放置在hive.aux.jars.path下【推荐】 ###

服务级别的配置，在hive-shell和hiveserver2都可以生效，需要重启Hive，

把elasticsearch-hadoop-hive-6.6.2.jar和commons-httpclient-3.1.jar 放在hiveserver2节点的/home/public/java\_project/udf/目录，此目录在CM中可配置，参数为hive.aux.jars.path。

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70][]

###  为什么要添加httpclient的jar？ ###

如果不加的话很可能会遇到下面的错误信息，将【/opt/cloudera/parcels/CDH/jars/commons-httpclient-3.1.jar】文件也通过上面的方式加到依赖中即可解决此问题：

*java.lang.ClassNotFoundException: org.apache.commons.httpclient.protocol.ProtocolSocketFactory*

Error: java.lang.RuntimeException: java.lang.NoClassDefFoundError: org/apache/commons/httpclient/protocol/ProtocolSocketFactory
    	at org.apache.hadoop.hive.ql.exec.mr.ExecMapper.map(ExecMapper.java:157)
    	at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
    	at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:465)
    	at org.apache.hadoop.mapred.MapTask.run(MapTask.java:349)
    	at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:174)
    	at java.security.AccessController.doPrivileged(Native Method)
    	at javax.security.auth.Subject.doAs(Subject.java:422)
    	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1875)
    	at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:168)
    Caused by: java.lang.NoClassDefFoundError: org/apache/commons/httpclient/protocol/ProtocolSocketFactory
    	at org.elasticsearch.hadoop.rest.commonshttp.CommonsHttpTransportFactory.create(CommonsHttpTransportFactory.java:40)
    	at org.elasticsearch.hadoop.rest.NetworkClient.selectNextNode(NetworkClient.java:102)
    	at org.elasticsearch.hadoop.rest.NetworkClient.<init>(NetworkClient.java:85)
    	at org.elasticsearch.hadoop.rest.NetworkClient.<init>(NetworkClient.java:61)
    	at org.elasticsearch.hadoop.rest.RestClient.<init>(RestClient.java:94)
    	at org.elasticsearch.hadoop.rest.InitializationUtils.discoverNodesIfNeeded(InitializationUtils.java:90)
    	at org.elasticsearch.hadoop.rest.RestService.createWriter(RestService.java:581)
    	at org.elasticsearch.hadoop.mr.EsOutputFormat$EsRecordWriter.init(EsOutputFormat.java:173)
    	at org.elasticsearch.hadoop.hive.EsHiveOutputFormat$EsHiveRecordWriter.write(EsHiveOutputFormat.java:58)
    	at org.apache.hadoop.hive.ql.exec.FileSinkOperator.process(FileSinkOperator.java:769)
    	at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:882)
    	at org.apache.hadoop.hive.ql.exec.SelectOperator.process(SelectOperator.java:95)
    	at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:882)
    	at org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:130)
    	at org.apache.hadoop.hive.ql.exec.MapOperator$MapOpCtx.forward(MapOperator.java:146)
    	at org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:484)
    	at org.apache.hadoop.hive.ql.exec.mr.ExecMapper.map(ExecMapper.java:148)
    	... 8 more
    Caused by: java.lang.ClassNotFoundException: org.apache.commons.httpclient.protocol.ProtocolSocketFactory
    	at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
    	at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
    	at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
    	at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
    	... 25 more

# 验证 #

通过上面第四种方式将jar放放置在hs2节点的hive.aux.jar.path路径下并重启Hive之后即可生效，在HUE中也可以直接通过Hive操作ES了。

## hive建表属性 ##

建表的TBLPROPERTIES中的属性可以在官网文档中查看：[hive建表配置][https_www.elastic.co_guide_en_elasticsearch_hadoop_current_configuration.html]

...
    STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
    TBLPROPERTIES ( 
    'es.index.auto.create'='false',--自动创建索引
    'es.index.read.missing.as.empty'='true', --防止查询为空值报错
    'es.mapping.names'='id:id,name:name,age:age,pt:pt', --hive字段对应的ES字段，手动指定或自动映射
    'es.mapping.id'='id', --指定hive的字段对应es索引的_id值
    'es.resource'='wyk_csdn/_doc'  --ES中的索引
    'es.net.http.auth.pass'='ES密码', --ES密码
    'es.net.http.auth.user'='ES登录名', --ES登录名
    'es.nodes'='localhost',  --ES地址
    'es.port'='9200', 
    'es.nodes.wan.only'='true', 
    'es.nodes.discovery' = 'false',
    'es.read.metadata'='true'
    )

## 类型映射规则 ##

hive中建表的时候可以不指定字段映射，也可以手动指定字段的类型映射，不指定的话会自动映射字段类型，映射规则如下：

<table style="width:500px;">  hive和ES类型映射规则  
 <thead> 
  <tr> 
   <th style="width:249px;">Hive type</th> 
   <th style="width:250px;">Elasticsearch type</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td style="width:249px;">void</td> 
   <td style="width:250px;">null</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">boolean</td> 
   <td style="width:250px;">boolean</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">tinyint</td> 
   <td style="width:250px;">byte</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">smallint</td> 
   <td style="width:250px;">short</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">int</td> 
   <td style="width:250px;">int</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">bigint</td> 
   <td style="width:250px;">bigint</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">double</td> 
   <td style="width:250px;">double</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">float</td> 
   <td style="width:250px;">float</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">string</td> 
   <td style="width:250px;">string</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">binary</td> 
   <td style="width:250px;">binary</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">timestamp</td> 
   <td style="width:250px;">date</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">struct</td> 
   <td style="width:250px;">map</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">map</td> 
   <td style="width:250px;">map</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">array</td> 
   <td style="width:250px;">array</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">union</td> 
   <td style="width:250px;">not supported (yet)</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">decimal</td> 
   <td style="width:250px;">string</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">date</td> 
   <td style="width:250px;">date</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">varchar</td> 
   <td style="width:250px;">string</td> 
  </tr> 
  <tr> 
   <td style="width:249px;">char</td> 
   <td style="width:250px;">string</td> 
  </tr> 
 </tbody> 
</table>

## 验证交互 ##

### **在Hive中创建ES外表并在ES中创建索引并插入数据：** ###

-- 在Hive中创建ES外表并在ES中创建索引并插入数据
    DROP TABLE IF exists default.es_bigdata_csdn01;
    CREATE EXTERNAL TABLE if not exists default.es_bigdata_csdn01 (
     name string,
     age bigint,
     email string
    )
    STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
    TBLPROPERTIES('es.resource' = 'wyk_hive_csdn01/_doc',
    'es.index.auto.create' = 'true', --自动建index
    'es.index.read.missing.as.empty'='true',
    'es.nodes' = '10.1.174.10',
    'es.port'='9200'
    );
    -- 此时建完hive表，在es中没有索引
    -- 插入一条数据后，在es中才能看到该索引
    insert into default.es_bigdata_csdn01 values('王义凯',28,'wyk@csdn.com');

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 1][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 2][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 3][]

### **建hive外表读ES中已有的索引：** ###

-- 建hive外表读已有的索引
    CREATE EXTERNAL TABLE if not exists default.es_bigdata_csdn02(
     name string,
     age bigint,
     email string
    )
    STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
    TBLPROPERTIES('es.resource' = 'wyk_hive_csdn01/_doc',
    'es.index.auto.create' = 'false', --因为是已有索引，所以无需自动建，其实就算选择了自动建，也可以读到已有的数据
    'es.index.read.missing.as.empty'='true',
    'es.nodes' = '10.1.174.10',
    'es.port'='9200'
    );

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 4][]

### **hive建表的时候指定ES索引的id唯一键映射：** ###

在上面的Kibana截图中可以看到这条通过hive插入的数据的\_id 属性的值是自动生成的，那么如果我们想指定该\_id列为hive表的name列，这样的话就可以通过hive对ES的数据进行更新了，因为ES中\_id相同的内容会自动更新。

-- 在hive中建ES外表并指定主键_id的映射字段
    CREATE EXTERNAL TABLE if not exists default.es_bigdata_csdn03 (
     name string,
     age bigint,
     email string
    )
    STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
    TBLPROPERTIES('es.resource' = 'wyk_hive_csdn03/_doc',
    'es.index.auto.create' = 'true', --若es中没有wyk_hive_csdn03索引则自动创建(需要在hive中对该索引插入数据才会生效)
    'es.mapping.id'='name', --指定_id对应hive表的name字段
    'es.index.read.missing.as.empty'='true',
    'es.nodes' = '10.1.174.10',
    'es.port'='9200'
    );
    
    insert into default.es_bigdata_csdn03 values('王义凯',28,'wyk@csdn.com');

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 5][]

此时我们在Hive中对该记录进行更新，看看在ES中该记录会变成什么样，注意在hive中无法对ES表使用update和delete命令，因此我们仍旧使用insert命令只要主键相同就会自动更新：

insert into default.es_bigdata_csdn03 values('王义凯',29,'wyk29@csdn.com');
    insert into default.es_bigdata_csdn03 values('Rick.Wang',30,'rick30@csdn.com');

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 6][]

### ** 全量覆盖 insert overwrite** ###

效果等同于append，insert into，如果有相同主键则更新没有则insert。

--insert overwrite的效果等同于insert into
    insert overwrite table default.es_bigdata_csdn03 select 'Rick.Wang',33,'rick33@csdn.com';

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 7][]

### **多类型测试** ###

在hive中建一个测试表，类型丰富，测试在ES中自动映射之后的类型：

drop table if exists default.es_bigdata_csdn04;
    CREATE  TABLE if not exists default.es_bigdata_csdn04(
     id bigint,
     str_type string,
     decimal_type decimal(5,2),
     double_type double,
     float_type float,
     ins_ts timestamp,
     arr array<string>
    )
    STORED BY 'org.elasticsearch.hadoop.hive.EsStorageHandler'
    TBLPROPERTIES('es.resource' = 'wyk_hive_csdn04/_doc',
    'es.index.auto.create' = 'true',
    'es.mapping.id'='id',
    'es.index.read.missing.as.empty'='true',
    'es.nodes' = '10.1.174.10',
    'es.port'='9200'
    );
    --插入记录
    insert into default.es_bigdata_csdn04 select 1,'str',3.14,4.13333,1.3333444,current_timestamp(),array('str1','str2','str3');

注意这里插入数据的时候不能用insert ... values(), 因为带有集合类型的记录，只能用insert .. select ...的写法，否则会报下面的错误：

FAILED: SemanticException [Error 10293]: Unable to create temp file for insert values Expression of type TOK_FUNCTION not supported in insert/values

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 8][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 9][]

### 从hive将数据导入ES ###

这个就很简单了，到目前未知应该很多人都能想到了，其实就是按照hive源表结构创建hive外表连接ES，然后在hive中执行下面的命令即可：

*insert into hive\_es select \* from hive\_src\_tbl;*

### hive连接ES索引的其他的注意事项 ###

1.  不支持update,delete,truncate命令；
2.  truncate命令对hive外表(不能对no-managed的表进行清空操作)；
3.  truncate命令对hive内表(不支持清空non-native 非原生表)；
4.  删除hive中的表(无论是External表还是Internal表)，都是只会删掉hive表，对ES中的索引无影响；
5.  insert overwrite 全表覆盖，效果等同于append，insert into，如果有相同主键则更新没有则insert；

希望本文对你有帮助，请点个赞鼓励一下作者吧~ 谢谢！

[ELK_ElasticSearch_Logstash_Kibana_Filebeat-v7.7.0]: https://blog.csdn.net/wsdc0521/article/details/106236499
[ELK_Kibana_RESTful_ES]: https://blog.csdn.net/wsdc0521/article/details/106241596
[ELK_Logstash]: https://blog.csdn.net/wsdc0521/article/details/106292639
[ELK_Logstash_nginx_ES]: https://blog.csdn.net/wsdc0521/article/details/106306584
[ELK_Logstash_timestamp]: https://blog.csdn.net/wsdc0521/article/details/106307452
[ELK_Nginx_Json_Logstash_ES]: https://blog.csdn.net/wsdc0521/article/details/106307938
[ELK_Filebeat_Logstash_ES]: https://blog.csdn.net/wsdc0521/article/details/106308441
[ELK_Filebeat_Redis_Logstash]: https://blog.csdn.net/wsdc0521/article/details/106344073
[ELK_ES_Kibana]: https://blog.csdn.net/wsdc0521/article/details/106344974
[ELK_ES_IK]: https://blog.csdn.net/wsdc0521/article/details/106368378
[ELK_ElasticSearch7.7.0_es-head]: https://blog.csdn.net/wsdc0521/article/details/106377407
[ELK_SQL_ElasticSearch7.7.0]: https://blog.csdn.net/wsdc0521/article/details/106381519
[https_www.elastic.co_guide_en_elasticsearch_hadoop_current_hive.html]: https://www.elastic.co/guide/en/elasticsearch/hadoop/current/hive.html
[https_www.elastic.co_cn_downloads_past-releases_es-hadoop]: https://www.elastic.co/cn/downloads/past-releases#es-hadoop
[https_www.elastic.co_guide_en_elasticsearch_hadoop_current_configuration.html]: https://www.elastic.co/guide/en/elasticsearch/hadoop/current/configuration.html
[20200604145819686.png]: https://img-blog.csdnimg.cn/20200604145819686.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200604145025685.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20200604155517907.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 2]: https://img-blog.csdnimg.cn/20200604155607147.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 3]: https://img-blog.csdnimg.cn/20200604155656849.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 4]: https://img-blog.csdnimg.cn/20200604161027795.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 5]: https://img-blog.csdnimg.cn/20200604161653822.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 6]: https://img-blog.csdnimg.cn/20200604163416962.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 7]: https://img-blog.csdnimg.cn/20200604163622462.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 8]: https://img-blog.csdnimg.cn/2020060416475014.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx_size_16_color_FFFFFF_t_70 9]: https://img-blog.csdnimg.cn/20200604164848845.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzZGMwNTIx,size_16,color_FFFFFF,t_70