安装HIVE
## 下载并解压缩
去主页选择镜像地址：https://www.apache.org/dyn/closer.cgi/hive/
在镜像地址中选择下载的版本，出于跟其他软件的兼容性考虑，我们这里选用的不是最新版（3.1.3），而是2017-04-07发布的2.3.9，下载地址如下：
https://mirrors.tuna.tsinghua.edu.cn/apache/hive/hive-2.3.9/
下载后上传到主节点root用户的主目录/root，再使用tar命令解压缩
```shell
[root@hadoop-1 software]# tar -xvf apache-hive-2.3.9-bin.tar.gz
```
使用mv命令将解压后的目录重命名为hive，以去掉版本号等信息
```shell
[root@hadoop-1 software]# mv apache-hive-2.3.9-bin hive
```
使用mv命令将hive目录移动到安装的目标目录/opt
```shell
[root@hadoop-1 software]# mv hive /opt
```
## 修改环境变量
使用vi命令打开并编辑/etc/profile文件
```shell
[root@hadoop-1 software]# vi /etc/profile
```
增加如下配置信息
```shell
# HIVE
export HIVE_HOME=/opt/hive
export PATH=$PATH:$HIVE_HOME/bin
```
使用source命令使配置文件生效
```shell
[root@hadoop-1 software]# source /etc/profile
```
## 创建并修改配置文件
进入conf目录
```shell
[root@hadoop-1 software]# cd $HIVE_HOME/conf
```
拷贝hive-env.sh.template文件为hive-env.sh
```shell
[root@hadoop-1 conf]# cp hive-env.sh.template hive-env.sh
```
打开hive-env.sh文件
```shell
[root@hadoop-1 conf]# vi hive-env.sh
```
在文件末尾增加如下参数：
```shell
HADOOP_HOME=/opt/hadoop
export HIVE_CONF_DIR=/opt/hive/conf
```
使用vi命令新建一个hive-site.xml
```shell
[root@hadoop-1 conf]# vi hive-site.xml
```
在打开的hive-site.xml文件中配置如下信息：
```xml
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>javax.jdo.option.ConnectionURL</name>
<value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true</value>
<description>JDBC connect string for a JDBC metastore</description>
</property>
<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.jdbc.Driver</value>
<description>Driver class name for a JDBC metastore</description>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>hive</value>
<description>username to use against metastore database</description>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>hive</value>
<description>password to use against metastore database</description>
</property>
</configuration>
```
## 安装mysql或mariadb数据库
若未安装mysql或mariadb数据库，请根据“**安装mysql或mariadb数据库**”教程先安装好数据库，然后再执行如下操作。
## 配置元数据库
从mysql官网中下载mysql驱动，地址如下：
> https://downloads.mysql.com/archives/c-j/
注意，下载5.1.49版本的即可，不要下载更高版本的。具体下载地址如下：
> https://cdn.mysql.com/archives/mysql-connector-java-5.1/mysql-connector-java-5.1.49.tar.gz
将下载好的mysql驱动mysql-connector-java-5.1.49.tar.gz上传至主节点
```shell
[root@hadoop-1 software]# ls
apache-hive-2.3.9-bin.tar.gz mysql-connector-java-5.1.49.tar.gz
```
解压mysql-connector-java-5.1.49.tar.gz
```shell
[root@hadoop-1 software]#
```
查看解压得到的文件
```shell
[root@hadoop-1 software]# ls
apache-hive-2.3.9-bin.tar.gz mysql-connector-java-5.1.49 mysql-connector-java-5.1.49.tar.gz
[root@hadoop-1 software]#
```
进入解压得到的mysql-connector-java-5.1.49目录，并查看有哪些文件
```shell
[root@hadoop-1 software]# cd mysql-connector-java-5.1.49
[root@hadoop-1 mysql-connector-java-5.1.49]# ls
build.xml COPYING mysql-connector-java-5.1.49.jar README.txt
CHANGES mysql-connector-java-5.1.49-bin.jar README src
[root@hadoop-1 mysql-connector-java-5.1.49]#
```
从上述解压结果可知，其含有一个mysql驱动文件mysql-connector-java-5.1.49.jar。
重命名mysql驱动文件的名称（去掉版本号，可以不去掉）
```shell
[root@hadoop-1 software]# mv mysql-connector-java-5.1.49-bin.jar mysql-connector-java.jar
```
将MySQL驱动移动到Hive安装目录的lib目录下
```shell
[root@hadoop-1 ~]# mv mysql-connector-java.jar /opt/hive/lib
```
登录Mariadb shell
```shell
[root@hadoop-1 conf]# mysql -u root -p
```
新建hive数据库，这个hive数据库与hive-site.xml中localhost:3306/hive的hive对应，用来保存hive元数据
```sql
MariaDB [(none)]> create database hive;
```
配置mysql允许hive接入，将所有数据库的所有表的所有权限赋给hive用户，后面的hive是配置hive-site.xml中配置的连接密码：
```sql
MariaDB [(none)]> grant all on *.* to hive@localhost identified by 'hive';
```
刷新mysql系统权限关系表
```sql
MariaDB [(none)]> flush privileges;
```
重要：修改hive元数据库的编码为latin1，若不修改则会导致在hive cli中使用create database（创建数据库）、create table（创建表）、drop talbe（删除表）等命令时出现卡住或报错而无法正确执行的问题。
```sql
MariaDB [(none)]> alter database hive character set latin1;
```
初始化schema
由于Hive中所有的元信息都需要存储到关系型数据库里面，因此需要初始化数据库表。
```shell
# 进入指定的目录
[root@hadoop-1 conf]# cd $HIVE_HOME/bin
# 初始化，如果要使用默认的derby数据库则将命令中的mysql替换成derby即可
[root@hadoop-1 bin]# ./schematool -initSchema -dbType mysql
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Metastore connection URL: jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true
Metastore Connection Driver : com.mysql.jdbc.Driver
Metastore connection User: hive
Loading class `com.mysql.jdbc.Driver'. This is deprecated. The new driver class is `com.mysql.cj.jdbc.Driver'. The driver is automatically registered via the SPI and manual loading of the driver class is generally unnecessary.
Starting metastore schema initialization to 2.3.0
Initialization script hive-schema-2.3.0.mysql.sql
Initialization script completed
schemaTool completed
[root@hadoop-1 bin]#
```
启动hive cli测试
> 注意：由于hive是使用HDFS来存储数据的，而且其语句默认是自动转换成MapReduce程序来执行的，所以在启动hive之前，需要<font color=red>先启动Hadoop集群</font>，否则将启动失败。
启动hadoop集群
```shell
[root@hadoop-1 bin]# start-all.sh
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [hadoop-1]
hadoop-1: starting namenode, logging to /opt/hadoop/logs/hadoop-root-namenode-hadoop-1.out
hadoop-3: starting datanode, logging to /opt/hadoop/logs/hadoop-root-datanode-hadoop-3.out
hadoop-2: starting datanode, logging to /opt/hadoop/logs/hadoop-root-datanode-hadoop-2.out
hadoop-1: starting datanode, logging to /opt/hadoop/logs/hadoop-root-datanode-hadoop-1.out
Starting secondary namenodes [hadoop-1]
hadoop-1: starting secondarynamenode, logging to /opt/hadoop/logs/hadoop-root-secondarynamenode-hadoop-1.out
starting yarn daemons
starting resourcemanager, logging to /opt/hadoop/logs/yarn-root-resourcemanager-hadoop-1.out
hadoop-3: starting nodemanager, logging to /opt/hadoop/logs/yarn-root-nodemanager-hadoop-3.out
hadoop-2: starting nodemanager, logging to /opt/hadoop/logs/yarn-root-nodemanager-hadoop-2.out
hadoop-1: starting nodemanager, logging to /opt/hadoop/logs/yarn-root-nodemanager-hadoop-1.out
[root@hadoop-1 bin]#
```
创建Hadoop相关目录并赋权（**可选操作**）
```shell
# 创建/tmp目录
[root@hadoop-1 conf]# hadoop fs -mkdir /tmp
# 创建/user/hive/warehouse目录，其中-p参数用于一次性创建多层目录
[root@hadoop-1 conf]# hadoop fs -mkdir -p /user/hive/warehouse
# 为目录赋权
[root@hadoop-1 conf]# hadoop fs -chmod g+w /tmp
[root@hadoop-1 conf]# hadoop fs -chmod g+w /user/hive/warehouse
```
启动Hive cli
```shell
[root@hadoop-1 bin]# hive
which: no hbase in (/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/java/bin:/opt/java/jre/bin:/opt/hadoop/bin:/opt/hadoop/sbin:/opt/hive/bin:/root/bin)
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Logging initialized using configuration in jar:file:/opt/hive/lib/hive-common-2.3.9.jar!/hive-log4j2.properties Async: true
Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
hive>
```
在Hive cli中，执行`show databases;`命令查看Hive中现在有哪些数据库。
```sql
hive> show databases;
OK
default
Time taken: 4.035 seconds, Fetched: 1 row(s)
hive>
```
至此，Hive就算安装完啦！
## 使用beeline
首先启动hiveserver2服务：
```bash
nohup ./bin/hiveserver2>> hiveserver2.log 2>&1 &
```
hiveserver2服务启动后，使用beeline客户端访问hiveserver2服务：
```bash
cd /opt/module/hive
# 进入beeline客户端
bin/beeline
# 执行连接hiveserver2操作
beeline> !connect jdbc:hive2://hadoop01:10000/default
# 或者
bin/beeline -u jdbc:hive2://hadoop01:10000/default -n root
```
> 注意：hive的默认引擎为MR！！！
## hive 安装 客户端
hive本身提供了thrift协议对外提供服务的功能。
如果某台机器已经配置好了hive，然后运行以下命令打开thrift，提供对外服务（打开后这台机器就为hive服务器）
```bash
# 启动hive服务器
nohup $HIVE_HOME/bin/hiveserver2 &
nohup $HIVE_HOME/bin/hive --service metastore &
# 关闭hive服务器
process="hive"
PID=$(ps x | grep $process | grep '/bin/java' | grep -v grep | awk '{print $1}')
ps -ef | grep $process | grep '/bin/java' | grep -v grep | awk '{print $2}' | xargs kill -9
```
远程机器想要使用hive，可以不做任何元数据和数据存储位置配置（都不需要知道这些配置细节），只需用hive的客户端功能连接hive服务器就行了。
这样配置连接hive服务器：
```xml
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>hive.metastore.local</name>
<value>false</value>
</property>
<property>
<name>hive.metastore.uris</name>
<value>thrift://192.168.0.101:9083</value>
</property>
</configuration>
```
然后在客户端机器运行hive命令，就能使用hive客户端功能了，和正常使用hive一样。
> 注意：
hive命令启动需要本地起了hdfs服务，不需要yarn服务
hive客户端从hive服务端拿到元数据，然后会根据元数据中记录的数据文件地址拿数据，但是元数据中记录的地址可能为如下形式：
hdfs://slave5:9000/user/hive/warehouse/...
也就是说hive客户端需要知道slave5对应ip才能访问数据文件，要求hive客户端的/etc/hosts文件里有ip映射。
如果不想配hosts，在服务端hive-site.xml配置文件里指定hive.metastore.warehouse.dir选项时，直接用ip地址（未测试过）。但是不建议这样，因为如果用了ip地址，一旦hdfs集群的NameNode换了ip，hdfs上的数据文件就不能用原来的ip访问到了，想用hive继续访问，需要修改hive的元数据内容。
## Hive创建数据库表可能遇到的问题
若hive中执行创建数据库或表操作的时候若遇到下面的问题
```sql
hive> create database if not exists hive;
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. com/mysql/jdbc/PreparedStatement$BatchParams
hive>
```
这是由于Hive的元数据库的字符集导致的问题，需要配置元数据库的字符集，进入Mariadb数据库并执行如下语句（注意将元数据库hive修改为自己的数据库名）：
```sql
mysql> alter database hive character set latin1;
```
执行完成上述操作之后，再次进入hive即可正常创建数据库或表
# 进行./schematool -initSchema -dbType mysql可能出现的问题
```shell
[root@hadoop01 bin]# ./schematool -initSchema -dbType mysql
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Exception in thread "main" java.lang.NoSuchMethodError: com.google.common.base.Preconditions.checkArgument(ZLjava/lang/String;Ljava/lang/Object;)V
at org.apache.hadoop.conf.Configuration.set(Configuration.java:1357)
at org.apache.hadoop.conf.Configuration.set(Configuration.java:1338)
at org.apache.hadoop.mapred.JobConf.setJar(JobConf.java:536)
at org.apache.hadoop.mapred.JobConf.setJarByClass(JobConf.java:554)
at org.apache.hadoop.mapred.JobConf.<init>(JobConf.java:448)
at org.apache.hadoop.hive.conf.HiveConf.initialize(HiveConf.java:4051)
at org.apache.hadoop.hive.conf.HiveConf.<init>(HiveConf.java:4014)
at org.apache.hive.beeline.HiveSchemaTool.<init>(HiveSchemaTool.java:82)
at org.apache.hive.beeline.HiveSchemaTool.main(HiveSchemaTool.java:1117)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:323)
at org.apache.hadoop.util.RunJar.main(RunJar.java:236)
```
原因：系统找不到相关jar包，或者同一类型的 jar 包有不同版本存在，系统无法决定使用哪一个。
而在我们Hadoop的文件里就有一个(/……/hadoop/share/hadoop/common/lib/guava-27.0-jre.jar)，hive的lib下又有一个(guava-14.0.1.jar),因此这是因为有不同版本的包存在造成的。
解决办法：
将hadoop的包复制过来即可：
```shell
cp /opt/hadoop/share/hadoop/common/lib/guava-27.0-jre.jar /opt/hive/lib
# 安装目录记得换成自己的
```
此时再执行./schematool -initSchema -dbType mysql就没有问题啦：
```shell
[root@hadoop01 bin]# ./schematool -initSchema -dbType mysql
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/hive/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.25.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Metastore connection URL: jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true
Metastore Connection Driver : com.mysql.jdbc.Driver
Metastore connection User: hive
Starting metastore schema initialization to 2.3.0
Initialization script hive-schema-2.3.0.mysql.sql
Initialization script completed
schemaTool completed
```
### 直接关机您可能遇到hive不能使用，例如类似于如下错误：
```shell
Exception in thread "main" java.lang.RuntimeException: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.hdfs.server.namenode.SafeModeException): Cannot create directory /tmp/hive/atguigu/ac2b1292-d550-4be4-9178-7694ed34350c. Name node is in safe mode.
The reported blocks 71 needs additional 2 blocks to reach the threshold 0.9990 of total blocks 73.
The number of live datanodes 3 has reached the minimum number 0. Safe mode will be turned off automatically once the thresholds have been reached.
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkNameNodeSafeMode(FSNamesystem.java:1327)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.mkdirs(FSNamesystem.java:3893)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.mkdirs(NameNodeRpcServer.java:983)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.mkdirs(ClientNamenodeProtocolServerSideTranslatorPB.java:622)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:969)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2049)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2045)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2043)
at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522)
at org.apache.hadoop.hive.cli.CliDriver.run(CliDriver.java:677)
at org.apache.hadoop.hive.cli.CliDriver.main(CliDriver.java:621)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.hdfs.server.namenode.SafeModeException): Cannot create directory /tmp/hive/atguigu/ac2b1292-d550-4be4-9178-7694ed34350c. Name node is in safe mode.
The reported blocks 71 needs additional 2 blocks to reach the threshold 0.9990 of total blocks 73.
The number of live datanodes 3 has reached the minimum number 0. Safe mode will be turned off automatically once the thresholds have been reached.
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.checkNameNodeSafeMode(FSNamesystem.java:1327)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.mkdirs(FSNamesystem.java:3893)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.mkdirs(NameNodeRpcServer.java:983)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.mkdirs(ClientNamenodeProtocolServerSideTranslatorPB.java:622)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:969)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2049)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2045)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2043)
at org.apache.hadoop.ipc.Client.call(Client.java:1475)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy15.mkdirs(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.mkdirs(ClientNamenodeProtocolTranslatorPB.java:558)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy16.mkdirs(Unknown Source)
at org.apache.hadoop.hdfs.DFSClient.primitiveMkdir(DFSClient.java:3000)
at org.apache.hadoop.hdfs.DFSClient.mkdirs(DFSClient.java:2970)
at org.apache.hadoop.hdfs.DistributedFileSystem$21.doCall(DistributedFileSystem.java:1047)
at org.apache.hadoop.hdfs.DistributedFileSystem$21.doCall(DistributedFileSystem.java:1043)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.mkdirsInternal(DistributedFileSystem.java:1043)
at org.apache.hadoop.hdfs.DistributedFileSystem.mkdirs(DistributedFileSystem.java:1036)
at org.apache.hadoop.hive.ql.session.SessionState.createPath(SessionState.java:639)
at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:574)
at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508)
... 8 more
```
原因可能是直接关机导致了hadoop进入了安全模式，所以这个hive进不去
解决方式：
```shell
[root@hadoop-01 root]$ hadoop dfsadmin -safemode leave
```
然后再次执行
```shell
[root@hadoop-01 root]# hive
Logging initialized using configuration in jar:file:/opt/hive/lib/hive-common-2.3.9.jar!/hive-log4j2.properties Async: true
Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
hive>
```
另外，这种情况的"并发症"是当你用hive启动hiveserver2连JDBC时也会报错
错误提示：Could not open client transport with JDBC Uri
Error: Could not open client transport with JDBC Uri: jdbc:hive2://hadoop-01:10000: java.net.ConnectException: 拒绝连接 (Connection refused) (state=08S01,code=0)
其实这也是因为上面的原因啦，当上面的情况排除掉后，这个问题也解决啦。
以下是hiveserver2连接jdbc的过程：
```shell
[root@hadoop-01 hive]$ bin/hiveserver2
[root@hadoop-01 hive]$ bin/beeline
Beeline version 1.2.1 by Apache Hive
beeline> !connect jdbc:hive2://hadoop-01:10000
Connecting to jdbc:hive2://hadoop-01:10000
Enter username for jdbc:hive2://hadoop-01:10000: hive
Enter password for jdbc:hive2://hadoop-01:10000: *********
Connected to: Apache Hive (version 1.2.1)
Driver: Hive JDBC (version 1.2.1)
Transaction isolation: TRANSACTION_REPEATABLE_READ
0: jdbc:hive2://hadoop-01:10000>
```