Hive实现自增序列及常见的Hive元数据问题处理

Hive实现自增序列

在利用数据仓库进行数据处理时，通常有这样一个业务场景，为一个Hive表新增一列自增字段（比如事实表和维度表之间的"代理主键"）。虽然Hive不像RDBMS如mysql一样本身提供自增主键的功能，但它本身可以通过函数来实现自增序列功能：利用row_number()窗口函数或者使用UDFRowSequence。

示例：table_src是我们经过业务需求处理的到的中间表数据，现在我们需要为table_src新增一列自增序列字段auto_increment_id，并将最终数据保存到table_dest中。

1. 利用row_number函数

场景1：table_dest中目前没有数据

insert into table table_dest
select row_number() over(order by 1) as auto_increment_id, table_src.* from table_src;

场景2: table_dest中有数据，并且已经经过新增自增字段处理

insert into table table_dest
select (row_number() over(order by 1) + dest.max_id) auto_increment_id, src.* from table_src src cross join (select max(auto_increment_id) max_id from table_dest) dest;

2. 利用UDFRowSequence

首先Hive环境要有hive-contrib相关jar包，然后执行

create temporary function row_sequence as 'org.apache.hadoop.hive.contrib.udf.UDFRowSequence';

针对上述场景一，可通过以下语句实现：

insert into table table_dest
select row_sequence() auto_increment_id, table_src.* from table_src;

场景2实现起来也很简单，这里不在赘述。

但是，需要注意二者的区别：

row_number函数是对整个数据集做处理，自增序列在当次排序中是连续的唯一的。

UDFRowSequence是按照任务排序，但是一个SQL可能并发执行的job不止一个，而每个job都会从1开始各自排序，所以不能保证序号全局唯一。可以考虑将UDFRowSequence扩展到一个第三方存储系统中，进行序号逻辑管理，来最终实现全局的连续自增唯一序号。

---

Hive元数据问题

以下基于hive-2.X版本说明。

Hive正常启动，但是执行show databases时报以下错误：

SemanticException org.apache.hadoop.hive.ql.metadata.HiveException:
java.lang.RuntimeException: Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient

首先从异常信息分析可知，是元数据问题导致的异常。

Hive默认将元数据存储在derby，但因为用derby作为元数据存储服务弊端太多，我们通常会选择将Hive的元数据存在mysql中。所以我们要确保hive-site.xml中mysql的信息要配置正确，Hive要有mysql的相关连接驱动jar包，并且有mysql的权限。

首先在hive-site.xml中配置mysql信息：

<configuration>
  <property>
    <!-- mysql中存储Hive元数据的库-->
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://localhost:3306/hive_metadata?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>
    <!-- mysql用户名-->
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>root</value>
    <description>username to use against metastore database</description>
  </property>
  <property>
    <!-- mysql密码-->
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>root</value>
    <description>password to use against metastore database</description>
  </property>
</configuration>

执行完上述操作后，如果配置了Hive metastore方式，还需要启动该服务：

nohup hive --service metastore &

如果想启动hiveserver2，则执行：

nohup hive --service hiveserver2 &

但是，此时可能由于你设置的mysql元数据存储库没有进行schema初始化，会报类似以下异常：

-- 异常1
Exception in thread "main" MetaException(message:Version information not found in metastore. )
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.<init>(RetryingHMSHandler.java:83)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:92)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:6896)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:6891)
at org.apache.hadoop.hive.metastore.HiveMetaStore.startMetaStore(HiveMetaStore.java:7149)
at org.apache.hadoop.hive.metastore.HiveMetaStore.main(HiveMetaStore.java:7076)
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:226)
at org.apache.hadoop.util.RunJar.main(RunJar.java:141)
Caused by: MetaException(message:Version information not found in metastore. )

-- 异常2
MetaException(message:Required table missing : "`DBS`" in Catalog "" Schema "". DataNucleus requires this table to perform its persistence operations. Either your MetaData is incorrect, or you need to enable "datanucleus.schema.autoCreateTables")
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.<init>(RetryingHMSHandler.java:83)
at org.apache.hadoop.hive.metastore.RetryingHMSHandler.getProxy(RetryingHMSHandler.java:92)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:6896)
at org.apache.hadoop.hive.metastore.HiveMetaStore.newRetryingHMSHandler(HiveMetaStore.java:6891)
at org.apache.hadoop.hive.metastore.HiveMetaStore.startMetaStore(HiveMetaStore.java:7149)
at org.apache.hadoop.hive.metastore.HiveMetaStore.main(HiveMetaStore.java:7076)
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:226)
        at org.apache.hadoop.util.RunJar.main(RunJar.java:141)

此时，还需要在hive-site.xml中配置以下信息：

<property>
<name>hive.metastore.schema.verification</name>
<value>false</value>
<description> Enforce metastore schema version consistency. True: Verify that version information stored in is compatible with one from Hive jars.  Also disable automatic schema migration attempt. Users are required to manually migrate schema after Hive upgrade which ensures   proper metastore schema migration. (Default); False: Warn if the version information stored in metastore doesn't match with one from in Hive jars.
</description>
</property>

<property>
<name>datanucleus.schema.autoCreateAll</name>
<value>true</value>
</property>

并执行schematool -initSchema -dbType mysql进行Hive元数据的初始化。出现以下信息则说明初始化完毕，可以到mysql中元数据库看到初始化生成的表。

SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/soft/apache-hive-2.3.7-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/soft/hadoop-2.7.7/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_metadata?createDatabaseIfNotExist=true
Metastore Connection Driver :    com.mysql.jdbc.Driver
Metastore connection User:       root
Starting metastore schema initialization to 2.3.0
Initialization script hive-schema-2.3.0.mysql.sql
Initialization script completed
schemaTool completed

最后，重新启动bin/hive，执行show databases、建表、查询等SQL语句进行测试，都能正常执行。

推荐文章：
SparkSQL中产生笛卡尔积的几种典型场景以及处理策略

Databricks说的Lakehouse是什么？

Hadoop支持的压缩格式对比和应用场景以及Hadoop native库

Hive数据导入HBase引起数据膨胀引发的思考

Spark存储Parquet数据到Hive，对map、array、struct字段类型的处理

---

关注微信公众号：大数据学习与分享，获取更对技术干货