元数据管理是数据仓库的核心，它不仅定义了数据仓库有什么，还指明了数据仓库中数据的内容和位置，刻画了数据的提取和转换规则，存储了与数据仓库主题有关的各种商业信息。本文主要介绍Hive Hook和MetaStore Listener，使用这些功能可以进行自动的元数据管理。通过本文你可以了解到：
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Hive Hooks 和 Metastore Listeners
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元数据管理
元数据定义
按照传统的定义，元数据（ Metadata ）是关于数据的数据。元数据打通了源数据、数据仓库、数据应用，记录了数据从产生到消费的全过程。元数据主要记录数据仓库中模型的定义、各层级间的映射关系、监控数据仓库的数据状态及ETL 的任务运行状态。在数据仓库系统中，元数据可以帮助数据仓库管理员和开发人员非常方便地找到他们所关心的数据，用于指导其进行数据管理和开发工作，提高工作效率。将元数据按用途的不同分为两类：技术元数据（ Technical Metadata)和业务元数据（ Business Metadata ）。技术元数据是存储关于数据仓库系统技术细节的数据，是用于开发和管理数据仓库使用的数据。
元数据分类
技术元数据
如Hive表、列、分区等信息。记录了表的表名。分区信息、责任人信息、文件大小、表类型，以及列的字段名、字段类型、字段备注、是否是分区字段等信息。
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分布式计算系统运行元数据
类似于Hive 的Job 日志，包括作业类型、实例名称、输入输出、SQL 、运行参数、执行时间等。
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任务调度元数据
任务的依赖类型、依赖关系等，以及不同类型调度任务的运行日志等。
业务元数据
业务元数据从业务角度描述了数据仓库中的数据，它提供了介于使用者和实际系统之间的语义层，使得不懂计算机技术的业务人员也能够“ 读懂”数据仓库中的数据。常见的业务元数据有：如维度及属性、业务过程、指标等的规范化定义，用于更好地管理和使用数据；数据应用元数据，如数据报表、数据产品等的配置和运行元数据。
元数据应用
数据的真正价值在于数据驱动决策，通过数据指导运营。通过数据驱动的方法，我们能够判断趋势，从而展开有效行动，帮助自己发现问题，推动创新或解决方案的产生。这就是数据化运营。同样，对于元数据，可以用于指导数据相关人员进行日常工作，实现数据化“运营”。比如对于数据使用者，可以通过元数据让其快速找到所需要的数据；对于ETL 工程师，可以通过元数据指导其进行模型设计、任务优化和任务下线等各种日常ETL 工作；对于运维工程师，可以通过元数据指导其进行整个集群的存储、计算和系统优化等运维工作。
Hive Hooks 和 Metastore Listeners
Hive Hooks
关于数据治理和元数据管理框架，业界有许多开源的系统，比如Apache Atlas，这些开源的软件可以在复杂的场景下满足元数据管理的需求。其实Apache Atlas对于Hive的元数据管理，使用的是Hive的Hooks。需要进行如下配置：
<property>
<name>hive.exec.post.hooks</name>
<value>org.apache.atlas.hive.hook.HiveHook<value/>
</property>
通过Hook监听Hive的各种事件，比如创建表，修改表等，然后按照特定的格式把收集的数据推送到Kafka，最后消费元数据并存储。
Hive Hooks分类
那么，究竟什么是Hooks呢？
Hooks 是一种事件和消息机制， 可以将事件绑定在内部 Hive 的执行流程中，而无需重新编译 Hive。Hook 提供了扩展和继承外部组件的方式。根据不同的 Hook 类型，可以在不同的阶段运行。关于Hooks的类型，主要分为以下几种：
从名称可以看出，在执行引擎执行查询之前被调用。这个需要在 Hive 对查询计划进行过优化之后才可以使用。使用该Hooks需要实现接口：org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext，具体在hive-site.xml中的配置如下：
<property>
<name>hive.exec.pre.hooks</name>
<value>实现类的全限定名<value/>
</property>
在执行计划执行结束结果返回给用户之前被调用。使用时需要实现接口：org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext，具体在hive-site.xml中的配置如下：
<property>
<name>hive.exec.post.hooks</name>
<value>实现类的全限定名<value/>
</property>
在执行计划失败之后被调用。使用时需要实现接口：org.apache.hadoop.hive.ql.hooks.ExecuteWithHookContext,具体在hive-site.xml中的配置如下：
<property>
<name>hive.exec.failure.hooks</name>
<value>实现类的全限定名<value/>
</property>
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hive.metastore.init.hooks
HMSHandler初始化是被调用。使用时需要实现接口：org.apache.hadoop.hive.metastore.MetaStoreInitListener，具体在hive-site.xml中的配置如下：
<property>
<name>hive.metastore.init.hooks</name>
<value>实现类的全限定名<value/>
</property>
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hive.exec.driver.run.hooks
在Driver.run开始或结束时运行，使用时需要实现接口：org.apache.hadoop.hive.ql.HiveDriverRunHook，具体在hive-site.xml中的配置如下：
<property>
<name>hive.exec.driver.run.hooks</name>
<value>实现类的全限定名<value/>
</property>
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hive.semantic.analyzer.hook
Hive 对查询语句进行语义分析的时候调用。使用时需要集成抽象类：org.apache.hadoop.hive.ql.parse.AbstractSemanticAnalyzerHook，具体在hive-site.xml中的配置如下：
<property>
<name>hive.semantic.analyzer.hook</name>
<value>实现类的全限定名<value/>
</property>
Hive Hooks的优缺点
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可以很方便地在各种查询阶段嵌入或者运行自定义的代码
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当使用Hooks时，获取到的元数据通常需要进一步解析，否则很难理解
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对于Hive Hooks，本文将给出hive.exec.post.hook的使用案例，该Hooks会在查询执行之后，返回结果之前运行。
Metastore Listeners
所谓Metastore Listeners，指的是对Hive metastore的监听。用户可以自定义一些代码，用来使用对元数据的监听。
当我们看HiveMetaStore这个类的源码时，会发现：在创建HiveMetaStore的init()方法中，同时创建了三种Listener,分别为MetaStorePreEventListener，MetaStoreEventListener和MetaStoreEndFunctionListener，这些Listener用于对每一步事件的监听。
public class HiveMetaStore extends ThriftHiveMetastore {
// ...省略代码
public static class HMSHandler extends FacebookBase implements
IHMSHandler {
// ...省略代码
public void init() throws MetaException {
// ...省略代码
// 获取MetaStorePreEventListener
preListeners = MetaStoreUtils.getMetaStoreListeners(MetaStorePreEventListener.class,
hiveConf,
hiveConf.getVar(HiveConf.ConfVars.METASTORE_PRE_EVENT_LISTENERS));
// 获取MetaStoreEventListener
listeners = MetaStoreUtils.getMetaStoreListeners(MetaStoreEventListener.class,
hiveConf,
hiveConf.getVar(HiveConf.ConfVars.METASTORE_EVENT_LISTENERS));
listeners.add(new SessionPropertiesListener(hiveConf));
// 获取MetaStoreEndFunctionListener
endFunctionListeners = MetaStoreUtils.getMetaStoreListeners(
MetaStoreEndFunctionListener.class,
hiveConf,
hiveConf.getVar(HiveConf.ConfVars.METASTORE_END_FUNCTION_LISTENERS));
// ...省略代码
}
}
}
Metastore Listeners分类
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hive.metastore.pre.event.listeners
需要扩展此抽象类，以提供在metastore上发生特定事件之前需要执行的操作实现。在metastore上发生事件之前，将调用这些方法。
使用时需要继承抽象类：org.apache.hadoop.hive.metastore.MetaStorePreEventListener，在Hive-site.xml中的配置为：
<property>
<name>hive.metastore.pre.event.listeners</name>
<value>实现类的全限定名</value>
</property>
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hive.metastore.event.listeners
需要扩展此抽象类，以提供在metastore上发生特定事件时需要执行的操作实现。每当Metastore上发生事件时，就会调用这些方法。
使用时需要继承抽象类：org.apache.hadoop.hive.metastore.MetaStoreEventListener，在Hive-site.xml中的配置为：
<property>
<name>hive.metastore.event.listeners</name>
<value>实现类的全限定名</value>
</property>
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hive.metastore.end.function.listeners
每当函数结束时，将调用这些方法。
使用时需要继承抽象类：org.apache.hadoop.hive.metastore.MetaStoreEndFunctionListener ，在Hive-site.xml中的配置为：
<property>
<name>hive.metastore.end.function.listeners</name>
<value>实现类的全限定名</value>
</property>
Metastore Listeners优缺点
对于metastore listener，本文会给出MetaStoreEventListener的使用案例，具体会实现两个方法：onCreateTable和onAlterTable
Hive Hooks基本使用
代码
具体实现代码如下：
public class CustomPostHook implements ExecuteWithHookContext {
private static final Logger LOGGER = LoggerFactory.getLogger(CustomPostHook.class);
// 存储Hive的SQL操作类型
private static final HashSet<String> OPERATION_NAMES = new HashSet<>();
// HiveOperation是一个枚举类，封装了Hive的SQL操作类型
// 监控SQL操作类型
static {
// 建表
OPERATION_NAMES.add(HiveOperation.CREATETABLE.getOperationName());
// 修改数据库属性
OPERATION_NAMES.add(HiveOperation.ALTERDATABASE.getOperationName());
// 修改数据库属主
OPERATION_NAMES.add(HiveOperation.ALTERDATABASE_OWNER.getOperationName());
// 修改表属性,添加列
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_ADDCOLS.getOperationName());
// 修改表属性,表存储路径
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_LOCATION.getOperationName());
// 修改表属性
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_PROPERTIES.getOperationName());
// 表重命名
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_RENAME.getOperationName());
// 列重命名
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_RENAMECOL.getOperationName());
// 更新列,先删除当前的列,然后加入新的列
OPERATION_NAMES.add(HiveOperation.ALTERTABLE_REPLACECOLS.getOperationName());
// 创建数据库
OPERATION_NAMES.add(HiveOperation.CREATEDATABASE.getOperationName());
// 删除数据库
OPERATION_NAMES.add(HiveOperation.DROPDATABASE.getOperationName());
// 删除表
OPERATION_NAMES.add(HiveOperation.DROPTABLE.getOperationName());
}
@Override
public void run(HookContext hookContext) throws Exception {
assert (hookContext.getHookType() == HookType.POST_EXEC_HOOK);
// 执行计划
QueryPlan plan = hookContext.getQueryPlan();
// 操作名称
String operationName = plan.getOperationName();
logWithHeader("执行的SQL语句: " + plan.getQueryString());
logWithHeader("操作名称: " + operationName);
if (OPERATION_NAMES.contains(operationName) && !plan.isExplain()) {
logWithHeader("监控SQL操作");
Set<ReadEntity> inputs = hookContext.getInputs();
Set<WriteEntity> outputs = hookContext.getOutputs();
for (Entity entity : inputs) {
logWithHeader("Hook metadata输入值: " + toJson(entity));
}
for (Entity entity : outputs) {
logWithHeader("Hook metadata输出值: " + toJson(entity));
}
} else {
logWithHeader("不在监控范围，忽略该hook!");
}
}
private static String toJson(Entity entity) throws Exception {
ObjectMapper mapper = new ObjectMapper();
// entity的类型
// 主要包括：
// DATABASE, TABLE, PARTITION, DUMMYPARTITION, DFS_DIR, LOCAL_DIR, FUNCTION
switch (entity.getType()) {
case DATABASE:
Database db = entity.getDatabase();
return mapper.writeValueAsString(db);
case TABLE:
return mapper.writeValueAsString(entity.getTable().getTTable());
}
return null;
}
/**
* 日志格式
*
* @param obj
*/
private void logWithHeader(Object obj) {
LOGGER.info("[CustomPostHook][Thread: " + Thread.currentThread().getName() + "] | " + obj);
}
}
使用过程解释
首先将上述代码编译成jar包，放在$HIVE_HOME/lib目录下，或者使用在Hive的客户端中执行添加jar包的命令：
0: jdbc:hive2://localhost:10000> add jar /opt/softwares/com.jmx.hive-1.0-SNAPSHOT.jar;
接着配置Hive-site.xml文件，为了方便，我们直接使用客户端命令进行配置：
0: jdbc:hive2://localhost:10000> set hive.exec.post.hooks=com.jmx.hooks.CustomPostHook;
查看表操作
上面的代码中我们对一些操作进行了监控，当监控到这些操作时会触发一些自定义的代码(比如输出日志)。当我们在Hive的beeline客户端中输入下面命令时：
0: jdbc:hive2://localhost:10000> show tables;
在$HIVE_HOME/logs/hive.log文件可以看到：
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[CustomPostHook][Thread: cab9a763-c63e-4f25-9f9a-affacb3cecdb main] | 执行的SQL语句: show tables
[CustomPostHook][Thread: cab9a763-c63e-4f25-9f9a-affacb3cecdb main] | 操作名称: SHOWTABLES
[CustomPostHook][Thread: cab9a763-c63e-4f25-9f9a-affacb3cecdb main] |不在监控范围，忽略该hook!
上面的查看表操作，不在监控范围，所以没有相对应的元数据日志。
建表操作
当我们在Hive的beeline客户端中创建一张表时，如下：
CREATE TABLE testposthook(
id int COMMENT "id",
name string COMMENT "姓名"
)COMMENT "建表_测试Hive Hooks"
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
LOCATION '/user/hive/warehouse/';
观察hive.log日志：
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上面的Hook metastore输出值有两个：第一个是数据库的元数据信息，第二个是表的元数据信息
{
"name":"default",
"description":"Default Hive database",
"locationUri":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"parameters":{
},
"privileges":null,
"ownerName":"public",
"ownerType":"ROLE",
"setParameters":true,
"parametersSize":0,
"setOwnerName":true,
"setOwnerType":true,
"setPrivileges":false,
"setName":true,
"setDescription":true,
"setLocationUri":true
}
{
"tableName":"testposthook",
"dbName":"default",
"owner":"anonymous",
"createTime":1597985444,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
],
"location":null,
"inputFormat":"org.apache.hadoop.mapred.SequenceFileInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.MetadataTypedColumnsetSerDe",
"parameters":{
"serialization.format":"1"
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":1,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0,
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0
},
"storedAsSubDirectories":false,
"colsSize":0,
"setParameters":true,
"parametersSize":0,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"setSkewedInfo":true,
"colsIterator":[
],
"setCompressed":false,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":false,
"setCols":true,
"setLocation":false,
"setInputFormat":true
},
"partitionKeys":[
],
"parameters":{
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":null,
"temporary":false,
"rewriteEnabled":false,
"partitionKeysSize":0,
"setDbName":true,
"setSd":true,
"setParameters":true,
"setCreateTime":true,
"setLastAccessTime":false,
"parametersSize":0,
"setTableName":true,
"setPrivileges":false,
"setOwner":true,
"setPartitionKeys":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setRetention":false,
"partitionKeysIterator":[
],
"setTemporary":false,
"setRewriteEnabled":false
}
我们发现上面的表元数据信息中，**cols[]**列没有数据，即没有建表时的字段id和字段name的信息。如果要获取这些信息，可以执行下面的命令：
ALTER TABLE testposthook
ADD COLUMNS (age int COMMENT '年龄');
再次观察日志信息：
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上面的日志中，Hook metastore只有一个输入和一个输出：都表示table的元数据信息。
{
"tableName":"testposthook",
"dbName":"default",
"owner":"anonymous",
"createTime":1597985445,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
{
"name":"id",
"type":"int",
"comment":"id",
"setName":true,
"setType":true,
"setComment":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setName":true,
"setType":true,
"setComment":true
}
],
"location":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"inputFormat":"org.apache.hadoop.mapred.TextInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe",
"parameters":{
"serialization.format":" ",
"field.delim":" "
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":2,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0,
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0
},
"storedAsSubDirectories":false,
"colsSize":2,
"setParameters":true,
"parametersSize":0,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"setSkewedInfo":true,
"colsIterator":[
{
"name":"id",
"type":"int",
"comment":"id",
"setName":true,
"setType":true,
"setComment":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setName":true,
"setType":true,
"setComment":true
}
],
"setCompressed":true,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":true,
"setCols":true,
"setLocation":true,
"setInputFormat":true
},
"partitionKeys":[
],
"parameters":{
"transient_lastDdlTime":"1597985445",
"comment":"建表_测试Hive Hooks",
"totalSize":"0",
"numFiles":"0"
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":null,
"temporary":false,
"rewriteEnabled":false,
"partitionKeysSize":0,
"setDbName":true,
"setSd":true,
"setParameters":true,
"setCreateTime":true,
"setLastAccessTime":true,
"parametersSize":4,
"setTableName":true,
"setPrivileges":false,
"setOwner":true,
"setPartitionKeys":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setRetention":true,
"partitionKeysIterator":[
],
"setTemporary":false,
"setRewriteEnabled":true
}
从上面的json中可以看出**"cols"**列的字段元数据信息，我们再来看一下输出json：
{
"tableName":"testposthook",
"dbName":"default",
"owner":"anonymous",
"createTime":1597985445,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
{
"name":"id",
"type":"int",
"comment":"id",
"setName":true,
"setType":true,
"setComment":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setName":true,
"setType":true,
"setComment":true
}
],
"location":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"inputFormat":"org.apache.hadoop.mapred.TextInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe",
"parameters":{
"serialization.format":" ",
"field.delim":" "
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":2,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0,
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0
},
"storedAsSubDirectories":false,
"colsSize":2,
"setParameters":true,
"parametersSize":0,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"setSkewedInfo":true,
"colsIterator":[
{
"name":"id",
"type":"int",
"comment":"id",
"setName":true,
"setType":true,
"setComment":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setName":true,
"setType":true,
"setComment":true
}
],
"setCompressed":true,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":true,
"setCols":true,
"setLocation":true,
"setInputFormat":true
},
"partitionKeys":[
],
"parameters":{
"transient_lastDdlTime":"1597985445",
"comment":"建表_测试Hive Hooks",
"totalSize":"0",
"numFiles":"0"
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":null,
"temporary":false,
"rewriteEnabled":false,
"partitionKeysSize":0,
"setDbName":true,
"setSd":true,
"setParameters":true,
"setCreateTime":true,
"setLastAccessTime":true,
"parametersSize":4,
"setTableName":true,
"setPrivileges":false,
"setOwner":true,
"setPartitionKeys":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setRetention":true,
"partitionKeysIterator":[
],
"setTemporary":false,
"setRewriteEnabled":true
}
该output对象不包含新列age，它表示修改表之前的元数据信息
Metastore Listeners基本使用
代码
具体实现代码如下：
public class CustomListener extends MetaStoreEventListener {
private static final Logger LOGGER = LoggerFactory.getLogger(CustomListener.class);
private static final ObjectMapper objMapper = new ObjectMapper();
public CustomListener(Configuration config) {
super(config);
logWithHeader(" created ");
}
// 监听建表操作
@Override
public void onCreateTable(CreateTableEvent event) {
logWithHeader(event.getTable());
}
// 监听修改表操作
@Override
public void onAlterTable(AlterTableEvent event) {
logWithHeader(event.getOldTable());
logWithHeader(event.getNewTable());
}
private void logWithHeader(Object obj) {
LOGGER.info("[CustomListener][Thread: " + Thread.currentThread().getName() + "] | " + objToStr(obj));
}
private String objToStr(Object obj) {
try {
return objMapper.writeValueAsString(obj);
} catch (IOException e) {
LOGGER.error("Error on conversion", e);
}
return null;
}
}
使用过程解释
使用方式与Hooks有一点不同，Hive Hook是与Hiveserver进行交互的，而Listener是与Metastore交互的，即Listener运行在Metastore进程中的。具体使用方式如下：
首先将jar包放在$HIVE_HOME/lib目录下，然后配置hive-site.xml文件，配置内容为：
<property>
<name>hive.metastore.event.listeners</name>
<value>com.jmx.hooks.CustomListener</value>
<description/>
</property>
配置完成之后，需要重新启动元数据服务：
bin/hive --service metastore &
建表操作
CREATE TABLE testlistener(
id int COMMENT "id",
name string COMMENT "姓名"
)COMMENT "建表_测试Hive Listener"
ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t'
LOCATION '/user/hive/warehouse/';
观察hive.log日志：
![]()
{
"tableName":"testlistener",
"dbName":"default",
"owner":"anonymous",
"createTime":1597989316,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
}
],
"location":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"inputFormat":"org.apache.hadoop.mapred.TextInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe",
"parameters":{
"serialization.format":" ",
"field.delim":" "
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":2,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0,
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0
},
"storedAsSubDirectories":false,
"setCols":true,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"colsSize":2,
"colsIterator":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
}
],
"setCompressed":true,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":true,
"setParameters":true,
"setLocation":true,
"setInputFormat":true,
"parametersSize":0,
"setSkewedInfo":true
},
"partitionKeys":[
],
"parameters":{
"transient_lastDdlTime":"1597989316",
"comment":"建表_测试Hive Listener",
"totalSize":"0",
"numFiles":"0"
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":{
"userPrivileges":{
"anonymous":[
{
"privilege":"INSERT",
"createTime":-1,
"grantor":"anonymous",
"grantorType":"USER",
"grantOption":true,
"setGrantOption":true,
"setCreateTime":true,
"setGrantor":true,
"setGrantorType":true,
"setPrivilege":true
},
{
"privilege":"SELECT",
"createTime":-1,
"grantor":"anonymous",
"grantorType":"USER",
"grantOption":true,
"setGrantOption":true,
"setCreateTime":true,
"setGrantor":true,
"setGrantorType":true,
"setPrivilege":true
},
{
"privilege":"UPDATE",
"createTime":-1,
"grantor":"anonymous",
"grantorType":"USER",
"grantOption":true,
"setGrantOption":true,
"setCreateTime":true,
"setGrantor":true,
"setGrantorType":true,
"setPrivilege":true
},
{
"privilege":"DELETE",
"createTime":-1,
"grantor":"anonymous",
"grantorType":"USER",
"grantOption":true,
"setGrantOption":true,
"setCreateTime":true,
"setGrantor":true,
"setGrantorType":true,
"setPrivilege":true
}
]
},
"groupPrivileges":null,
"rolePrivileges":null,
"setUserPrivileges":true,
"setGroupPrivileges":false,
"setRolePrivileges":false,
"userPrivilegesSize":1,
"groupPrivilegesSize":0,
"rolePrivilegesSize":0
},
"temporary":false,
"rewriteEnabled":false,
"setParameters":true,
"setPartitionKeys":true,
"partitionKeysSize":0,
"setSd":true,
"setLastAccessTime":true,
"setRetention":true,
"partitionKeysIterator":[
],
"parametersSize":4,
"setTemporary":true,
"setRewriteEnabled":false,
"setTableName":true,
"setDbName":true,
"setOwner":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setPrivileges":true,
"setCreateTime":true
}
当我们再执行修改表操作时
ALTER TABLE testlistener
ADD COLUMNS (age int COMMENT '年龄');
再次观察日志：
![]()
可以看出上面有两条记录，第一条记录是old table的信息，第二条是修改之后的表的信息。
{
"tableName":"testlistener",
"dbName":"default",
"owner":"anonymous",
"createTime":1597989316,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
}
],
"location":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"inputFormat":"org.apache.hadoop.mapred.TextInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe",
"parameters":{
"serialization.format":" ",
"field.delim":" "
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":2,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0,
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0
},
"storedAsSubDirectories":false,
"setCols":true,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"colsSize":2,
"colsIterator":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
}
],
"setCompressed":true,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":true,
"setParameters":true,
"setLocation":true,
"setInputFormat":true,
"parametersSize":0,
"setSkewedInfo":true
},
"partitionKeys":[
],
"parameters":{
"totalSize":"0",
"numFiles":"0",
"transient_lastDdlTime":"1597989316",
"comment":"建表_测试Hive Listener"
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":null,
"temporary":false,
"rewriteEnabled":false,
"setParameters":true,
"setPartitionKeys":true,
"partitionKeysSize":0,
"setSd":true,
"setLastAccessTime":true,
"setRetention":true,
"partitionKeysIterator":[
],
"parametersSize":4,
"setTemporary":false,
"setRewriteEnabled":true,
"setTableName":true,
"setDbName":true,
"setOwner":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setPrivileges":false,
"setCreateTime":true
}
{
"tableName":"testlistener",
"dbName":"default",
"owner":"anonymous",
"createTime":1597989316,
"lastAccessTime":0,
"retention":0,
"sd":{
"cols":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"age",
"type":"int",
"comment":"年龄",
"setComment":true,
"setType":true,
"setName":true
}
],
"location":"hdfs://kms-1.apache.com:8020/user/hive/warehouse",
"inputFormat":"org.apache.hadoop.mapred.TextInputFormat",
"outputFormat":"org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat",
"compressed":false,
"numBuckets":-1,
"serdeInfo":{
"name":null,
"serializationLib":"org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe",
"parameters":{
"serialization.format":" ",
"field.delim":" "
},
"setSerializationLib":true,
"setParameters":true,
"parametersSize":2,
"setName":false
},
"bucketCols":[
],
"sortCols":[
],
"parameters":{
},
"skewedInfo":{
"skewedColNames":[
],
"skewedColValues":[
],
"skewedColValueLocationMaps":{
},
"setSkewedColNames":true,
"setSkewedColValues":true,
"setSkewedColValueLocationMaps":true,
"skewedColNamesSize":0,
"skewedColNamesIterator":[
],
"skewedColValuesSize":0,
"skewedColValuesIterator":[
],
"skewedColValueLocationMapsSize":0
},
"storedAsSubDirectories":false,
"setCols":true,
"setOutputFormat":true,
"setSerdeInfo":true,
"setBucketCols":true,
"setSortCols":true,
"colsSize":3,
"colsIterator":[
{
"name":"id",
"type":"int",
"comment":"id",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"name",
"type":"string",
"comment":"姓名",
"setComment":true,
"setType":true,
"setName":true
},
{
"name":"age",
"type":"int",
"comment":"年龄",
"setComment":true,
"setType":true,
"setName":true
}
],
"setCompressed":true,
"setNumBuckets":true,
"bucketColsSize":0,
"bucketColsIterator":[
],
"sortColsSize":0,
"sortColsIterator":[
],
"setStoredAsSubDirectories":true,
"setParameters":true,
"setLocation":true,
"setInputFormat":true,
"parametersSize":0,
"setSkewedInfo":true
},
"partitionKeys":[
],
"parameters":{
"totalSize":"0",
"last_modified_time":"1597989660",
"numFiles":"0",
"transient_lastDdlTime":"1597989660",
"comment":"建表_测试Hive Listener",
"last_modified_by":"anonymous"
},
"viewOriginalText":null,
"viewExpandedText":null,
"tableType":"MANAGED_TABLE",
"privileges":null,
"temporary":false,
"rewriteEnabled":false,
"setParameters":true,
"setPartitionKeys":true,
"partitionKeysSize":0,
"setSd":true,
"setLastAccessTime":true,
"setRetention":true,
"partitionKeysIterator":[
],
"parametersSize":6,
"setTemporary":false,
"setRewriteEnabled":true,
"setTableName":true,
"setDbName":true,
"setOwner":true,
"setViewOriginalText":false,
"setViewExpandedText":false,
"setTableType":true,
"setPrivileges":false,
"setCreateTime":true
}
可以看出：修改之后的表的元数据信息中，包含新添加的列age。
总结
在本文中，我们介绍了如何在Hive中操作元数据，从而能够自动进行元数据管理。我们给出了Hive Hooks和Metastore Listener的基本使用方式，这些方式可以帮助我们实现操作元数据。当然也可以将这些元数据信息推送到Kafka中，以此构建自己的元数据管理系统。
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