在Hive 3.0.0以及之后,Hive Metastore便可独立于Hive单独运行,可作为各数据的元数据中心。本文介绍使用Docker运行Hive Standalone Metastore,并以Presto中的Hive连接器为例,通过Hive Metastore管理MinIO(S3兼容的对象存储)中的数据。
本文涉及的组件及其版本:
组件名称 | 组件版本 |
Hive Standalone Metastore | 3.1.2 |
hadoop | 3.2.2 |
mysql | 5.7.35 |
presto | 0.261 |
MinIO | 8.3.3 |
如果您还未安装Minio,可参考:https://min.io/download
mysql安装方式参考:https://lrting-top.blog.csdn.net/article/details/120424755
presto安装方式参考:https://blog.csdn.net/weixin_39636364/article/details/120518455
构建Dockerfile
Hive MetaStore需要以关系型数据库作为元数据管理,本文以MySQL为例,作为元数据存储。
- MySQL版本:5.7.35
- hostname:192.168.1.15
- port:3306
- username:root
- password:Pass-123-root
- database:metastore
除此之外,在上文中我们说到,要用此Hive MetaStore作为MinIO的元数据管理,所以您还需配置MinIO的配置信息:
- fs.s3a.endpoint:http://192.168.1.15:9000
- fs.s3a.path.style.access:true
- fs.s3a.connection.ssl.enabled:false
- fs.s3a.access.key:minio
- fs.s3a.secret.key:minio123
以上述配置信息构建Hive Metastore的配置信息,metastore-site.xml
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>fs.s3a.access.key</name>
<value>M6ZBZGI1IIDA1O130OP8</value>
</property>
<property>
<name>fs.s3a.secret.key</name>
<value>f0BSwBw5GLKSS8hpIZd+qhJBIKooqq7xQdiowhpy</value>
</property>
<property>
<name>fs.s3a.connection.ssl.enabled</name>
<value>false</value>
</property>
<property>
<name>fs.s3a.path.style.access</name>
<value>true</value>
</property>
<property>
<name>fs.s3a.endpoint</name>
<value>http://192.168.1.15:9000</value>
</property>
<property>
<name>javax.jdo.option.ConnectionURL</name>
<value>jdbc:mysql://192.168.1.15:3306/metastore?useSSL=false&serverTimezone=UTC</value>
</property>
<property>
<name>javax.jdo.option.ConnectionDriverName</name>
<value>com.mysql.jdbc.Driver</value>
</property>
<property>
<name>javax.jdo.option.ConnectionUserName</name>
<value>root</value>
</property>
<property>
<name>javax.jdo.option.ConnectionPassword</name>
<value>m98Edicines</value>
</property>
<property>
<name>hive.metastore.event.db.notification.api.auth</name>
<value>false</value>
</property>
<property>
<name>metastore.thrift.uris</name>
<value>thrift://localhost:9083</value>
<description>Thrift URI for the remote metastore. Used by metastore client to connect to remote metastore.</description>
</property>
<property>
<name>metastore.task.threads.always</name>
<value>org.apache.hadoop.hive.metastore.events.EventCleanerTask</value>
</property>
<property>
<name>metastore.expression.proxy</name>
<value>org.apache.hadoop.hive.metastore.DefaultPartitionExpressionProxy</value>
</property>
<property>
<name>metastore.warehouse.dir</name>
<value>/user/hive/warehouse</value>
</property>
</configuration>
在构建Hive Metastore镜像时,你还需要下载如下安装包以及JAR包:
- hive-standalone-metastore-3.1.2-bin.tar.gz
- hadoop-3.2.2.tar.gz
- mysql-connector-java-5.1.49.jar
本文以将上述软件包放置于HTTP服务器为例:
全部Dockerfile为:
FROM centos:centos7
RUN yum install -y wget java-1.8.0-openjdk-devel && yum clean all
ARG HTTP_SERVER_HOSTNAME_PORT=192.168.1.15:11180
WORKDIR /install
RUN wget http://${HTTP_SERVER_HOSTNAME}/downloads/hive-standalone-metastore-3.1.2-bin.tar.gz
RUN tar zxvf hive-standalone-metastore-3.1.2-bin.tar.gz
RUN rm -rf hive-standalone-metastore-3.1.2-bin.tar.gz
RUN mv apache-hive-metastore-3.1.2-bin metastore
RUN wget http://${HTTP_SERVER_HOSTNAME}/downloads/hadoop-3.2.2.tar.gz
RUN tar zxvf hadoop-3.2.2.tar.gz
RUN rm -rf hadoop-3.2.2.tar.gz
RUN mv hadoop-3.2.2 hadoop
RUN wget http://${HTTP_SERVER_HOSTNAME}/downloads/mysql-connector-java-5.1.49.jar
RUN cp mysql-connector-java-5.1.49.jar ./metastore/lib
ENV JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk
ENV HADOOP_HOME=/install/hadoop
RUN rm -f /install/metastore/lib/guava-19.0.jar
&& cp ${HADOOP_HOME}/share/hadoop/common/lib/guava-27.0-jre.jar /install/metastore/lib
&& cp ${HADOOP_HOME}/share/hadoop/tools/lib/hadoop-aws-3.2.2.jar /install/metastore/lib
&& cp ${HADOOP_HOME}/share/hadoop/tools/lib/aws-java-sdk-bundle-*.jar /install/metastore/lib
# copy Hive metastore configuration file
COPY metastore-site.xml /install/metastore/conf/
# Hive metastore data folder
VOLUME ["/user/hive/warehouse"]
WORKDIR /install/metastore
RUN bin/schematool -initSchema -dbType mysql
CMD ["/install/metastore/bin/start-metastore"]
构建Docker镜像
将metastore-site.xml与Dockerfile文件放置于同一个目录下,并进入该目录中执行:
docker build . -t minio-hive-standalone-metastore:v1.0
运行Hive Metastore
docker run -d -p 9083:9083/tcp --name minio-hive-metastore minio-hive-standalone-metastore:v1.0
使用Presto测试Hive Metastore
如果您还没有安装好Presto,请先按照文档https://blog.csdn.net/weixin_39636364/article/details/120518455对catalog配置进行如下修改,并启动presto server
connector.name=hive-hadoop2
hive.metastore.uri=thrift://URL:9083
hive.metastore.username=metastore
hive.s3.aws-access-key=minio
hive.s3.aws-secret-key=minio123
hive.s3.endpoint=http://URL:9000
hive.s3.path-style-access=true
进入presto cli,查看catalogs:
show catalogs;
得到:
创建schema:
已知我们在MinIO上有一个hive-storage的buckets,那么执行如下命令创建schema
create schema hive.hive_storage with (location = 's3a://hive-storage/');
在该schema中创建表:
CREATE TABLE hive.hive_storage.sample_table (
col1 varchar,
col2 varchar);
在表中插入数据
insert into hive.hive_storage.sample_table select 'value1', 'value2';
数据查询:
select * from hive.hive_storage.sample_table;
全部操作结果为:
本文为从大数据到人工智能博主「xiaozhch5」的原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接及本声明。
原文链接:https://lrting.top/backend/2801/
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