hive和hadoop哪个好用(图文apache-hive-1.2.1-bin)
更多资源:https://github.com/opensourceteams
技能标签
- 下载apache hive 安装包
- 进行apache-hive-1.2.1-bin.tar.gz安装
- 配置mysql存储元数据
- 配置HDFS存储 /user/hive/warehouse
- 该Hive版本1.2.1默认集成在(spark1.6 到 Spark2.4)
下载
- 下载安装包apache-hive-1.2.1-bin.tar.gz: https://archive.apache.org/dist/hive/hive-1.2.1
- 由于spark-2.4.0-bin-hadoop2.7 预编译好的捆绑hive版本为hive-1.2.1,为了方便所以选用版本apache-hive-1.2.1-bin
- 如果spark支持其它版本的hive,需要重新手动编译spark源码也可以实现
安装
解压安装包
tar -zxvf apache-hive-1.2.1-bin.tar.gz -C /opt/module/bigdata/
配置环境变量
export HIVE_HOME=/opt/module/bigdata/apache-hive-1.2.1-bin export PATH=$HIVE_HOME/lib:#PATH
HDFS新建目录
bin/hadoop fs -mkdir -p /user/hive/warehouse #创建目录 bin/hadoop fs -chmod -R 777 /user/hive/warehouse #新建的目录赋予读写权限 bin/hadoop fs -mkdir -p /tmp/hive/#新建/tmp/hive/目录 bin/hadoop fs -chmod -R 777 /tmp/hive #目录赋予读写权限 #用以下命令检查目录是否创建成功 bin/hadoop fs -ls /user/hive bin/hadoop fs -ls /tmp/hive
连接mysql数据库
- 复制jdbc连接驱动
cp mysql-connector-java-8.0.13.jar $HIVE_HOME/lib/
新建hive-site.xml数据库相关的配置
- touch hive-site.xml文件
<?xml version="1.0" encoding="UTF-8" standalone="no"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <configuration> <property> <name>hive.metastore.warehouse.dir</name> <value>/user/hive/warehouse</value> </property> <property> <name>hive.exec.scratchdir</name> <value>/tmp/hive</value> </property> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://macbookmysql.com: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.cj.jdbc.Driver</value> <description>Driver class name for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>admin</value> <description>username to use against metastore database</description> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>000000</value> <description>password to use against metastore database</description> </property> </configuration>
新建hive-env.sh
- cp hive-env.sh.template
# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # Set Hive and hadoop environment variables here. These variables can be used # to control the execution of Hive. It should be used by admins to configure # the Hive installation (so that users do not have to set environment variables # or set command line parameters to get correct behavior). # # The hive service being invoked (CLI/HWI etc.) is available via the environment # variable SERVICE # Hive Client memory usage can be an issue if a large number of clients # are running at the same time. The flags below have been useful in # reducing memory usage: # # if [ "$SERVICE" = "cli" ]; then # if [ -z "$DEBUG" ]; then # export HADOOP_OPTS="$HADOOP_OPTS -XX:NewRatio=12 -Xms10m -XX:MaxHeapFreeRatio=40 -XX:MinHeapFreeRatio=15 -XX: UseParNewGC -XX:-UseGCOverheadLimit" # else # export HADOOP_OPTS="$HADOOP_OPTS -XX:NewRatio=12 -Xms10m -XX:MaxHeapFreeRatio=40 -XX:MinHeapFreeRatio=15 -XX:-UseGCOverheadLimit" # fi # fi # The heap size of the jvm stared by hive shell script can be controlled via: # # export HADOOP_HEAPSIZE=1024 # # Larger heap size may be required when running queries over large number of files or partitions. # By default hive shell scripts use a heap size of 256 (MB). Larger heap size would also be # appropriate for hive server (hwi etc). # Set HADOOP_HOME to point to a specific hadoop install directory # HADOOP_HOME=${bin}/../../hadoop # Hive Configuration Directory can be controlled by: # export HIVE_CONF_DIR= # Folder containing extra ibraries required for hive compilation/execution can be controlled by: # export HIVE_AUX_JARS_PATH= HADOOP_HOME=/opt/module/bigdata/hadoop-2.9.2 export HIVE_CONF_DIR=/opt/module/bigdata/apache-hive-1.2.1-bin/conf export HIVE_AUX_JARS_PATH=/opt/module/bigdata/apache-hive-1.2.1-bin/lib
初使化元数据数据库
schematool -initSchema -dbType mysql
启动hive
hive
- hive启动说明
启动hive metastore服务
- 启动该服务会开一个 9083端口
- netstat -ntlup 可以查看服务端占用的端口
hive --service metastore &
停止hive metastore服务
ps -ef|grep hive kill -9 pid
启动hiveserver服务 (该服务可以不启动)
hive --service hiveserver2 &
操作
启动 hive
hive
退出 hive命令
exit;
创建database
create database;
显示所有的database
show databases;
显示所有的表
show tables;
创建表
CREATE TABLE IF NOT EXISTS employee ( name String, salary String) COMMENT 'Employee details' ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' LINES TERMINATED BY '\n' STORED AS TEXTFILE;
插入数据
- 数据文件 employee.txt
小明 100000 小王 50000 小李 60000
- 插入数据文件到hive上
LOAD DATA LOCAL INPATH '/home/liuwen/temp/employee.txt' OVERWRITE INTO TABLE employee;
查看表数据
select * from employee;
问题处理
无法访问spark-assembly-*.jar
[liuwen@standalone lib]$ schematool -initSchema -dbType mysql ls: 无法访问/opt/module/bigdata/spark-2.4.0-bin-without-hadoop/lib/spark-assembly-*.jar: 没有那个文件或目录 Metastore connection URL: jdbc:mysql://macbookmysql.com:3306/hive?createDatabaseIfNotExist=true Metastore Connection Driver : com.mysql.cj.jdbc.Driver Metastore connection User: admin Starting metastore schema initialization to 1.2.0 Initialization script hive-schema-1.2.0.mysql.sql Error: Duplicate key name 'PCS_STATS_IDX' (state=42000,code=1061) org.apache.hadoop.hive.metastore.HiveMetaException: Schema initialization FAILED! Metastore state would be inconsistent !! *** schemaTool failed ***
- 处理方法
- 处理$HIVE_HOME/bin/hive
#sparkAssemblyPath=`ls ${SPARK_HOME}/lib/spark-assembly-*.jar` sparkAssemblyPath=`ls ${SPARK_HOME}/jars/*.jar`
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