Hive的下载
下载地址http://mirrors.hust.edu.cn/apache/
选择合适的Hive版本进行下载，进到stable-2文件夹可以看到稳定的2.x的版本是2.3.3
Hive的安装
1、本人使用MySQL做为Hive的元数据库，所以先安装MySQL。
MySql安装过程http://www.cnblogs.com/qingyunzong/p/8294876.html
2、上传Hive安装包
3、解压安装包
[hadoop@hadoop3 ~] schematool -dbType mysql -initSchema
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/apps/apache-hive-2.3.3-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/apps/hadoop-2.7.5/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://hadoop1:3306/hivedb?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
[hadoop@hadoop3 ~]$
9、 启动 Hive 客户端
hive --service cli和hive效果一样
[hadoop@hadoop3 ~]$ hive --service cli
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/apps/apache-hive-2.3.3-bin/lib/log4j-slf4j-impl-2.6.2.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/apps/hadoop-2.7.5/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:/home/hadoop/apps/apache-hive-2.3.3-bin/lib/hive-common-2.3.3.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>
基本使用
现有一个文件student.txt，将其存入hive中，student.txt数据格式如下：
95002,刘晨,女,19,IS
95017,王风娟,女,18,IS
95018,王一,女,19,IS
95013,冯伟,男,21,CS
95014,王小丽,女,19,CS
95019,邢小丽,女,19,IS
95020,赵钱,男,21,IS
95003,王敏,女,22,MA
95004,张立,男,19,IS
95012,孙花,女,20,CS
95010,孔小涛,男,19,CS
95005,刘刚,男,18,MA
95006,孙庆,男,23,CS
95007,易思玲,女,19,MA
95008,李娜,女,18,CS
95021,周二,男,17,MA
95022,郑明,男,20,MA
95001,李勇,男,20,CS
95011,包小柏,男,18,MA
95009,梦圆圆,女,18,MA
95015,王君,男,18,MA
1、创建一个数据库myhive
hive> create database myhive;
OK
Time taken: 7.847 seconds
hive>
2、使用新的数据库myhive
hive> use myhive;
OK
Time taken: 0.047 seconds
hive>
3、查看当前正在使用的数据库
hive> select current_database();
OK
myhive
Time taken: 0.728 seconds, Fetched: 1 row(s)
hive>
4、在数据库myhive创建一张student表
hive> create table student(id int, name string, sex string, age int, department string) row format delimited fields terminated by ",";
OK
Time taken: 0.718 seconds
hive>
5、往表中加载数据
hive> load data local inpath "/home/hadoop/student.txt" into table student;
Loading data to table myhive.student
OK
Time taken: 1.854 seconds
hive>
6、查询数据
hive> select * from student;
OK
95002 刘晨 女 19 IS
95017 王风娟 女 18 IS
95018 王一 女 19 IS
95013 冯伟 男 21 CS
95014 王小丽 女 19 CS
95019 邢小丽 女 19 IS
95020 赵钱 男 21 IS
95003 王敏 女 22 MA
95004 张立 男 19 IS
95012 孙花 女 20 CS
95010 孔小涛 男 19 CS
95005 刘刚 男 18 MA
95006 孙庆 男 23 CS
95007 易思玲 女 19 MA
95008 李娜 女 18 CS
95021 周二 男 17 MA
95022 郑明 男 20 MA
95001 李勇 男 20 CS
95011 包小柏 男 18 MA
95009 梦圆圆 女 18 MA
95015 王君 男 18 MA
Time taken: 2.455 seconds, Fetched: 21 row(s)
hive>
7、查看表结构
hive> desc student;
OK
id int
name string
sex string
age int
department string
Time taken: 0.102 seconds, Fetched: 5 row(s)
hive>
hive> desc extended student;
OK
id int
name string
sex string
age int
department string
Detailed Table Information Table(tableName:student, dbName:myhive, owner:hadoop, createTime:1522750487, lastAccessTime:0, retention:0, sd:StorageDescriptor(cols:[FieldSchema(name:id, type:int, comment:null), FieldSchema(name:name, type:string, comment:null), FieldSchema(name:sex, type:string, comment:null), FieldSchema(name:age, type:int, comment:null), FieldSchema(name:department, type:string, comment:null)], location:hdfs://myha01/user/hive/warehouse/myhive.db/student, inputFormat:org.apache.hadoop.mapred.TextInputFormat, outputFormat:org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat, compressed:false, numBuckets:-1, serdeInfo:SerDeInfo(name:null, serializationLib:org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe, parameters:{serialization.format=,, field.delim=,}), bucketCols:[], sortCols:[], parameters:{}, skewedInfo:SkewedInfo(skewedColNames:[], skewedColValues:[], skewedColValueLocationMaps:{}), storedAsSubDirectories:false), partitionKeys:[], parameters:{transient_lastDdlTime=1522750695, totalSize=523, numRows=0, rawDataSize=0, numFiles=1}, viewOriginalText:null, viewExpandedText:null, tableType:MANAGED_TABLE, rewriteEnabled:false)
Time taken: 0.127 seconds, Fetched: 7 row(s)
hive>
hive> desc formatted student;
OK
col_name data_type comment
id int
name string
sex string
age int
department string
Detailed Table Information
Database: myhive
Owner: hadoop
CreateTime: Tue Apr 03 18:14:47 CST 2018
LastAccessTime: UNKNOWN
Retention: 0
Location: hdfs://myha01/user/hive/warehouse/myhive.db/student
Table Type: MANAGED_TABLE
Table Parameters:
numFiles 1
numRows 0
rawDataSize 0
totalSize 523
transient_lastDdlTime 1522750695
Storage Information
SerDe Library: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
InputFormat: org.apache.hadoop.mapred.TextInputFormat
OutputFormat: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
Compressed: No
Num Buckets: -1
Bucket Columns: []
Sort Columns: []
Storage Desc Params:
field.delim ,
serialization.format ,
Time taken: 0.13 seconds, Fetched: 34 row(s)
hive>
京公网安备 11010502036488号