宝剑锋从磨砺出，梅花香自苦寒来。这篇文章主要讲述Hadoop基础-12-Hive相关的知识，希望能为你提供帮助。
源码见：https://github.com/hiszm/hadoop-train
Hive概述
http://hive.apache.org/

• Hive是什么

Hive 是一个构建在 Hadoop 之上的数据仓库，它可以将结构化的数据文件映射成表，并提供类 SQL 查询功能，用于查询的 SQL 语句会被转化为 MapReduce 作业，然后提交到 Hadoop 上运行。

• 为什么要使用Hive
  • MappReduce 编程不便
  • 同时也要RDBMS关系型数据库
  • HDFS上没有schema的概念

(schema就是数据库对象的集合 , 所谓的数据库对象也就是常说的表，索引，视图，存储过程等。)

• Hive特点：

1. 简单、容易 上手 (提供了类似 SQL 的查询语言 HQL)，使得精通 sql 但是不了解 java 编程的人也能很好地进行大数据分析；
2. 灵活 性高，底层引擎支持 MR/ Tez /Spark；
3. 为超大的数据集设计的计算和存储能力，集群扩展容易;
4. 统一的元数据管理，可与presto／impala／sparksql等 共享 数据；
5. 执行延迟高，不适合做数据的实时处理，但适合做海量数据的 离线 处理。

Hive体系架构

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• client : shell , jdbc, webUI(zeppelin)
• metastore : 指数据库中的元数据

Hive部署架构

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Hive与RDBMS的区别

	Hive	RDBMS
查询语言	Hive SQL	SQL
数据储存	HDFS	Raw Device or Local FS
索引	无(支持比较弱)	有
执行	MapReduce、 Tez	Excutor
执行时延	高，离线	低 , 在线
数据规模	非常大, 大	小

Hive部署

• 获得wget hive-1.1.0-cdh5.15.1.tar.gz(url)
• 解压 tar -zxvf hive-1.1.0-cdh5.15.1.tar.gz -C ~/app/
• 配置环境变量

export HIVE_HOME=/home/hadoop/app/hive-1.1.0-cdh5.15.1 export PATH=$HIVE_HOME/bin:$PATH

• 生效 source ~/.bash_profile

[hadoop@hadoop000 app]$ source ~/.bash_profile [hadoop@hadoop000 app]$ echo $HIVE_HOME /home/hadoop/app/hive-1.1.0-cdh5.15.1

• 修改配置

[hadoop@hadoop000 conf]$ cat hive-site.xml < ?xml version="1.0"?> < ?xml-stylesheet type="text/xsl" href="https://www.songbingjia.com/android/configuration.xsl"?> < configuration> < property> < name> javax.jdo.option.ConnectionURL< /name> < value> jdbc:mysql://hadoop000:3306/hadoop_hive?createDatabaseIfNotExist=true< /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> root< /value> < /property> < /configuration> [hadoop@hadoop000 conf]$

• MySQL驱动 mysql-connector-java-5.1.27-bin.jar
  
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拷贝到目录home/hadoop/app/hive-1.1.0-cdh5.15.1/lib

• 安装数据库 用yum 安装

[hadoop@hadoop000 lib]$ mysql -uroot -proot Warning: Using a password on the command line interface can be insecure. Welcome to the MySQL monitor.Commands end with ; or \\g. Your MySQL connection id is 2 Server version: 5.6.42 MySQL Community Server (GPL)Copyright (c) 2000, 2018, Oracle and/or its affiliates. All rights reserved.Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.Type \'help; \' or \'\\h\' for help. Type \'\\c\' to clear the current input statement.mysql>

Hive快速入门

• 启动hive

[hadoop@hadoop000 sbin]$ jps 3218 SecondaryNameNode 3048 DataNode 3560 NodeManager 3451 ResourceManager 2940 NameNode 3599 Jps

hive> create database test > ; OK

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mysql> mysql> select * from DBS\\G; *************************** 1. row *************************** DB_ID: 1 DESC: Default Hive database DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse NAME: default OWNER_NAME: public OWNER_TYPE: ROLE *************************** 2. row *************************** DB_ID: 3 DESC: NULL DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse/hive.db NAME: hive OWNER_NAME: hadoop OWNER_TYPE: USER *************************** 3. row *************************** DB_ID: 4 DESC: NULL DB_LOCATION_URI: hdfs://hadoop000:8020/test/location NAME: hive2 OWNER_NAME: hadoop OWNER_TYPE: USER *************************** 4. row *************************** DB_ID: 6 DESC: NULL DB_LOCATION_URI: hdfs://hadoop000:8020/user/hive/warehouse/test.db NAME: test OWNER_NAME: hadoop OWNER_TYPE: USER 4 rows in set (0.00 sec)ERROR: No query specified

Hive DDL
【Hadoop基础-12-Hive】Hive DDL=Hive Data Definition Language

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数据库操作

• Create Database

CREATE (DATABASE|SCHEMA) [IF NOT EXISTS] database_name [COMMENT database_comment] [LOCATION hdfs_path] [MANAGEDLOCATION hdfs_path] [WITH DBPROPERTIES (property_name=property_value, ...)];

Drop Database

DROP (DATABASE|SCHEMA) [IF EXISTS] database_name [RESTRICT|CASCADE];

hive> create DATABASE hive_test; OK Time taken: 0.154 seconds hive>

再HDFS上的 默认路径 /user/hive/warehouse/hive_test.db
默认的hive数据库没有default.db的路径/user/hive/warehouse/

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hive> create DATABASE hive_test2 LOCATION \'/test/hive\' > ; OK Time taken: 0.119 seconds hive> [hadoop@hadoop000 network-scripts]$ hadoop fs -ls /test/ Found 1 items drwxr-xr-x- hadoop supergroup0 2020-09-09 06:29 /test/hive

DESC DATABASE [EXTENDED] db_name; --EXTENDED 表示是否显示额外属性

hive> create DATABASE hive_test3 LOCATION \'/test/hive\' > with DBPROPERTIES(\'creator\'=\'jack\'); OK Time taken: 0.078 seconds hive> desc database hive_test3 > ; OK hive_test3hdfs://hadoop000:8020/test/hive hadoop USER Time taken: 0.048 seconds, Fetched: 1 row(s) hive> desc database extended hive_test3; OK hive_test3hdfs://hadoop000:8020/test/hive hadoop USER {creator=jack} Time taken: 0.018 seconds, Fetched: 1 row(s) hive>

hive> set hive.cli.print.current.db; hive.cli.print.current.db=false hive> set hive.cli.print.current.db=true; hive (default)>

• Drop Database

DROP (DATABASE|SCHEMA) [IF EXISTS] database_name [RESTRICT|CASCADE];

hive (default)> show databases; OK default hive hive2 hive_test hive_test3 test Time taken: 0.02 seconds, Fetched: 6 row(s) hive (default)> drop database hive_test3; OK Time taken: 0.099 seconds hive (default)> show databases; OK default hive hive2 hive_test test Time taken: 0.019 seconds, Fetched: 5 row(s) hive (default)>

• 查找数据库

hive (default)> show databases like \'hive*\'; OK hive hive2 hive_test Time taken: 0.024 seconds, Fetched: 3 row(s) hive (default)>

• 使用数据库

USE database_name;

表操作

• 创建表

CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name--表名 [(col_name data_type [COMMENT col_comment], ... [constraint_specification])]--列名 列数据类型 [COMMENT table_comment]--表描述 [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)]--分区表分区规则 [ CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS ]--分桶表分桶规则 [SKEWED BY (col_name, col_name, ...) ON ((col_value, col_value, ...), (col_value, col_value, ...), ...) [STORED AS DIRECTORIES] ]--指定倾斜列和值 [ [ROW FORMAT row_format] [STORED AS file_format] | STORED BY \'storage.handler.class.name\' [WITH SERDEPROPERTIES (...)] ]-- 指定行分隔符、存储文件格式或采用自定义存储格式 [LOCATION hdfs_path]-- 指定表的存储位置 [TBLPROPERTIES (property_name=property_value, ...)]--指定表的属性 [AS select_statement]; --从查询结果创建表

CREATE TABLE emp( empno int , ename string, job string, mgr int, hiredate string, sal double, comm double, deptno int ) ROW FORMAT DELIMITED FIELDS TERMINATED BY \'\\t\';

hive> CREATE TABLE emp( > empno int , > ename string, > job string, > mgr int, > hiredate string, > sal double, > comm double, > deptno int > ) ROW FORMAT DELIMITED FIELDS TERMINATED BY \'\\t\'; OK Time taken: 0.115 seconds hive> desc formatted emp; OK # col_namedata_typecommentempnoint enamestring jobstring mgrint hiredatestring saldouble commdouble deptnoint# Detailed Table Information Database:hive Owner:hadoop CreateTime:Wed Sep 09 09:34:57 CST 2020 LastAccessTime:UNKNOWN Protect Mode:None Retention:0 Location:hdfs://hadoop000:8020/user/hive/warehouse/hive.db/emp Table Type:MANAGED_TABLE Table Parameters: transient_lastDdlTime 1599615297# 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\\t serialization.format \\t Time taken: 0.131 seconds, Fetched: 34 row(s)

• 加载数据

用DML的加载数据

LOAD DATA [LOCAL] INPATH \'filepath\' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] LOAD DATA [LOCAL] INPATH \'filepath\' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] [INPUTFORMAT \'inputformat\' SERDE \'serde\'] (3.0 or later)

LOAD DATA LOCAL INPATH \'/home/hadoop/data/emp.txt\' OVERWRITE INTO TABLE emp;

hive> LOAD DATA LOCAL INPATH\'/home/hadoop/data/emp.txt\' OVERWRITE INTO TABLE emp; Loading data to table hive.emp Table hive.emp stats: [numFiles=1, totalSize=700] OK Time taken: 2.482 seconds hive> select * from emp; OK 7369 SMITH CLERK 7902 1980-12-17 800.0 NULL 20 7499 ALLEN SALESMAN 7698 1981-2-20 1600.0 300.0 30 7521 WARD SALESMAN 7698 1981-2-22 1250.0 500.0 30 7566 JONES MANAGER 7839 1981-4-2 2975.0 NULL 20 7654 MARTIN SALESMAN 7698 1981-9-28 1250.0 1400.0 30 7698 BLAKE MANAGER 7839 1981-5-1 2850.0 NULL 30 7782 CLARK MANAGER 7839 1981-6-9 2450.0 NULL 10 7788 SCOTT ANALYST 7566 1987-4-19 3000.0 NULL 20 7839 KING PRESIDENT NULL 1981-11-17 5000.0 NULL 10 7844 TURNER SALESMAN 7698 1981-9-8 1500.0 0.0 30 7876 ADAMS CLERK 7788 1987-5-23 1100.0 NULL 20 7900 JAMES CLERK 7698 1981-12-3 950.0 NULL 30 7902 FORD ANALYST 7566 1981-12-3 3000.0 NULL 20 7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10 8888 HIVE PROGRAM 7839 1988-1-23 10300.0 NULL NULL Time taken: 0.363 seconds, Fetched: 15 row(s) hive>

• 更改表名

ALTER TABLE table_name RENAME TO new_table_name;

Hive DML
Hive Data Manipulation Language

LOAD DATA [LOCAL] INPATH \'filepath\' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] LOAD DATA [LOCAL] INPATH \'filepath\' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)] [INPUTFORMAT \'inputformat\' SERDE \'serde\'] (3.0 or later)

• LOCAL: 有 就是从服务器目录获取文件, 无则从HDFS系统
  
• OVERWRITE: 有 表示新建数据 ; 无 表示追加数据
  
• INPATH
  
  • a relative path, such as project/data1
  • an absolute path, such as /user/hive/project/data1
  • a full URI with scheme and (optionally) an authority, such as hdfs://namenode:9000/user/hive/project/data1

创建查询表create table emp_1 as select * from emp;

• 导出数据

INSERT OVERWRITE LOCAL DIRECTORY \'/tmp/hive\' ROW FORMAT DELIMITED FIELDS TERMINATED BY \'\\t\' select empno , ename ,sal,deptno from emp;

hive> > INSERT OVERWRITE LOCAL DIRECTORY \'/tmp/hive\' > ROW FORMAT DELIMITED FIELDS TERMINATED BY \'\\t\' > select empno , ename ,sal,deptno from emp; Query ID = hadoop_20200909102020_aeb2ef7d-cf18-4bcb-b903-8c6ea1719626 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there\'s no reduce operator Starting Job = job_1599583423179_0001, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0001/ Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job-kill job_1599583423179_0001 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0 2020-09-09 10:21:18,074 Stage-1 map = 0%,reduce = 0% 2020-09-09 10:21:29,109 Stage-1 map = 100%,reduce = 0%, Cumulative CPU 5.64 sec MapReduce Total cumulative CPU time: 5 seconds 640 msec Ended Job = job_1599583423179_0001 Copying data to local directory /tmp/hive MapReduce Jobs Launched: Stage-Stage-1: Map: 1Cumulative CPU: 5.64 secHDFS Read: 4483 HDFS Write: 313 SUCCESS Total MapReduce CPU Time Spent: 5 seconds 640 msec OK Time taken: 35.958 seconds hive> [hadoop@hadoop000 hive]$ cat 000000_0 7369 SMITH 800.0 20 7499 ALLEN 1600.0 30 7521 WARD 1250.0 30 7566 JONES 2975.0 20 7654 MARTIN 1250.0 30 7698 BLAKE 2850.0 30 7782 CLARK 2450.0 10 7788 SCOTT 3000.0 20 7839 KING 5000.0 10 7844 TURNER 1500.0 30 7876 ADAMS 1100.0 20 7900 JAMES 950.0 30 7902 FORD 3000.0 20 7934 MILLER 1300.0 10 8888 HIVE 10300.0 \\N [hadoop@hadoop000 hive]$

Hive QL

• 基本统计

和普通的sql并无两样
select * from emp where deptno=10;

• 聚合函数

hive> select count(1) from emp where deptno=10; Query ID = hadoop_20200909104949_1ce185de-2025-4633-9324-3e47f30fb157 Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks determined at compile time: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=< number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=< number> In order to set a constant number of reducers: set mapreduce.job.reduces=< number> Starting Job = job_1599583423179_0002, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0002/ Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job-kill job_1599583423179_0002 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 2020-09-09 10:50:00,361 Stage-1 map = 0%,reduce = 0% 2020-09-09 10:50:10,092 Stage-1 map = 100%,reduce = 0%, Cumulative CPU 6.52 sec 2020-09-09 10:50:25,233 Stage-1 map = 100%,reduce = 100%, Cumulative CPU 11.72 sec MapReduce Total cumulative CPU time: 11 seconds 720 msec Ended Job = job_1599583423179_0002 MapReduce Jobs Launched: Stage-Stage-1: Map: 1Reduce: 1Cumulative CPU: 11.72 secHDFS Read: 9708 HDFS Write: 2 SUCCESS Total MapReduce CPU Time Spent: 11 seconds 720 msec OK 3 Time taken: 38.666 seconds, Fetched: 1 row(s) hive> select * from emp where deptno=10; OK 7782 CLARK MANAGER 7839 1981-6-9 2450.0 NULL 10 7839 KING PRESIDENT NULL 1981-11-17 5000.0 NULL 10 7934 MILLER CLERK 7782 1982-1-23 1300.0 NULL 10 Time taken: 0.209 seconds, Fetched: 3 row(s) hive>

• 分组函数

select deptno , avg(sal) from group by deptno;
注意select的字段没有再聚合函数就要出现再group by 里面

• join的使用

用于涉及到多表

CREATE TABLE dept( deptno int, dname string, loc string )ROW FORMAT DELIMITED FIELDS TERMINATED BY \'\\t\';

LOAD DATA LOCAL INPATH \'/home/hadoop/data/dept.txt\' OVERWRITE INTO TABLE dept;

select e.empno,e.ename,e.sal,e.deptno,d.dname from emp e join dept d on e.deptno=d.deptno;

hive> select e.empno,e.ename,e.sal,e.deptno,d.dname > from emp e join dept d > on e.deptno=d.deptno; Query ID = hadoop_20200909140808_8635204d-8e8a-4267-8503-ef242f022ebc Total jobs = 1 2020-09-09 02:08:51 Starting to launch local task to process map join; maximum memory = 477626368 2020-09-09 02:08:54 End of local task; Time Taken: 3.023 sec. Execution completed successfully MapredLocal task succeeded Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there\'s no reduce operator Starting Job = job_1599583423179_0004, Tracking URL = http://hadoop000:8088/proxy/application_1599583423179_0004/ Kill Command = /home/hadoop/app/hadoop-2.6.0-cdh5.15.1/bin/hadoop job-kill job_1599583423179_0004 Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 0 2020-09-09 14:09:06,852 Stage-3 map = 0%,reduce = 0% 2020-09-09 14:09:18,823 Stage-3 map = 100%,reduce = 0%, Cumulative CPU 6.7 sec MapReduce Total cumulative CPU time: 6 seconds 700 msec Ended Job = job_1599583423179_0004 MapReduce Jobs Launched: Stage-Stage-3: Map: 1Cumulative CPU: 6.7 secHDFS Read: 7649 HDFS Write: 406 SUCCESS Total MapReduce CPU Time Spent: 6 seconds 700 msec OK 7369 SMITH 800.0 20 RESEARCH 7499 ALLEN 1600.0 30 SALES 7521 WARD 1250.0 30 SALES 7566 JONES 2975.0 20 RESEARCH 7654 MARTIN 1250.0 30 SALES 7698 BLAKE 2850.0 30 SALES 7782 CLARK 2450.0 10 ACCOUNTING 7788 SCOTT 3000.0 20 RESEARCH 7839 KING 5000.0 10 ACCOUNTING 7844 TURNER 1500.0 30 SALES 7876 ADAMS 1100.0 20 RESEARCH 7900 JAMES 950.0 30 SALES 7902 FORD 3000.0 20 RESEARCH 7934 MILLER 1300.0 10 ACCOUNTING Time taken: 46.765 seconds, Fetched: 14 row(s) hive>

• 执行计划

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explain select e.empno,e.ename,e.sal,e.deptno,d.dname from emp e join dept d on e.deptno=d.deptno;

hive> explain > select e.empno,e.ename,e.sal,e.deptno,d.dname > from emp e join dept d > on e.deptno=d.deptno; OK STAGE DEPENDENCIES: Stage-4 is a root stage Stage-3 depends on stages: Stage-4 Stage-0 depends on stages: Stage-3STAGE PLANS: Stage: Stage-4 Map Reduce Local Work Alias -> Map Local Tables: d Fetch Operator limit: -1 Alias -> Map Local Operator Tree: d TableScan alias: d Statistics: Num rows: 1 Data size: 79 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: deptno is not null (type: boolean) Statistics: Num rows: 1 Data size: 79 Basic stats: COMPLETE Column stats: NONE HashTable Sink Operator keys: 0 deptno (type: int) 1 deptno (type: int)Stage: Stage-3 Map Reduce Map Operator Tree: TableScan alias: e Statistics: Num rows: 6 Data size: 700 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: deptno is not null (type: boolean) Statistics: Num rows: 3 Data size: 350 Basic stats: COMPLETE Column stats: NONE Map Join Operator condition map: Inner Join 0 to 1 keys: 0 deptno (type: int) 1 deptno (type: int) outputColumnNames: _col0, _col1, _col5, _col7, _col12 Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col5 (type: double), _col7 (type: int), _col12 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4 Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false Statistics: Num rows: 3 Data size: 385 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.TextInputFormat output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Local Work: Map Reduce Local WorkStage: Stage-0 Fetch Operator limit: -1 Processor Tree: ListSink

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