要使用Sqoop将PostgreSQL表导入Hive表，首先需要确保已经安装了Sqoop和相关的依赖库。然后按照以下步骤操作：，，1. 编写一个名为sqoop_import.sh的脚本文件，内容如下：，，“bash，#!/bin/bash，sqoop import \n--connect jdbc:postgresql://:/ \n--username \n--password \n--table \n--hive-import \n--hive-table \n--m 1，`，，注意替换、、、、、和为实际的值。，，2. 为脚本文件添加可执行权限：，，`bash，chmod +x sqoop_import.sh，`，，3. 运行脚本文件：，，`bash，./sqoop_import.sh，“，，这样，PostgreSQL表中的数据就会被导入到Hive表中。
Sqoop是一个用于在Hadoop和结构化数据存储（如关系数据库）之间进行大量数据传输的工具，它可以将关系数据库中的数据导入到Hadoop的HDFS、Hive、HBase等分布式文件系统中，也可以将Hadoop中的数据导出到关系数据库中，本文将介绍如何使用Sqoop将PostgreSQL表导入到Hive表中。
环境准备
1、安装并配置好Hadoop、Hive、PostgreSQL和Sqoop。
2、在PostgreSQL中创建一个表，
CREATE TABLE test_postgresql (
id INT PRIMARY KEY,
name VARCHAR(50),
age INT
);
3、在Hive中创建一个与PostgreSQL表结构相同的表：
CREATE EXTERNAL TABLE test_hive (
id INT,
name STRING,
age INT
) STORED BY 'org.apache.hadoop.hive.jdbc.storage.postgresql.PostgresStorageHandler'
TBLPROPERTIES (
'hive.database' = 'default',
'hive.table' = 'test_hive',
'hive.external.jdbc.driver' = 'org.postgresql.Driver',
'hive.external.jdbc.url' = 'jdbc:postgresql://localhost:5432/test',
'hive.external.jdbc.username' = 'postgres',
'hive.external.jdbc.password' = 'password',
'hive.exec.dynamic.partition.mode' = 'nonstrict',
'hive.compactor.initiator.on' = 'true',
'hive.compactor.worker.threads' = '1',
'hive.compactor.worker.checkinterval' = '600',
'hive.compactor.worker.iothreads' = '1',
'hive.compactor.heapsize' = '1073741824',
'hive.compactor.logcleaner.maxbackups' = '100',
'hive.compactor.logcleaner.minbackupstokeep' = '10',
'hive.compactor.logcleaner.retaindeletes' = 'false',
'hive.compactor.logcleaner.ttl' = '7200',
'hive.compactor.compaction.enabled' = 'true',
'hive.compactor.compaction.deltatargetsize' = '134217728',
'hive.compactor.compaction.maxnumdeltapartitions' = '1000000',
'hive.compactor.compaction.minnumdeltapartitions' = '100000',
'hive.compactor.compaction.numthreads' = '1',
'hive.compactor.compaction.queuesize' = '1000000',
'hive.compactor.compaction.smallfilesthresholdmb' = '16',
'hive.compactor.compaction.largefilesthresholdmb' = '134217728',
'hive.compactor.compaction.initialnumofworkers' = '2',
'hive.compactor.compaction.maxnumofworkers' = '20',
'hive.compactor.compaction.policyclassname' = '',
'hive.compactor.compactionschedulerclassname' = '',
'hive.compactor.compactiontaskmanagerclassname' = '',
'hive.compactor.compactiontaskexecutorclassname' = '',
'hive.compactor.compactiontaskexecutorparams' = '',
'hive.compactor.logcleanerclassname' => '',
'hive.compactor.logcleanerschedulerclassname' => '',
'hive.compactor.logcleanertaskmanagerclassname' => '',
'hive.compactor.logcleanertaskexecutorclassname' => '',
'hive.compactor.logcleanertaskexecutorparams' => '',
'mapreduce.jobtrackeraddresses' => '',
'mapreduce.frameworkjarsdirs': '',
'mapreduce.jobhistoryserveraddress': '',
'mapreduce.jobhistoryserverport': '',
'mapreduce.jobhistoryserverwebappurl': '',
'mapreduceclientsubmitterpluginclass': '',
'mapreduceclientsubmitterpluginpath': '',
'mapreduceclientjobsubmitterpluginclass': '',
'mapreduceclientjobsubmitterpluginpath': '',
'mapreduceclientjobcompleterpluginclass': '',
'mapreduceclientjobcompleterpluginpath': '',
'mapreduceclientsideinputpluginclass': '',
'mapreduceclientsideinputpluginpath': '',
'mapreduceclientsideoutputpluginclass': '',
'mapreduceclientsideoutputpluginpath': '',
'mapreduceclientshufflepluginclass': '',
'mapreduceclientshufflepluginpath': '',
'mapreduceclientsortpluginclass': '',
'mapreduceclientsortpluginpath': '',
'mapreduceclientaggregatorpluginclass': '',
'mapreduceclientaggregatorpluginpath': '',
);
使用Sqoop将PostgreSQL表导入到Hive表中
1、使用以下命令将PostgreSQL表中的数据导入到Hive表中：
sqoop import connect jdbc:postgresql://localhost:5432/test username postgres password password table test_postgresql columns "id","name","age" targetdir /user/hadoop/test_hive astextfile nullstring '\N'; nullif 'N'; linesperrecord 1 m 1 direct mappers 1 fields terminated by '\t'; batch numFiles 20 outdir /user/hadoop/test_import;
2、执行完上述命令后，Sqoop会将PostgreSQL表中的数据导入到Hive表中，可以使用以下命令查看Hive表中的数据：
beeline u "jdbc:hive2://localhost:10000/default" e "select * from test_hive;" outputformat=tsv2;
