suchen
HeimDatenbankMySQL-TutorialSqoop安装配置及演示

Sqoop是一个用来将Hadoop(Hive、HBase)和关系型数据库中的数据相互转移的工具,可以将一个关系型数据库(例如:MySQL ,Oracle ,Postgres等)中的数据导入到Hadoop的HDFS中,也可以将HDFS的数据导入到关系型数据库中。Sqoop目前已经是Apache的顶级项目了,

Sqoop是一个用来将Hadoop(Hive、HBase)和关系型数据库中的数据相互转移的工具,可以将一个关系型数据库(例如:MySQL ,Oracle ,Postgres等)中的数据导入到Hadoop的HDFS中,也可以将HDFS的数据导入到关系型数据库中。 Sqoop目前已经是Apache的顶级项目了,目前版本是1.4.4 和 Sqoop2 1.99.3,本文以1.4.4的版本为例讲解基本的安装配置和简单应用的演示。
  • 安装配置
  • 准备测试数据
  • 导入数据到HDFS
  • 导入数据到Hive
  • 导入数据到HBase
[一]、安装配置 选择Sqoop 1.4.4 版本:sqoop-1.4.4.bin__hadoop-2.0.4-alpha.tar.gz 1.1、下载后解压配置:
tar -zxvf sqoop-1.4.4.bin__hadoop-2.0.4-alpha.tar.gz /usr/local/
cd /usr/local
ln -s sqoop-1.4.4.bin__hadoop-2.0.4-alpha sqoop
1.2、环境变量配置 vi ~/.bash_profile
#Sqoop  add by micmiu.com
export SQOOP_HOME=/usr/local/sqoop
export PATH=$SQOOP_HOME/bin:$PATH
1.3、配置Sqoop参数: 复制/conf/sqoop-env-template.sh 一份重命名为:/conf/sqoop-env.sh vi ?<sqoop_home>/conf/sqoop-env.sh</sqoop_home>
# 指定各环境变量的实际配置
# Set Hadoop-specific environment variables here.
#Set path to where bin/hadoop is available
#export HADOOP_COMMON_HOME=
#Set path to where hadoop-*-core.jar is available
#export HADOOP_MAPRED_HOME=
#set the path to where bin/hbase is available
#export HBASE_HOME=
#Set the path to where bin/hive is available
#export HIVE_HOME=
ps:因为我当前用户的默认环境变量中已经配置了相关变量,故该配置文件无需再修改:
# Hadoop  
export HADOOP_PREFIX="/usr/local/hadoop"  
export HADOOP_HOME=${HADOOP_PREFIX}  
export PATH=$PATH:$HADOOP_PREFIX/bin:$HADOOP_PREFIX/sbin
export HADOOP_COMMON_HOME=${HADOOP_PREFIX}  
export HADOOP_HDFS_HOME=${HADOOP_PREFIX}  
export HADOOP_MAPRED_HOME=${HADOOP_PREFIX}
export HADOOP_YARN_HOME=${HADOOP_PREFIX}  
# Native Path  
export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_PREFIX}/lib/native  
export HADOOP_OPTS="-Djava.library.path=$HADOOP_PREFIX/lib/native" 
# Hadoop end
#Hive
export HIVE_HOME=/usr/local/hive
export PATH=$HIVE_HOME/bin:$PATH
#HBase
export HBASE_HOME=/usr/local/hbase
export PATH=$HBASE
#add by micmiu.com
1.4、驱动jar包 下面测试演示以MySQL为例,则需要把mysql对应的驱动lib文件copy到 <sqoop_home>/lib</sqoop_home> 目录下。 [二]、测试数据准备 以MySQL 为例:
  • 192.168.6.77(hostname:Master.Hadoop)
  • database: test
  • 用户:root 密码:micmiu
准备两张测试表一个有主键表demo_blog,一个无主键表 demo_log
CREATE TABLE `demo_blog` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `blog` varchar(100) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=MyISAM  DEFAULT CHARSET=utf8;
CREATE TABLE `demo_log` (
  `operator` varchar(16) NOT NULL,
  `log` varchar(100) NOT NULL
) ENGINE=MyISAM  DEFAULT CHARSET=utf8;
插入测试数据:
insert into demo_blog (id, blog) values (1, "micmiu.com");
insert into demo_blog (id, blog) values (2, "ctosun.com");
insert into demo_blog (id, blog) values (3, "baby.micmiu.com");
insert into demo_log (operator, log) values ("micmiu", "create");
insert into demo_log (operator, log) values ("micmiu", "update");
insert into demo_log (operator, log) values ("michael", "edit");
insert into demo_log (operator, log) values ("michael", "delete");
[三]、导入数据到HDFS 3.1、导入有主键的表 比如我需要把表 demo_blog (含主键) 的数据导入到HDFS中,执行如下命令:
sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog
执行过程如下:
$ sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog
Warning: /usr/lib/hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
14/04/09 09:58:43 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
14/04/09 09:58:43 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
14/04/09 09:58:43 INFO tool.CodeGenTool: Beginning code generation
14/04/09 09:58:43 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 09:58:43 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 09:58:43 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/local/hadoop
Note: /tmp/sqoop-hadoop/compile/e8fd26a5bca5b7f51cdb03bf847ce389/demo_blog.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
14/04/09 09:58:44 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/e8fd26a5bca5b7f51cdb03bf847ce389/demo_blog.jar
14/04/09 09:58:44 WARN manager.MySQLManager: It looks like you are importing from mysql.
14/04/09 09:58:44 WARN manager.MySQLManager: This transfer can be faster! Use the --direct
14/04/09 09:58:44 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
14/04/09 09:58:44 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
14/04/09 09:58:44 INFO mapreduce.ImportJobBase: Beginning import of demo_blog
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/hbase-0.98.0-hadoop2/lib/slf4j-log4j12-1.6.4.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.slf4j.impl.Log4jLoggerFactory]
14/04/09 09:58:44 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
14/04/09 09:58:45 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
14/04/09 09:58:45 INFO client.RMProxy: Connecting to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 09:58:47 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(`id`), MAX(`id`) FROM `demo_blog`
14/04/09 09:58:47 INFO mapreduce.JobSubmitter: number of splits:3
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.job.classpath.files is deprecated. Instead, use mapreduce.job.classpath.files
14/04/09 09:58:47 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.cache.files.filesizes is deprecated. Instead, use mapreduce.job.cache.files.filesizes
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.cache.files is deprecated. Instead, use mapreduce.job.cache.files
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
14/04/09 09:58:47 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
14/04/09 09:58:47 INFO Configuration.deprecation: mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
14/04/09 09:58:47 INFO Configuration.deprecation: mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.cache.files.timestamps is deprecated. Instead, use mapreduce.job.cache.files.timestamps
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
14/04/09 09:58:47 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
14/04/09 09:58:47 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1396936838233_0001
14/04/09 09:58:47 INFO impl.YarnClientImpl: Submitted application application_1396936838233_0001 to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 09:58:47 INFO mapreduce.Job: The url to track the job: http://Master.Hadoop:8088/proxy/application_1396936838233_0001/
14/04/09 09:58:47 INFO mapreduce.Job: Running job: job_1396936838233_0001
14/04/09 09:59:00 INFO mapreduce.Job: Job job_1396936838233_0001 running in uber mode : false
14/04/09 09:59:00 INFO mapreduce.Job:  map 0% reduce 0%
14/04/09 09:59:14 INFO mapreduce.Job:  map 33% reduce 0%
14/04/09 09:59:16 INFO mapreduce.Job:  map 67% reduce 0%
14/04/09 09:59:19 INFO mapreduce.Job:  map 100% reduce 0%
14/04/09 09:59:19 INFO mapreduce.Job: Job job_1396936838233_0001 completed successfully
14/04/09 09:59:19 INFO mapreduce.Job: Counters: 27
	File System Counters
		FILE: Number of bytes read=0
		FILE: Number of bytes written=271866
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=295
		HDFS: Number of bytes written=44
		HDFS: Number of read operations=12
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=6
	Job Counters 
		Launched map tasks=3
		Other local map tasks=3
		Total time spent by all maps in occupied slots (ms)=43032
		Total time spent by all reduces in occupied slots (ms)=0
	Map-Reduce Framework
		Map input records=3
		Map output records=3
		Input split bytes=295
		Spilled Records=0
		Failed Shuffles=0
		Merged Map outputs=0
		GC time elapsed (ms)=590
		CPU time spent (ms)=6330
		Physical memory (bytes) snapshot=440934400
		Virtual memory (bytes) snapshot=3882573824
		Total committed heap usage (bytes)=160563200
	File Input Format Counters 
		Bytes Read=0
	File Output Format Counters 
		Bytes Written=44
14/04/09 09:59:19 INFO mapreduce.ImportJobBase: Transferred 44 bytes in 34.454 seconds (1.2771 bytes/sec)
14/04/09 09:59:19 INFO mapreduce.ImportJobBase: Retrieved 3 records.
验证导入到hdfs上的数据:
$ hdfs dfs -ls /user/hadoop/demo_blog
Found 4 items
-rw-r--r--   3 hadoop supergroup          0 2014-04-09 09:59 /user/hadoop/demo_blog/_SUCCESS
-rw-r--r--   3 hadoop supergroup         13 2014-04-09 09:59 /user/hadoop/demo_blog/part-m-00000
-rw-r--r--   3 hadoop supergroup         13 2014-04-09 09:59 /user/hadoop/demo_blog/part-m-00001
-rw-r--r--   3 hadoop supergroup         18 2014-04-09 09:59 /user/hadoop/demo_blog/part-m-00002
[hadoop@Master ~]$ hdfs dfs -cat /user/hadoop/demo_blog/part-m-0000*
1,micmiu.com
2,ctosun.com
3,baby.micmiu.com
ps:默认设置下导入到hdfs上的路径是:?/user/username/tablename/(files),比如我的当前用户是hadoop,那么实际路径即:?/user/hadoop/demo_blog/(files)。 如果要自定义路径需要增加参数:--warehouse-dir 比如:
sqoop import --connect jdbc:mysql://Master.Hadoop/test --username root --password micmiu --table demo_blog --warehouse-dir /user/micmiu/sqoop
3.2、导入不含主键的表 比如需要把表 demo_log(无主键) 的数据导入到hdfs中,执行如下命令:
sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_log --warehouse-dir /user/micmiu/sqoop --split-by operator
ps:无主键表的导入需要增加参数? --split-by xxx ?或者 -m 1 执行过程:
$ sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_log --warehouse-dir /user/micmiu/sqoop --split-by operator
Warning: /usr/lib/hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
14/04/09 15:02:06 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
14/04/09 15:02:06 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
14/04/09 15:02:06 INFO tool.CodeGenTool: Beginning code generation
14/04/09 15:02:06 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_log` AS t LIMIT 1
14/04/09 15:02:06 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_log` AS t LIMIT 1
14/04/09 15:02:06 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/local/hadoop
Note: /tmp/sqoop-hadoop/compile/dddc1bcdba30515f95a2d604f22e4fe9/demo_log.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
14/04/09 15:02:07 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/dddc1bcdba30515f95a2d604f22e4fe9/demo_log.jar
14/04/09 15:02:07 WARN manager.MySQLManager: It looks like you are importing from mysql.
14/04/09 15:02:07 WARN manager.MySQLManager: This transfer can be faster! Use the --direct
14/04/09 15:02:07 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
14/04/09 15:02:07 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
14/04/09 15:02:07 INFO mapreduce.ImportJobBase: Beginning import of demo_log
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/hbase-0.98.0-hadoop2/lib/slf4j-log4j12-1.6.4.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.slf4j.impl.Log4jLoggerFactory]
14/04/09 15:02:07 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
14/04/09 15:02:08 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
14/04/09 15:02:08 INFO client.RMProxy: Connecting to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 15:02:10 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(`operator`), MAX(`operator`) FROM `demo_log`
14/04/09 15:02:10 WARN db.TextSplitter: Generating splits for a textual index column.
14/04/09 15:02:10 WARN db.TextSplitter: If your database sorts in a case-insensitive order, this may result in a partial import or duplicate records.
14/04/09 15:02:10 WARN db.TextSplitter: You are strongly encouraged to choose an integral split column.
14/04/09 15:02:10 INFO mapreduce.JobSubmitter: number of splits:4
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.job.classpath.files is deprecated. Instead, use mapreduce.job.classpath.files
14/04/09 15:02:10 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.cache.files.filesizes is deprecated. Instead, use mapreduce.job.cache.files.filesizes
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.cache.files is deprecated. Instead, use mapreduce.job.cache.files
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
14/04/09 15:02:10 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
14/04/09 15:02:10 INFO Configuration.deprecation: mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
14/04/09 15:02:10 INFO Configuration.deprecation: mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.cache.files.timestamps is deprecated. Instead, use mapreduce.job.cache.files.timestamps
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
14/04/09 15:02:10 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
14/04/09 15:02:10 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1396936838233_0003
14/04/09 15:02:10 INFO impl.YarnClientImpl: Submitted application application_1396936838233_0003 to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 15:02:10 INFO mapreduce.Job: The url to track the job: http://Master.Hadoop:8088/proxy/application_1396936838233_0003/
14/04/09 15:02:10 INFO mapreduce.Job: Running job: job_1396936838233_0003
14/04/09 15:02:17 INFO mapreduce.Job: Job job_1396936838233_0003 running in uber mode : false
14/04/09 15:02:17 INFO mapreduce.Job:  map 0% reduce 0%
14/04/09 15:02:28 INFO mapreduce.Job:  map 25% reduce 0%
14/04/09 15:02:30 INFO mapreduce.Job:  map 50% reduce 0%
14/04/09 15:02:33 INFO mapreduce.Job:  map 100% reduce 0%
14/04/09 15:02:33 INFO mapreduce.Job: Job job_1396936838233_0003 completed successfully
14/04/09 15:02:33 INFO mapreduce.Job: Counters: 27
	File System Counters
		FILE: Number of bytes read=0
		FILE: Number of bytes written=362536
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=516
		HDFS: Number of bytes written=56
		HDFS: Number of read operations=16
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=8
	Job Counters 
		Launched map tasks=4
		Other local map tasks=4
		Total time spent by all maps in occupied slots (ms)=44481
		Total time spent by all reduces in occupied slots (ms)=0
	Map-Reduce Framework
		Map input records=4
		Map output records=4
		Input split bytes=516
		Spilled Records=0
		Failed Shuffles=0
		Merged Map outputs=0
		GC time elapsed (ms)=429
		CPU time spent (ms)=6650
		Physical memory (bytes) snapshot=587669504
		Virtual memory (bytes) snapshot=5219356672
		Total committed heap usage (bytes)=205848576
	File Input Format Counters 
		Bytes Read=0
	File Output Format Counters 
		Bytes Written=56
14/04/09 15:02:33 INFO mapreduce.ImportJobBase: Transferred 56 bytes in 25.2746 seconds (2.2157 bytes/sec)
14/04/09 15:02:33 INFO mapreduce.ImportJobBase: Retrieved 4 records.
验证导入的数据:
$ hdfs dfs -ls /user/micmiu/sqoop/demo_log
Found 5 items
-rw-r--r--   3 hadoop supergroup          0 2014-04-09 15:02 /user/micmiu/sqoop/demo_log/_SUCCESS
-rw-r--r--   3 hadoop supergroup         28 2014-04-09 15:02 /user/micmiu/sqoop/demo_log/part-m-00000
-rw-r--r--   3 hadoop supergroup          0 2014-04-09 15:02 /user/micmiu/sqoop/demo_log/part-m-00001
-rw-r--r--   3 hadoop supergroup          0 2014-04-09 15:02 /user/micmiu/sqoop/demo_log/part-m-00002
-rw-r--r--   3 hadoop supergroup         28 2014-04-09 15:02 /user/micmiu/sqoop/demo_log/part-m-00003
$ hdfs dfs -cat /user/micmiu/sqoop/demo_log/part-m-0000*
michael,edit
michael,delete
micmiu,create
micmiu,update
[四]、导入数据到Hive 比如把表demo_blog 数据导入到Hive中,增加参数 --hive-import?:
sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog  --warehouse-dir /user/sqoop --hive-import --create-hive-table
执行过程如下:
$ sqoop import --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog  --warehouse-dir /user/sqoop --hive-import --create-hive-table 
Warning: /usr/lib/hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
14/04/09 10:44:21 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
14/04/09 10:44:21 INFO tool.BaseSqoopTool: Using Hive-specific delimiters for output. You can override
14/04/09 10:44:21 INFO tool.BaseSqoopTool: delimiters with --fields-terminated-by, etc.
14/04/09 10:44:21 WARN tool.BaseSqoopTool: It seems that you've specified at least one of following:
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--hive-home
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--hive-overwrite
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--create-hive-table
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--hive-table
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--hive-partition-key
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--hive-partition-value
14/04/09 10:44:21 WARN tool.BaseSqoopTool: 	--map-column-hive
14/04/09 10:44:21 WARN tool.BaseSqoopTool: Without specifying parameter --hive-import. Please note that
14/04/09 10:44:21 WARN tool.BaseSqoopTool: those arguments will not be used in this session. Either
14/04/09 10:44:21 WARN tool.BaseSqoopTool: specify --hive-import to apply them correctly or remove them
14/04/09 10:44:21 WARN tool.BaseSqoopTool: from command line to remove this warning.
14/04/09 10:44:21 INFO tool.BaseSqoopTool: Please note that --hive-home, --hive-partition-key, 
14/04/09 10:44:21 INFO tool.BaseSqoopTool: 	 hive-partition-value and --map-column-hive options are 
14/04/09 10:44:21 INFO tool.BaseSqoopTool: 	 are also valid for HCatalog imports and exports
14/04/09 10:44:21 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
14/04/09 10:44:21 INFO tool.CodeGenTool: Beginning code generation
14/04/09 10:44:21 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 10:44:21 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 10:44:21 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/local/hadoop
Note: /tmp/sqoop-hadoop/compile/c071f02ecad006293202fd2c2fad0dce/demo_blog.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
14/04/09 10:44:22 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/c071f02ecad006293202fd2c2fad0dce/demo_blog.jar
14/04/09 10:44:22 WARN manager.MySQLManager: It looks like you are importing from mysql.
14/04/09 10:44:22 WARN manager.MySQLManager: This transfer can be faster! Use the --direct
14/04/09 10:44:22 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
14/04/09 10:44:22 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
14/04/09 10:44:22 INFO mapreduce.ImportJobBase: Beginning import of demo_blog
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/hbase-0.98.0-hadoop2/lib/slf4j-log4j12-1.6.4.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.slf4j.impl.Log4jLoggerFactory]
14/04/09 10:44:22 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
14/04/09 10:44:23 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
14/04/09 10:44:23 INFO client.RMProxy: Connecting to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 10:44:25 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(`id`), MAX(`id`) FROM `demo_blog`
14/04/09 10:44:25 INFO mapreduce.JobSubmitter: number of splits:3
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.job.classpath.files is deprecated. Instead, use mapreduce.job.classpath.files
14/04/09 10:44:25 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.cache.files.filesizes is deprecated. Instead, use mapreduce.job.cache.files.filesizes
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.cache.files is deprecated. Instead, use mapreduce.job.cache.files
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
14/04/09 10:44:25 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
14/04/09 10:44:25 INFO Configuration.deprecation: mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
14/04/09 10:44:25 INFO Configuration.deprecation: mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.cache.files.timestamps is deprecated. Instead, use mapreduce.job.cache.files.timestamps
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
14/04/09 10:44:25 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
14/04/09 10:44:25 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1396936838233_0002
14/04/09 10:44:25 INFO impl.YarnClientImpl: Submitted application application_1396936838233_0002 to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 10:44:25 INFO mapreduce.Job: The url to track the job: http://Master.Hadoop:8088/proxy/application_1396936838233_0002/
14/04/09 10:44:25 INFO mapreduce.Job: Running job: job_1396936838233_0002
14/04/09 10:44:33 INFO mapreduce.Job: Job job_1396936838233_0002 running in uber mode : false
14/04/09 10:44:33 INFO mapreduce.Job:  map 0% reduce 0%
14/04/09 10:44:46 INFO mapreduce.Job:  map 67% reduce 0%
14/04/09 10:44:48 INFO mapreduce.Job:  map 100% reduce 0%
14/04/09 10:44:49 INFO mapreduce.Job: Job job_1396936838233_0002 completed successfully
14/04/09 10:44:49 INFO mapreduce.Job: Counters: 27
	File System Counters
		FILE: Number of bytes read=0
		FILE: Number of bytes written=271860
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=295
		HDFS: Number of bytes written=44
		HDFS: Number of read operations=12
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=6
	Job Counters 
		Launched map tasks=3
		Other local map tasks=3
		Total time spent by all maps in occupied slots (ms)=34047
		Total time spent by all reduces in occupied slots (ms)=0
	Map-Reduce Framework
		Map input records=3
		Map output records=3
		Input split bytes=295
		Spilled Records=0
		Failed Shuffles=0
		Merged Map outputs=0
		GC time elapsed (ms)=505
		CPU time spent (ms)=5350
		Physical memory (bytes) snapshot=427388928
		Virtual memory (bytes) snapshot=3881439232
		Total committed heap usage (bytes)=171638784
	File Input Format Counters 
		Bytes Read=0
	File Output Format Counters 
		Bytes Written=44
14/04/09 10:44:49 INFO mapreduce.ImportJobBase: Transferred 44 bytes in 26.0401 seconds (1.6897 bytes/sec)
14/04/09 10:44:49 INFO mapreduce.ImportJobBase: Retrieved 3 records.
14/04/09 10:44:49 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 10:44:49 INFO hive.HiveImport: Loading uploaded data into Hive
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.min.split.size is deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.reduce.tasks.speculative.execution is deprecated. Instead, use mapreduce.reduce.speculative
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.min.split.size.per.node is deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize.per.node
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.input.dir.recursive is deprecated. Instead, use mapreduce.input.fileinputformat.input.dir.recursive
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.min.split.size.per.rack is deprecated. Instead, use mapreduce.input.fileinputformat.split.minsize.per.rack
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.max.split.size is deprecated. Instead, use mapreduce.input.fileinputformat.split.maxsize
14/04/09 10:44:52 INFO hive.HiveImport: 14/04/09 10:44:52 INFO Configuration.deprecation: mapred.committer.job.setup.cleanup.needed is deprecated. Instead, use mapreduce.job.committer.setup.cleanup.needed
14/04/09 10:44:53 INFO hive.HiveImport: 14/04/09 10:44:53 WARN conf.HiveConf: DEPRECATED: hive.metastore.ds.retry.* no longer has any effect.  Use hive.hmshandler.retry.* instead
14/04/09 10:44:53 INFO hive.HiveImport: 
14/04/09 10:44:53 INFO hive.HiveImport: Logging initialized using configuration in file:/usr/local/hive-0.13.0-bin/conf/hive-log4j.properties
14/04/09 10:44:53 INFO hive.HiveImport: SLF4J: Class path contains multiple SLF4J bindings.
14/04/09 10:44:53 INFO hive.HiveImport: SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
14/04/09 10:44:53 INFO hive.HiveImport: SLF4J: Found binding in [jar:file:/usr/local/hbase-0.98.0-hadoop2/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
14/04/09 10:44:53 INFO hive.HiveImport: SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
14/04/09 10:44:53 INFO hive.HiveImport: SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
14/04/09 10:44:57 INFO hive.HiveImport: OK
14/04/09 10:44:57 INFO hive.HiveImport: Time taken: 0.773 seconds
14/04/09 10:44:57 INFO hive.HiveImport: Loading data to table default.demo_blog
14/04/09 10:44:57 INFO hive.HiveImport: Table default.demo_blog stats: [numFiles=4, numRows=0, totalSize=44, rawDataSize=0]
14/04/09 10:44:57 INFO hive.HiveImport: OK
14/04/09 10:44:57 INFO hive.HiveImport: Time taken: 0.25 seconds
14/04/09 10:44:57 INFO hive.HiveImport: Hive import complete.
14/04/09 10:44:57 INFO hive.HiveImport: Export directory is empty, removing it
Hive CLI中验证导入的数据:
hive> show tables;
OK
demo_blog
hbase_table_1
hbase_table_2
hbase_table_3
micmiu_blog
micmiu_hx_master
pokes
xflow_dstip
Time taken: 0.073 seconds, Fetched: 8 row(s)
hive> select * from demo_blog;
OK
1	micmiu.com
2	ctosun.com
3	baby.micmiu.com
Time taken: 0.506 seconds, Fetched: 3 row(s)
[五]、导入数据到HBase 演示把表 demo_blog 数据导入到HBase ,指定Hbase中表名为 demo_sqoop2hbase 的命令:
sqoop  import  --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog --hbase-table demo_sqoop2hbase --hbase-create-table --hbase-row-key id --column-family url
执行过程:
$ sqoop  import  --connect jdbc:mysql://192.168.6.77/test --username root --password micmiu --table demo_blog --hbase-table demo_sqoop2hbase --hbase-create-table --hbase-row-key id --column-family url
Warning: /usr/lib/hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
14/04/09 16:23:38 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
14/04/09 16:23:38 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
14/04/09 16:23:38 INFO tool.CodeGenTool: Beginning code generation
14/04/09 16:23:39 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 16:23:39 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `demo_blog` AS t LIMIT 1
14/04/09 16:23:39 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/local/hadoop
Note: /tmp/sqoop-hadoop/compile/85408c854ee8fba75bbb2458e5e25093/demo_blog.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
14/04/09 16:23:40 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/85408c854ee8fba75bbb2458e5e25093/demo_blog.jar
14/04/09 16:23:40 WARN manager.MySQLManager: It looks like you are importing from mysql.
14/04/09 16:23:40 WARN manager.MySQLManager: This transfer can be faster! Use the --direct
14/04/09 16:23:40 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
14/04/09 16:23:40 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
14/04/09 16:23:40 INFO mapreduce.ImportJobBase: Beginning import of demo_blog
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/local/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/local/hbase-0.98.0-hadoop2/lib/slf4j-log4j12-1.6.4.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.slf4j.impl.Log4jLoggerFactory]
14/04/09 16:23:40 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
14/04/09 16:23:40 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:zookeeper.version=3.4.5-1392090, built on 09/30/2012 17:52 GMT
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:host.name=Master.Hadoop
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.version=1.6.0_20
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.vendor=Sun Microsystems Inc.
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.home=/java/jdk1.6.0_20/jre
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.class.path=/usr/local/hadoop/etc/hadoop: .......
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.library.path=/usr/local/hadoop/lib/native
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.io.tmpdir=/tmp
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:java.compiler=
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:os.name=Linux
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:os.arch=amd64
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:os.version=2.6.32-71.el6.x86_64
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:user.name=hadoop
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:user.home=/home/hadoop
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Client environment:user.dir=/home/hadoop
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181 sessionTimeout=90000 watcher=hconnection-0x57c8b24d, quorum=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181, baseZNode=/hbase
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Opening socket connection to server Slave5.Hadoop/192.168.8.205:2181. Will not attempt to authenticate using SASL (Unable to locate a login configuration)
14/04/09 16:23:41 INFO zookeeper.RecoverableZooKeeper: Process identifier=hconnection-0x57c8b24d connecting to ZooKeeper ensemble=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Socket connection established to Slave5.Hadoop/192.168.8.205:2181, initiating session
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Session establishment complete on server Slave5.Hadoop/192.168.8.205:2181, sessionid = 0x453fecb6c50009, negotiated timeout = 90000
14/04/09 16:23:41 INFO Configuration.deprecation: hadoop.native.lib is deprecated. Instead, use io.native.lib.available
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181 sessionTimeout=90000 watcher=catalogtracker-on-hconnection-0x57c8b24d, quorum=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181, baseZNode=/hbase
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Opening socket connection to server Slave7.Hadoop/192.168.8.207:2181. Will not attempt to authenticate using SASL (Unable to locate a login configuration)
14/04/09 16:23:41 INFO zookeeper.RecoverableZooKeeper: Process identifier=catalogtracker-on-hconnection-0x57c8b24d connecting to ZooKeeper ensemble=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Socket connection established to Slave7.Hadoop/192.168.8.207:2181, initiating session
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: Session establishment complete on server Slave7.Hadoop/192.168.8.207:2181, sessionid = 0x2453fecb6f50008, negotiated timeout = 90000
14/04/09 16:23:41 INFO zookeeper.ZooKeeper: Session: 0x2453fecb6f50008 closed
14/04/09 16:23:41 INFO zookeeper.ClientCnxn: EventThread shut down
14/04/09 16:23:41 INFO mapreduce.HBaseImportJob: Creating missing HBase table demo_sqoop2hbase
14/04/09 16:23:42 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181 sessionTimeout=90000 watcher=catalogtracker-on-hconnection-0x57c8b24d, quorum=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181, baseZNode=/hbase
14/04/09 16:23:42 INFO zookeeper.RecoverableZooKeeper: Process identifier=catalogtracker-on-hconnection-0x57c8b24d connecting to ZooKeeper ensemble=Slave6.Hadoop:2181,Slave5.Hadoop:2181,Slave7.Hadoop:2181
14/04/09 16:23:42 INFO zookeeper.ClientCnxn: Opening socket connection to server Slave7.Hadoop/192.168.8.207:2181. Will not attempt to authenticate using SASL (Unable to locate a login configuration)
14/04/09 16:23:42 INFO zookeeper.ClientCnxn: Socket connection established to Slave7.Hadoop/192.168.8.207:2181, initiating session
14/04/09 16:23:42 INFO zookeeper.ClientCnxn: Session establishment complete on server Slave7.Hadoop/192.168.8.207:2181, sessionid = 0x2453fecb6f50009, negotiated timeout = 90000
14/04/09 16:23:42 INFO zookeeper.ZooKeeper: Session: 0x2453fecb6f50009 closed
14/04/09 16:23:42 INFO zookeeper.ClientCnxn: EventThread shut down
14/04/09 16:23:42 INFO client.RMProxy: Connecting to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 16:23:47 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(`id`), MAX(`id`) FROM `demo_blog`
14/04/09 16:23:47 INFO mapreduce.JobSubmitter: number of splits:3
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.job.classpath.files is deprecated. Instead, use mapreduce.job.classpath.files
14/04/09 16:23:47 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.cache.files.filesizes is deprecated. Instead, use mapreduce.job.cache.files.filesizes
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.cache.files is deprecated. Instead, use mapreduce.job.cache.files
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.reduce.tasks is deprecated. Instead, use mapreduce.job.reduces
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
14/04/09 16:23:47 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
14/04/09 16:23:47 INFO Configuration.deprecation: mapreduce.inputformat.class is deprecated. Instead, use mapreduce.job.inputformat.class
14/04/09 16:23:47 INFO Configuration.deprecation: mapreduce.outputformat.class is deprecated. Instead, use mapreduce.job.outputformat.class
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.cache.files.timestamps is deprecated. Instead, use mapreduce.job.cache.files.timestamps
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
14/04/09 16:23:47 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
14/04/09 16:23:47 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1396936838233_0005
14/04/09 16:23:47 INFO impl.YarnClientImpl: Submitted application application_1396936838233_0005 to ResourceManager at Master.Hadoop/192.168.6.77:8032
14/04/09 16:23:47 INFO mapreduce.Job: The url to track the job: http://Master.Hadoop:8088/proxy/application_1396936838233_0005/
14/04/09 16:23:47 INFO mapreduce.Job: Running job: job_1396936838233_0005
14/04/09 16:23:55 INFO mapreduce.Job: Job job_1396936838233_0005 running in uber mode : false
14/04/09 16:23:55 INFO mapreduce.Job:  map 0% reduce 0%
14/04/09 16:24:05 INFO mapreduce.Job:  map 33% reduce 0%
14/04/09 16:24:12 INFO mapreduce.Job:  map 100% reduce 0%
14/04/09 16:24:12 INFO mapreduce.Job: Job job_1396936838233_0005 completed successfully
14/04/09 16:24:12 INFO mapreduce.Job: Counters: 27
	File System Counters
		FILE: Number of bytes read=0
		FILE: Number of bytes written=354636
		FILE: Number of read operations=0
		FILE: Number of large read operations=0
		FILE: Number of write operations=0
		HDFS: Number of bytes read=295
		HDFS: Number of bytes written=0
		HDFS: Number of read operations=3
		HDFS: Number of large read operations=0
		HDFS: Number of write operations=0
	Job Counters 
		Launched map tasks=3
		Other local map tasks=3
		Total time spent by all maps in occupied slots (ms)=35297
		Total time spent by all reduces in occupied slots (ms)=0
	Map-Reduce Framework
		Map input records=3
		Map output records=3
		Input split bytes=295
		Spilled Records=0
		Failed Shuffles=0
		Merged Map outputs=0
		GC time elapsed (ms)=381
		CPU time spent (ms)=11050
		Physical memory (bytes) snapshot=543367168
		Virtual memory (bytes) snapshot=3918925824
		Total committed heap usage (bytes)=156958720
	File Input Format Counters 
		Bytes Read=0
	File Output Format Counters 
		Bytes Written=0
14/04/09 16:24:12 INFO mapreduce.ImportJobBase: Transferred 0 bytes in 29.7126 seconds (0 bytes/sec)
14/04/09 16:24:12 INFO mapreduce.ImportJobBase: Retrieved 3 records.
hbase shell中验证导入的数据:
hbase(main):009:0> list
TABLE                                                                                                       
demo_sqoop2hbase                                                                                            
table_02                                                                                                    
table_03                                                                                                    
test_table                                                                                                  
xyz                                                                                                         
5 row(s) in 0.0310 seconds
=> ["demo_sqoop2hbase", "table_02", "table_03", "test_table", "xyz"]
hbase(main):010:0> scan "demo_sqoop2hbase"
ROW                          COLUMN+CELL                                                                    
 1                           column=url:blog, timestamp=1397031850700, value=micmiu.com                     
 2                           column=url:blog, timestamp=1397031844106, value=ctosun.com                     
 3                           column=url:blog, timestamp=1397031849888, value=baby.micmiu.com                
3 row(s) in 0.0730 seconds
hbase(main):011:0> describe "demo_sqoop2hbase"
DESCRIPTION                                                            ENABLED                              
 'demo_sqoop2hbase', {NAME => 'url', DATA_BLOCK_ENCODING => 'NONE', BL true                                 
 OOMFILTER => 'ROW', REPLICATION_SCOPE => '0', VERSIONS => '1', COMPRE                                      
 SSION => 'NONE', MIN_VERSIONS => '0', TTL => '2147483647', KEEP_DELET                                      
 ED_CELLS => 'false', BLOCKSIZE => '65536', IN_MEMORY => 'false', BLOC                                      
 KCACHE => 'true'}                                                                                          
1 row(s) in 0.0580 seconds
hbase(main):012:0>
验证导入成功。 本文到此已经把MySQL中的数据迁移到 HDFS、Hive、HBase的三种基本情况演示结束。 参考:
  • http://sqoop.apache.org/docs/1.4.4/SqoopUserGuide.html
—————– ?EOF?@Michael Sun?—————–
Stellungnahme
Der Inhalt dieses Artikels wird freiwillig von Internetnutzern beigesteuert und das Urheberrecht liegt beim ursprünglichen Autor. Diese Website übernimmt keine entsprechende rechtliche Verantwortung. Wenn Sie Inhalte finden, bei denen der Verdacht eines Plagiats oder einer Rechtsverletzung besteht, wenden Sie sich bitte an admin@php.cn
Mysqls Platz: Datenbanken und ProgrammierungMysqls Platz: Datenbanken und ProgrammierungApr 13, 2025 am 12:18 AM

Die Position von MySQL in Datenbanken und Programmierung ist sehr wichtig. Es handelt sich um ein Open -Source -Verwaltungssystem für relationale Datenbankverwaltung, das in verschiedenen Anwendungsszenarien häufig verwendet wird. 1) MySQL bietet effiziente Datenspeicher-, Organisations- und Abruffunktionen und unterstützt Systeme für Web-, Mobil- und Unternehmensebene. 2) Es verwendet eine Client-Server-Architektur, unterstützt mehrere Speichermotoren und Indexoptimierung. 3) Zu den grundlegenden Verwendungen gehören das Erstellen von Tabellen und das Einfügen von Daten, und erweiterte Verwendungen beinhalten Multi-Table-Verknüpfungen und komplexe Abfragen. 4) Häufig gestellte Fragen wie SQL -Syntaxfehler und Leistungsprobleme können durch den Befehl erklären und langsam abfragen. 5) Die Leistungsoptimierungsmethoden umfassen die rationale Verwendung von Indizes, eine optimierte Abfrage und die Verwendung von Caches. Zu den Best Practices gehört die Verwendung von Transaktionen und vorbereiteten Staten

MySQL: Von kleinen Unternehmen bis zu großen UnternehmenMySQL: Von kleinen Unternehmen bis zu großen UnternehmenApr 13, 2025 am 12:17 AM

MySQL ist für kleine und große Unternehmen geeignet. 1) Kleinunternehmen können MySQL für das grundlegende Datenmanagement verwenden, z. B. das Speichern von Kundeninformationen. 2) Große Unternehmen können MySQL verwenden, um massive Daten und komplexe Geschäftslogik zu verarbeiten, um die Abfrageleistung und die Transaktionsverarbeitung zu optimieren.

Was liest Phantom und wie verhindert InnoDB sie (Sperren des nächsten Schlägers)?Was liest Phantom und wie verhindert InnoDB sie (Sperren des nächsten Schlägers)?Apr 13, 2025 am 12:16 AM

InnoDB verhindert effektiv das Phantom-Lesen durch den Mechanismus für den nächsten Kleien. 1) Nächstschlüsselmesser kombiniert Zeilensperr- und Gap-Sperre, um Datensätze und deren Lücken zu sperren, um zu verhindern, dass neue Datensätze eingefügt werden. 2) In praktischen Anwendungen kann durch Optimierung der Abfragen und Anpassung der Isolationsstufen die Verringerungswettbewerb reduziert und die Gleichzeitleistung verbessert werden.

MySQL: Keine Programmiersprache, sondern ...MySQL: Keine Programmiersprache, sondern ...Apr 13, 2025 am 12:03 AM

MySQL ist keine Programmiersprache, aber seine Abfragesprache SQL hat die Eigenschaften einer Programmiersprache: 1. SQL unterstützt bedingte Beurteilung, Schleifen und variable Operationen; 2. Durch gespeicherte Prozeduren, Auslöser und Funktionen können Benutzer komplexe logische Operationen in der Datenbank ausführen.

MySQL: Eine Einführung in die beliebteste Datenbank der WeltMySQL: Eine Einführung in die beliebteste Datenbank der WeltApr 12, 2025 am 12:18 AM

MySQL ist ein Open Source Relational Database Management -System, das hauptsächlich zum schnellen und zuverlässigen Speicher und Abrufen von Daten verwendet wird. Sein Arbeitsprinzip umfasst Kundenanfragen, Abfragebedingungen, Ausführung von Abfragen und Rückgabergebnissen. Beispiele für die Nutzung sind das Erstellen von Tabellen, das Einsetzen und Abfragen von Daten sowie erweiterte Funktionen wie Join -Operationen. Häufige Fehler umfassen SQL -Syntax, Datentypen und Berechtigungen sowie Optimierungsvorschläge umfassen die Verwendung von Indizes, optimierte Abfragen und die Partitionierung von Tabellen.

Die Bedeutung von MySQL: Datenspeicherung und -verwaltungDie Bedeutung von MySQL: Datenspeicherung und -verwaltungApr 12, 2025 am 12:18 AM

MySQL ist ein Open Source Relational Database Management -System, das für Datenspeicher, Verwaltung, Abfrage und Sicherheit geeignet ist. 1. Es unterstützt eine Vielzahl von Betriebssystemen und wird in Webanwendungen und anderen Feldern häufig verwendet. 2. Durch die Client-Server-Architektur und verschiedene Speichermotoren verarbeitet MySQL Daten effizient. 3. Die grundlegende Verwendung umfasst das Erstellen von Datenbanken und Tabellen, das Einfügen, Abfragen und Aktualisieren von Daten. 4. Fortgeschrittene Verwendung beinhaltet komplexe Abfragen und gespeicherte Verfahren. 5. Häufige Fehler können durch die Erklärungserklärung debuggen. 6. Die Leistungsoptimierung umfasst die rationale Verwendung von Indizes und optimierte Abfrageanweisungen.

Warum MySQL verwenden? Vorteile und VorteileWarum MySQL verwenden? Vorteile und VorteileApr 12, 2025 am 12:17 AM

MySQL wird für seine Leistung, Zuverlässigkeit, Benutzerfreundlichkeit und Unterstützung der Gemeinschaft ausgewählt. 1.MYSQL bietet effiziente Datenspeicher- und Abruffunktionen, die mehrere Datentypen und erweiterte Abfragevorgänge unterstützen. 2. Übernehmen Sie die Architektur der Client-Server und mehrere Speichermotoren, um die Transaktion und die Abfrageoptimierung zu unterstützen. 3. Einfach zu bedienend unterstützt eine Vielzahl von Betriebssystemen und Programmiersprachen. V.

Beschreiben Sie InnoDB-Verriegelungsmechanismen (gemeinsame Schlösser, exklusive Schlösser, Absichtssperrungen, Aufzeichnungsschlösser, Lückensperrungen, Sperren der nächsten Schlüsse).Beschreiben Sie InnoDB-Verriegelungsmechanismen (gemeinsame Schlösser, exklusive Schlösser, Absichtssperrungen, Aufzeichnungsschlösser, Lückensperrungen, Sperren der nächsten Schlüsse).Apr 12, 2025 am 12:16 AM

Zu den Verriegelungsmechanismen von InnoDB gehören gemeinsame Schlösser, exklusive Schlösser, Absichtsschlösser, Aufzeichnungsschlösser, Lückensperrungen und nächste Schlüsselschlösser. 1. Shared Lock ermöglicht es Transaktionen, Daten zu lesen, ohne dass andere Transaktionen lesen. 2. Exklusives Schloss verhindert, dass andere Transaktionen Daten lesen und ändern. 3.. Intention Lock optimiert die Sperreffizienz. 4. Rekord -Sperr -Indexdatensatz. 5. Gap Lock Locks Index -Aufzeichnungslücke. 6. Die nächste Schlüsselsperrung ist eine Kombination aus Datensatzsperr- und Lückensperrung, um die Datenkonsistenz zu gewährleisten.

See all articles

Heiße KI -Werkzeuge

Undresser.AI Undress

Undresser.AI Undress

KI-gestützte App zum Erstellen realistischer Aktfotos

AI Clothes Remover

AI Clothes Remover

Online-KI-Tool zum Entfernen von Kleidung aus Fotos.

Undress AI Tool

Undress AI Tool

Ausziehbilder kostenlos

Clothoff.io

Clothoff.io

KI-Kleiderentferner

AI Hentai Generator

AI Hentai Generator

Erstellen Sie kostenlos Ai Hentai.

Heißer Artikel

R.E.P.O. Energiekristalle erklärten und was sie tun (gelber Kristall)
3 Wochen vorBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Beste grafische Einstellungen
3 Wochen vorBy尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. So reparieren Sie Audio, wenn Sie niemanden hören können
3 Wochen vorBy尊渡假赌尊渡假赌尊渡假赌
WWE 2K25: Wie man alles in Myrise freischaltet
4 Wochen vorBy尊渡假赌尊渡假赌尊渡假赌

Heiße Werkzeuge

MantisBT

MantisBT

Mantis ist ein einfach zu implementierendes webbasiertes Tool zur Fehlerverfolgung, das die Fehlerverfolgung von Produkten unterstützen soll. Es erfordert PHP, MySQL und einen Webserver. Schauen Sie sich unsere Demo- und Hosting-Services an.

MinGW – Minimalistisches GNU für Windows

MinGW – Minimalistisches GNU für Windows

Dieses Projekt wird derzeit auf osdn.net/projects/mingw migriert. Sie können uns dort weiterhin folgen. MinGW: Eine native Windows-Portierung der GNU Compiler Collection (GCC), frei verteilbare Importbibliotheken und Header-Dateien zum Erstellen nativer Windows-Anwendungen, einschließlich Erweiterungen der MSVC-Laufzeit zur Unterstützung der C99-Funktionalität. Die gesamte MinGW-Software kann auf 64-Bit-Windows-Plattformen ausgeführt werden.

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Leistungsstarke integrierte PHP-Entwicklungsumgebung

EditPlus chinesische Crack-Version

EditPlus chinesische Crack-Version

Geringe Größe, Syntaxhervorhebung, unterstützt keine Code-Eingabeaufforderungsfunktion

Senden Sie Studio 13.0.1

Senden Sie Studio 13.0.1

Leistungsstarke integrierte PHP-Entwicklungsumgebung