使用 sqoop 将mysql数据导入到hdfs（import）

Sqoop 将mysql 数据导入到hdfs(import)

1.创建mysql表

CREATE TABLE `sqoop_test` (
`id` int() DEFAULT NULL,
`name` varchar() DEFAULT NULL,
`age` int() DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=latin1

插入数据

2.hive 建表

hive> create external table sqoop_test(id int,name string,age int)
> ROW FORMAT DELIMITED
> FIELDS TERMINATED BY ','
> STORED AS TEXTFILE
> location '/user/hive/external/sqoop_test';
OK
Time taken: 0.145 seconds

3.使用sqoop将mysql数据导入到hdfs

sqoop import --connect jdbc:mysql://localhost:3306/sqooptest --username root --password 123qwe --table sqoop_test --columns id,name,age --fields-terminated-by , --delete-target-dir --target-dir /user/hive/external/sqoop_test/ -m 1

--delete-target-dir:如果目标目录存在则删除。

EFdeMacBook-Pro:bin FengZhen$ sqoop import --connect jdbc:mysql://localhost:3306/sqooptest --username root --password 123qwe --table sqoop_test --columns id,name,age --fields-terminated-by , --delete-target-dir --target-dir /user/hive/external/sqoop_test/ -m 1
Warning: /Users/FengZhen/Desktop/Hadoop/sqoop-1.4..bin__hadoop-2.0.-alpha/../hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
Warning: /Users/FengZhen/Desktop/Hadoop/sqoop-1.4..bin__hadoop-2.0.-alpha/../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/Users/FengZhen/Desktop/Hadoop/hadoop-2.8./share/hadoop/common/lib/slf4j-log4j12-1.7..jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/Users/FengZhen/Desktop/Hadoop/hbase-1.3./lib/slf4j-log4j12-1.7..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]
// :: INFO sqoop.Sqoop: Running Sqoop version: 1.4.
// :: WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
// :: INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
// :: INFO tool.CodeGenTool: Beginning code generation
// :: INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `sqoop_test` AS t LIMIT
// :: INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `sqoop_test` AS t LIMIT
// :: INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /Users/FengZhen/Desktop/Hadoop/hadoop-2.8.
// :: INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-FengZhen/compile/1a0c4154ffefb21d4af720813dd0b3fc/sqoop_test.jar
// :: WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
// :: INFO tool.ImportTool: Destination directory /user/hive/external/sqoop_test deleted.
// :: WARN manager.MySQLManager: It looks like you are importing from mysql.
// :: WARN manager.MySQLManager: This transfer can be faster! Use the --direct
// :: WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.
// :: INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)
// :: INFO mapreduce.ImportJobBase: Beginning import of sqoop_test
// :: INFO Configuration.deprecation: mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address
// :: INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
// :: INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
// :: INFO client.RMProxy: Connecting to ResourceManager at localhost/127.0.0.1:
// :: INFO db.DBInputFormat: Using read commited transaction isolation
// :: INFO mapreduce.JobSubmitter: number of splits:
// :: INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1505268150495_0008
// :: INFO impl.YarnClientImpl: Submitted application application_1505268150495_0008
// :: INFO mapreduce.Job: The url to track the job: http://192.168.1.64:8088/proxy/application_1505268150495_0008/
// :: INFO mapreduce.Job: Running job: job_1505268150495_0008
// :: INFO mapreduce.Job: Job job_1505268150495_0008 running in uber mode : false
// :: INFO mapreduce.Job: map % reduce %
// :: INFO mapreduce.Job: map % reduce %
// :: INFO mapreduce.Job: Job job_1505268150495_0008 completed successfully
// :: INFO mapreduce.Job: Counters:
File System Counters
FILE: Number of bytes read=
FILE: Number of bytes written=
FILE: Number of read operations=
FILE: Number of large read operations=
FILE: Number of write operations=
HDFS: Number of bytes read=
HDFS: Number of bytes written=
HDFS: Number of read operations=
HDFS: Number of large read operations=
HDFS: Number of write operations=
Job Counters
Launched map tasks=
Other local map tasks=
Total time spent by all maps in occupied slots (ms)=
Total time spent by all reduces in occupied slots (ms)=
Total time spent by all map tasks (ms)=
Total vcore-milliseconds taken by all map tasks=
Total megabyte-milliseconds taken by all map tasks=
Map-Reduce Framework
Map input records=
Map output records=
Input split bytes=
Spilled Records=
Failed Shuffles=
Merged Map outputs=
GC time elapsed (ms)=
CPU time spent (ms)=
Physical memory (bytes) snapshot=
Virtual memory (bytes) snapshot=
Total committed heap usage (bytes)=
File Input Format Counters
Bytes Read=
File Output Format Counters
Bytes Written=
// :: INFO mapreduce.ImportJobBase: Transferred  bytes in 18.6372 seconds (1.3951 bytes/sec)
// :: INFO mapreduce.ImportJobBase: Retrieved  records.

可在hdfs看到传入的数据

EFdeMacBook-Pro:jarfile FengZhen$ hadoop fs -ls /user/hive/external/sqoop_test
Found  items
-rw-r--r--    FengZhen supergroup           -- : /user/hive/external/sqoop_test/_SUCCESS
-rw-r--r--    FengZhen supergroup          -- : /user/hive/external/sqoop_test/part-m-

可在hive中查看数据。

hive> select * from sqoop_test;
OK
    fz
    dx
    test
Time taken: 1.756 seconds, Fetched:  row(s)

使用sqoop将hive数据导出到mysql(export)