sqoop导入查询给出重复的名称错误

时间：2017-11-19 07:43:09

标签： mysql join sqoop

我在mysql中有三个名为movie，moviegenre，genre的表。当我尝试使用sqoop自由格式查询将它们导入hdfs时：

sqoop import --connect jdbc:mysql://localhost/movielens --username user --password *** 
--query 'select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name 
from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid 
WHERE $CONDITIONS' --split-by m.id --target-dir /user/sqoop/moviegenre

它抛出错误：

  

导入失败：指定了重复的列标识符：＆＃39; name＆＃39;。

当我在mysql中编写相同的查询时，它给出了输出，这就是我想要的：

id       movie_name         year   genre_name
 1       Toy Story          1995   Animation 
 2       Jumanji            1995   Adventure
 ..      .......            ....   ........

我按照这个链接完成答案：enter image description here但这似乎没有帮助。

表格中的字段如下： movie = id，name，year

genre = id，name

moviegenre = movieid，genreid

请在我的查询中指出错误。

1 个答案:

答案 0 :(得分：0)

SQOOP命令中没有任何错误。我刚刚在我的cloudera快速启动VM中创建了表并运行了SQOOP导入。它运作良好并产生了结果。在添加别名之前，您可能已经运行了该命令。另一个区别是我已经格式化了命令。

如果你需要它，下面是我跑的

MySQL命令 

mysql> use retail_db;
mysql> create table movie (id integer, name varchar(100), year integer);
mysql> insert into movie values (1, 'TEST', 2016);
mysql> create table genre (id integer, name varchar(100));
mysql> insert into genre values (1, 'TEST');
mysql> create table moviegenre (movieid integer, genreid integer);
mysql> insert into moviegenre values (1, 1);

SQOOP Command 

sqoop import \
--connect jdbc:mysql://localhost/retail_db \
--username root \
--password cloudera \
--query 'select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE $CONDITIONS' --split-by m.id --target-dir /user/cloudera/moviegenre

SQOOP标准输出 

[cloudera@quickstart ~]$ sqoop import \
> --connect jdbc:mysql://localhost/retail_db \
> --username root \
> --password cloudera \
> --query 'select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE $CONDITIONS' --split-by m.id --target-dir /user/cloudera/moviegenre
Warning: /usr/lib/sqoop/../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
17/11/19 13:08:01 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6-cdh5.10.0
17/11/19 13:08:01 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
17/11/19 13:08:01 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
17/11/19 13:08:01 INFO tool.CodeGenTool: Beginning code generation
17/11/19 13:08:02 INFO manager.SqlManager: Executing SQL statement: select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE  (1 = 0) 
17/11/19 13:08:02 INFO manager.SqlManager: Executing SQL statement: select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE  (1 = 0) 
17/11/19 13:08:02 INFO manager.SqlManager: Executing SQL statement: select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE  (1 = 0) 
17/11/19 13:08:02 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/lib/hadoop-mapreduce
Note: /tmp/sqoop-cloudera/compile/3b35f51458e53da94c6852dcfc0b904a/QueryResult.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
17/11/19 13:08:04 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-cloudera/compile/3b35f51458e53da94c6852dcfc0b904a/QueryResult.jar
17/11/19 13:08:04 INFO mapreduce.ImportJobBase: Beginning query import.
17/11/19 13:08:04 INFO Configuration.deprecation: mapred.job.tracker is deprecated. Instead, use mapreduce.jobtracker.address
17/11/19 13:08:04 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
17/11/19 13:08:05 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
17/11/19 13:08:05 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
17/11/19 13:08:08 WARN hdfs.DFSClient: Caught exception 
java.lang.InterruptedException
    at java.lang.Object.wait(Native Method)
    at java.lang.Thread.join(Thread.java:1281)
    at java.lang.Thread.join(Thread.java:1355)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.closeResponder(DFSOutputStream.java:951)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.endBlock(DFSOutputStream.java:689)
    at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:878)
17/11/19 13:08:08 INFO db.DBInputFormat: Using read commited transaction isolation
17/11/19 13:08:08 INFO db.DataDrivenDBInputFormat: BoundingValsQuery: SELECT MIN(t1.id), MAX(t1.id) FROM (select m.id as id,m.name as movie_name,m.year as year, g.name as genre_name from movie m join moviegenre mg on m.id = mg.movieid join genre g on g.id = mg.genreid WHERE  (1 = 1) ) AS t1
17/11/19 13:08:08 INFO db.IntegerSplitter: Split size: 0; Num splits: 4 from: 1 to: 1
17/11/19 13:08:08 INFO mapreduce.JobSubmitter: number of splits:1
17/11/19 13:08:08 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1510865312807_0011
17/11/19 13:08:09 INFO impl.YarnClientImpl: Submitted application application_1510865312807_0011
17/11/19 13:08:09 INFO mapreduce.Job: The url to track the job: http://quickstart.cloudera:8088/proxy/application_1510865312807_0011/
17/11/19 13:08:09 INFO mapreduce.Job: Running job: job_1510865312807_0011
17/11/19 13:08:33 INFO mapreduce.Job: Job job_1510865312807_0011 running in uber mode : false
17/11/19 13:08:33 INFO mapreduce.Job:  map 0% reduce 0%
17/11/19 13:08:52 INFO mapreduce.Job:  map 100% reduce 0%
17/11/19 13:08:52 INFO mapreduce.Job: Job job_1510865312807_0011 completed successfully
17/11/19 13:08:52 INFO mapreduce.Job: Counters: 30
    File System Counters
        FILE: Number of bytes read=0
        FILE: Number of bytes written=148008
        FILE: Number of read operations=0
        FILE: Number of large read operations=0
        FILE: Number of write operations=0
        HDFS: Number of bytes read=99
        HDFS: Number of bytes written=17
        HDFS: Number of read operations=4
        HDFS: Number of large read operations=0
        HDFS: Number of write operations=2
    Job Counters 
        Launched map tasks=1
        Other local map tasks=1
        Total time spent by all maps in occupied slots (ms)=16886
        Total time spent by all reduces in occupied slots (ms)=0
        Total time spent by all map tasks (ms)=16886
        Total vcore-seconds taken by all map tasks=16886
        Total megabyte-seconds taken by all map tasks=17291264
    Map-Reduce Framework
        Map input records=1
        Map output records=1
        Input split bytes=99
        Spilled Records=0
        Failed Shuffles=0
        Merged Map outputs=0
        GC time elapsed (ms)=702
        CPU time spent (ms)=2330
        Physical memory (bytes) snapshot=231743488
        Virtual memory (bytes) snapshot=1567064064
        Total committed heap usage (bytes)=221249536
    File Input Format Counters 
        Bytes Read=0
    File Output Format Counters 
        Bytes Written=17
17/11/19 13:08:52 INFO mapreduce.ImportJobBase: Transferred 17 bytes in 46.7631 seconds (0.3635 bytes/sec)
17/11/19 13:08:52 INFO mapreduce.ImportJobBase: Retrieved 1 records.
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