这是sqoop命令，我正在使用它将数据从sqlserver导入配置单元 sqoop-import-all-tables --connect "jdbc:sqlserver://ip.ip.ip.ip\MIGERATIONSERVER;port=1433;username=sa;password=blablaq;database=sqlserverdb" --create-hive-table --hive-import --hive-database hivemtdb 问题是 sqlserverdb 有大约100个表，但当我发出这个命令时，它只是将6或7个随机表导入到配置单元中。这种行为对我来说真的很奇怪。我找不到我犯了什么错误。
编辑：1
Warning: /usr/hdp/2.4.3.0-227/accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
16/10/13 13:17:38 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6.2.4.3.0-227
16/10/13 13:17:38 INFO tool.BaseSqoopTool: Using Hive-specific delimiters for output. You can override
16/10/13 13:17:38 INFO tool.BaseSqoopTool: delimiters with --fields-terminated-by, etc.
16/10/13 13:17:38 INFO manager.SqlManager: Using default fetchSize of 1000
16/10/13 13:17:38 INFO tool.CodeGenTool: Beginning code generation
16/10/13 13:17:38 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM [UserMessage] AS t WHERE 1=0
16/10/13 13:17:38 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/hdp/2.4.3.0-227/hadoop-mapreduce
Note: /tmp/sqoop-sherry/compile/c809ee201c0aec1edf2ed5a1ef4aed4c/UserMessage.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
16/10/13 13:17:39 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-sherry/compile/c809ee201c0aec1edf2ed5a1ef4aed4c/UserMessage.jar
16/10/13 13:17:39 INFO mapreduce.ImportJobBase: Beginning import of UserMessage
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/usr/hdp/2.4.3.0-227/hadoop/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/usr/hdp/2.4.3.0-227/zookeeper/lib/slf4j-log4j12-1.6.1.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]
16/10/13 13:17:40 INFO impl.TimelineClientImpl: Timeline service address: http://machine-02-xx:8188/ws/v1/timeline/
16/10/13 13:17:40 INFO client.RMProxy: Connecting to ResourceManager at machine-02-xx/xxx.xx.xx.xx:8050
16/10/13 13:17:42 INFO db.DBInputFormat: Using read commited transaction isolation
16/10/13 13:17:42 INFO mapreduce.JobSubmitter: number of splits:1
16/10/13 13:17:42 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1475746531098_0317
16/10/13 13:17:43 INFO impl.YarnClientImpl: Submitted application application_1475746531098_0317
16/10/13 13:17:43 INFO mapreduce.Job: The url to track the job: http://machine-02-xx:8088/proxy/application_1475746531098_0317/
16/10/13 13:17:43 INFO mapreduce.Job: Running job: job_1475746531098_0317
16/10/13 13:17:48 INFO mapreduce.Job: Job job_1475746531098_0317 running in uber mode : false
16/10/13 13:17:48 INFO mapreduce.Job: map 0% reduce 0%
16/10/13 13:17:52 INFO mapreduce.Job: map 100% reduce 0%
16/10/13 13:17:52 INFO mapreduce.Job: Job job_1475746531098_0317 completed successfully
16/10/13 13:17:52 INFO mapreduce.Job: Counters: 30
File System Counters
FILE: Number of bytes read=0
FILE: Number of bytes written=156179
FILE: Number of read operations=0
FILE: Number of large read operations=0
FILE: Number of write operations=0
HDFS: Number of bytes read=87
HDFS: Number of bytes written=0
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)=3486
Total time spent by all reduces in occupied slots (ms)=0
Total time spent by all map tasks (ms)=1743
Total vcore-seconds taken by all map tasks=1743
Total megabyte-seconds taken by all map tasks=2677248
Map-Reduce Framework
Map input records=0
Map output records=0
Input split bytes=87
Spilled Records=0
Failed Shuffles=0
Merged Map outputs=0
GC time elapsed (ms)=30
CPU time spent (ms)=980
Physical memory (bytes) snapshot=233308160
Virtual memory (bytes) snapshot=3031945216
Total committed heap usage (bytes)=180879360
File Input Format Counters
Bytes Read=0
File Output Format Counters
Bytes Written=0
16/10/13 13:17:52 INFO mapreduce.ImportJobBase: Transferred 0 bytes in 12.6069 seconds (0 bytes/sec)
16/10/13 13:17:52 INFO mapreduce.ImportJobBase: Retrieved 0 records.
16/10/13 13:17:52 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM [UserMessage] AS t WHERE 1=0
16/10/13 13:17:52 WARN hive.TableDefWriter: Column SendDate had to be cast to a less precise type in Hive
16/10/13 13:17:52 INFO hive.HiveImport: Loading uploaded data into Hive
Logging initialized using configuration in jar:file:/usr/hdp/2.4.3.0-227/hive/lib/hive-common-1.2.1000.2.4.3.0-227.jar!/hive-log4j.properties
OK
Time taken: 1.286 seconds
Loading data to table sqlcmc.usermessage
Table sqlcmc.usermessage stats: [numFiles=1, totalSize=0]
OK
Time taken: 0.881 seconds
Note: /tmp/sqoop-sherry/compile/c809ee201c0aec1edf2ed5a1ef4aed4c/DadChMasConDig.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
Logging initialized using configuration in jar:file:/usr/hdp/2.4.3.0-227/hive/lib/hive-common-1.2.1000.2.4.3.0-227.jar!/hive-log4j.properties
OK
2条答案
按热度按时间yhxst69z1#
我也有同样的问题，下面的方法对我有效。尽管通常--创建配置单元表和--配置单元覆盖不能同时进行，也没有意义。但没有其他组合起作用，每次只有10个表中的3个或一小部分表被导入
edqdpe6u2#
首先
import-all-tables将为所有表运行导入表。如果没有定义作业中Map器的数量，sqoop将默认选择4个Map器。所以，它需要表有主键或者您指定
--split-by列名。如果是这种情况，您将看到如下错误：
error tool.importalltablestool:导入期间出错：找不到表测试的主键。请使用--split by指定一个，或使用'-m1'执行顺序导入。
因此，您可以使用1Map器，这将使您的导入过程缓慢。
更好的方法是添加
--autoreset-to-one-mapper，它将导入带有命令中提到的Map器数量的主键表，并将自动为没有主键的表使用1个Map器。说到你的问题，
表的sqoop导入失败
DadChMasConDig.我不知道为什么它没有登录到控制台。
导入此表时可能会出现如下异常
运行导入作业时遇到ioexception:java.io.ioexception:配置单元不支持列的sql类型
<somecolumn>例如，varbinary不支持。如果只导入hdfs中的数据，这应该不是问题。您可以尝试：
sqoop-import-all-tables --connect "jdbc:sqlserver://ip.ip.ip.ip\MIGERATIONSERVER;port=1433;username=sa;password=blablaq;database=sqlserverdb"