thanks a lot，I solve this。
在 2016/8/17 0:53, Eason 写道:
hi jinzhu,
whether this happen on multiple instance loading the same table?
currently ,it is no support concurrent load on same table.
for this exception
1.please check if any locks are created under system temp folder
with<databasename>/<tablename>/lockfile, if it exists please delete.
2.try to change the lock ype:
carbon.lock.type = ZOOKEEPERLOCK Regards,
Eason
在 2016年08月12日 14:25, 金铸 写道:
hi ： /usr/hdp/2.4.0.0-169/spark/bin/spark-shell --master yarn-client
--jars
/opt/incubator-carbondata/assembly/target/scala-2.10/carbondata_2.10-0.1.0-incubating-SNAPSHOT-shade-hadoop2.2.0.jar,/usr/hdp/2.4.0.0-169/spark/lib/datanucleus-api-jdo-3.2.6.jar,/usr/hdp/2.4.0.0-169/spark/lib/datanucleus-rdbms-3.2.9.jar,/usr/hdp/2.4.0.0-169/spark/lib/datanucleus-core-3.2.10.jar,/opt//mysql-connector-java-5.1.37.jar
scala>import org.apache.spark.sql.CarbonContext scala>import
java.io.File scala>import org.apache.hadoop.hive.conf.HiveConf
scala>val cc = new CarbonContext(sc,
"hdfs://hadoop01/data/carbondata01/store")
scala>cc.setConf("hive.metastore.warehouse.dir",
"/apps/hive/warehouse")
scala>cc.setConf(HiveConf.ConfVars.HIVECHECKFILEFORMAT.varname,
"false")
scala>cc.setConf("carbon.kettle.home","/usr/hdp/2.4.0.0-169/spark/carbonlib/carbonplugins")
scala>
cc.setConf("carbon.kettle.home","/usr/hdp/2.4.0.0-169/spark/carbonlib/carbonplugins")
scala> cc.sql(s"load data local inpath 'hdfs://hadoop01/sample.csv'
into table t4 options('FILEHEADER'='id,name,city,age')") INFO 12-08
14:21:24,461 - main Query [LOAD DATA LOCAL INPATH
'HDFS://HADOOP01/SAMPLE.CSV' INTO TABLE T4
OPTIONS('FILEHEADER'='ID,NAME,CITY,AGE')] INFO 12-08 14:21:39,475 -
Table MetaData Unlocked Successfully after data load
java.lang.RuntimeException: Table is locked for updation. Please try
after some time at scala.sys.package$.error(package.scala:27)
at
org.apache.spark.sql.execution.command.LoadTable.run(carbonTableSchema.scala:1049)
at
org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58)
at
org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56)
at
org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132)
at
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
thanks a lot
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