Hi, Exception says input path '/opt/incubator-carbondata/sample.csv' does not exist. So please make sure following things, 1. Whether the the sample.csv file is present in the location ' /opt/incubator-carbondata/' 2. Are you running the Spark in local mode or cluster mode.(If it is running in cluster mode please keep the csv file in hdfs.) 3. Please try to keep the csv file in hdfs and load the data.
Thanks & Regards, Ravindra On 31 July 2016 at 07:37, 金铸 <[email protected]> wrote: > hi Liang： > > Thanks your repay。 > > I have already used the “/opt/incubator-carbondata/sample.csv” > ，Reported the same error。 > > > > 在 2016/7/30 22:44, Liang Big data 写道: > >> Hi jinzhu金铸: >> >> >> please check the below error:the input path having some issues. >> Please use the absolute path to try it again. >> ----------------------------------------------- >> ERROR 29-07 16:39:46,904 - main >> org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path >> does not exist: /opt/incubator-carbondata/sample.csv >> >> Regards >> Liang >> >> 2016-07-29 8:47 GMT+08:00 金铸 <[email protected]>: >> >> [hadoop@slave2 ~]$ cat /opt/incubator-carbondata/sample.csv >>> id,name,city,age >>> 1,david,shenzhen,31 >>> 2,eason,shenzhen,27 >>> 3,jarry,wuhan,35 >>> [hadoop@slave2 ~]$ >>> >>> > load data inpath '../sample.csv' into table test_table; >>> INFO 29-07 16:39:46,087 - main Property file path: >>> /opt/incubator-carbondata/bin/../../../conf/carbon.properties >>> INFO 29-07 16:39:46,087 - main ------Using Carbon.properties -------- >>> INFO 29-07 16:39:46,087 - main {} >>> INFO 29-07 16:39:46,088 - main Query [LOAD DATA INPATH '../SAMPLE.CSV' >>> INTO TABLE TEST_TABLE] >>> INFO 29-07 16:39:46,527 - Successfully able to get the table metadata >>> file lock >>> INFO 29-07 16:39:46,537 - main Initiating Direct Load for the Table : >>> (default.test_table) >>> INFO 29-07 16:39:46,541 - Generate global dictionary from source data >>> files! >>> INFO 29-07 16:39:46,569 - [Block Distribution] >>> INFO 29-07 16:39:46,569 - totalInputSpaceConsumed : 74 , >>> defaultParallelism : 6 >>> INFO 29-07 16:39:46,569 - mapreduce.input.fileinputformat.split.maxsize >>> : >>> 16777216 >>> INFO 29-07 16:39:46,689 - Block broadcast_0 stored as values in memory >>> (estimated size 232.6 KB, free 232.6 KB) >>> INFO 29-07 16:39:46,849 - Block broadcast_0_piece0 stored as bytes in >>> memory (estimated size 19.7 KB, free 252.3 KB) >>> INFO 29-07 16:39:46,850 - Added broadcast_0_piece0 in memory on >>> 192.168.241.223:41572 (size: 19.7 KB, free: 511.5 MB) >>> INFO 29-07 16:39:46,856 - Created broadcast 0 from NewHadoopRDD at >>> CarbonTextFile.scala:45 >>> ERROR 29-07 16:39:46,904 - generate global dictionary failed >>> ERROR 29-07 16:39:46,904 - main >>> org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path >>> does not exist: /opt/incubator-carbondata/sample.csv >>> at >>> >>> org.apache.hadoop.mapreduce.lib.input.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:321) >>> at >>> >>> org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:264) >>> at >>> >>> org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:385) >>> at >>> org.apache.spark.rdd.NewHadoopRDD.getPartitions(NewHadoopRDD.scala:120) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237) >>> at >>> >>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:237) >>> at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1307) >>> at >>> >>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) >>> at >>> >>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111) >>> at org.apache.spark.rdd.RDD.withScope(RDD.scala:316) >>> at org.apache.spark.rdd.RDD.take(RDD.scala:1302) >>> at >>> >>> com.databricks.spark.csv.CarbonCsvRelation.firstLine$lzycompute(CarbonCsvRelation.scala:175) >>> at >>> >>> com.databricks.spark.csv.CarbonCsvRelation.firstLine(CarbonCsvRelation.scala:170) >>> at >>> >>> com.databricks.spark.csv.CarbonCsvRelation.inferSchema(CarbonCsvRelation.scala:141) >>> at >>> >>> com.databricks.spark.csv.CarbonCsvRelation.<init>(CarbonCsvRelation.scala:71) >>> at >>> >>> com.databricks.spark.csv.newapi.DefaultSource.createRelation(DefaultSource.scala:142) >>> at >>> >>> com.databricks.spark.csv.newapi.DefaultSource.createRelation(DefaultSource.scala:44) >>> at >>> >>> org.apache.spark.sql.execution.datasources.ResolvedDataSource$.apply(ResolvedDataSource.scala:158) >>> at >>> org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:119) >>> at >>> org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:109) >>> at >>> >>> org.carbondata.spark.util.GlobalDictionaryUtil$.loadDataFrame(GlobalDictionaryUtil.scala:365) >>> at >>> >>> org.carbondata.spark.util.GlobalDictionaryUtil$.generateGlobalDictionary(GlobalDictionaryUtil.scala:676) >>> at >>> >>> org.apache.spark.sql.execution.command.LoadTable.run(carbonTableSchema.scala:1159) >>> at >>> >>> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult$lzycompute(commands.scala:58) >>> at >>> >>> org.apache.spark.sql.execution.ExecutedCommand.sideEffectResult(commands.scala:56) >>> at >>> >>> org.apache.spark.sql.execution.ExecutedCommand.doExecute(commands.scala:70) >>> at >>> >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:132) >>> at >>> >>> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$5.apply(SparkPlan.scala:130) >>> at >>> >>> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150) >>> at >>> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:130) >>> at >>> >>> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:55) >>> at >>> >>> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:55) >>> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:145) >>> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:130) >>> at >>> >>> org.carbondata.spark.rdd.CarbonDataFrameRDD.<init>(CarbonDataFrameRDD.scala:23) >>> at org.apache.spark.sql.CarbonContext.sql(CarbonContext.scala:131) >>> at >>> >>> org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:63) >>> at >>> >>> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:311) >>> at >>> org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:376) >>> at >>> >>> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:226) >>> at >>> >>> org.apache.spark.sql.hive.cli.CarbonSQLCLIDriver$.main(CarbonSQLCLIDriver.scala:40) >>> at >>> >>> org.apache.spark.sql.hive.cli.CarbonSQLCLIDriver.main(CarbonSQLCLIDriver.scala) >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>> at >>> >>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) >>> at >>> >>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) >>> at java.lang.reflect.Method.invoke(Method.java:606) >>> at >>> >>> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731) >>> at >>> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181) >>> at >>> org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206) >>> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121) >>> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) >>> >>> -- >>> 金铸 >>> >>> >>> >>> >>> >>> >>> >>> --------------------------------------------------------------------------------------------------- >>> Confidentiality Notice: The information contained in this e-mail and any >>> accompanying attachment(s) >>> is intended only for the use of the intended recipient and may be >>> confidential and/or privileged of >>> Neusoft Corporation, its subsidiaries and/or its affiliates. If any >>> reader >>> of this communication is >>> not the intended recipient, unauthorized use, forwarding, printing, >>> storing, disclosure or copying >>> is strictly prohibited, and may be unlawful.If you have received this >>> communication in error,please >>> immediately notify the sender by return e-mail, and delete the original >>> message and all copies from >>> your system. Thank you. >>> >>> >>> --------------------------------------------------------------------------------------------------- >>> >>> >> >> > -- > 金铸 > 技术发展部（TDD） > 东软集团股份有限公司 > 沈阳浑南新区新秀街2号东软软件园A2-105A > Postcode:110179 > Tel: (86 24)8366 2049 > Mobile：13897999526 > > > > > > > --------------------------------------------------------------------------------------------------- > Confidentiality Notice: The information contained in this e-mail and any > accompanying attachment(s) > is intended only for the use of the intended recipient and may be > confidential and/or privileged of > Neusoft Corporation, its subsidiaries and/or its affiliates. If any reader > of this communication is > not the intended recipient, unauthorized use, forwarding, printing, > storing, disclosure or copying > is strictly prohibited, and may be unlawful.If you have received this > communication in error,please > immediately notify the sender by return e-mail, and delete the original > message and all copies from > your system. Thank you. > > --------------------------------------------------------------------------------------------------- > -- Thanks & Regards, Ravi
