apache spark sql AnalysisException Text data source does not support int data type

0 votes

Hello guys,

I am new in Hive. I tried to save some output in a text file after doing some operation, but I am getting the below error?

apache.spark.sql.AnalysisException: Text data source does not support int data type.;
  at org.apache.spark.sql.execution.datasources.DataSourceUtils$$anonfun$verifySchema$1.apply(DataSourceUtils.scala:69)
  at org.apache.spark.sql.execution.datasources.DataSourceUtils$$anonfun$verifySchema$1.apply(DataSourceUtils.scala:67)
  at scala.collection.Iterator$class.foreach(Iterator.scala:891)
  at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
  at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
  at org.apache.spark.sql.types.StructType.foreach(StructType.scala:99)
  at org.apache.spark.sql.execution.datasources.DataSourceUtils$.verifySchema(DataSourceUtils.scala:67)
  at org.apache.spark.sql.execution.datasources.DataSourceUtils$.verifyWriteSchema(DataSourceUtils.scala:34)
  at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:100)
  at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:159)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
  at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
  at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
  at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
  at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
  at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
  at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
  at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
  at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
  at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
  at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
  at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285)
  at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271)
                                                                                              183,1         88%

Feb 13, 2020 in Big Data Hadoop by akhtar
• 38,230 points
2,438 views

1 answer to this question.

0 votes
Hi@akhtar,

I think your output is in different format, but you tried to save it in text format. Check your output data type and then save accordingly.

Thank You
answered Feb 13, 2020 by MD
• 95,320 points

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