Re: java.lang.NoSuchMethodError while saving a random forest model Spark version 1.5

2015-12-17 Thread Yanbo Liang 
Spark 1.5 officially use Parquet 1.7.0, but Spark 1.3 use Parquet 1.6.0.
It's better to check which version of Parquet is used in your environment.

2015-12-17 10:26 GMT+08:00 Joseph Bradley :

> This method is tested in the Spark 1.5 unit tests, so I'd guess it's a
> problem with the Parquet dependency.  What version of Parquet are you
> building Spark 1.5 off of?  (I'm not that familiar with Parquet issues
> myself, but hopefully a SQL person can chime in.)
>
> On Tue, Dec 15, 2015 at 3:23 PM, Rachana Srivastava <
> rachana.srivast...@markmonitor.com> wrote:
>
>> I have recently upgraded spark version but when I try to run save a random 
>> forest model using model save command I am getting nosuchmethoderror.  My 
>> code works fine with 1.3x version.
>>
>>
>>
>> model.save(sc.sc(), "modelsavedir");
>>
>>
>>
>>
>>
>> ERROR:
>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation -
>> Aborting job.
>>
>> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
>> in stage 22.0 failed 1 times, most recent failure: Lost task 0.0 in stage
>> 22.0 (TID 230, localhost): java.lang.NoSuchMethodError:
>> parquet.schema.Types$GroupBuilder.addField(Lparquet/schema/Type;)Lparquet/schema/Types$BaseGroupBuilder;
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convertField$1.apply(CatalystSchemaConverter.scala:517)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convertField$1.apply(CatalystSchemaConverter.scala:516)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51)
>>
>> at
>> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:60)
>>
>> at
>> scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:108)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convertField(CatalystSchemaConverter.scala:516)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convertField(CatalystSchemaConverter.scala:312)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convert$1.apply(CatalystSchemaConverter.scala:305)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convert$1.apply(CatalystSchemaConverter.scala:305)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>>
>> at
>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>>
>> at
>> scala.collection.Iterator$class.foreach(Iterator.scala:727)
>>
>> at
>> scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>>
>> at
>> scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
>>
>> at
>> org.apache.spark.sql.types.StructType.foreach(StructType.scala:92)
>>
>> at
>> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
>>
>> at
>> org.apache.spark.sql.types.StructType.map(StructType.scala:92)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convert(CatalystSchemaConverter.scala:305)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.ParquetTypesConverter$.convertFromAttributes(ParquetTypesConverter.scala:58)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.RowWriteSupport.init(ParquetTableSupport.scala:55)
>>
>> at
>> parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:287)
>>
>> at
>> parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:261)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.(ParquetRelation.scala:94)
>>
>> at
>> org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:272)
>>
>> at
>> org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:233)
>>
>> at
>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>>
>> at
>> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>>
>> at
>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>
>> at org.apache.spark.scheduler.Task.run(Task.scala:88)
>>
>> at
>>

Re: java.lang.NoSuchMethodError while saving a random forest model Spark version 1.5

2015-12-16 Thread Joseph Bradley 
This method is tested in the Spark 1.5 unit tests, so I'd guess it's a
problem with the Parquet dependency.  What version of Parquet are you
building Spark 1.5 off of?  (I'm not that familiar with Parquet issues
myself, but hopefully a SQL person can chime in.)

On Tue, Dec 15, 2015 at 3:23 PM, Rachana Srivastava <
rachana.srivast...@markmonitor.com> wrote:

> I have recently upgraded spark version but when I try to run save a random 
> forest model using model save command I am getting nosuchmethoderror.  My 
> code works fine with 1.3x version.
>
>
>
> model.save(sc.sc(), "modelsavedir");
>
>
>
>
>
> ERROR:
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation -
> Aborting job.
>
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
> in stage 22.0 failed 1 times, most recent failure: Lost task 0.0 in stage
> 22.0 (TID 230, localhost): java.lang.NoSuchMethodError:
> parquet.schema.Types$GroupBuilder.addField(Lparquet/schema/Type;)Lparquet/schema/Types$BaseGroupBuilder;
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convertField$1.apply(CatalystSchemaConverter.scala:517)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convertField$1.apply(CatalystSchemaConverter.scala:516)
>
> at
> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51)
>
> at
> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:60)
>
> at
> scala.collection.mutable.ArrayOps$ofRef.foldLeft(ArrayOps.scala:108)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convertField(CatalystSchemaConverter.scala:516)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convertField(CatalystSchemaConverter.scala:312)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convert$1.apply(CatalystSchemaConverter.scala:305)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter$$anonfun$convert$1.apply(CatalystSchemaConverter.scala:305)
>
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>
> at
> scala.collection.Iterator$class.foreach(Iterator.scala:727)
>
> at
> scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>
> at
> scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
>
> at
> org.apache.spark.sql.types.StructType.foreach(StructType.scala:92)
>
> at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
>
> at
> org.apache.spark.sql.types.StructType.map(StructType.scala:92)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.CatalystSchemaConverter.convert(CatalystSchemaConverter.scala:305)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetTypesConverter$.convertFromAttributes(ParquetTypesConverter.scala:58)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.RowWriteSupport.init(ParquetTableSupport.scala:55)
>
> at
> parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:287)
>
> at
> parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:261)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.(ParquetRelation.scala:94)
>
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:272)
>
> at
> org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:233)
>
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
>
> at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>
> at org.apache.spark.scheduler.Task.run(Task.scala:88)
>
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>
> at java.lang.Thread.run(Thread.java:745)
>
>
>