Re: TreeNodeException: Unresolved attributes

2015-03-04 Thread Anusha Shamanur 
I tried. I still get the same error.

15/03/04 09:01:50 INFO parse.ParseDriver: Parsing command: select * from
TableName where value like '%Restaurant%'

15/03/04 09:01:50 INFO parse.ParseDriver: Parse Completed.

15/03/04 09:01:50 INFO metastore.HiveMetaStore: 0: get_table : db=default
tbl=TableName

15/03/04 09:01:50 INFO HiveMetaStore.audit: ugi=as7339
ip=unknown-ip-addr cmd=get_table
: db=default tbl=TableName
results: org.apache.spark.sql.SchemaRDD =

SchemaRDD[86] at RDD at SchemaRDD.scala:108
== Query Plan ==

== Physical Plan ==

org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
attributes: *, tree:

'Project [*]

'Filter ('value LIKE Restaurant)
  MetastoreRelation default, TableName, None



On Wed, Mar 4, 2015 at 5:39 AM, Arush Kharbanda ar...@sigmoidanalytics.com
wrote:

 Why don't you formulate a string before you pass it to the hql function
 (appending strings), and hql function is deprecated. You should use sql.


 http://spark.apache.org/docs/1.1.0/api/scala/index.html#org.apache.spark.sql.hive.HiveContext

 On Wed, Mar 4, 2015 at 6:15 AM, Anusha Shamanur anushas...@gmail.com
 wrote:

 Hi,


 I am trying to run a simple select query on a table.


 val restaurants=hiveCtx.hql(select * from TableName where column like
 '%SomeString%' )

 This gives an error as below:

 org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
 Unresolved attributes: *, tree:

 How do I solve this?


 --
 Regards,
 Anusha




 --

 [image: Sigmoid Analytics] http://htmlsig.com/www.sigmoidanalytics.com

 *Arush Kharbanda* || Technical Teamlead

 ar...@sigmoidanalytics.com || www.sigmoidanalytics.com




-- 
Regards,
Anusha

Re: TreeNodeException: Unresolved attributes

2015-03-04 Thread Zhan Zhang 
Which spark version did you use? I tried spark-1.2.1 and didn’t meet this 
problem.

scala val m = hiveContext.sql( select * from  testtable where value like 
'%Restaurant%')
15/03/05 02:02:30 INFO ParseDriver: Parsing command: select * from  testtable 
where value like '%Restaurant%'
15/03/05 02:02:30 INFO ParseDriver: Parse Completed
15/03/05 02:02:30 INFO MemoryStore: ensureFreeSpace(462299) called with 
curMem=1087888, maxMem=280248975
15/03/05 02:02:30 INFO MemoryStore: Block broadcast_2 stored as values in 
memory (estimated size 451.5 KB, free 265.8 MB)
15/03/05 02:02:30 INFO MemoryStore: ensureFreeSpace(81645) called with 
curMem=1550187, maxMem=280248975
15/03/05 02:02:30 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in 
memory (estimated size 79.7 KB, free 265.7 MB)
15/03/05 02:02:30 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 
c6402.ambari.apache.orghttp://c6402.ambari.apache.org:33696 (size: 79.7 KB, 
free: 267.0 MB)
15/03/05 02:02:30 INFO BlockManagerMaster: Updated info of block 
broadcast_2_piece0
15/03/05 02:02:30 INFO DefaultExecutionContext: Created broadcast 2 from 
broadcast at TableReader.scala:68
m: org.apache.spark.sql.SchemaRDD =
SchemaRDD[3] at RDD at SchemaRDD.scala:108
== Query Plan ==
== Physical Plan ==
Filter Contains(value#5, Restaurant)
 HiveTableScan [key#4,value#5], (MetastoreRelation default, testtable, None), 
None

scala


Thanks.

Zhan Zhang

On Mar 4, 2015, at 9:09 AM, Anusha Shamanur 
anushas...@gmail.commailto:anushas...@gmail.com wrote:

I tried. I still get the same error.

15/03/04 09:01:50 INFO parse.ParseDriver: Parsing command: select * from 
TableName where value like '%Restaurant%'

15/03/04 09:01:50 INFO parse.ParseDriver: Parse Completed.

15/03/04 09:01:50 INFO metastore.HiveMetaStore: 0: get_table : db=default 
tbl=TableName

15/03/04 09:01:50 INFO HiveMetaStore.audit: ugi=as7339 ip=unknown-ip-addr 
cmd=get_table : db=default tbl=TableName
results: org.apache.spark.sql.SchemaRDD =

SchemaRDD[86] at RDD at SchemaRDD.scala:108
== Query Plan ==

== Physical Plan ==

org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved 
attributes: *, tree:

'Project [*]

'Filter ('value LIKE Restaurant)
  MetastoreRelation default, TableName, None



On Wed, Mar 4, 2015 at 5:39 AM, Arush Kharbanda 
ar...@sigmoidanalytics.commailto:ar...@sigmoidanalytics.com wrote:
Why don't you formulate a string before you pass it to the hql function 
(appending strings), and hql function is deprecated. You should use sql.

http://spark.apache.org/docs/1.1.0/api/scala/index.html#org.apache.spark.sql.hive.HiveContext

On Wed, Mar 4, 2015 at 6:15 AM, Anusha Shamanur 
anushas...@gmail.commailto:anushas...@gmail.com wrote:
Hi,

I am trying to run a simple select query on a table.

val restaurants=hiveCtx.hql(select * from TableName where column like 
'%SomeString%' )
This gives an error as below:
org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved 
attributes: *, tree:

How do I solve this?


--
Regards,
Anusha



--

[Sigmoid Analytics]http://htmlsig.com/www.sigmoidanalytics.com

Arush Kharbanda || Technical Teamlead

ar...@sigmoidanalytics.commailto:ar...@sigmoidanalytics.com || 
www.sigmoidanalytics.comhttp://www.sigmoidanalytics.com/



--
Regards,
Anusha

Re: TreeNodeException: Unresolved attributes

2015-03-04 Thread Arush Kharbanda 
Why don't you formulate a string before you pass it to the hql function
(appending strings), and hql function is deprecated. You should use sql.

http://spark.apache.org/docs/1.1.0/api/scala/index.html#org.apache.spark.sql.hive.HiveContext

On Wed, Mar 4, 2015 at 6:15 AM, Anusha Shamanur anushas...@gmail.com
wrote:

 Hi,


 I am trying to run a simple select query on a table.


 val restaurants=hiveCtx.hql(select * from TableName where column like
 '%SomeString%' )

 This gives an error as below:

 org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
 attributes: *, tree:

 How do I solve this?


 --
 Regards,
 Anusha




-- 

[image: Sigmoid Analytics] http://htmlsig.com/www.sigmoidanalytics.com

*Arush Kharbanda* || Technical Teamlead

ar...@sigmoidanalytics.com || www.sigmoidanalytics.com

Re: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved attributes: pyspark on yarn

2015-03-03 Thread Gustavo Enrique Salazar Torres 
Hi Sam:

Shouldn't you define the table schema? I had the same problem in Scala and
then I solved it defining the schema. I did this:

sqlContext.applySchema(dataRDD, tableSchema).registerTempTable(tableName)

Hope it helps.

On Mon, Jan 5, 2015 at 7:01 PM, Sam Flint sam.fl...@magnetic.com wrote:

 Below is the code that I am running.  I get an error for unresolved
 attributes.  Can anyone point me in the right direction?  Running from
 pyspark shell using yarn MASTER=yarn-client pyspark

 Error is below code:


 # Import SQLContext and data types
 from pyspark.sql import *

 # sc is an existing SparkContext.
 sqlContext = SQLContext(sc)

 # The result of loading a parquet file is also a SchemaRDD.
 # Try loading all data that you have
 parquetFile =
 sqlContext.parquetFile(/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.7.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.8.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.9.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.4.parq)



 # Parquet files can also be registered as tables and then used in SQL
 statements.
 parquetFile.registerTempTable(parquetFileone)


 results = sqlContext.sql(SELECT * FROM parquetFileone where key=20141001
 )

 #print results
 for result in results.collect():
   print result



 Traceback (most recent call last):
   File stdin, line 1, in module
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
 line 1615, in collect
 rows = RDD.collect(self)
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/rdd.py,
 line 678, in collect
 bytesInJava = self._jrdd.collect().iterator()
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
 line 1527, in _jrdd
 self._lazy_jrdd = self._jschema_rdd.javaToPython()
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py,
 line 538, in __call__
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py,
 line 300, in get_return_value
 py4j.protocol.Py4JJavaError: An error occurred while calling
 o29.javaToPython.
 : org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
 Unresolved attributes: *, tree:
 Project [*]
  Filter ('key = 20141001)
   Subquery parquetFileone
ParquetRelation
 /user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.7.parq,/user/hive/warehouse/impala_new_4/key=20141001

Re: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved attributes: pyspark on yarn

2015-03-03 Thread Michael Armbrust 
In Spark 1.2 you'll have to create a partitioned hive table
https://cwiki.apache.org/confluence/display/Hive/LanguageManual+DDL#LanguageManualDDL-AddPartitions
in order to read parquet data in this format.  In Spark 1.3 the parquet
data source will auto discover partitions when they are laid out in this
format.

Michael

On Mon, Jan 5, 2015 at 1:01 PM, Sam Flint sam.fl...@magnetic.com wrote:

 Below is the code that I am running.  I get an error for unresolved
 attributes.  Can anyone point me in the right direction?  Running from
 pyspark shell using yarn MASTER=yarn-client pyspark

 Error is below code:


 # Import SQLContext and data types
 from pyspark.sql import *

 # sc is an existing SparkContext.
 sqlContext = SQLContext(sc)

 # The result of loading a parquet file is also a SchemaRDD.
 # Try loading all data that you have
 parquetFile =
 sqlContext.parquetFile(/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.7.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.8.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.9.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.4.parq)



 # Parquet files can also be registered as tables and then used in SQL
 statements.
 parquetFile.registerTempTable(parquetFileone)


 results = sqlContext.sql(SELECT * FROM parquetFileone where key=20141001
 )

 #print results
 for result in results.collect():
   print result



 Traceback (most recent call last):
   File stdin, line 1, in module
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
 line 1615, in collect
 rows = RDD.collect(self)
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/rdd.py,
 line 678, in collect
 bytesInJava = self._jrdd.collect().iterator()
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
 line 1527, in _jrdd
 self._lazy_jrdd = self._jschema_rdd.javaToPython()
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py,
 line 538, in __call__
   File
 /opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py,
 line 300, in get_return_value
 py4j.protocol.Py4JJavaError: An error occurred while calling
 o29.javaToPython.
 : org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
 Unresolved attributes: *, tree:
 Project [*]
  Filter ('key = 20141001)
   Subquery parquetFileone
ParquetRelation
 /user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17

TreeNodeException: Unresolved attributes

2015-03-03 Thread Anusha Shamanur 
Hi,


I am trying to run a simple select query on a table.


val restaurants=hiveCtx.hql(select * from TableName where column like
'%SomeString%' )

This gives an error as below:

org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
attributes: *, tree:

How do I solve this?


-- 
Regards,
Anusha

org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved attributes: pyspark on yarn

2015-01-05 Thread Sam Flint 
Below is the code that I am running.  I get an error for unresolved
attributes.  Can anyone point me in the right direction?  Running from
pyspark shell using yarn MASTER=yarn-client pyspark

Error is below code:


# Import SQLContext and data types
from pyspark.sql import *

# sc is an existing SparkContext.
sqlContext = SQLContext(sc)

# The result of loading a parquet file is also a SchemaRDD.
# Try loading all data that you have
parquetFile =
sqlContext.parquetFile(/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.7.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.8.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.9.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.4.parq)



# Parquet files can also be registered as tables and then used in SQL
statements.
parquetFile.registerTempTable(parquetFileone)


results = sqlContext.sql(SELECT * FROM parquetFileone where key=20141001 )

#print results
for result in results.collect():
  print result



Traceback (most recent call last):
  File stdin, line 1, in module
  File
/opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
line 1615, in collect
rows = RDD.collect(self)
  File
/opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/rdd.py,
line 678, in collect
bytesInJava = self._jrdd.collect().iterator()
  File
/opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/pyspark/sql.py,
line 1527, in _jrdd
self._lazy_jrdd = self._jschema_rdd.javaToPython()
  File
/opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py,
line 538, in __call__
  File
/opt/cloudera/parcels/CDH-5.2.1-1.cdh5.2.1.p0.12/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py,
line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling
o29.javaToPython.
: org.apache.spark.sql.catalyst.errors.package$TreeNodeException:
Unresolved attributes: *, tree:
Project [*]
 Filter ('key = 20141001)
  Subquery parquetFileone
   ParquetRelation
/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.1.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.10.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.11.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.2.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.3.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.4.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.5.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.6.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.7.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.8.parq,/user/hive/warehouse/impala_new_4/key=20141001/69446344000a3a17-c90aac1f33a0fbc_875501925_data.9.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.0.parq,/user/hive/warehouse/impala_new_4/key=20141001/f1448ca083a5e224-159572f61b50d7a3_854675293_data.1