Hmm, yeah looks like the table name is not getting applied to the
attributes of m. You can work around this by rewriting your query as:
hql("select s.id from (SELECT * FROM m) m join s on (s.id=m.id) order by
s.id"
This explicitly gives the alias m to the attributes of that table. You can
also open a JIRA and we can look in to the root cause in more detail.
Michael
On Thu, Jul 10, 2014 at 5:45 PM, Jerry Lam <chiling...@gmail.com> wrote:
> Hi Michael,
>
> I got the log you asked for. Note that I manually edited the table name
> and the field names to hide some sensitive information.
>
> == Logical Plan ==
> Project ['s.id]
> Join Inner, Some((id#106 = 'm.id))
> Project [id#96 AS id#62]
> MetastoreRelation test, m, None
> MetastoreRelation test, s, Some(s)
>
> == Optimized Logical Plan ==
> Project ['s.id]
> Join Inner, Some((id#106 = 'm.id))
> Project []
> MetastoreRelation test, m, None
> Project [id#106]
> MetastoreRelation test, s, Some(s)
>
> == Physical Plan ==
> Project ['s.id]
> Filter (id#106:0 = 'm.id)
> CartesianProduct
> HiveTableScan [], (MetastoreRelation test, m, None), None
> HiveTableScan [id#106], (MetastoreRelation test, s, Some(s)), None
>
> Best Regards,
>
> Jerry
>
>
>
> On Thu, Jul 10, 2014 at 7:16 PM, Michael Armbrust <mich...@databricks.com>
> wrote:
>
>> Hi Jerry,
>>
>> Thanks for reporting this. It would be helpful if you could provide the
>> output of the following command:
>>
>> println(hql("select s.id from m join s on (s.id=m_id)").queryExecution)
>>
>> Michael
>>
>>
>> On Thu, Jul 10, 2014 at 8:15 AM, Jerry Lam <chiling...@gmail.com> wrote:
>>
>>> Hi Spark developers,
>>>
>>> I have the following hqls that spark will throw exceptions of this kind:
>>> 14/07/10 15:07:55 INFO TaskSetManager: Loss was due to
>>> org.apache.spark.TaskKilledException [duplicate 17]
>>> org.apache.spark.SparkException: Job aborted due to stage failure: Task
>>> 0.0:736 failed 4 times, most recent failure: Exception failure in TID 167
>>> on host etl2-node05:
>>> org.apache.spark.sql.catalyst.errors.package$TreeNodeException: No function
>>> to evaluate expression. type: UnresolvedAttribute, tree: 'm.id
>>>
>>> org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute.eval(unresolved.scala:59)
>>>
>>> org.apache.spark.sql.catalyst.expressions.Equals.eval(predicates.scala:151)
>>>
>>> org.apache.spark.sql.execution.Filter$$anonfun$2$$anonfun$apply$1.apply(basicOperators.scala:52)
>>>
>>> org.apache.spark.sql.execution.Filter$$anonfun$2$$anonfun$apply$1.apply(basicOperators.scala:52)
>>> scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:390)
>>> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> scala.collection.Iterator$class.foreach(Iterator.scala:727)
>>> scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
>>>
>>> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
>>>
>>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
>>>
>>> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
>>> scala.collection.TraversableOnce$class.to
>>> (TraversableOnce.scala:273)
>>> scala.collection.AbstractIterator.to(Iterator.scala:1157)
>>>
>>> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
>>> scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
>>>
>>> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
>>> scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
>>> org.apache.spark.rdd.RDD$$anonfun$15.apply(RDD.scala:717)
>>> org.apache.spark.rdd.RDD$$anonfun$15.apply(RDD.scala:717)
>>>
>>> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1080)
>>>
>>> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1080)
>>>
>>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
>>> org.apache.spark.scheduler.Task.run(Task.scala:51)
>>>
>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
>>>
>>> java.util.concurrent.ThreadPoolExecutor$Worker.runTask(ThreadPoolExecutor.java:886)
>>>
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:908)
>>> java.lang.Thread.run(Thread.java:662)
>>>
>>> The hql looks like this (I trimmed the hql down to the essentials to
>>> demonstrate the potential bugs, the actual join is more complex and
>>> irrelevant to the bug):
>>>
>>> val hiveContext = new org.apache.spark.sql.hive.HiveContext(sc)
>>> import hiveContext._
>>> hql("USE test")
>>> hql("select id from m").registerAsTable("m")
>>> hql("select s.id from m join s on (s.id=m.id
>>> )").collect().foreach(println)
>>>
>>> Apparently, spark is unable to understand the m.id in the "(s.id=m.id)".
>>> If I change it to:
>>> hql("select m_id from m").registerAsTable("m")
>>> hql("select s.id from m join s on (s.id
>>> =m_id)").collect().foreach(println)
>>>
>>> It will work. Am I doing something wrong or it is a bug in spark sql?
>>>
>>> Best Regards,
>>>
>>> Jerry
>>>
>>>
>>
>
