I have opened https://issues.apache.org/jira/browse/SPARK-2474 to track
this bug. I will also explain my understanding of the root cause.
On Thu, Jul 10, 2014 at 6:03 PM, Michael Armbrust <mich...@databricks.com>
wrote:
> 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
>>>>
>>>>
>>>
>>
>
