val sc: SparkContext = new SparkContext(conf)
val sqlCassContext = new CassandraAwareSQLContext(sc) // I used some
Calliope Cassandra Spark connector
val rdd : SchemaRDD = sqlCassContext.sql("select * from db.profile " )
rdd.cache
rdd.registerTempTable("profile")
rdd.first //enforce caching
val q = "select from_unixtime(floor(createdAt/1000)) from profile
where sampling_bucket=0 "
val rdd2 = rdd.sqlContext.sql(q )
println ("Result: " + rdd2.first)
And I get the following errors:
xception in thread "main"
org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
attributes: 'from_unixtime('floor(('createdAt / 1000))) AS c0#7, tree:
Project ['from_unixtime('floor(('createdAt / 1000))) AS c0#7]
Filter (sampling_bucket#10 = 0)
Subquery profile
Project
[company#8,bucket#9,sampling_bucket#10,profileid#11,createdat#12L,modifiedat#13L,version#14]
CassandraRelation localhost, 9042, 9160, normaldb_sampling, profile,
org.apache.spark.sql.CassandraAwareSQLContext@778b692d, None, None, false,
Some(Configuration: core-default.xml, core-site.xml, mapred-default.xml,
mapred-site.xml)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$apply$1.applyOrElse(
Analyzer.scala:72)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$apply$1.applyOrElse(
Analyzer.scala:70)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(
TreeNode.scala:165)
at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(
TreeNode.scala:183)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265
)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(
TreeNode.scala:212)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(
TreeNode.scala:168)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:156
)
at org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(
Analyzer.scala:70)
at org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(
Analyzer.scala:68)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(
RuleExecutor.scala:61)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(
RuleExecutor.scala:59)
at scala.collection.IndexedSeqOptimized$class.foldl(
IndexedSeqOptimized.scala:51)
at scala.collection.IndexedSeqOptimized$class.foldLeft(
IndexedSeqOptimized.scala:60)
at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:34)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(
RuleExecutor.scala:59)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(
RuleExecutor.scala:51)
at scala.collection.immutable.List.foreach(List.scala:318)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(
RuleExecutor.scala:51)
at org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(
SQLContext.scala:402)
at org.apache.spark.sql.SQLContext$QueryExecution.analyzed(
SQLContext.scala:402)
at org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(
SQLContext.scala:403)
at org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(
SQLContext.scala:403)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(
SQLContext.scala:407)
at org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(
SQLContext.scala:405)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(
SQLContext.scala:411)
at org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(
SQLContext.scala:411)
at org.apache.spark.sql.SchemaRDD.collect(SchemaRDD.scala:438)
at org.apache.spark.sql.SchemaRDD.take(SchemaRDD.scala:440)
at org.apache.spark.sql.SchemaRDD.take(SchemaRDD.scala:103)
at org.apache.spark.rdd.RDD.first(RDD.scala:1091)
at boot.SQLDemo$.main(SQLDemo.scala:65) //my code
at boot.SQLDemo.main(SQLDemo.scala) //my code
On Tue, Mar 3, 2015 at 8:57 AM, Cheng, Hao <hao.ch...@intel.com> wrote:
> Can you provide the detailed failure call stack?
>
>
>
> *From:* shahab [mailto:shahab.mok...@gmail.com]
> *Sent:* Tuesday, March 3, 2015 3:52 PM
> *To:* user@spark.apache.org
> *Subject:* Supporting Hive features in Spark SQL Thrift JDBC server
>
>
>
> Hi,
>
>
>
> According to Spark SQL documentation, "....Spark SQL supports the vast
> majority of Hive features, such as User Defined Functions( UDF) ", and one
> of these UFDs is "current_date()" function, which should be supported.
>
>
>
> However, i get error when I am using this UDF in my SQL query. There are
> couple of other UDFs which cause similar error.
>
>
>
> Am I missing something in my JDBC server ?
>
>
>
> /Shahab
>
