I have a feeling I’m missing a Jar that provides the support or could this
may be related to https://issues.apache.org/jira/browse/SPARK-5792. If it
is a Jar where would I find that ? I would have thought in the $HIVE/lib
folder, but not sure which jar contains it.
Error:
Create Metric Temporary Table for querying15/04/01 14:41:44 INFO
HiveMetaStore: 0: Opening raw store with implemenation
class:org.apache.hadoop.hive.metastore.ObjectStore15/04/01 14:41:44
INFO ObjectStore: ObjectStore, initialize called15/04/01 14:41:45 INFO
Persistence: Property hive.metastore.integral.jdo.pushdown unknown -
will be ignored15/04/01 14:41:45 INFO Persistence: Property
datanucleus.cache.level2 unknown - will be ignored15/04/01 14:41:45
INFO BlockManager: Removing broadcast 015/04/01 14:41:45 INFO
BlockManager: Removing block broadcast_015/04/01 14:41:45 INFO
MemoryStore: Block broadcast_0 of size 1272 dropped from memory (free
278018571)15/04/01 14:41:45 INFO BlockManager: Removing block
broadcast_0_piece015/04/01 14:41:45 INFO MemoryStore: Block
broadcast_0_piece0 of size 869 dropped from memory (free
278019440)15/04/01 14:41:45 INFO BlockManagerInfo: Removed
broadcast_0_piece0 on 192.168.1.5:63230 in memory (size: 869.0 B,
free: 265.1 MB)15/04/01 14:41:45 INFO BlockManagerMaster: Updated info
of block broadcast_0_piece015/04/01 14:41:45 INFO BlockManagerInfo:
Removed broadcast_0_piece0 on 192.168.1.5:63278 in memory (size: 869.0
B, free: 530.0 MB)15/04/01 14:41:45 INFO ContextCleaner: Cleaned
broadcast 015/04/01 14:41:46 INFO ObjectStore: Setting MetaStore
object pin classes with
hive.metastore.cache.pinobjtypes="Table,StorageDescriptor,SerDeInfo,Partition,Database,Type,FieldSchema,Order"15/04/01
14:41:46 INFO Datastore: The class
"org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
"embedded-only" so does not have its own datastore table.15/04/01
14:41:46 INFO Datastore: The class
"org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
"embedded-only" so does not have its own datastore table.15/04/01
14:41:47 INFO Datastore: The class
"org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
"embedded-only" so does not have its own datastore table.15/04/01
14:41:47 INFO Datastore: The class
"org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
"embedded-only" so does not have its own datastore table.15/04/01
14:41:47 INFO Query: Reading in results for query
"org.datanucleus.store.rdbms.query.SQLQuery@0" since the connection
used is closing15/04/01 14:41:47 INFO ObjectStore: Initialized
ObjectStore15/04/01 14:41:47 INFO HiveMetaStore: Added admin role in
metastore15/04/01 14:41:47 INFO HiveMetaStore: Added public role in
metastore15/04/01 14:41:48 INFO HiveMetaStore: No user is added in
admin role, since config is empty15/04/01 14:41:48 INFO SessionState:
No Tez session required at this point.
hive.execution.engine=mr.15/04/01 14:41:49 INFO ParseDriver: Parsing
command: SELECT path, name, value, v1.peValue, v1.peName
FROM metric
lateral view json_tuple(pathElements, 'name', 'value') v1
as peName, peValue15/04/01 14:41:49 INFO ParseDriver:
Parse CompletedException in thread "main"
java.lang.ClassNotFoundException: json_tuple
at java.net.URLClassLoader$1.run(URLClassLoader.java:372)
at java.net.URLClassLoader$1.run(URLClassLoader.java:361)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:360)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at
org.apache.spark.sql.hive.HiveFunctionWrapper.createFunction(Shim13.scala:141)
at
org.apache.spark.sql.hive.HiveGenericUdtf.function$lzycompute(hiveUdfs.scala:261)
at org.apache.spark.sql.hive.HiveGenericUdtf.function(hiveUdfs.scala:261)
at
org.apache.spark.sql.hive.HiveGenericUdtf.outputInspector$lzycompute(hiveUdfs.scala:267)
at
org.apache.spark.sql.hive.HiveGenericUdtf.outputInspector(hiveUdfs.scala:267)
at
org.apache.spark.sql.hive.HiveGenericUdtf.outputDataTypes$lzycompute(hiveUdfs.scala:272)
at
org.apache.spark.sql.hive.HiveGenericUdtf.outputDataTypes(hiveUdfs.scala:272)
at org.apache.spark.sql.hive.HiveGenericUdtf.makeOutput(hiveUdfs.scala:278)
at
org.apache.spark.sql.catalyst.expressions.Generator.output(generators.scala:60)
at
org.apache.spark.sql.catalyst.plans.logical.Generate$$anonfun$1.apply(basicOperators.scala:50)
at
org.apache.spark.sql.catalyst.plans.logical.Generate$$anonfun$1.apply(basicOperators.scala:50)
at scala.Option.map(Option.scala:145)
at
org.apache.spark.sql.catalyst.plans.logical.Generate.generatorOutput(basicOperators.scala:50)
at
org.apache.spark.sql.catalyst.plans.logical.Generate.output(basicOperators.scala:60)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveChildren$1.apply(LogicalPlan.scala:118)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveChildren$1.apply(LogicalPlan.scala:118)
at
scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at
scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
at scala.collection.immutable.List.foreach(List.scala:318)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveChildren(LogicalPlan.scala:118)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$6$$anonfun$applyOrElse$1.applyOrElse(Analyzer.scala:159)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$6$$anonfun$applyOrElse$1.applyOrElse(Analyzer.scala:156)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$transformExpressionDown$1(QueryPlan.scala:71)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1$$anonfun$apply$1.apply(QueryPlan.scala:85)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.AbstractTraversable.map(Traversable.scala:105)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$1.apply(QueryPlan.scala:84)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:89)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:60)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$6.applyOrElse(Analyzer.scala:156)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$$anonfun$apply$6.applyOrElse(Analyzer.scala:153)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:206)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:153)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveReferences$.apply(Analyzer.scala:152)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
at
scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$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$lzycompute(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData$lzycompute(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:418)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:416)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:422)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:422)
at org.apache.spark.sql.SchemaRDD.collect(SchemaRDD.scala:444)
at
com.opsdatastore.elasticsearch.spark.ElasticSearchReadWrite$.main(ElasticSearchReadWrite.scala:119)
at
com.opsdatastore.elasticsearch.spark.ElasticSearchReadWrite.main(ElasticSearchReadWrite.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:358)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:75)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Json:
"metric": {
"path": "/PA/Pittsburgh/12345 Westbrook Drive/main/theromostat-1",
"pathElements": [
{
"node": "State",
"value": "PA"
},
{
"node": "City",
"value": "Pittsburgh"
},
{
"node": "Street",
"value": "12345 Westbrook Drive"
},
{
"node": "level",
"value": "main"
},
{
"node": "device",
"value": "thermostat"
}
],
"name": "Current Temperature",
"value": 29.590943279257175,
"timestamp": "2015-03-27T14:53:46+0000"
}
Here is the code that produces the error:
// Spark importsimport org.apache.spark.{SparkConf,
SparkContext}import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.{SchemaRDD,SQLContext}import
org.apache.spark.sql.hive._
// ES importsimport org.elasticsearch.spark._import
org.elasticsearch.spark.sql._
def main(args: Array[String]) {
val sc = sparkInit
@transient
val hiveContext = new org.apache.spark.sql.hive.HiveContext(sc)
import hiveContext._
val start = System.currentTimeMillis()
/*
* Read from ES and provide some insights with SparkSQL
*/
val esData = sc.esRDD(s"${ElasticSearch.Index}/${ElasticSearch.Type}")
esData.collect.foreach(println(_))
val end = System.currentTimeMillis()
println(s"Total time: ${end-start} ms")
println("Create Metric Temporary Table for querying")
val schemaRDD = hiveContext.sql(
"CREATE TEMPORARY TABLE metric " +
"USING org.elasticsearch.spark.sql " +
"OPTIONS (resource 'device/metric')" )
hiveContext.sql(
"""SELECT path, name, value, v1.peValue, v1.peName
FROM metric
lateral view json_tuple(pathElements, 'name', 'value') v1
as peName, peValue
""")
.collect.foreach(println(_))
}
}
More than likely I’m missing a jar, but not sure what that would be.
-Todd
