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Posted to user@spark.apache.org by Todd Nist <ts...@gmail.com> on 2015/04/01 21:19:21 UTC

Spark Sql - Missing Jar ? json_tuple NoClassDefFoundError

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