I placed it there. It was downloaded from MySql site. On Fri, Apr 3, 2015 at 6:25 AM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> wrote:
> Akhil > you mentioned /usr/local/spark/lib/mysql-connector-java-5.1.34-bin.jar . > how come you got this lib into spark/lib folder. > 1) did you place it there ? > 2) What is download location ? > > > On Fri, Apr 3, 2015 at 3:42 PM, Todd Nist <tsind...@gmail.com> wrote: > >> Started the spark shell with the one jar from hive suggested: >> >> ./bin/spark-shell --master spark://radtech.io:7077 --total-executor-cores 2 >> --driver-class-path /usr/local/spark/lib/mysql-connector-java-5.1.34-bin.jar >> --jars /opt/apache-hive-0.13.1-bin/lib/hive-exec-0.13.1.jar >> >> Results in the same error: >> >> scala> sql( | """SELECT path, name, value, v1.peValue, v1.peName >> | FROM metric_table | lateral view >> json_tuple(pathElements, 'name', 'value') v1 | as peName, >> peValue | """) >> 15/04/03 06:01:30 INFO ParseDriver: Parsing command: SELECT path, name, >> value, v1.peValue, v1.peName FROM metric_table lateral >> view json_tuple(pathElements, 'name', 'value') v1 as peName, >> peValue >> 15/04/03 06:01:31 INFO ParseDriver: Parse Completed >> res2: org.apache.spark.sql.SchemaRDD = >> SchemaRDD[5] at RDD at SchemaRDD.scala:108== Query Plan ==== Physical Plan == >> java.lang.ClassNotFoundException: json_tuple >> >> I will try the rebuild. Thanks again for the assistance. >> >> -Todd >> >> >> On Fri, Apr 3, 2015 at 5:34 AM, Akhil Das <ak...@sigmoidanalytics.com> >> wrote: >> >>> Can you try building Spark >>> <https://spark.apache.org/docs/1.2.0/building-spark.html#building-with-hive-and-jdbc-support%23building-with-hive-and-jdbc-support> >>> with hive support? Before that try to run the following: >>> >>> ./bin/spark-shell --master spark://radtech.io:7077 --total-executor- >>> cores 2 --driver-class-path /usr/local/spark/lib/mysql-connector-java-5. >>> 1.34-bin.jar --jars /opt/hive/0.13.1/lib/hive-exec.jar >>> >>> Thanks >>> Best Regards >>> >>> On Fri, Apr 3, 2015 at 2:55 PM, Todd Nist <tsind...@gmail.com> wrote: >>> >>>> Hi Akhil, >>>> >>>> This is for version 1.2.1. Well the other thread that you reference >>>> was me attempting it in 1.3.0 to see if the issue was related to 1.2.1. I >>>> did not build Spark but used the version from the Spark download site for >>>> 1.2.1 Pre Built for Hadoop 2.4 or Later. >>>> >>>> Since I get the error in both 1.2.1 and 1.3.0, >>>> >>>> 15/04/01 14:41:49 INFO ParseDriver: Parse Completed Exception in >>>> thread "main" java.lang.ClassNotFoundException: json_tuple at >>>> java.net.URLClassLoader$1.run( >>>> >>>> It looks like I just don't have the jar. Even including all jars in >>>> the $HIVE/lib directory did not seem to work. Though when looking in >>>> $HIVE/lib for 0.13.1, I do not see any json serde or jackson files. I do >>>> see that hive-exec.jar contains >>>> the org/apache/hadoop/hive/ql/udf/generic/GenericUDTFJSONTuple class. Do >>>> you know if there is another Jar that is required or should it work just by >>>> including all jars from $HIVE/lib? >>>> >>>> I can build it locally, but did not think that was required based on >>>> the version I downloaded; is that not the case? >>>> >>>> Thanks for the assistance. >>>> >>>> -Todd >>>> >>>> >>>> On Fri, Apr 3, 2015 at 2:06 AM, Akhil Das <ak...@sigmoidanalytics.com> >>>> wrote: >>>> >>>>> How did you build spark? which version of spark are you having? >>>>> Doesn't this thread already explains it? >>>>> https://www.mail-archive.com/user@spark.apache.org/msg25505.html >>>>> >>>>> Thanks >>>>> Best Regards >>>>> >>>>> On Thu, Apr 2, 2015 at 11:10 PM, Todd Nist <tsind...@gmail.com> wrote: >>>>> >>>>>> Hi Akhil, >>>>>> >>>>>> Tried your suggestion to no avail. I actually to not see and >>>>>> "jackson" or "json serde" jars in the $HIVE/lib directory. This is hive >>>>>> 0.13.1 and spark 1.2.1 >>>>>> >>>>>> Here is what I did: >>>>>> >>>>>> I have added the lib folder to the –jars option when starting the >>>>>> spark-shell, >>>>>> but the job fails. The hive-site.xml is in the $SPARK_HOME/conf >>>>>> directory. >>>>>> >>>>>> I start the spark-shell as follows: >>>>>> >>>>>> ./bin/spark-shell --master spark://radtech.io:7077 >>>>>> --total-executor-cores 2 --driver-class-path >>>>>> /usr/local/spark/lib/mysql-connector-java-5.1.34-bin.jar >>>>>> >>>>>> and like this >>>>>> >>>>>> ./bin/spark-shell --master spark://radtech.io:7077 >>>>>> --total-executor-cores 2 --driver-class-path >>>>>> /usr/local/spark/lib/mysql-connector-java-5.1.34-bin.jar --jars >>>>>> /opt/hive/0.13.1/lib/* >>>>>> >>>>>> I’m just doing this in the spark-shell now: >>>>>> >>>>>> import org.apache.spark.sql.hive._val sqlContext = new >>>>>> HiveContext(sc)import sqlContext._case class MetricTable(path: String, >>>>>> pathElements: String, name: String, value: String)val mt = new >>>>>> MetricTable("""path": "/DC1/HOST1/""", >>>>>> """pathElements": [{"node": "DataCenter","value": "DC1"},{"node": >>>>>> "host","value": "HOST1"}]""", >>>>>> """name": "Memory Usage (%)""", >>>>>> """value": 29.590943279257175""")val rdd1 = sc.makeRDD(List(mt)) >>>>>> rdd1.printSchema() >>>>>> rdd1.registerTempTable("metric_table") >>>>>> sql( >>>>>> """SELECT path, name, value, v1.peValue, v1.peName >>>>>> FROM metric_table >>>>>> lateral view json_tuple(pathElements, 'name', 'value') v1 >>>>>> as peName, peValue >>>>>> """) >>>>>> .collect.foreach(println(_)) >>>>>> >>>>>> It results in the same error: >>>>>> >>>>>> 15/04/02 12:33:59 INFO ParseDriver: Parsing command: SELECT path, name, >>>>>> value, v1.peValue, v1.peName FROM metric_table lateral >>>>>> view json_tuple(pathElements, 'name', 'value') v1 as peName, >>>>>> peValue >>>>>> 15/04/02 12:34:00 INFO ParseDriver: Parse Completed >>>>>> res2: org.apache.spark.sql.SchemaRDD = >>>>>> SchemaRDD[5] at RDD at SchemaRDD.scala:108== Query Plan ==== Physical >>>>>> Plan == >>>>>> java.lang.ClassNotFoundException: json_tuple >>>>>> >>>>>> Any other suggestions or am I doing something else wrong here? >>>>>> >>>>>> -Todd >>>>>> >>>>>> >>>>>> >>>>>> On Thu, Apr 2, 2015 at 2:00 AM, Akhil Das <ak...@sigmoidanalytics.com >>>>>> > wrote: >>>>>> >>>>>>> Try adding all the jars in your $HIVE/lib directory. If you want the >>>>>>> specific jar, you could look fr jackson or json serde in it. >>>>>>> >>>>>>> Thanks >>>>>>> Best Regards >>>>>>> >>>>>>> On Thu, Apr 2, 2015 at 12:49 AM, Todd Nist <tsind...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> 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 >>>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> > > > -- > Deepak > >
