[geomesa-users] NoSuchMethodError: thrift.TabletClientService$Client.sen

[Diethard Steiner <diethard.steiner@xxxxxxxxx>]

Hi,

I am trying to follow the Spark Examples (http://www.geomesa.org/documentation/tutorials/spark.html), and while I managed to create the fat jar successfully, I get this error when running the spark job:

```
NoSuchMethodError: org.apache.accumulo.core.tabletserver.thrift.TabletClientService$Client.sendBaseOneway
```

(I did some research online which indicated that there might be some version problem, however, I seem to be using the correct versions ... )

Local Dev Env:

Linux Fedora 25

Java 8

Hadoop 2.8.0 (pseudo distributed setup)

Accumulo 1.8.1
geomesa-accumulo-dist_2.11-1.3.1
spark-2.1.0-bin-hadoop2.7

I am running Spark in standalone mode (so not via Yarn).

I am not using maven, but sbt. Here is my build.sbt:

```
name := "GeoMesaSparkExample"

version := "0.1"

scalaVersion := "2.11.8"

libraryDependencies ++= Seq(
  "org.apache.spark" %% "spark-core" % "2.0.2" % "provided"
  , "org.apache.spark" %% "spark-catalyst" % "2.0.2" % "provided"
  , "org.apache.spark" %% "spark-sql" % "2.0.2" % "provided"
/**  , "org.apache.spark" %% "spark-yarn" % "2.0.2" % "provided" **/
  , "org.locationtech.geomesa" %% "geomesa-accumulo-datastore" % "1.3.1"
  , "org.locationtech.geomesa" %% "geomesa-accumulo-spark" % "1.3.1"
  , "ch.qos.logback" % "logback-classic" % "1.1.7"
  , "com.typesafe.scala-logging" %% "scala-logging" % "3.5.0"
  , "org.apache.accumulo" % "accumulo-core" % "1.8.1"
)

assemblyMergeStrategy in assembly := {
  case path => {
    val strategy = (assemblyMergeStrategy in assembly).value(path)
    if (strategy == MergeStrategy.deduplicate) {
      MergeStrategy.first
    } else {
      strategy
    }
  }
}
```

CountByDay.scala

```
package examples

import java.text.SimpleDateFormat

import org.apache.hadoop.conf.Configuration
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}
import org.geotools.data.{DataStoreFinder, Query}
import org.geotools.factory.CommonFactoryFinder
import org.geotools.filter.text.ecql.ECQL
import org.locationtech.geomesa.accumulo.data.AccumuloDataStore
import org.locationtech.geomesa.spark.GeoMesaSpark
import org.opengis.feature.simple.SimpleFeature

import scala.collection.JavaConversions._

object CountByDay {

  val params = Map(
    "instanceId" -> "MY_INSTANCE",
    // zookeeper info can be found in ACCUMULO_HOME/conf/accumulo-site.xml
    "zookeepers" -> "localhost:2181",
    "user"       -> "root",
    "password"   -> "password",
    // no authentication required for local dev env setup
    //"auths"      -> "USER,ADMIN",
    "tableName"  -> "myNamespace.gdelt"
    )

  // see geomesa-tools/conf/sfts/gdelt/reference.conf
  val typeName = "gdelt"
  val geom     = "geom"
  val date     = "dtg"

  val bbox   = "-80, 35, -79, 36"
  val during = "2014-01-01T00:00:00.000Z/2014-01-31T12:00:00.000Z"

  // val filter = s"bbox($geom, $bbox) AND $date during $during"
  val filter = s"bbox($geom, $bbox)"

  def main(args: Array[String]) {
    // Get a handle to the data store
    val ds = DataStoreFinder.getDataStore(params).asInstanceOf[AccumuloDataStore]

    // Construct a CQL query to filter by bounding box
    val q = new Query(typeName, ECQL.toFilter(filter))

    // Configure Spark
    val conf = new SparkConf().setAppName("testSpark")
    val sc = SparkContext.getOrCreate(conf)

    // Get the appropriate spatial RDD provider
    val spatialRDDProvider = GeoMesaSpark(params)

    // Get an RDD[SimpleFeature] from the spatial RDD provider
    val rdd = spatialRDDProvider.rdd(new Configuration, sc, params, q)

    // Collect the results and print
    countByDay(rdd).collect().foreach(println)
    println("\n")

    ds.dispose()
  }

  def countByDay(rdd: RDD[SimpleFeature], dateField: String = "dtg") = {
    val dayAndFeature = rdd.mapPartitions { iter =>
      val df = new SimpleDateFormat("yyyyMMdd")
      val ff = CommonFactoryFinder.getFilterFactory2
      val exp = ff.property(dateField)
      iter.map { f => (df.format(exp.evaluate(f).asInstanceOf[java.util.Date]), f) }
    }
    dayAndFeature.map( x => (x._1, 1)).reduceByKey(_ + _)
  }
}
```

I submit the jar like so:

```
spark-submit --master local[4] \
  --class examples.CountByDay \
  target/scala-2.11/GeoMesaSparkExample-assembly-0.1.jar

```

Can someone please point out what I am doing wrong here?

Thanks,

Diethard