Hi Randy,
z.load() supposed to make dependencies available to all driver and
executors.
However, it might not work correctly in yarn-client mode. Are you using
yarn-client mode?
Best,
moon
On Mon, Aug 24, 2015 at 9:12 AM Randy Gelhausen <rgel...@gmail.com> wrote:
> Any ideas?
>
> Is z.load supposed to make dependencies available to all Spark JVMs
> (driver AND executors)?
>
> Thanks,
> -Randy
>
> On Sun, Aug 23, 2015 at 2:41 PM, Randy Gelhausen <rgel...@gmail.com>
> wrote:
>
>> It seems Spark executors are not being provided with the requisite
>> dependencies. With spark-shell I can pass --jars /path/to/dep.jar. How can
>> we achieve this with Zeppelin, preferable inside a Note?
>>
>> %spark.dep
>> z.addRepo("hortonworks").url("
>> http://repo.hortonworks.com/content/repositories/releases/";)
>> z.load("org.apache.phoenix:phoenix-spark:4.4.0.2.3.0.0-2557")
>> z.load("org.apache.phoenix:phoenix-core:4.4.0.2.3.0.0-2557")
>> z.load("com.databricks:spark-csv_2.10:1.2.0")
>>
>> %spark
>> import org.apache.spark.sql._
>> import org.apache.phoenix.spark._
>> import java.sql.Connection
>> import java.sql.DriverManager
>>
>> val input = "/user/root/crimes/atlanta"
>> val zkUrl = "docker.dev:2181:/hbase-unsecure"
>> val table = "CRIMES"
>>
>> // Read CSV file, clean field names
>> var df =
>> sqlContext.read.format("com.databricks.spark.csv").option("header",
>> "true").option("DROPMALFORMED", "true").load(input)
>> val columns = df.columns.map(x => x.toUpperCase.replaceAll(" ", "_"))
>> df = df.toDF(columns:_*)
>>
>> df.save("org.apache.phoenix.spark", SaveMode.Overwrite, Map("table" ->
>> table, "zkUrl" -> zkUrl))
>>
>> Results:
>> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
>> in stage 1.0 failed 4 times, most recent failure: Lost task 0.3 in stage
>> 1.0 (TID 5, docker.dev): java.lang.RuntimeException: java.sql.SQLException:
>> No suitable driver found for jdbc:phoenix:docker.dev:2181:/hbase-unsecure;
>> at
>> org.apache.phoenix.mapreduce.PhoenixOutputFormat.getRecordWriter(PhoenixOutputFormat.java:58)
>> at
>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1030)
>> at
>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsNewAPIHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1014)
>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63) at
>> org.apache.spark.scheduler.Task.run(Task.scala:70) at
>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>> at java.lang.Thread.run(Thread.java:745) Caused by: java.sql.SQLException:
>> No suitable driver found for jdbc:phoenix:docker.dev:2181:/hbase-unsecure;
>> at java.sql.DriverManager.getConnection(DriverManager.java:689) at
>> java.sql.DriverManager.getConnection(DriverManager.java:208) at
>> org.apache.phoenix.mapreduce.util.ConnectionUtil.getConnection(ConnectionUtil.java:92)
>> at
>> org.apache.phoenix.mapreduce.util.ConnectionUtil.getOutputConnection(ConnectionUtil.java:80)
>> at
>> org.apache.phoenix.mapreduce.util.ConnectionUtil.getOutputConnection(ConnectionUtil.java:68)
>> at
>> org.apache.phoenix.mapreduce.PhoenixRecordWriter.<init>(PhoenixRecordWriter.java:49)
>> at
>> org.apache.phoenix.mapreduce.PhoenixOutputFormat.getRecordWriter(PhoenixOutputFormat.java:55)
>> ... 8 more Driver stacktrace: at
>> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1273)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1264)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1263)
>> at
>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at
>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1263)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
>> at scala.Option.foreach(Option.scala:236) at
>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1457)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1418)
>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>>
>
>
