Hi,
How can I expect to work on HiveContext on the executor? If only the
driver can see HiveContext, does it mean I have to collect all datasets
(very large) to the driver and use HiveContext there? It will be memory
overload on the driver and fail.
BR,
Patcharee
On 07. juni 2015 11:51, Cheng Lian wrote:
Hi,
This is expected behavior. HiveContext.sql (and also
DataFrame.registerTempTable) is only expected to be invoked on driver
side. However, the closure passed to RDD.foreach is executed on
executor side, where no viable HiveContext instance exists.
Cheng
On 6/7/15 10:06 AM, patcharee wrote:
Hi,
I try to insert data into a partitioned hive table. The groupByKey is
to combine dataset into a partition of the hive table. After the
groupByKey, I converted the iterable[X] to DB by X.toList.toDF(). But
the hiveContext.sql throws NullPointerException, see below. Any
suggestions? What could be wrong? Thanks!
val varWHeightFlatRDD =
varWHeightRDD.flatMap(FlatMapUtilClass().flatKeyFromWrf).groupByKey()
.foreach(
x => {
val zone = x._1._1
val z = x._1._2
val year = x._1._3
val month = x._1._4
val df_table_4dim = x._2.toList.toDF()
df_table_4dim.registerTempTable("table_4Dim")
hiveContext.sql("INSERT OVERWRITE table 4dim partition
(zone=" + zone + ",z=" + z + ",year=" + year + ",month=" + month + ")
" +
"select date, hh, x, y, height, u, v, w, ph, phb, t, p,
pb, qvapor, qgraup, qnice, qnrain, tke_pbl, el_pbl from table_4Dim");
})
java.lang.NullPointerException
at org.apache.spark.sql.hive.HiveContext.sql(HiveContext.scala:100)
at
no.uni.computing.etl.LoadWrfIntoHiveOptReduce1$$anonfun$7.apply(LoadWrfIntoHiveOptReduce1.scala:113)
at
no.uni.computing.etl.LoadWrfIntoHiveOptReduce1$$anonfun$7.apply(LoadWrfIntoHiveOptReduce1.scala:103)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at
org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:798)
at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:798)
at
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1511)
at
org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1511)
at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
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