Mao, Wei created SPARK-13758:
--------------------------------
Summary: Error message is misleading when RDD refer to null spark
context
Key: SPARK-13758
URL: https://issues.apache.org/jira/browse/SPARK-13758
Project: Spark
Issue Type: Bug
Components: Spark Core, Streaming
Reporter: Mao, Wei
We have a recoverable Spark streaming job with checkpoint enabled, it could be
executed correctly at first time, but throw following exception when restarted
and recovered from checkpoint.
{noformat}
org.apache.spark.SparkException: RDD transformations and actions can only be
invoked by the driver, not inside of other transformations; for example,
rdd1.map(x => rdd2.values.count() * x) is invalid because the values
transformation and count action cannot be performed inside of the rdd1.map
transformation. For more information, see SPARK-5063.
at org.apache.spark.rdd.RDD.org$apache$spark$rdd$RDD$$sc(RDD.scala:87)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:352)
at org.apache.spark.rdd.RDD.union(RDD.scala:565)
at
org.apache.spark.streaming.Repo$$anonfun$createContext$1.apply(Repo.scala:23)
at
org.apache.spark.streaming.Repo$$anonfun$createContext$1.apply(Repo.scala:19)
at
org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
...
{noformat}
According to exception, it shows I invoked transformations and actions in other
transformations, but I did not. The real reason is that I used external RDD in
DStream operation. External RDD data is not stored in checkpoint, so that
during recovering, the initial value of _sc in this RDD is assigned to null and
hit above exception. But you can find the error message is misleading, it
indicates nothing about the real issue
Here is the code to reproduce it.
{code:java}
object Repo {
def createContext(ip: String, port: Int, checkpointDirectory:
String):StreamingContext = {
println("Creating new context")
val sparkConf = new SparkConf().setAppName("Repo").setMaster("local[2]")
val ssc = new StreamingContext(sparkConf, Seconds(2))
ssc.checkpoint(checkpointDirectory)
var cached = ssc.sparkContext.parallelize(Seq("apple, banana"))
val words = ssc.socketTextStream(ip, port).flatMap(_.split(" "))
words.foreachRDD((rdd: RDD[String]) => {
val res = rdd.map(word => (word, word.length)).collect()
println("words: " + res.mkString(", "))
cached = cached.union(rdd)
cached.checkpoint()
println("cached words: " + cached.collect.mkString(", "))
})
ssc
}
def main(args: Array[String]) {
val ip = "localhost"
val port = 9999
val dir = "/home/maowei/tmp"
val ssc = StreamingContext.getOrCreate(dir,
() => {
createContext(ip, port, dir)
})
ssc.start()
ssc.awaitTermination()
}
}
{code}
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