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I cannot access programmatically a file within a CDH 5.4.2.0 image running in vmware

avatar
Explorer

I have a vmware cloudera image, cdh-5.4.2.0 running with centos6, i am using OS X as my host machine, i have modified my /etc/hosts file with a line like this:

MacBook-Pro-Retina-de-Alonso:bin aironman$ cat /etc/hosts
127.0.0.1 localhost
127.0.0.1 my-cassandra-node-001
255.255.255.255 broadcasthost
::1 localhost
192.168.30.137 quickstart.cloudera quickstart

You can see that i can reach to the vmware machine from the host machine:

$:bin aironman$ ping quickstart.cloudera
PING quickstart.cloudera (192.168.30.137): 56 data bytes
64 bytes from 192.168.30.137: icmp_seq=0 ttl=64 time=0.293 ms
64 bytes from 192.168.30.137: icmp_seq=1 ttl=64 time=0.273 ms
64 bytes from 192.168.30.137: icmp_seq=2 ttl=64 time=0.207 ms
64 bytes from 192.168.30.137: icmp_seq=3 ttl=64 time=0.240 ms
64 bytes from 192.168.30.137: icmp_seq=4 ttl=64 time=0.402 ms
^C
--- quickstart.cloudera ping statistics ---
5 packets transmitted, 5 packets received, 0.0% packet loss
round-trip min/avg/max/stddev = 0.207/0.283/0.402/0.066 ms

And i can reach to 8020 port from that machine:

$:bin aironman$ telnet quickstart.cloudera 8020
Trying 192.168.30.137...
Connected to quickstart.cloudera.
Escape character is '^]'.

I can do a ls command in the vmware machine:

[cloudera@quickstart ~]$ hdfs dfs -ls /user/cloudera/ratings.csv
-rw-r--r-- 1 cloudera cloudera 16906296 2016-05-30 11:29 /user/cloudera/ratings.csv

I can read its content:

[cloudera@quickstart ~]$ hdfs dfs -cat /user/cloudera/ratings.csv | wc -l
568454

The code is quite simple, just trying to map its content:

 

val ratingFile="hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv"

case class AmazonRating(userId: String, productId: String, rating: Double)

val NumRecommendations = 10
val MinRecommendationsPerUser = 10
val MaxRecommendationsPerUser = 20
val MyUsername = "myself"
val NumPartitions = 20

  
println("Using this ratingFile: " + ratingFile)
  // first create an RDD out of the rating file
val rawTrainingRatings = sc.textFile(ratingFile).map {
    line =>
      val Array(userId, productId, scoreStr) = line.split(",")
      AmazonRating(userId, productId, scoreStr.toDouble)
}

  // only keep users that have rated between MinRecommendationsPerUser and MaxRecommendationsPerUser products
val trainingRatings = rawTrainingRatings.groupBy(_.userId).filter(r => MinRecommendationsPerUser <= r._2.size  && r._2.size < MaxRecommendationsPerUser).flatMap(_._2).repartition(NumPartitions).cache()

println(s"Parsed $ratingFile. Kept ${trainingRatings.count()} ratings out of ${rawTrainingRatings.count()}")

I am getting this message:

 

Parsed hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv. Kept 0 ratings out of 568454

because if i run the exact code in the spark-shell, i got this message:

Parsed hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv. Kept 73279 ratings out of 568454


Why is it working fine within the spark-shell but it is not programmatically running in the vmware image?

Thank your for reading until here.

1 ACCEPTED SOLUTION

avatar
Rising Star

It looks like the networking issue is resolved with the changes to hostfiles. For the remaining issues you may have better luck posting in the Spark forum specifically (http://community.cloudera.com/t5/Advanced-Analytics-Apache-Spark/bd-p/Spark) - I suspect outside of the forum there won't be that many readers familiar with the tricker parts of Spark configuration and SBT-pack in particular.

View solution in original post

15 REPLIES 15

avatar
Explorer

Updating the thread with better info, why i cant modify the previous thread like in StackOverflow?

 

I have a vmware cloudera image, cdh-5.7 running with centos6.8, i am using OS X as my development machine, and the cdh image to run the code, i have modified my /etc/hosts file located in the cdh image with a line like this:

 

127.0.0.1 quickstart.cloudera quickstart localhost localhost.domain
192.168.30.138 quickstart.cloudera quickstart localhost localhost.domain


The cloudera version that i am running is:

 

[cloudera@quickstart bin]$ cat /usr/lib/hadoop/cloudera/cdh_version.properties
# Autogenerated build properties
version=2.6.0-cdh5.7.0
git.hash=c00978c67b0d3fe9f3b896b5030741bd40bf541a
cloudera.hash=c00978c67b0d3fe9f3b896b5030741bd40bf541a
cloudera.cdh.hash=e7465a27c5da4ceee397421b89e924e67bc3cbe1
cloudera.cdh-packaging.hash=8f9a1632ebfb9da946f7d8a3a8cf86efcdccec76
cloudera.base-branch=cdh5-base-2.6.0
cloudera.build-branch=cdh5-2.6.0_5.7.0
cloudera.pkg.version=2.6.0+cdh5.7.0+1280
cloudera.pkg.release=1.cdh5.7.0.p0.92
cloudera.cdh.release=cdh5.7.0
cloudera.build.time=2016.03.23-18:30:29GMT

I can do a ls command in the vmware machine:

 

[cloudera@quickstart ~]$ hdfs dfs -ls /user/cloudera/ratings.csv
-rw-r--r-- 1 cloudera cloudera 16906296 2016-05-30 11:29 /user/cloudera/ratings.csv
I can read its content:
[cloudera@quickstart ~]$ hdfs dfs -cat /user/cloudera/ratings.csv | wc -l
568454

The code is quite simple, just trying to map its content:

 

val ratingFile="hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv"
case class AmazonRating(userId: String, productId: String, rating: Double)
val NumRecommendations = 10
val MinRecommendationsPerUser = 10
val MaxRecommendationsPerUser = 20
val MyUsername = "myself"
val NumPartitions = 20

println("Using this ratingFile: " + ratingFile)
// first create an RDD out of the rating file
val rawTrainingRatings = sc.textFile(ratingFile).map {
line =>
val Array(userId, productId, scoreStr) = line.split(",")
AmazonRating(userId, productId, scoreStr.toDouble)
}
// only keep users that have rated between MinRecommendationsPerUser and MaxRecommendationsPerUser products
val trainingRatings = rawTrainingRatings.groupBy(_.userId).filter(r => MinRecommendationsPerUser <= r._2.size && r._2.size < MaxRecommendationsPerUser).flatMap(_._2).repartition(NumPartitions).cache()
println(s"Parsed $ratingFile. Kept ${trainingRatings.count()} ratings out of ${rawTrainingRatings.count()}")

I am getting this message:

Parsed hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv. Kept 0 ratings out of 568454

because if i run the exact code within the spark-shell, i got this message:

Parsed hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv. Kept 73279 ratings out of 568454

Why is it working fine within the spark-shell but it is not programmatically running in the vmware image?

 

UPDATE

I am running the code using sbt-pack plugin to generate unix commands and run them within the vmware image which has the spark pseudocluster,

This is the code i use to instantiate the sparkconf:

val sparkConf = new SparkConf().setAppName("AmazonKafkaConnector")
.setMaster("local[4]") .set("spark.driver.allowMultipleContexts", "true")
val sc = new SparkContext(sparkConf)
val sqlContext = new SQLContext(sc)
val ssc = new StreamingContext(sparkConf, Seconds(2))
//this checkpointdir should be in a conf file, for now it is hardcoded!
val streamingCheckpointDir = "/home/cloudera/my-recommendation-spark-engine/checkpoint"
ssc.checkpoint(streamingCheckpointDir)

I have tried to use this way of setting spark master, but an exception raises, i suspect that this is symptomatic of my problem. //.setMaster("spark://quickstart.cloudera:7077")

 

The exception when i try to use the fully qualified domain name:

.setMaster("spark://quickstart.cloudera:7077")

java.io.IOException: Failed to connect to quickstart.cloudera/127.0.0.1:7077
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:200)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:187)
at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:183)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: quickstart.cloudera/127.0.0.1:7077
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)
at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)

I can ping to quickstart.cloudera in the cloudera terminal, so why i can't use .setMaster("spark://quickstart.cloudera:7077") instead of .setMaster("local[*]"):

 

[cloudera@quickstart bin]$ ping quickstart.cloudera
PING quickstart.cloudera (127.0.0.1) 56(84) bytes of data.
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=1 ttl=64 time=0.019 ms
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=2 ttl=64 time=0.026 ms
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=3 ttl=64 time=0.026 ms
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=4 ttl=64 time=0.028 ms
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=5 ttl=64 time=0.026 ms
64 bytes from quickstart.cloudera (127.0.0.1): icmp_seq=6 ttl=64 time=0.020 ms

And the port 7077 is listening to incoming calls:

 

[cloudera@quickstart bin]$ netstat -nap | grep 7077
(Not all processes could be identified, non-owned process info
will not be shown, you would have to be root to see it all.)
tcp 0 0 192.168.30.138:7077 0.0.0.0:* LISTEN

[cloudera@quickstart bin]$ ping 192.168.30.138
PING 192.168.30.138 (192.168.30.138) 56(84) bytes of data.
64 bytes from 192.168.30.138: icmp_seq=1 ttl=64 time=0.023 ms
64 bytes from 192.168.30.138: icmp_seq=2 ttl=64 time=0.026 ms
64 bytes from 192.168.30.138: icmp_seq=3 ttl=64 time=0.028 ms
^C
--- 192.168.30.138 ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2810ms
rtt min/avg/max/mdev = 0.023/0.025/0.028/0.006 ms
[cloudera@quickstart bin]$ ifconfig
eth2 Link encap:Ethernet HWaddr 00:0C:29:6F:80:D2 
inet addr:192.168.30.138 Bcast:192.168.30.255 Mask:255.255.255.0
UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1
RX packets:8612 errors:0 dropped:0 overruns:0 frame:0
TX packets:8493 errors:0 dropped:0 overruns:0 carrier:0
collisions:0 txqueuelen:1000 
RX bytes:2917515 (2.7 MiB) TX bytes:849750 (829.8 KiB)
lo Link encap:Local Loopback 
inet addr:127.0.0.1 Mask:255.0.0.0
UP LOOPBACK RUNNING MTU:65536 Metric:1
RX packets:57534 errors:0 dropped:0 overruns:0 frame:0
TX packets:57534 errors:0 dropped:0 overruns:0 carrier:0
collisions:0 txqueuelen:0 
RX bytes:44440656 (42.3 MiB) TX bytes:44440656 (42.3 MiB)

I think that this must be a misconfiguration in a cloudera configuration file, but which one?

 

Thank you very much for reading until here.

avatar
Rising Star

Your original question is answered here: http://community.cloudera.com/t5/Apache-Hadoop-Concepts-and/About-ports-to-write-to-HDFS-in-pseudo-d...

 

One problem that may explain some of the behavior you're seeing in Spark is that your hosts file has quickstart.cloudera mapped to both 127.0.0.1 and your bridged IP address. quickstart.cloudera should only resolve to the IP address you'll use everywhere - otherwise what you see happening is Spark is looking up the IP for quickstart.cloudera and thinking it's 127.0.0.1 - but that means different machines depending on where it's resolved.

avatar
Explorer

Hi Sean, thanks for the answer, but, ¿what are you exactly suggesting i have to do? I mean, i have a vmware process running a cloudera image simulating a spark cluster inside of a OS X host. In this host i am running a single instance of kafka and the spark process has not any problem trying to reach to that kafka process when i use setMaster("local[*]"), but the software crashes quickly when i try to use setMaster("spark://quickstart.cloudera:7077"). An exception rises...

 

java.io.IOException: Failed to connect to quickstart.cloudera/127.0.0.1:7077
        at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
        at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
        at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:200)
        at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:187)
        at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:183)
        at java.util.concurrent.FutureTask.run(FutureTask.java:262)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: quickstart.cloudera/127.0.0.1:7077
        at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
        at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)
        at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
        at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
        at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
        at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
        at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
        at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)

I was thinking that this could be related with used dependencies, this is my build.sbt:

 

[cloudera@quickstart awesome-recommendation-engine]$ cat build.sbt 
name := "my-recommendation-spark-engine"

version := "1.0-SNAPSHOT"

scalaVersion := "2.10.4"

val sparkVersion = "1.6.1"

val akkaVersion = "2.3.11" // override Akka to be this version to match the one in Spark

libraryDependencies ++= Seq(
  "org.apache.kafka" % "kafka_2.10" % "0.8.1"
      exclude("javax.jms", "jms")
      exclude("com.sun.jdmk", "jmxtools")
      exclude("com.sun.jmx", "jmxri"),
   //not working play module!! check
   //jdbc,
   //anorm,
   //cache,
   // HTTP client
   "net.databinder.dispatch" %% "dispatch-core" % "0.11.1",
   // HTML parser
   "org.jodd" % "jodd-lagarto" % "3.5.2",
   "com.typesafe" % "config" % "1.2.1",
   "com.typesafe.play" % "play-json_2.10" % "2.4.0-M2",
   "org.scalatest" % "scalatest_2.10" % "2.2.1" % "test",
   "org.twitter4j" % "twitter4j-core" % "4.0.2",
   "org.twitter4j" % "twitter4j-stream" % "4.0.2",
   "org.codehaus.jackson" % "jackson-core-asl" % "1.6.1",
   "org.scala-tools.testing" % "specs_2.8.0" % "1.6.5" % "test",
   "org.apache.spark" % "spark-streaming-kafka_2.10" % "1.6.1",
   "org.apache.spark" % "spark-core_2.10" % "1.6.1",
   "org.apache.spark" % "spark-streaming_2.10" % "1.6.1",
   "org.apache.spark" % "spark-sql_2.10" % "1.6.1",
   "org.apache.spark" % "spark-mllib_2.10" % "1.6.1",
   "com.google.code.gson" % "gson" % "2.6.2",
   "commons-cli" % "commons-cli" % "1.3.1",
   "com.stratio.datasource" % "spark-mongodb_2.10" % "0.11.1",
   // Akka
   "com.typesafe.akka" %% "akka-actor" % akkaVersion,
   "com.typesafe.akka" %% "akka-slf4j" % akkaVersion,
   // MongoDB
   "org.reactivemongo" %% "reactivemongo" % "0.10.0"
)

packAutoSettings

resolvers ++= Seq(
  "JBoss Repository" at "http://repository.jboss.org/nexus/content/repositories/releases/",
  "Spray Repository" at "http://repo.spray.cc/",
  "Cloudera Repository" at "https://repository.cloudera.com/artifactory/cloudera-repos/",
  "Akka Repository" at "http://repo.akka.io/releases/",
  "Twitter4J Repository" at "http://twitter4j.org/maven2/",
  "Apache HBase" at "https://repository.apache.org/content/repositories/releases",
  "Twitter Maven Repo" at "http://maven.twttr.com/",
  "scala-tools" at "https://oss.sonatype.org/content/groups/scala-tools",
  "Typesafe repository" at "http://repo.typesafe.com/typesafe/releases/",
  "Second Typesafe repo" at "http://repo.typesafe.com/typesafe/maven-releases/",
  "Mesosphere Public Repository" at "http://downloads.mesosphere.io/maven",
  Resolver.sonatypeRepo("public")
)

Could it be that i have to use the spark jars from cloudera? With this build.sbt, i am getting that exception...

avatar
Explorer

Updating thread with relevant update (06/01/2016):

 

I have a vmware cloudera image, cdh-5.7 running with centos6.8, i am using OS X as my development machine, and the cdh image to run the code.

 

UPDATE

This is the build.sbt that i am currently using, i just have updated spark version from official (1.6.1) to 1.6.0-cdh5.7.0:

 

[cloudera@quickstart awesome-recommendation-engine]$ cat build.sbt 
name := "my-recommendation-spark-engine"
version := "1.0-SNAPSHOT"
scalaVersion := "2.10.4"
val sparkVersion = "1.6.0-cdh5.7.0"
val akkaVersion = "2.3.11" // override Akka to be this version to match the one in Spark
libraryDependencies ++= Seq(
"org.apache.kafka" % "kafka_2.10" % "0.8.1"
exclude("javax.jms", "jms")
exclude("com.sun.jdmk", "jmxtools")
exclude("com.sun.jmx", "jmxri"),
// HTTP client to request data to Amazon
"net.databinder.dispatch" %% "dispatch-core" % "0.11.1",
// HTML parser
"org.jodd" % "jodd-lagarto" % "3.5.2",
"com.typesafe" % "config" % "1.2.1",
"com.typesafe.play" % "play-json_2.10" % "2.4.0-M2",
"org.scalatest" % "scalatest_2.10" % "2.2.1" % "test",
"org.twitter4j" % "twitter4j-core" % "4.0.2",
"org.twitter4j" % "twitter4j-stream" % "4.0.2",
"org.codehaus.jackson" % "jackson-core-asl" % "1.6.1",
"org.scala-tools.testing" % "specs_2.8.0" % "1.6.5" % "test",
"org.apache.spark" % "spark-streaming-kafka_2.10" % "1.6.0-cdh5.7.0",
"org.apache.spark" % "spark-core_2.10" % "1.6.0-cdh5.7.0",
"org.apache.spark" % "spark-streaming_2.10" % "1.6.0-cdh5.7.0",
"org.apache.spark" % "spark-sql_2.10" % "1.6.0-cdh5.7.0",
"org.apache.spark" % "spark-mllib_2.10" % "1.6.0-cdh5.7.0",
"com.google.code.gson" % "gson" % "2.6.2",
"commons-cli" % "commons-cli" % "1.3.1",
"com.stratio.datasource" % "spark-mongodb_2.10" % "0.11.1",
// Akka
"com.typesafe.akka" %% "akka-actor" % akkaVersion,
"com.typesafe.akka" %% "akka-slf4j" % akkaVersion,
// MongoDB
"org.reactivemongo" %% "reactivemongo" % "0.10.0"
)
packAutoSettings
resolvers ++= Seq(
"JBoss Repository" at "http://repository.jboss.org/nexus/content/repositories/releases/",
"Spray Repository" at "http://repo.spray.cc/",
"Cloudera Repository" at "https://repository.cloudera.com/artifactory/cloudera-repos/",
"Akka Repository" at "http://repo.akka.io/releases/",
"Twitter4J Repository" at "http://twitter4j.org/maven2/",
"Apache HBase" at "https://repository.apache.org/content/repositories/releases",
"Twitter Maven Repo" at "http://maven.twttr.com/",
"scala-tools" at "https://oss.sonatype.org/content/groups/scala-tools",
"Typesafe repository" at "http://repo.typesafe.com/typesafe/releases/",
"Second Typesafe repo" at "http://repo.typesafe.com/typesafe/maven-releases/",
"Mesosphere Public Repository" at "http://downloads.mesosphere.io/maven",
Resolver.sonatypeRepo("public")
)


This is my /etc/hosts file located in the cdh image with a line like this:

127.0.0.1 quickstart.cloudera quickstart localhost localhost.domain


The cloudera version that i am running is:

 

 

[cloudera@quickstart bin]$ cat /usr/lib/hadoop/cloudera/cdh_version.properties
# Autogenerated build properties
version=2.6.0-cdh5.7.0
git.hash=c00978c67b0d3fe9f3b896b5030741bd40bf541a
cloudera.hash=c00978c67b0d3fe9f3b896b5030741bd40bf541a
cloudera.cdh.hash=e7465a27c5da4ceee397421b89e924e67bc3cbe1
cloudera.cdh-packaging.hash=8f9a1632ebfb9da946f7d8a3a8cf86efcdccec76
cloudera.base-branch=cdh5-base-2.6.0
cloudera.build-branch=cdh5-2.6.0_5.7.0
cloudera.pkg.version=2.6.0+cdh5.7.0+1280
cloudera.pkg.release=1.cdh5.7.0.p0.92
cloudera.cdh.release=cdh5.7.0
cloudera.build.time=2016.03.23-18:30:29GMT

I can do a ls command in the vmware machine:

[cloudera@quickstart ~]$ hdfs dfs -ls /user/cloudera/ratings.csv
-rw-r--r-- 1 cloudera cloudera 16906296 2016-05-30 11:29 /user/cloudera/ratings.csv

I can read its content:

[cloudera@quickstart ~]$ hdfs dfs -cat /user/cloudera/ratings.csv | wc -l
568454

The code is quite simple, just trying to map its content:

 

val ratingFile="hdfs://192.168.1.40:8020/user/cloudera/ratings.csv"
//where 192.168.1.40 is the eth0 assigned ip of cloudera image
case class AmazonRating(userId: String, productId: String, rating: Double)
val NumRecommendations = 10
val MinRecommendationsPerUser = 10
val MaxRecommendationsPerUser = 20
val MyUsername = "myself"
val NumPartitions = 20
println("Using this ratingFile: " + ratingFile)
// first create an RDD out of the rating file
val rawTrainingRatings = sc.textFile(ratingFile).map {
line =>
val Array(userId, productId, scoreStr) = line.split(",")
AmazonRating(userId, productId, scoreStr.toDouble)
}
// only keep users that have rated between MinRecommendationsPerUser and MaxRecommendationsPerUser products
val trainingRatings = rawTrainingRatings.groupBy(_.userId).filter(r => MinRecommendationsPerUser <= r._2.size && r._2.size < MaxRecommendationsPerUser).flatMap(_._2).repartition(NumPartitions).cache()
println(s"Parsed $ratingFile. Kept ${trainingRatings.count()} ratings out of ${rawTrainingRatings.count()}")

I am getting this message:

**16/06/01 17:20:04 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources**


because if i run the exact code within the spark-shell, i got this message:

Parsed hdfs://quickstart.cloudera:8020/user/cloudera/ratings.csv. Kept 73279 ratings out of 568454

Why is it working fine within the spark-shell but it is not programmatically running in the vmware image?

 

UPDATE

I am running the code using sbt-pack plugin to generate unix commands and run them within the vmware image which has the spark pseudocluster,

This is the code i use to instantiate the sparkconf:

val sparkConf = new SparkConf().setAppName("AmazonKafkaConnector")
.setMaster("spark://192.168.1.40:7077") .set("spark.driver.allowMultipleContexts", "true")
val sc = new SparkContext(sparkConf)
val sqlContext = new SQLContext(sc)
val ssc = new StreamingContext(sparkConf, Seconds(2))
//this checkpointdir should be in a conf file, for now it is hardcoded!
val streamingCheckpointDir = "/home/cloudera/my-recommendation-spark-engine/checkpoint"
ssc.checkpoint(streamingCheckpointDir)

I think that this must be a misconfiguration in a cloudera configuration file, but which one?

 

UPDATE2 06/01/2016

 

Ok, changing the ip (192.168.1.40) instead of the fully qualified name (quickstart.cloudera) now eliminates the previous exception but now this warning arises:

 

**16/06/01 17:20:04 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources**

If i run the next commands:

[cloudera@quickstart awesome-recommendation-engine]$ sudo service spark-master status
Spark master is running [ OK ]
[cloudera@quickstart awesome-recommendation-engine]$ sudo service spark-worker status
Spark worker is running [ OK ]

I can see that spark-master and spark-worker are running, but when i check in 192.168.1.40:18081, the web page that checks spark-worker status, i see:

 

 

ID: worker-20160601173323-192.168.1.40-7078
Master URL:
Cores: 1 (0 Used)
Memory: 2.7 GB (0.0 B Used)
Back to Master
Running Executors (0)
ExecutorID Cores State Memory Job Details Logs

Nothing to show!, no ExecutorID, no Cores, no State, no Memory, nothing at all!

In fact, after few minutes or less, when i run the next status command:

[cloudera@quickstart awesome-recommendation-engine]$ sudo service spark-worker status
Spark worker is dead and pid file exists [FAILED]
[cloudera@quickstart awesome-recommendation-engine]$ sudo service spark-master status
Spark master is running [ OK ]

I guess that i have to increase resources to the vmware image, more ram and maybe another available core from host machine, isn't?

 

Thank you very much for reading until here.

 

avatar
Guru
I don't know much about Spark internals to give much intelligent advice
here, but it's possible it's a matter of resources. You still have the
problem in your hosts file that I described above. The hosts file you
posted maps 127.0.0.1 AND your public IP to quickstart.cloudera. You should
remove quickstart and quickstart.cloudera from the 127.0.0.1 line and have
only your public IP map to that (as shown below). You'll need to restart
all services after you make this change.

127.0.0.1 localhost localhost.localdomain
quickstart.cloudera quickstart

avatar
Explorer

Hi Sean, if i update /etc/hosts removing the line with 127.0.0.1 and using a line with the assigned ip instead of 127.0.0.1, i am getting this exception:

 

 

Caused by: java.io.IOException: org.apache.spark.SparkException: Failed to get broadcast_1_piece0 of broadcast_1
	at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1223)
	at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165)
	at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
	at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
	at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88)
	at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:65)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
	at org.apache.spark.scheduler.Task.run(Task.scala:89)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Failed to get broadcast_1_piece0 of broadcast_1
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$2.apply(TorrentBroadcast.scala:138)
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1$$anonfun$2.apply(TorrentBroadcast.scala:138)
	at scala.Option.getOrElse(Option.scala:120)
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply$mcVI$sp(TorrentBroadcast.scala:137)
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:120)
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:120)
	at scala.collection.immutable.List.foreach(List.scala:318)
	at org.apache.spark.broadcast.TorrentBroadcast.org$apache$spark$broadcast$TorrentBroadcast$$readBlocks(TorrentBroadcast.scala:120)
	at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:175)
	at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1220)

I I am pretty sure that i can reach to my host machine and i can reach to vmware image from my host.

 

host -> vmware image

MacBook-Pro-Retina-de-Alonso:my-recommendation-spark-engine aironman$ ping 192.168.30.139
PING 192.168.30.139 (192.168.30.139): 56 data bytes
64 bytes from 192.168.30.139: icmp_seq=0 ttl=64 time=0.462 ms
64 bytes from 192.168.30.139: icmp_seq=1 ttl=64 time=0.353 ms
64 bytes from 192.168.30.139: icmp_seq=2 ttl=64 time=0.311 ms
64 bytes from 192.168.30.139: icmp_seq=3 ttl=64 time=0.310 ms
64 bytes from 192.168.30.139: icmp_seq=4 ttl=64 time=0.273 ms

vmware image -> host

 

[cloudera@quickstart bin]$ ping 192.168.1.35
PING 192.168.1.35 (192.168.1.35) 56(84) bytes of data.
64 bytes from 192.168.1.35: icmp_seq=1 ttl=128 time=0.272 ms
64 bytes from 192.168.1.35: icmp_seq=2 ttl=128 time=0.416 ms
64 bytes from 192.168.1.35: icmp_seq=3 ttl=128 time=0.348 ms
64 bytes from 192.168.1.35: icmp_seq=4 ttl=128 time=0.367 ms
64 bytes from 192.168.1.35: icmp_seq=5 ttl=128 time=0.432 ms

It is not a problem of the software trying to talk with the kafka server located in host machine, i can do a telnet to host machine and kafka port:

 

[cloudera@quickstart bin]$ telnet 192.168.1.35 9092
Trying 192.168.1.35...
Connected to 192.168.1.35.
Escape character is '^]'.


Connection closed by foreign host.

Please, help me Sean, i am desperate, i cannot run nothing in this vmware image...

avatar
Explorer

Hi Sean, i am adding more research about this issue.

 

I have added programmatically this line to SparkConf

 

 

.set("spark.cores.max", "2")

and this line to /etc/spark/conf/spark-env.sh

 

##ADDED!!
export SPARK_MASTER_OPTS="-Dspark.deploy.defaultCores=4"

with no luck, if i i check /var/log/spark-worker.out file, these are last 50 lines:

 

16/06/02 20:47:43 INFO worker.Worker: Retrying connection to master (attempt # 11)
16/06/02 20:47:43 INFO worker.Worker: Connecting to master quickstart.cloudera:7077...
16/06/02 20:47:43 WARN worker.Worker: Failed to connect to master quickstart.cloudera:7077
java.io.IOException: Failed to connect to quickstart.cloudera/127.0.0.1:7077
	at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:216)
	at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:167)
	at org.apache.spark.rpc.netty.NettyRpcEnv.createClient(NettyRpcEnv.scala:199)
	at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:190)
	at org.apache.spark.rpc.netty.Outbox$$anon$1.call(Outbox.scala:186)
	at java.util.concurrent.FutureTask.run(FutureTask.java:262)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused: quickstart.cloudera/127.0.0.1:7077
	at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
	at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)
	at io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224)
	at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289)
	at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
	at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
	at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
	at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)

the worker cannot talk to master. I starting to think that this vmware image running with 8GB and 4 cores is not enough to run a simple spark job programmatically, but why i can run the same code within a spark-shell?

 

Please, help, i do not want what to do...

 

avatar
Explorer

I wanted to say, 

 

i do not know what to do next. I have readed this blog post, http://www.datastax.com/dev/blog/common-spark-troubleshooting, using that post i figure out to modify programmatically this variable:

 

 .set("spark.cores.max", "2")

and modify /etc/spark/conf/spark-env.sh to put this export:

 

export SPARK_MASTER_OPTS="-Dspark.deploy.defaultCores=4"

Is there anything i can do in order to run a simple spark job with a file of 16MB?

 

another thing i noticed is that i HAVE to put this programmatically in the sparkconf in order to run the job:

 

.set("spark.driver.allowMultipleContexts", "true")

Please help...

avatar
Rising Star
What does your /etc/hosts file look like now? You shouldn't remove the
127.0.0.1 line completely - just don't have quickstart or
quickstart.cloudera on that line.