Re: No output from Spark Streaming program with Spark 1.0

2014-05-24 Thread Jim Donahue
I looked at the Streaming UI for my job and it reports that it has
processed many batches, but that none of the batches had any records in
them. Unfortunately, that’s what I expected.  :-(

I’ve tried multiple test programs and I’m seeing the same thing.  The
Kafka sources are alive and well and the programs all worked on 0.9 from
Eclipse.  And there’s no indication of any failure — just no records are
being delivered.

Any ideas would be much appreciated …


Thanks,

Jim


On 5/23/14, 7:29 PM, Tathagata Das tathagata.das1...@gmail.com wrote:

Few more suggestions.
1. See the web ui, is the system running any jobs? If not, then you may
need to give the system more nodes. Basically the system should have more
cores than the number of receivers.
2. Furthermore there is a streaming specific web ui which gives more
streaming specific data.


On Fri, May 23, 2014 at 6:02 PM, Patrick Wendell pwend...@gmail.com
wrote:

 Also one other thing to try, try removing all of the logic form inside
 of foreach and just printing something. It could be that somehow an
 exception is being triggered inside of your foreach block and as a
 result the output goes away.

 On Fri, May 23, 2014 at 6:00 PM, Patrick Wendell pwend...@gmail.com
 wrote:
  Hey Jim,
 
  Do you see the same behavior if you run this outside of eclipse?
 
  Also, what happens if you print something to standard out when setting
  up your streams (i.e. not inside of the foreach) do you see that? This
  could be a streaming issue, but it could also be something related to
  the way it's running in eclipse.
 
  - Patrick
 
  On Fri, May 23, 2014 at 2:57 PM, Jim Donahue jdona...@adobe.com
wrote:
  I¹m trying out 1.0 on a set of small Spark Streaming tests and am
 running
  into problems.  Here¹s one of the little programs I¹ve used for a
long
  time ‹ it reads a Kafka stream that contains Twitter JSON tweets and
 does
  some simple counting.  The program starts OK (it connects to the
Kafka
  stream fine) and generates a stream of INFO logging messages, but
never
  generates any output. :-(
 
  I¹m running this in Eclipse, so there may be some class loading issue
  (loading the wrong class or something like that), but I¹m not seeing
  anything in the console output.
 
  Thanks,
 
  Jim Donahue
  Adobe
 
 
 
  val kafka_messages =
KafkaUtils.createStream[Array[Byte], Array[Byte],
  kafka.serializer.DefaultDecoder,
kafka.serializer.DefaultDecoder](ssc,
  propsMap, topicMap, StorageLevel.MEMORY_AND_DISK)
 
 
   val messages = kafka_messages.map(_._2)
 
 
   val total = ssc.sparkContext.accumulator(0)
 
 
   val startTime = new java.util.Date().getTime()
 
 
   val jsonstream = messages.map[JSONObject](message =
{val string = new String(message);
val json = new JSONObject(string);
total += 1
json
}
  )
 
 
  val deleted = ssc.sparkContext.accumulator(0)
 
 
  val msgstream = jsonstream.filter(json =
if (!json.has(delete)) true else { deleted += 1; false}
)
 
 
  msgstream.foreach(rdd = {
if(rdd.count()  0){
val data = rdd.map(json = (json.has(entities),
  json.length())).collect()
val entities: Double = data.count(t = t._1)
val fieldCounts = data.sortBy(_._2)
val minFields = fieldCounts(0)._2
val maxFields = fieldCounts(fieldCounts.size - 1)._2
val now = new java.util.Date()
val interval = (now.getTime() - startTime) / 1000
System.out.println(now.toString)
System.out.println(processing time:  + interval +  seconds)
System.out.println(total messages:  + total.value)
System.out.println(deleted messages:  + deleted.value)
System.out.println(message receipt rate:  +
 (total.value/interval)
  +  per second)
System.out.println(messages this interval:  + data.length)
System.out.println(message fields varied between:  +
minFields
 + 
  and  + maxFields)
System.out.println(fraction with entities is  + (entities /
  data.length))
}
  }
  )
 
  ssc.start()
 




Re: No output from Spark Streaming program with Spark 1.0

2014-05-24 Thread Tathagata Das
What does the kafka receiver status on the streaming UI say when you are
connected to the Kafka sources? Does it show any error?

Can you find out which machine the receiver is running and see the worker
logs for any exceptions / error messages? Try turning on the DEBUG level in
log4j.

TD
On May 24, 2014 4:58 PM, Jim Donahue jdona...@adobe.com wrote:

 I looked at the Streaming UI for my job and it reports that it has
 processed many batches, but that none of the batches had any records in
 them. Unfortunately, that’s what I expected.  :-(

 I’ve tried multiple test programs and I’m seeing the same thing.  The
 Kafka sources are alive and well and the programs all worked on 0.9 from
 Eclipse.  And there’s no indication of any failure — just no records are
 being delivered.

 Any ideas would be much appreciated …


 Thanks,

 Jim


 On 5/23/14, 7:29 PM, Tathagata Das tathagata.das1...@gmail.com wrote:

 Few more suggestions.
 1. See the web ui, is the system running any jobs? If not, then you may
 need to give the system more nodes. Basically the system should have more
 cores than the number of receivers.
 2. Furthermore there is a streaming specific web ui which gives more
 streaming specific data.
 
 
 On Fri, May 23, 2014 at 6:02 PM, Patrick Wendell pwend...@gmail.com
 wrote:
 
  Also one other thing to try, try removing all of the logic form inside
  of foreach and just printing something. It could be that somehow an
  exception is being triggered inside of your foreach block and as a
  result the output goes away.
 
  On Fri, May 23, 2014 at 6:00 PM, Patrick Wendell pwend...@gmail.com
  wrote:
   Hey Jim,
  
   Do you see the same behavior if you run this outside of eclipse?
  
   Also, what happens if you print something to standard out when setting
   up your streams (i.e. not inside of the foreach) do you see that? This
   could be a streaming issue, but it could also be something related to
   the way it's running in eclipse.
  
   - Patrick
  
   On Fri, May 23, 2014 at 2:57 PM, Jim Donahue jdona...@adobe.com
 wrote:
   I¹m trying out 1.0 on a set of small Spark Streaming tests and am
  running
   into problems.  Here¹s one of the little programs I¹ve used for a
 long
   time ‹ it reads a Kafka stream that contains Twitter JSON tweets and
  does
   some simple counting.  The program starts OK (it connects to the
 Kafka
   stream fine) and generates a stream of INFO logging messages, but
 never
   generates any output. :-(
  
   I¹m running this in Eclipse, so there may be some class loading issue
   (loading the wrong class or something like that), but I¹m not seeing
   anything in the console output.
  
   Thanks,
  
   Jim Donahue
   Adobe
  
  
  
   val kafka_messages =
 KafkaUtils.createStream[Array[Byte], Array[Byte],
   kafka.serializer.DefaultDecoder,
 kafka.serializer.DefaultDecoder](ssc,
   propsMap, topicMap, StorageLevel.MEMORY_AND_DISK)
  
  
val messages = kafka_messages.map(_._2)
  
  
val total = ssc.sparkContext.accumulator(0)
  
  
val startTime = new java.util.Date().getTime()
  
  
val jsonstream = messages.map[JSONObject](message =
 {val string = new String(message);
 val json = new JSONObject(string);
 total += 1
 json
 }
   )
  
  
   val deleted = ssc.sparkContext.accumulator(0)
  
  
   val msgstream = jsonstream.filter(json =
 if (!json.has(delete)) true else { deleted += 1; false}
 )
  
  
   msgstream.foreach(rdd = {
 if(rdd.count()  0){
 val data = rdd.map(json = (json.has(entities),
   json.length())).collect()
 val entities: Double = data.count(t = t._1)
 val fieldCounts = data.sortBy(_._2)
 val minFields = fieldCounts(0)._2
 val maxFields = fieldCounts(fieldCounts.size - 1)._2
 val now = new java.util.Date()
 val interval = (now.getTime() - startTime) / 1000
 System.out.println(now.toString)
 System.out.println(processing time:  + interval +  seconds)
 System.out.println(total messages:  + total.value)
 System.out.println(deleted messages:  + deleted.value)
 System.out.println(message receipt rate:  +
  (total.value/interval)
   +  per second)
 System.out.println(messages this interval:  + data.length)
 System.out.println(message fields varied between:  +
 minFields
  + 
   and  + maxFields)
 System.out.println(fraction with entities is  + (entities /
   data.length))
 }
   }
   )
  
   ssc.start()
  
 




No output from Spark Streaming program with Spark 1.0

2014-05-23 Thread Jim Donahue
I¹m trying out 1.0 on a set of small Spark Streaming tests and am running
into problems.  Here¹s one of the little programs I¹ve used for a long
time ‹ it reads a Kafka stream that contains Twitter JSON tweets and does
some simple counting.  The program starts OK (it connects to the Kafka
stream fine) and generates a stream of INFO logging messages, but never
generates any output. :-(

I¹m running this in Eclipse, so there may be some class loading issue
(loading the wrong class or something like that), but I¹m not seeing
anything in the console output.

Thanks,

Jim Donahue
Adobe



val kafka_messages =
  KafkaUtils.createStream[Array[Byte], Array[Byte],
kafka.serializer.DefaultDecoder, kafka.serializer.DefaultDecoder](ssc,
propsMap, topicMap, StorageLevel.MEMORY_AND_DISK)


 val messages = kafka_messages.map(_._2)

 
 val total = ssc.sparkContext.accumulator(0)

 
 val startTime = new java.util.Date().getTime()

 
 val jsonstream = messages.map[JSONObject](message =
  {val string = new String(message);
  val json = new JSONObject(string);
  total += 1
  json
  }
)


val deleted = ssc.sparkContext.accumulator(0)


val msgstream = jsonstream.filter(json =
  if (!json.has(delete)) true else { deleted += 1; false}
  )


msgstream.foreach(rdd = {
  if(rdd.count()  0){
  val data = rdd.map(json = (json.has(entities),
json.length())).collect()
  val entities: Double = data.count(t = t._1)
  val fieldCounts = data.sortBy(_._2)
  val minFields = fieldCounts(0)._2
  val maxFields = fieldCounts(fieldCounts.size - 1)._2
  val now = new java.util.Date()
  val interval = (now.getTime() - startTime) / 1000
  System.out.println(now.toString)
  System.out.println(processing time:  + interval +  seconds)
  System.out.println(total messages:  + total.value)
  System.out.println(deleted messages:  + deleted.value)
  System.out.println(message receipt rate:  + (total.value/interval)
+  per second)
  System.out.println(messages this interval:  + data.length)
  System.out.println(message fields varied between:  + minFields + 
and  + maxFields)
  System.out.println(fraction with entities is  + (entities /
data.length))
  }
}
)

ssc.start()



Re: No output from Spark Streaming program with Spark 1.0

2014-05-23 Thread Patrick Wendell
Also one other thing to try, try removing all of the logic form inside
of foreach and just printing something. It could be that somehow an
exception is being triggered inside of your foreach block and as a
result the output goes away.

On Fri, May 23, 2014 at 6:00 PM, Patrick Wendell pwend...@gmail.com wrote:
 Hey Jim,

 Do you see the same behavior if you run this outside of eclipse?

 Also, what happens if you print something to standard out when setting
 up your streams (i.e. not inside of the foreach) do you see that? This
 could be a streaming issue, but it could also be something related to
 the way it's running in eclipse.

 - Patrick

 On Fri, May 23, 2014 at 2:57 PM, Jim Donahue jdona...@adobe.com wrote:
 I¹m trying out 1.0 on a set of small Spark Streaming tests and am running
 into problems.  Here¹s one of the little programs I¹ve used for a long
 time ‹ it reads a Kafka stream that contains Twitter JSON tweets and does
 some simple counting.  The program starts OK (it connects to the Kafka
 stream fine) and generates a stream of INFO logging messages, but never
 generates any output. :-(

 I¹m running this in Eclipse, so there may be some class loading issue
 (loading the wrong class or something like that), but I¹m not seeing
 anything in the console output.

 Thanks,

 Jim Donahue
 Adobe



 val kafka_messages =
   KafkaUtils.createStream[Array[Byte], Array[Byte],
 kafka.serializer.DefaultDecoder, kafka.serializer.DefaultDecoder](ssc,
 propsMap, topicMap, StorageLevel.MEMORY_AND_DISK)


  val messages = kafka_messages.map(_._2)


  val total = ssc.sparkContext.accumulator(0)


  val startTime = new java.util.Date().getTime()


  val jsonstream = messages.map[JSONObject](message =
   {val string = new String(message);
   val json = new JSONObject(string);
   total += 1
   json
   }
 )


 val deleted = ssc.sparkContext.accumulator(0)


 val msgstream = jsonstream.filter(json =
   if (!json.has(delete)) true else { deleted += 1; false}
   )


 msgstream.foreach(rdd = {
   if(rdd.count()  0){
   val data = rdd.map(json = (json.has(entities),
 json.length())).collect()
   val entities: Double = data.count(t = t._1)
   val fieldCounts = data.sortBy(_._2)
   val minFields = fieldCounts(0)._2
   val maxFields = fieldCounts(fieldCounts.size - 1)._2
   val now = new java.util.Date()
   val interval = (now.getTime() - startTime) / 1000
   System.out.println(now.toString)
   System.out.println(processing time:  + interval +  seconds)
   System.out.println(total messages:  + total.value)
   System.out.println(deleted messages:  + deleted.value)
   System.out.println(message receipt rate:  + (total.value/interval)
 +  per second)
   System.out.println(messages this interval:  + data.length)
   System.out.println(message fields varied between:  + minFields + 
 and  + maxFields)
   System.out.println(fraction with entities is  + (entities /
 data.length))
   }
 }
 )

 ssc.start()



Re: No output from Spark Streaming program with Spark 1.0

2014-05-23 Thread Tathagata Das
Few more suggestions.
1. See the web ui, is the system running any jobs? If not, then you may
need to give the system more nodes. Basically the system should have more
cores than the number of receivers.
2. Furthermore there is a streaming specific web ui which gives more
streaming specific data.


On Fri, May 23, 2014 at 6:02 PM, Patrick Wendell pwend...@gmail.com wrote:

 Also one other thing to try, try removing all of the logic form inside
 of foreach and just printing something. It could be that somehow an
 exception is being triggered inside of your foreach block and as a
 result the output goes away.

 On Fri, May 23, 2014 at 6:00 PM, Patrick Wendell pwend...@gmail.com
 wrote:
  Hey Jim,
 
  Do you see the same behavior if you run this outside of eclipse?
 
  Also, what happens if you print something to standard out when setting
  up your streams (i.e. not inside of the foreach) do you see that? This
  could be a streaming issue, but it could also be something related to
  the way it's running in eclipse.
 
  - Patrick
 
  On Fri, May 23, 2014 at 2:57 PM, Jim Donahue jdona...@adobe.com wrote:
  I¹m trying out 1.0 on a set of small Spark Streaming tests and am
 running
  into problems.  Here¹s one of the little programs I¹ve used for a long
  time ‹ it reads a Kafka stream that contains Twitter JSON tweets and
 does
  some simple counting.  The program starts OK (it connects to the Kafka
  stream fine) and generates a stream of INFO logging messages, but never
  generates any output. :-(
 
  I¹m running this in Eclipse, so there may be some class loading issue
  (loading the wrong class or something like that), but I¹m not seeing
  anything in the console output.
 
  Thanks,
 
  Jim Donahue
  Adobe
 
 
 
  val kafka_messages =
KafkaUtils.createStream[Array[Byte], Array[Byte],
  kafka.serializer.DefaultDecoder, kafka.serializer.DefaultDecoder](ssc,
  propsMap, topicMap, StorageLevel.MEMORY_AND_DISK)
 
 
   val messages = kafka_messages.map(_._2)
 
 
   val total = ssc.sparkContext.accumulator(0)
 
 
   val startTime = new java.util.Date().getTime()
 
 
   val jsonstream = messages.map[JSONObject](message =
{val string = new String(message);
val json = new JSONObject(string);
total += 1
json
}
  )
 
 
  val deleted = ssc.sparkContext.accumulator(0)
 
 
  val msgstream = jsonstream.filter(json =
if (!json.has(delete)) true else { deleted += 1; false}
)
 
 
  msgstream.foreach(rdd = {
if(rdd.count()  0){
val data = rdd.map(json = (json.has(entities),
  json.length())).collect()
val entities: Double = data.count(t = t._1)
val fieldCounts = data.sortBy(_._2)
val minFields = fieldCounts(0)._2
val maxFields = fieldCounts(fieldCounts.size - 1)._2
val now = new java.util.Date()
val interval = (now.getTime() - startTime) / 1000
System.out.println(now.toString)
System.out.println(processing time:  + interval +  seconds)
System.out.println(total messages:  + total.value)
System.out.println(deleted messages:  + deleted.value)
System.out.println(message receipt rate:  +
 (total.value/interval)
  +  per second)
System.out.println(messages this interval:  + data.length)
System.out.println(message fields varied between:  + minFields
 + 
  and  + maxFields)
System.out.println(fraction with entities is  + (entities /
  data.length))
}
  }
  )
 
  ssc.start()