*bump*
On Thu, Apr 23, 2015 at 3:46 PM, Sourav Chandra <
sourav.chan...@livestream.com> wrote:
> HI TD,
>
> Some observations:
>
> 1. If I submit the application using spark-submit tool with *client as
> deploy mode* it works fine with single master and worker (driver, master
> and worker are running in same machine)
> 2. If I submit the application using spark-submit tool with client as
> deploy mode it *crashes after some time with StackOverflowError* *single
> master and 2 workers* (driver, master and 1 worker is running in same
> machine, other
> worker is in different machine)
> *15/04/23 05:42:04 Executor: Exception in task 0.0 in stage 23153.0
> (TID 5412)*
> *java.lang.StackOverflowError*
> * at
> java.io.ObjectInputStream$BlockDataInputStream.readUTF(ObjectInputStream.java:2864)*
> * at java.io.ObjectInputStream.readUTF(ObjectInputStream.java:1072)*
> * at
> java.io.ObjectStreamClass.readNonProxy(ObjectStreamClass.java:671)*
> * at
> java.io.ObjectInputStream.readClassDescriptor(ObjectInputStream.java:830)*
> * at
> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1601)*
> * at
> java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1517)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)*
> * at
> scala.collection.immutable.$colon$colon.readObject(List.scala:362)*
> * at sun.reflect.GeneratedMethodAccessor12.invoke(Unknown Source)*
> * at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
> * at java.lang.reflect.Method.invoke(Method.java:606)*
> * at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)*
> * at
> scala.collection.immutable.$colon$colon.readObject(List.scala:362)*
> * at sun.reflect.GeneratedMethodAccessor12.invoke(Unknown Source)*
> * at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
> * at java.lang.reflect.Method.invoke(Method.java:606)*
> * at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)*
> * at
> scala.collection.immutable.$colon$colon.readObject(List.scala:366)*
> * at sun.reflect.GeneratedMethodAccessor12.invoke(Unknown Source)*
>
>
> 3. If I submit the application using spark-submit tool with *cluster as
> deploy mode* it *crashes after some time with Out Of Memory error *with
> single master and worker (driver, master and worker are running in same
> machine)
>
> * 15/04/23 05:47:49 Executor: Exception in task 0.0 in stage 858.0 (TID
> 1464)*
> *java.lang.OutOfMemoryError: Java heap space*
> * at
> org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)*
> * at
> org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2564)*
> * at
> org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:285)*
> * at
> org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:77)*
> * at
> org.apache.spark.SerializableWritable$$anonfun$readObject$1.apply$mcV$sp(SerializableWritable.scala:43)*
> * at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:927)*
> * at
> org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:39)*
> * at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)*
> * at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)*
> * at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
> * at java.lang.reflect.Method.invoke(Method.java:606)*
> * at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)*
> * at
> com.esotericsoftware.kryo.serializers.JavaSerializer.read(JavaSerializer.java:40)*
> * at
> com.esotericsoftware.kryo.Kryo.readClassAndObject(Kryo.java:729)*
> * at
> org.apache.spark.serializer.KryoDeserializationStream.readObject(KryoSerializer.scala:133)*
> * at
> org.apache.spark.broadcast.TorrentBroadcast$.unBlockifyObject(TorrentBroadcast.scala:236)*
> * at
> org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readObject$1.apply$mcV$sp(TorrentBroadcast.scala:169)*
> * at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:927)*
> * at
> org.apache.spark.broadcast.TorrentBroadcast.readObject(TorrentBroadcast.scala:155)*
> * at sun.reflect.GeneratedMethodAccessor15.invoke(Unknown Source)*
> * at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
> * at java.lang.reflect.Method.invoke(Method.java:606)*
> * at
> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1893)*
> * at
> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)*
> * at
> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)*
> * at
> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990)*
> * at
> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915)*
>
> Thanks,
> Sourav
>
> On Wed, Apr 22, 2015 at 11:40 PM, Tathagata Das <t...@databricks.com>
> wrote:
>
>> It could very well be that your executor memory is not enough to store
>> the state RDDs AND operate on the data. 1G per executor is quite low.
>> Definitely give more memory. And have you tried increasing the number of
>> partitions (specify number of partitions in updateStateByKey) ?
>>
>> On Wed, Apr 22, 2015 at 2:34 AM, Sourav Chandra <
>> sourav.chan...@livestream.com> wrote:
>>
>>> Anyone?
>>>
>>> On Wed, Apr 22, 2015 at 12:29 PM, Sourav Chandra <
>>> sourav.chan...@livestream.com> wrote:
>>>
>>> > Hi Olivier,
>>> >
>>> > *the update function is as below*:
>>> >
>>> > *val updateFunc = (values: Seq[IConcurrentUsers], state: Option[(Long,
>>> > Long)]) => {*
>>> > * val previousCount = state.getOrElse((0L, 0L))._2*
>>> > * var startValue: IConcurrentUsers = ConcurrentViewers(0)*
>>> > * var currentCount = 0L*
>>> > * val lastIndexOfConcurrentUsers =*
>>> > * values.lastIndexWhere(_.isInstanceOf[ConcurrentViewers])*
>>> > * val subList = values.slice(0, lastIndexOfConcurrentUsers)*
>>> > * val currentCountFromSubList = subList.foldLeft(startValue)(_ op
>>> > _).count + previousCount*
>>> > * val lastConcurrentViewersCount =
>>> > values(lastIndexOfConcurrentUsers).count*
>>> >
>>> > * if (math.abs(lastConcurrentViewersCount -
>>> currentCountFromSubList)
>>> > >= 1) {*
>>> > * logger.error(*
>>> > * s"Count using state updation $currentCountFromSubList, " +*
>>> > * s"ConcurrentUsers count $lastConcurrentViewersCount" +*
>>> > * s" resetting to $lastConcurrentViewersCount"*
>>> > * )*
>>> > * currentCount = lastConcurrentViewersCount*
>>> > * }*
>>> > * val remainingValuesList = values.diff(subList)*
>>> > * startValue = ConcurrentViewers(currentCount)*
>>> > * currentCount = remainingValuesList.foldLeft(startValue)(_ op
>>> > _).count*
>>> >
>>> > * if (currentCount < 0) {*
>>> >
>>> > * logger.error(*
>>> > * s"ERROR: Got new count $currentCount < 0, value:$values,
>>> > state:$state, resetting to 0"*
>>> > * )*
>>> > * currentCount = 0*
>>> > * }*
>>> > * // to stop pushing subsequent 0 after receiving first 0*
>>> > * if (currentCount == 0 && previousCount == 0) None*
>>> > * else Some(previousCount, currentCount)*
>>> > * }*
>>> >
>>> > *trait IConcurrentUsers {*
>>> > * val count: Long*
>>> > * def op(a: IConcurrentUsers): IConcurrentUsers =
>>> > IConcurrentUsers.op(this, a)*
>>> > *}*
>>> >
>>> > *object IConcurrentUsers {*
>>> > * def op(a: IConcurrentUsers, b: IConcurrentUsers): IConcurrentUsers =
>>> > (a, b) match {*
>>> > * case (_, _: ConcurrentViewers) => *
>>> > * ConcurrentViewers(b.count)*
>>> > * case (_: ConcurrentViewers, _: IncrementConcurrentViewers) => *
>>> > * ConcurrentViewers(a.count + b.count)*
>>> > * case (_: ConcurrentViewers, _: DecrementConcurrentViewers) => *
>>> > * ConcurrentViewers(a.count - b.count)*
>>> > * }*
>>> > *}*
>>> >
>>> > *case class IncrementConcurrentViewers(count: Long) extends
>>> > IConcurrentUsers*
>>> > *case class DecrementConcurrentViewers(count: Long) extends
>>> > IConcurrentUsers*
>>> > *case class ConcurrentViewers(count: Long) extends IConcurrentUsers*
>>> >
>>> >
>>> > *also the error stack trace copied from executor logs is:*
>>> >
>>> > *java.lang.OutOfMemoryError: Java heap space*
>>> > * at
>>> >
>>> org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)*
>>> > * at
>>> >
>>> org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2564)*
>>> > * at
>>> >
>>> org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:285)*
>>> > * at
>>> > org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:77)*
>>> > * at
>>> >
>>> org.apache.spark.SerializableWritable$$anonfun$readObject$1.apply$mcV$sp(SerializableWritable.scala:43)*
>>> > * at
>>> org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:927)*
>>> > * at
>>> >
>>> org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:39)*
>>> > * at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
>>> Method)*
>>> > * at
>>> >
>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)*
>>> > * at
>>> >
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
>>> > * at java.lang.reflect.Method.invoke(Method.java:601)*
>>> > * at
>>> >
>>> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)*
>>> > * at
>>> > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1866)*
>>> > * at
>>> >
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771)*
>>> > * at
>>> > java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)*
>>> > * at
>>> > java.io.ObjectInputStream.readObject(ObjectInputStream.java:369)*
>>> > * at
>>> >
>>> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:62)*
>>> > * at
>>> >
>>> org.apache.spark.broadcast.TorrentBroadcast$.unBlockifyObject(TorrentBroadcast.scala:236)*
>>> > * at
>>> >
>>> org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readObject$1.apply$mcV$sp(TorrentBroadcast.scala:169)*
>>> > * at
>>> org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:927)*
>>> > * at
>>> >
>>> org.apache.spark.broadcast.TorrentBroadcast.readObject(TorrentBroadcast.scala:155)*
>>> > * at sun.reflect.GeneratedMethodAccessor5.invoke(Unknown
>>> Source)*
>>> > * at
>>> >
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)*
>>> > * at java.lang.reflect.Method.invoke(Method.java:601)*
>>> > * at
>>> >
>>> java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)*
>>> > * at
>>> > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1866)*
>>> > * at
>>> >
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771)*
>>> > * at
>>> > java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)*
>>> > * at
>>> >
>>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1964)*
>>> > * at
>>> > java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1888)*
>>> > * at
>>> >
>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771)*
>>> > * at
>>> > java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)*
>>> > *15/04/21 15:51:23 ERROR ExecutorUncaughtExceptionHandler: Uncaught
>>> > exception in thread Thread[Executor task launch worker-1,5,main]*
>>> >
>>> >
>>> >
>>> > On Wed, Apr 22, 2015 at 1:32 AM, Olivier Girardot <ssab...@gmail.com>
>>> > wrote:
>>> >
>>> >> Hi Sourav,
>>> >> Can you post your updateFunc as well please ?
>>> >>
>>> >> Regards,
>>> >>
>>> >> Olivier.
>>> >>
>>> >> Le mar. 21 avr. 2015 à 12:48, Sourav Chandra <
>>> >> sourav.chan...@livestream.com> a écrit :
>>> >>
>>> >>> Hi,
>>> >>>
>>> >>> We are building a spark streaming application which reads from kafka,
>>> >>> does updateStateBykey based on the received message type and finally
>>> stores
>>> >>> into redis.
>>> >>>
>>> >>> After running for few seconds the executor process get killed by
>>> >>> throwing OutOfMemory error.
>>> >>>
>>> >>> The code snippet is below:
>>> >>>
>>> >>>
>>> >>> *NoOfReceiverInstances = 1*
>>> >>>
>>> >>> *val kafkaStreams = (1 to NoOfReceiverInstances).map(*
>>> >>> * _ => KafkaUtils.createStream(ssc, ZKQuorum, ConsumerGroup,
>>> TopicsMap)*
>>> >>> *)*
>>> >>> *val updateFunc = (values: Seq[IConcurrentUsers], state:
>>> Option[(Long,
>>> >>> Long)]) => {...}*
>>> >>>
>>> >>>
>>> >>>
>>> *ssc.union(kafkaStreams).map(KafkaMessageMapper(_)).filter(...)..updateStateByKey(updateFunc).foreachRDD(_.foreachPartition(RedisHelper.update(_)))*
>>> >>>
>>> >>>
>>> >>>
>>> >>> *object RedisHelper {*
>>> >>> * private val client = scredis.Redis(*
>>> >>> *
>>> >>>
>>> ConfigFactory.parseProperties(System.getProperties).getConfig(namespace)*
>>> >>> * )*
>>> >>>
>>> >>> * def update(**itr: Iterator[(String, (Long, Long))]) {*
>>> >>> * // redis save operation*
>>> >>> * }*
>>> >>>
>>> >>> *}*
>>> >>>
>>> >>>
>>> >>> *Below is the spark configuration:*
>>> >>>
>>> >>>
>>> >>> * spark.app.name <http://spark.app.name> = "XXXXXXX"*
>>> >>> * spark.jars = "xxxx.jar"*
>>> >>> * spark.home = "/spark-1.1.1-bin-hadoop2.4"*
>>> >>> * spark.executor.memory = 1g*
>>> >>> * spark.streaming.concurrentJobs = 1000*
>>> >>> * spark.logConf = true*
>>> >>> * spark.cleaner.ttl = 3600 //in milliseconds*
>>> >>> * spark.default.parallelism = 12*
>>> >>> * spark.executor.extraJavaOptions = "-Xloggc:gc.log
>>> >>> -XX:+PrintGCDetails -XX:+UseConcMarkSweepGC -XX:HeapDumpPath=1.hprof
>>> >>> -XX:+HeapDumpOnOutOfMemoryError"*
>>> >>> * spark.executor.logs.rolling.strategy = "size"*
>>> >>> * spark.executor.logs.rolling.size.maxBytes = 104857600 // 100 MB*
>>> >>> * spark.executor.logs.rolling.maxRetainedFiles = 10*
>>> >>> * spark.serializer = "org.apache.spark.serializer.KryoSerializer"*
>>> >>> * spark.kryo.registrator = "xxx.NoOpKryoRegistrator"*
>>> >>>
>>> >>>
>>> >>> other configurations are below
>>> >>>
>>> >>> *streaming {*
>>> >>> * // All streaming context related configs should come here*
>>> >>> * batch-duration = "1 second"*
>>> >>> * checkpoint-directory = "/tmp"*
>>> >>> * checkpoint-duration = "10 seconds"*
>>> >>> * slide-duration = "1 second"*
>>> >>> * window-duration = "1 second"*
>>> >>> * partitions-for-shuffle-task = 32*
>>> >>> * }*
>>> >>> * kafka {*
>>> >>> * no-of-receivers = 1*
>>> >>> * zookeeper-quorum = "xxxx:2181"*
>>> >>> * consumer-group = "xxxxx"*
>>> >>> * topic = "xxxxx:2"*
>>> >>> * }*
>>>
>>> >>>
>>> >>> We tried different combinations like
>>> >>> - with spark 1.1.0 and 1.1.1.
>>> >>> - by increasing executor memory
>>> >>> - by changing the serialization strategy (switching between kryo and
>>> >>> normal java)
>>> >>> - by changing broadcast strategy (switching between http and torrent
>>> >>> broadcast)
>>> >>>
>>> >>>
>>> >>> Can anyone give any insight what we are missing here? How can we fix
>>> >>> this?
>>> >>>
>>> >>> Due to akka version mismatch with some other libraries we cannot
>>> upgrade
>>> >>> the spark version.
>>> >>>
>>> >>> Thanks,
>>> >>> --
>>> >>>
>>> >>> Sourav Chandra
>>> >>>
>>> >>> Senior Software Engineer
>>> >>>
>>> >>> · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
>>> >>>
>>> >>> sourav.chan...@livestream.com
>>> >>>
>>> >>> o: +91 80 4121 8723
>>> >>>
>>> >>> m: +91 988 699 3746
>>> >>>
>>> >>> skype: sourav.chandra
>>> >>>
>>> >>> Livestream
>>> >>>
>>> >>> "Ajmera Summit", First Floor, #3/D, 68 Ward, 3rd Cross, 7th C Main,
>>> 3rd
>>> >>> Block, Koramangala Industrial Area,
>>> >>>
>>> >>> Bangalore 560034
>>> >>>
>>> >>> www.livestream.com
>>> >>>
>>> >>
>>> >
>>> >
>>> > --
>>> >
>>> > Sourav Chandra
>>> >
>>> > Senior Software Engineer
>>> >
>>> > · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
>>> >
>>> > sourav.chan...@livestream.com
>>> >
>>> > o: +91 80 4121 8723
>>> >
>>> > m: +91 988 699 3746
>>> >
>>> > skype: sourav.chandra
>>> >
>>> > Livestream
>>> >
>>> > "Ajmera Summit", First Floor, #3/D, 68 Ward, 3rd Cross, 7th C Main, 3rd
>>> > Block, Koramangala Industrial Area,
>>> >
>>> > Bangalore 560034
>>> >
>>> > www.livestream.com
>>> >
>>>
>>>
>>>
>>> --
>>>
>>> Sourav Chandra
>>>
>>> Senior Software Engineer
>>>
>>> · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
>>>
>>> sourav.chan...@livestream.com
>>>
>>> o: +91 80 4121 8723
>>>
>>> m: +91 988 699 3746
>>>
>>> skype: sourav.chandra
>>>
>>> Livestream
>>>
>>> "Ajmera Summit", First Floor, #3/D, 68 Ward, 3rd Cross, 7th C Main, 3rd
>>> Block, Koramangala Industrial Area,
>>>
>>> Bangalore 560034
>>>
>>> www.livestream.com
>>>
>>
>>
>
>
> --
>
> Sourav Chandra
>
> Senior Software Engineer
>
> · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
>
> sourav.chan...@livestream.com
>
> o: +91 80 4121 8723
>
> m: +91 988 699 3746
>
> skype: sourav.chandra
>
> Livestream
>
> "Ajmera Summit", First Floor, #3/D, 68 Ward, 3rd Cross, 7th C Main, 3rd
> Block, Koramangala Industrial Area,
>
> Bangalore 560034
>
> www.livestream.com
>
--
Sourav Chandra
Senior Software Engineer
· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·
sourav.chan...@livestream.com
o: +91 80 4121 8723
m: +91 988 699 3746
skype: sourav.chandra
Livestream
"Ajmera Summit", First Floor, #3/D, 68 Ward, 3rd Cross, 7th C Main, 3rd
Block, Koramangala Industrial Area,
Bangalore 560034
www.livestream.com
