Re: How to restart Twitter spark stream
Yes, that is correct, sorry for confusing you. But i guess this is what you
are looking for, let me know if that doesn't help:
val filtered_statuses = stream.transform(rdd ={
//Instead of hardcoding, you can fetch these from a MySQL or a file
or whatever
val sampleHashTags =
Array(#teenchoice.toLowerCase,#android.toLowerCase,#iphone.toLowerCase)
val filtered = rdd.filter(status ={
var found = false
for(tag - sampleHashTags){
if(status.getText.toLowerCase.contains(tag)) found = true
}
found
})
filtered
})
Thanks
Best Regards
On Fri, Jul 24, 2015 at 11:25 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil,
Thank you for sending this code. My apologize if I will ask something that
is obvious here, since I'm newbie in Scala, but I still don't see how I can
use this code. Maybe my original question was not very clear.
What I need is to get each Twitter Status that contains one of the
hashtags I'm following. I'm implementing learning platform, where each
course will have at least one hashtag, e.g. #cs270computersciencecourse. If
somebody post anything on Twitter with that hashtag, I want to get it and
save Twitter status in the system, so it can be shown in the application.
Other tweets should be ignored, but each tweet containing one of the
hashtags I'm following should be stored in the application, so I can't
process most popular tweets or something like that where it's possible
that I miss somebody's post. There is a list of hashtags that is followed
by stream, and this list should be possible to be updated by users.
If I understood well, code you sent me extracts hashtags from statuses
received through the stream, and it continue processing these hashtags, but
at the end I will have only hashtags without statuses. Is that correct, or
I missed something?
Thanks,
Zoran
On Wed, Jul 22, 2015 at 12:41 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
That was a pseudo code, working version would look like this:
val stream = TwitterUtils.createStream(ssc, None)
val hashTags = stream.flatMap(status = status.getText.split(
).filter(_.startsWith(#))).map(x = (x.toLowerCase,1))
val topCounts10 = hashTags.map((_, 1)).reduceByKeyAndWindow(_ + _,
Seconds(10))
.map{case (topic, count) = (count, topic)}
.transform(_.sortByKey(false)).map(x = x._2)
topCounts10.print()
val filteredStream = topCounts10.transform(rdd ={
*val samplehashtags =
ssc.sparkContext.parallelize(Array(#RobinWilliams.toLowerCase,#android.toLowerCase,#iphone.toLowerCase))*
val newRDD = samplehashtags.map { x = (x,1) }
val joined = newRDD.join(rdd)
joined
})
filteredStream.print()
Thanks
Best Regards
On Wed, Jul 22, 2015 at 3:58 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil and Jorn,
I tried as you suggested to create some simple scenario, but I have an
error on rdd.join(newRDD): value join is not a member of
org.apache.spark.rdd.RDD[twitter4j.Status]. The code looks like:
val stream = TwitterUtils.createStream(ssc, auth)
val filteredStream= stream.transform(rdd ={
val samplehashtags=Array(music,film)
val newRDD= samplehashtags.map { x = (x,1) }
rdd.join(newRDD)
})
Did I miss something here?
Thanks,
Zoran
On Mon, Jul 20, 2015 at 9:54 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Thanks for explanation.
If I understand this correctly, in this approach I would actually
stream everything from Twitter, and perform filtering in my application
using Spark. Isn't this too much overhead if my application is interested
in listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the
problem to open new streams if number of hashtags go over 400 which is the
Twitter limit for User stream filtering, but on the other side I'm concern
about how much it will affect application performance if I stream
everything that is posted on Twitter and filter it locally. It would be
great if somebody with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic
zoran.jere...@gmail.com wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better
if
there is
Re: How to restart Twitter spark stream
Hi Akhil,
That's exactly what I needed. You saved my day :)
Thanks a lot,
Best,
Zoran
On Fri, Jul 24, 2015 at 12:28 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Yes, that is correct, sorry for confusing you. But i guess this is what
you are looking for, let me know if that doesn't help:
val filtered_statuses = stream.transform(rdd ={
//Instead of hardcoding, you can fetch these from a MySQL or a file
or whatever
val sampleHashTags =
Array(#teenchoice.toLowerCase,#android.toLowerCase,#iphone.toLowerCase)
val filtered = rdd.filter(status ={
var found = false
for(tag - sampleHashTags){
if(status.getText.toLowerCase.contains(tag)) found = true
}
found
})
filtered
})
Thanks
Best Regards
On Fri, Jul 24, 2015 at 11:25 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil,
Thank you for sending this code. My apologize if I will ask something
that is obvious here, since I'm newbie in Scala, but I still don't see how
I can use this code. Maybe my original question was not very clear.
What I need is to get each Twitter Status that contains one of the
hashtags I'm following. I'm implementing learning platform, where each
course will have at least one hashtag, e.g. #cs270computersciencecourse. If
somebody post anything on Twitter with that hashtag, I want to get it and
save Twitter status in the system, so it can be shown in the application.
Other tweets should be ignored, but each tweet containing one of the
hashtags I'm following should be stored in the application, so I can't
process most popular tweets or something like that where it's possible
that I miss somebody's post. There is a list of hashtags that is followed
by stream, and this list should be possible to be updated by users.
If I understood well, code you sent me extracts hashtags from statuses
received through the stream, and it continue processing these hashtags, but
at the end I will have only hashtags without statuses. Is that correct, or
I missed something?
Thanks,
Zoran
On Wed, Jul 22, 2015 at 12:41 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
That was a pseudo code, working version would look like this:
val stream = TwitterUtils.createStream(ssc, None)
val hashTags = stream.flatMap(status = status.getText.split(
).filter(_.startsWith(#))).map(x = (x.toLowerCase,1))
val topCounts10 = hashTags.map((_, 1)).reduceByKeyAndWindow(_ + _,
Seconds(10))
.map{case (topic, count) = (count, topic)}
.transform(_.sortByKey(false)).map(x = x._2)
topCounts10.print()
val filteredStream = topCounts10.transform(rdd ={
*val samplehashtags =
ssc.sparkContext.parallelize(Array(#RobinWilliams.toLowerCase,#android.toLowerCase,#iphone.toLowerCase))*
val newRDD = samplehashtags.map { x = (x,1) }
val joined = newRDD.join(rdd)
joined
})
filteredStream.print()
Thanks
Best Regards
On Wed, Jul 22, 2015 at 3:58 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil and Jorn,
I tried as you suggested to create some simple scenario, but I have an
error on rdd.join(newRDD): value join is not a member of
org.apache.spark.rdd.RDD[twitter4j.Status]. The code looks like:
val stream = TwitterUtils.createStream(ssc, auth)
val filteredStream= stream.transform(rdd ={
val samplehashtags=Array(music,film)
val newRDD= samplehashtags.map { x = (x,1) }
rdd.join(newRDD)
})
Did I miss something here?
Thanks,
Zoran
On Mon, Jul 20, 2015 at 9:54 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Thanks for explanation.
If I understand this correctly, in this approach I would actually
stream everything from Twitter, and perform filtering in my application
using Spark. Isn't this too much overhead if my application is interested
in listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the
problem to open new streams if number of hashtags go over 400 which is the
Twitter limit for User stream filtering, but on the other side I'm concern
about how much it will affect application performance if I stream
everything that is posted on Twitter and filter it locally. It would be
great if somebody with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das
ak...@sigmoidanalytics.com wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic
zoran.jere...@gmail.com wrote:
Hi Jorn,
I didn't know that it is possible to change filter without
re-opening twitter stream. Actually, I already had that question
Re: How to restart Twitter spark stream
Hi Akhil,
Thank you for sending this code. My apologize if I will ask something that
is obvious here, since I'm newbie in Scala, but I still don't see how I can
use this code. Maybe my original question was not very clear.
What I need is to get each Twitter Status that contains one of the hashtags
I'm following. I'm implementing learning platform, where each course will
have at least one hashtag, e.g. #cs270computersciencecourse. If somebody
post anything on Twitter with that hashtag, I want to get it and save
Twitter status in the system, so it can be shown in the application. Other
tweets should be ignored, but each tweet containing one of the hashtags I'm
following should be stored in the application, so I can't process most
popular tweets or something like that where it's possible that I miss
somebody's post. There is a list of hashtags that is followed by stream,
and this list should be possible to be updated by users.
If I understood well, code you sent me extracts hashtags from statuses
received through the stream, and it continue processing these hashtags, but
at the end I will have only hashtags without statuses. Is that correct, or
I missed something?
Thanks,
Zoran
On Wed, Jul 22, 2015 at 12:41 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
That was a pseudo code, working version would look like this:
val stream = TwitterUtils.createStream(ssc, None)
val hashTags = stream.flatMap(status = status.getText.split(
).filter(_.startsWith(#))).map(x = (x.toLowerCase,1))
val topCounts10 = hashTags.map((_, 1)).reduceByKeyAndWindow(_ + _,
Seconds(10))
.map{case (topic, count) = (count, topic)}
.transform(_.sortByKey(false)).map(x = x._2)
topCounts10.print()
val filteredStream = topCounts10.transform(rdd ={
*val samplehashtags =
ssc.sparkContext.parallelize(Array(#RobinWilliams.toLowerCase,#android.toLowerCase,#iphone.toLowerCase))*
val newRDD = samplehashtags.map { x = (x,1) }
val joined = newRDD.join(rdd)
joined
})
filteredStream.print()
Thanks
Best Regards
On Wed, Jul 22, 2015 at 3:58 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil and Jorn,
I tried as you suggested to create some simple scenario, but I have an
error on rdd.join(newRDD): value join is not a member of
org.apache.spark.rdd.RDD[twitter4j.Status]. The code looks like:
val stream = TwitterUtils.createStream(ssc, auth)
val filteredStream= stream.transform(rdd ={
val samplehashtags=Array(music,film)
val newRDD= samplehashtags.map { x = (x,1) }
rdd.join(newRDD)
})
Did I miss something here?
Thanks,
Zoran
On Mon, Jul 20, 2015 at 9:54 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Thanks for explanation.
If I understand this correctly, in this approach I would actually stream
everything from Twitter, and perform filtering in my application using
Spark. Isn't this too much overhead if my application is interested in
listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the
problem to open new streams if number of hashtags go over 400 which is the
Twitter limit for User stream filtering, but on the other side I'm concern
about how much it will affect application performance if I stream
everything that is posted on Twitter and filter it locally. It would be
great if somebody with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better
if
there is some other way to add new hashtags or to remove old hashtags that
user stopped following. I guess the second request would be more
difficult.
However, it would be great if you can give me some short example how
to make this. I didn't understand well from your explanation what you mean
by join it with a rdd loading the newest hash tags from disk in a regular
interval.
Thanks,
Zoran
On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com
wrote:
Why do you even want to stop it? You can join it with a rdd loading
the newest hash tags from disk in a regular interval
Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com
a écrit :
Hi,
I have a twitter spark stream
Re: How to restart Twitter spark stream
That was a pseudo code, working version would look like this:
val stream = TwitterUtils.createStream(ssc, None)
val hashTags = stream.flatMap(status = status.getText.split(
).filter(_.startsWith(#))).map(x = (x.toLowerCase,1))
val topCounts10 = hashTags.map((_, 1)).reduceByKeyAndWindow(_ + _,
Seconds(10))
.map{case (topic, count) = (count, topic)}
.transform(_.sortByKey(false)).map(x = x._2)
topCounts10.print()
val filteredStream = topCounts10.transform(rdd ={
*val samplehashtags =
ssc.sparkContext.parallelize(Array(#RobinWilliams.toLowerCase,#android.toLowerCase,#iphone.toLowerCase))*
val newRDD = samplehashtags.map { x = (x,1) }
val joined = newRDD.join(rdd)
joined
})
filteredStream.print()
Thanks
Best Regards
On Wed, Jul 22, 2015 at 3:58 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Akhil and Jorn,
I tried as you suggested to create some simple scenario, but I have an
error on rdd.join(newRDD): value join is not a member of
org.apache.spark.rdd.RDD[twitter4j.Status]. The code looks like:
val stream = TwitterUtils.createStream(ssc, auth)
val filteredStream= stream.transform(rdd ={
val samplehashtags=Array(music,film)
val newRDD= samplehashtags.map { x = (x,1) }
rdd.join(newRDD)
})
Did I miss something here?
Thanks,
Zoran
On Mon, Jul 20, 2015 at 9:54 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Thanks for explanation.
If I understand this correctly, in this approach I would actually stream
everything from Twitter, and perform filtering in my application using
Spark. Isn't this too much overhead if my application is interested in
listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the
problem to open new streams if number of hashtags go over 400 which is the
Twitter limit for User stream filtering, but on the other side I'm concern
about how much it will affect application performance if I stream
everything that is posted on Twitter and filter it locally. It would be
great if somebody with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better if
there is some other way to add new hashtags or to remove old hashtags that
user stopped following. I guess the second request would be more difficult.
However, it would be great if you can give me some short example how to
make this. I didn't understand well from your explanation what you mean by
join it with a rdd loading the newest hash tags from disk in a regular
interval.
Thanks,
Zoran
On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com
wrote:
Why do you even want to stop it? You can join it with a rdd loading
the newest hash tags from disk in a regular interval
Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com
a écrit :
Hi,
I have a twitter spark stream initialized in the following way:
val ssc:StreamingContext =
SparkLauncher.getSparkScalaStreamingContext()
val config = getTwitterConfigurationBuilder.build()
val auth: Option[twitter4j.auth.Authorization] =
Some(new
twitter4j.auth.OAuthAuthorization(config))
val stream = TwitterUtils.createStream(ssc, auth,
filters)
This works fine when I initialy start it. However, at some point I
need to update filters since users might add new hashtags they want to
follow. I tried to stop the running stream and spark streaming context
without stoping spark context, e.g:
stream.stop()
ssc.stop(false)
Afterward, I'm trying to initialize a new Twitter stream like I did
previously. However, I got this exception:
Exception in thread Firestorm JMX Monitor
java.lang.IllegalStateException: Adding new inputs, transformations, and
output operations after stopping a context is not supported
at
org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224)
at
org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64)
at
org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41)
at
Re: How to restart Twitter spark stream
Hi Akhil and Jorn,
I tried as you suggested to create some simple scenario, but I have an
error on rdd.join(newRDD): value join is not a member of
org.apache.spark.rdd.RDD[twitter4j.Status]. The code looks like:
val stream = TwitterUtils.createStream(ssc, auth)
val filteredStream= stream.transform(rdd ={
val samplehashtags=Array(music,film)
val newRDD= samplehashtags.map { x = (x,1) }
rdd.join(newRDD)
})
Did I miss something here?
Thanks,
Zoran
On Mon, Jul 20, 2015 at 9:54 AM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Thanks for explanation.
If I understand this correctly, in this approach I would actually stream
everything from Twitter, and perform filtering in my application using
Spark. Isn't this too much overhead if my application is interested in
listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the
problem to open new streams if number of hashtags go over 400 which is the
Twitter limit for User stream filtering, but on the other side I'm concern
about how much it will affect application performance if I stream
everything that is posted on Twitter and filter it locally. It would be
great if somebody with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better if
there is some other way to add new hashtags or to remove old hashtags that
user stopped following. I guess the second request would be more difficult.
However, it would be great if you can give me some short example how to
make this. I didn't understand well from your explanation what you mean by
join it with a rdd loading the newest hash tags from disk in a regular
interval.
Thanks,
Zoran
On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com
wrote:
Why do you even want to stop it? You can join it with a rdd loading the
newest hash tags from disk in a regular interval
Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com
a écrit :
Hi,
I have a twitter spark stream initialized in the following way:
val ssc:StreamingContext =
SparkLauncher.getSparkScalaStreamingContext()
val config = getTwitterConfigurationBuilder.build()
val auth: Option[twitter4j.auth.Authorization] =
Some(new
twitter4j.auth.OAuthAuthorization(config))
val stream = TwitterUtils.createStream(ssc, auth,
filters)
This works fine when I initialy start it. However, at some point I
need to update filters since users might add new hashtags they want to
follow. I tried to stop the running stream and spark streaming context
without stoping spark context, e.g:
stream.stop()
ssc.stop(false)
Afterward, I'm trying to initialize a new Twitter stream like I did
previously. However, I got this exception:
Exception in thread Firestorm JMX Monitor
java.lang.IllegalStateException: Adding new inputs, transformations, and
output operations after stopping a context is not supported
at
org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224)
at
org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64)
at
org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41)
at
org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41)
at
org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46)
at
org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162)
at
org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41)
at
Re: How to restart Twitter spark stream
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD = scc.sc.textFile(/this/file/will/be/updated/frequently).map(x
= (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better if
there is some other way to add new hashtags or to remove old hashtags that
user stopped following. I guess the second request would be more difficult.
However, it would be great if you can give me some short example how to
make this. I didn't understand well from your explanation what you mean by
join it with a rdd loading the newest hash tags from disk in a regular
interval.
Thanks,
Zoran
On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com wrote:
Why do you even want to stop it? You can join it with a rdd loading the
newest hash tags from disk in a regular interval
Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com a
écrit :
Hi,
I have a twitter spark stream initialized in the following way:
val ssc:StreamingContext =
SparkLauncher.getSparkScalaStreamingContext()
val config = getTwitterConfigurationBuilder.build()
val auth: Option[twitter4j.auth.Authorization] =
Some(new
twitter4j.auth.OAuthAuthorization(config))
val stream = TwitterUtils.createStream(ssc, auth,
filters)
This works fine when I initialy start it. However, at some point I need
to update filters since users might add new hashtags they want to follow. I
tried to stop the running stream and spark streaming context without
stoping spark context, e.g:
stream.stop()
ssc.stop(false)
Afterward, I'm trying to initialize a new Twitter stream like I did
previously. However, I got this exception:
Exception in thread Firestorm JMX Monitor
java.lang.IllegalStateException: Adding new inputs, transformations, and
output operations after stopping a context is not supported
at
org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224)
at
org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64)
at
org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41)
at
org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41)
at
org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46)
at
org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162)
at
org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41)
at
org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$$anon$1.run(HashtagsUpdatesBuffer.scala:19)
at java.util.TimerThread.mainLoop(Timer.java:555)
at java.util.TimerThread.run(Timer.java:505)
INFO[2015-07-18 22:24:23,430] [Twitter Stream consumer-1[Disposing
thread]] twitter4j.TwitterStreamImpl (SLF4JLogger.java:83) Inflater
has been closed
ERROR[2015-07-18 22:24:32,503]
[sparkDriver-akka.actor.default-dispatcher-3]
streaming.receiver.ReceiverSupervisorImpl (Logging.scala:75) Error
stopping receiver
0org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:116)
Anybody can explain how to solve this issue?
Thanks,
Zoran
--
***
Zoran Jeremic, PhD
Senior System Analyst Programmer
Athabasca University
Tel: +1 604 92 89 944
E-mail: zoran.jere...@gmail.com zoran.jere...@va.mod.gov.rs
Homepage: http://zoranjeremic.org
**
Re: How to restart Twitter spark stream
Thanks for explanation.
If I understand this correctly, in this approach I would actually stream
everything from Twitter, and perform filtering in my application using
Spark. Isn't this too much overhead if my application is interested in
listening for couple of hundreds or thousands hashtags?
On one side, this will be better approach since I will not have the problem
to open new streams if number of hashtags go over 400 which is the Twitter
limit for User stream filtering, but on the other side I'm concern about
how much it will affect application performance if I stream everything that
is posted on Twitter and filter it locally. It would be great if somebody
with experience on this could comment on these concerns.
Thanks,
Zoran
On Mon, Jul 20, 2015 at 12:19 AM, Akhil Das ak...@sigmoidanalytics.com
wrote:
Jorn meant something like this:
val filteredStream = twitterStream.transform(rdd ={
val newRDD =
scc.sc.textFile(/this/file/will/be/updated/frequently).map(x = (x,1))
rdd.join(newRDD)
})
newRDD will work like a filter when you do the join.
Thanks
Best Regards
On Sun, Jul 19, 2015 at 9:32 PM, Zoran Jeremic zoran.jere...@gmail.com
wrote:
Hi Jorn,
I didn't know that it is possible to change filter without re-opening
twitter stream. Actually, I already had that question earlier at the
stackoverflow
http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming
and I got the answer that it's not possible, but it would be even better if
there is some other way to add new hashtags or to remove old hashtags that
user stopped following. I guess the second request would be more difficult.
However, it would be great if you can give me some short example how to
make this. I didn't understand well from your explanation what you mean by
join it with a rdd loading the newest hash tags from disk in a regular
interval.
Thanks,
Zoran
On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com
wrote:
Why do you even want to stop it? You can join it with a rdd loading the
newest hash tags from disk in a regular interval
Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com a
écrit :
Hi,
I have a twitter spark stream initialized in the following way:
val ssc:StreamingContext =
SparkLauncher.getSparkScalaStreamingContext()
val config = getTwitterConfigurationBuilder.build()
val auth: Option[twitter4j.auth.Authorization] =
Some(new
twitter4j.auth.OAuthAuthorization(config))
val stream = TwitterUtils.createStream(ssc, auth,
filters)
This works fine when I initialy start it. However, at some point I need
to update filters since users might add new hashtags they want to follow. I
tried to stop the running stream and spark streaming context without
stoping spark context, e.g:
stream.stop()
ssc.stop(false)
Afterward, I'm trying to initialize a new Twitter stream like I did
previously. However, I got this exception:
Exception in thread Firestorm JMX Monitor
java.lang.IllegalStateException: Adding new inputs, transformations, and
output operations after stopping a context is not supported
at
org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224)
at
org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64)
at
org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41)
at
org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41)
at
org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46)
at
org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174)
at
org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162)
at
org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41)
at
org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$$anon$1.run(HashtagsUpdatesBuffer.scala:19)
at java.util.TimerThread.mainLoop(Timer.java:555)
at java.util.TimerThread.run(Timer.java:505)
INFO[2015-07-18 22:24:23,430] [Twitter Stream
consumer-1[Disposing thread]] twitter4j.TwitterStreamImpl
(SLF4JLogger.java:83) Inflater has been closed
ERROR[2015-07-18 22:24:32,503]
[sparkDriver-akka.actor.default-dispatcher-3]
streaming.receiver.ReceiverSupervisorImpl (Logging.scala:75) Error
stopping receiver
0org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:116)
Anybody can explain how to solve
Re: How to restart Twitter spark stream
Why do you even want to stop it? You can join it with a rdd loading the newest hash tags from disk in a regular interval Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com a écrit : Hi, I have a twitter spark stream initialized in the following way: val ssc:StreamingContext = SparkLauncher.getSparkScalaStreamingContext() val config = getTwitterConfigurationBuilder.build() val auth: Option[twitter4j.auth.Authorization] = Some(new twitter4j.auth.OAuthAuthorization(config)) val stream = TwitterUtils.createStream(ssc, auth, filters) This works fine when I initialy start it. However, at some point I need to update filters since users might add new hashtags they want to follow. I tried to stop the running stream and spark streaming context without stoping spark context, e.g: stream.stop() ssc.stop(false) Afterward, I'm trying to initialize a new Twitter stream like I did previously. However, I got this exception: Exception in thread Firestorm JMX Monitor java.lang.IllegalStateException: Adding new inputs, transformations, and output operations after stopping a context is not supported at org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224) at org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64) at org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41) at org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41) at org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46) at org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$$anon$1.run(HashtagsUpdatesBuffer.scala:19) at java.util.TimerThread.mainLoop(Timer.java:555) at java.util.TimerThread.run(Timer.java:505) INFO[2015-07-18 22:24:23,430] [Twitter Stream consumer-1[Disposing thread]] twitter4j.TwitterStreamImpl (SLF4JLogger.java:83) Inflater has been closed ERROR[2015-07-18 22:24:32,503] [sparkDriver-akka.actor.default-dispatcher-3] streaming.receiver.ReceiverSupervisorImpl (Logging.scala:75) Error stopping receiver 0org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:116) Anybody can explain how to solve this issue? Thanks, Zoran
Re: How to restart Twitter spark stream
Hi Jorn, I didn't know that it is possible to change filter without re-opening twitter stream. Actually, I already had that question earlier at the stackoverflow http://stackoverflow.com/questions/30960984/apache-spark-twitter-streaming and I got the answer that it's not possible, but it would be even better if there is some other way to add new hashtags or to remove old hashtags that user stopped following. I guess the second request would be more difficult. However, it would be great if you can give me some short example how to make this. I didn't understand well from your explanation what you mean by join it with a rdd loading the newest hash tags from disk in a regular interval. Thanks, Zoran On Sun, Jul 19, 2015 at 5:01 AM, Jörn Franke jornfra...@gmail.com wrote: Why do you even want to stop it? You can join it with a rdd loading the newest hash tags from disk in a regular interval Le dim. 19 juil. 2015 à 7:40, Zoran Jeremic zoran.jere...@gmail.com a écrit : Hi, I have a twitter spark stream initialized in the following way: val ssc:StreamingContext = SparkLauncher.getSparkScalaStreamingContext() val config = getTwitterConfigurationBuilder.build() val auth: Option[twitter4j.auth.Authorization] = Some(new twitter4j.auth.OAuthAuthorization(config)) val stream = TwitterUtils.createStream(ssc, auth, filters) This works fine when I initialy start it. However, at some point I need to update filters since users might add new hashtags they want to follow. I tried to stop the running stream and spark streaming context without stoping spark context, e.g: stream.stop() ssc.stop(false) Afterward, I'm trying to initialize a new Twitter stream like I did previously. However, I got this exception: Exception in thread Firestorm JMX Monitor java.lang.IllegalStateException: Adding new inputs, transformations, and output operations after stopping a context is not supported at org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224) at org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64) at org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41) at org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41) at org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46) at org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$$anon$1.run(HashtagsUpdatesBuffer.scala:19) at java.util.TimerThread.mainLoop(Timer.java:555) at java.util.TimerThread.run(Timer.java:505) INFO[2015-07-18 22:24:23,430] [Twitter Stream consumer-1[Disposing thread]] twitter4j.TwitterStreamImpl (SLF4JLogger.java:83) Inflater has been closed ERROR[2015-07-18 22:24:32,503] [sparkDriver-akka.actor.default-dispatcher-3] streaming.receiver.ReceiverSupervisorImpl (Logging.scala:75) Error stopping receiver 0org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:116) Anybody can explain how to solve this issue? Thanks, Zoran -- *** Zoran Jeremic, PhD Senior System Analyst Programmer Athabasca University Tel: +1 604 92 89 944 E-mail: zoran.jere...@gmail.com zoran.jere...@va.mod.gov.rs Homepage: http://zoranjeremic.org **
How to restart Twitter spark stream
Hi, I have a twitter spark stream initialized in the following way: val ssc:StreamingContext = SparkLauncher.getSparkScalaStreamingContext() val config = getTwitterConfigurationBuilder.build() val auth: Option[twitter4j.auth.Authorization] = Some(new twitter4j.auth.OAuthAuthorization(config)) val stream = TwitterUtils.createStream(ssc, auth, filters) This works fine when I initialy start it. However, at some point I need to update filters since users might add new hashtags they want to follow. I tried to stop the running stream and spark streaming context without stoping spark context, e.g: stream.stop() ssc.stop(false) Afterward, I'm trying to initialize a new Twitter stream like I did previously. However, I got this exception: Exception in thread Firestorm JMX Monitor java.lang.IllegalStateException: Adding new inputs, transformations, and output operations after stopping a context is not supported at org.apache.spark.streaming.dstream.DStream.validateAtInit(DStream.scala:224) at org.apache.spark.streaming.dstream.DStream.init(DStream.scala:64) at org.apache.spark.streaming.dstream.InputDStream.init(InputDStream.scala:41) at org.apache.spark.streaming.dstream.ReceiverInputDStream.init(ReceiverInputDStream.scala:41) at org.apache.spark.streaming.twitter.TwitterInputDStream.init(TwitterInputDStream.scala:46) at org.apache.spark.streaming.twitter.TwitterUtils$.createStream(TwitterUtils.scala:44) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.initializeNewStream(TwitterHashtagsStreamsManager.scala:113) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.restartHashTagsStream(TwitterHashtagsStreamsManager.scala:174) at org.prosolo.bigdata.scala.twitter.TwitterHashtagsStreamsManager$.addHashTagsFromBufferAndRestartStream(TwitterHashtagsStreamsManager.scala:162) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$.processBufferEvents(HashtagsUpdatesBuffer.scala:41) at org.prosolo.bigdata.scala.twitter.HashtagsUpdatesBuffer$$anon$1.run(HashtagsUpdatesBuffer.scala:19) at java.util.TimerThread.mainLoop(Timer.java:555) at java.util.TimerThread.run(Timer.java:505) INFO[2015-07-18 22:24:23,430] [Twitter Stream consumer-1[Disposing thread]] twitter4j.TwitterStreamImpl (SLF4JLogger.java:83) Inflater has been closed ERROR[2015-07-18 22:24:32,503] [sparkDriver-akka.actor.default-dispatcher-3] streaming.receiver.ReceiverSupervisorImpl (Logging.scala:75) Error stopping receiver 0org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:116) Anybody can explain how to solve this issue? Thanks, Zoran
