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 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
>>>>>
>>>>> **********************************************************************************
>>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>>
>>> *******************************************************************************
>>> 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
>>>
>>> **********************************************************************************
>>>
>>
>>
>>
>> --
>>
>> *******************************************************************************
>> 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
>>
>> **********************************************************************************
>>
>
>
--
*******************************************************************************
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
**********************************************************************************
