azmatsiddique / pyspark-twitter-stream-mining

Real-time Machine Learning with Apache Spark on Twitter Public Stream

Real-Time Twitter Mining with Apache Spark (PySpark)

Motivation

I love python and I love Machine Learning, specially in real-time. Up to now, Apache Spark does not have any Twitter Stream integration, so I put up a little workaround to be able to use spark on twitter data. Even better, I integrated the result into visualizations. So far, there is only a d3 wordcloud but I am planning to add more.

Getting Started

• Install Docker and Docker-compose
• Install Python and Pip
• Install dependecies: pip install psutil && pip install tweepy && pip install websockets
• Make sure you have Apache Spark installed. This repo works with spark-1.5.1-bin-hadoop2.6 verison perfectly. After that, you just need to remember where you extracted spark, we call it $SPARK_HOME, Ogey?
• Get your API keys from [https://dev.twitter.com/](Twitter Developers) and put them in data/config.json.
• set docker in your etc/hosts to point to your machine

How to Run the Example?

First, run the Kafka server with the following command:

docker-compose up

Then, fire up the stream source:

python twitter_stream.py

Now submit the trending_keywords_sparkjob.py to spark-submit:

$SPARK_HOME/bin/spark-submit --jars jar/spark-streaming-kafka-assembly_2.10-1.5.1 sparkjob.py

You will start to see the most frequently used words in the tweets from your opened stream like this:

-------------------------------------------
Time: 2015-12-18 21:11:17
-------------------------------------------
(u'python', 461)
(u'url', 282)
(u'#python', 125)
(u'user', 102)
(u'como', 70)
(u'de', 59)
(u'con', 43)
(u'monty', 42)
(u'este', 36)
(u'culebra', 35)
...

After that, you are gonna have a stateful count of all realtime feed of twitter stream with most used words (stop words and non-alpha numeric words are striped). The log will show you the top 10 words sorted by number of appearence. Note that spark will create a folder called twitter-checkpoint to keep state of the application and puts some rules for failover computation there.

You should see the most frequent words in Tweets that have Python in them. Why Python? Becuase it's awesome! For now, change the query here. Also, [change the topic in the Kafka example] ().

###Real-time D3.js WordCloud

First, make sure that all the previous steps are running simultaneously. Then:

cd html

bower install

python -m SimpleHTTPServer 9000

Go to http://localhost:9000 and see the running wordcloud updating every 10 seoncds.

###Share & Support Please help me make this repo a better project by sharing your ideas, forks, creating issues and features you need, I will appreciate any feedbacks. Send me a tweet at [https://twitter.com/_ambodi](_ambodi @ Twitter ).

###License See the LICENSE file for license rights and limitations (MIT).