1. Python Script is written to do the tweet collection through API and then extraction of urls & hashtags.
2. It seeks users choice of keyword(s) to search for the corresponding tweets and storing it into a json file.
3. Twarc command 'search' is used to collect the respective tweets with a timeout of 15 Minutes(i.e., the collection
    of tweets is suspended if the search command is not done by 15 minutes).
4. The tweets collected will be stored in a json file 'tweets_keywords'.
5. Urls and HashTags are extracted from 'tweets_keywords' into a text file 'twitter_out.txt'.
    i.  While reading Tweets, empty tweets are ignored and the tweets with at least one url or one hashtag is extracted/ 
    ii. There are several kinds of urls exist in the url entity of tweet. The main url is being extracted into text file 
        ignoring remaining kind of urls.
    iii. Similarly, all the hashtags of tweets are extracted into the output text file. 

1. Extracting urls & hashtags from the collected tweets for given user keyword(s)

2. Moving extracted text file 'twitter_out' from local folder to hdfs folder.

3. Running Hadoop MapReduce WordCount on 'twitter_out.txt' present in 'your_hdfs_folder' and place the generated output under 'output'

4. The generated output can be found in the hdfs folder named 'output'.
5. Running Spark MapReduce WordCount on twitter_extraction and extracting the wordcount output into Spark_Output file which will be stored in local folder.