• 10 mins presentation
• 8 slides
• 8-10 pages of report

• Introduction
• Dataset
• Persisted Data Model and Datastores
  • Describe your user and tweet data model in detail (preferably with diagrams).
  • Describe how you stored the data in the datastores.
  • What did you optimize for? What were the tradeoffs?
  • Did you create any indexes for the datastores?
• Processing tweets for storing in datastores
  • Make sure that you processed the tweets and stored the information (users, tweets) in the datastores one at a time (DO NOT load all the data into a dataframe and then load the dataframe into the datastore)
• Search Application Design
  • What types of searches are allowed? What kinds of drill-downs are allowed?
  • How were search queries translated into queries for the datastores?
  • What was your notion of relevance (i.e. how did you order the results of the search queries)?
  • How is the cache used?
• Results
  • Show the results of each type of query.
  • Timings of your test search queries (make sure you are hitting cached and non cached data)
• Conclusions
  • What are your conclusions regarding your design and experiments?
  • What did you learn from the project?
• References
• List what each team member did for the project.

Goal: Efficiently store the data for fast access.

• Datastores
  store the information in the tweets in at least 2 datastores.
  • relational datastore
  • non-relational datastore
• Cache
  Design and implement a cache for storing "popular" (frequently accessed) data.
• Search Application
  Design a search application for your tweet store. You must provide several options such as search by string, hashtag,  and user at the minimum.