- 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.
