This document summarizes a study on real-time analytics using Apache Storm. It outlines four parts to the study: 1) learning the theory, setup, and basics of Storm, 2) using Storm with Twitter streams, 3) going beyond basic Storm concepts with an example join, and 4) participating in a Storm project and hackathon. It then describes two practices - parsing tweet URLs and tracking top hashtags - to demonstrate Storm's use for real-time analytics on Twitter data streams.

1. Real-Time Analytics
with Apache Storm
Tae-woo Kim
tu_k@naver.com
1

2. The Progress of Study
1. Theory, Setup and Basic Storm
2. Storm with Twitter Streams
3. Beyond Storm Basics
4. Storm Project and Hackathon
2

3. Practice 1. Parsing tweet URLs
3
tweet-spout report-bolt
count-boltpython-URLs-bolt
python-split-sentence
urltext.py splitsentence.py

4. urltext.py
4
Using bs4 package
- Beautifulsoup4
>> HTML에서 데이터를 추출

5. 5
Run a program

6. 6
Result

7. Practice 2. TopN Hashtags
7
tweet-spout
count-boltpython-URLs-bolt
python-split-sentence
urltext.py splitsentence.py
report-bolt
Intermediate-ranker total-ranker

8. Hashtag Parsing
8

9. 9
Run a program

10. 10
Result

11. Plan of Study
1. Theory, Setup and Basic Storm
2. Storm with Twitter Streams
3. Beyond Storm Basics (Join 예제 수행)
4. Storm Project and Hackathon << 진행
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