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780 high scalability-2010-02-19-Twitter’s Plan to Analyze 100 Billion Tweets


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Introduction: If Twitter is the “nervous system of the web” as some people think, then what is the brain that makes sense of all those signals (tweets) from the nervous system? That brain is the Twitter Analytics System and Kevin Weil, as Analytics Lead at Twitter, is the homunculus within in charge of figuring out what those over 100 billion tweets (approximately the number of neurons in the human brain) mean. Twitter has only 10% of the expected 100 billion tweets now, but a good brain always plans ahead. Kevin gave a talk, Hadoop and Protocol Buffers at Twitter , at the Hadoop Meetup , explaining how Twitter plans to use all that data to an answer key business questions. What type of questions is Twitter interested in answering? Questions that help them better understand Twitter. Questions like: How many requests do we serve in a day? What is the average latency? How many searches happen in day? How many unique queries, how many unique users, what is their geographic dist


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1 If Twitter is the “nervous system of the web” as some people think, then what is the brain that makes sense of all those signals (tweets) from the nervous system? [sent-1, score-0.239]

2 That brain is the Twitter Analytics System and Kevin Weil, as Analytics Lead at Twitter, is the homunculus within in charge of figuring out what those over 100 billion tweets (approximately the number of neurons in the human brain) mean. [sent-2, score-0.52]

3 Twitter has only 10% of the expected 100 billion tweets now, but a good brain always plans ahead. [sent-3, score-0.52]

4 Kevin gave a talk, Hadoop and Protocol Buffers at Twitter , at the Hadoop Meetup , explaining how Twitter plans to use all that data to an answer key business questions. [sent-4, score-0.162]

5 What type of questions is Twitter interested in answering? [sent-5, score-0.101]

6 How many unique queries, how many unique users, what is their geographic distribution? [sent-10, score-0.126]

7 The questions help them understand Twitter, their analytics system helps them get the answers faster. [sent-20, score-0.176]

8 Your choice has a lot to do with performance, how much data can be stored, and how agile you can be in reacting to future changes. [sent-34, score-0.223]

9 Each tweet has 12 fields, 3 of which have sub structure, and the fields can and will change over time as new features are added. [sent-35, score-0.118]

10 Protocol Buffer is a way of encoding structured data in an efficient yet extensible format. [sent-38, score-0.247]

11 What is often considered a weakness, Protocol Buffer’s use of an IDL to describe data structures, is actually considered a big win by Twitter. [sent-46, score-0.271]

12 Having to define data structure IDL is often seen as a useless waste of time. [sent-47, score-0.166]

13 All the code that once was written by hand for each new data structure is now simply auto generated from the IDL. [sent-49, score-0.448]

14 This saves ton of effort and the code is much less buggy. [sent-50, score-0.154]

15 At one point model driven auto generation was a common tactic on many projects. [sent-52, score-0.145]

16 Once you hand generate everything you start really worrying about the verbosity of your language, which moved everyone to more dynamic languages, and ironically DSLs were still often listed as an advantage of languages like Ruby. [sent-55, score-0.304]

17 Another consequence of hand coding was the framework of the weekitis. [sent-56, score-0.127]

18 It’s good to see code generation coming into fashion again. [sent-58, score-0.157]

19 I like seeing the careful evaluation of different options based on knowing what you want and why. [sent-62, score-0.128]

20 - RECAP Twitter says "Today, we are seeing 50 million tweets per day—that's an average of 600 tweets per second. [sent-66, score-0.572]


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