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diff --git a/chapter/9/streaming.md b/chapter/9/streaming.md index d2e2975..c9585e1 100644 --- a/chapter/9/streaming.md +++ b/chapter/9/streaming.md @@ -117,7 +117,7 @@ Till now we have talked about what is stream processing and what are the differe Despite all the differences among them, they all started with more or less the same goal: to be *the* stream processing system that would be used by companies, and we showed several examples of why companies might need such system. In this section, we would discuss two companies that use the stream processing system as the core of their bussiness: Twitter and Spotify. ## Twitter -Twitter is one of the 'go-to' exmaples that people would think of when considering large scale stream processing system, since it has a huge amount of data that needed to be processed in real-time. Twitter bought the company that created *Storm* and used *Storm* as its real-time analysis tool for several years {% cite toshniwal2014storm --file streaming %}. However, as the data volume along with the more complex use cases increased, Twitter needed to build a new real-time stream data processing system as *Storm* can no longer satisfies the new requirements. We would talk about how *Storm* was used at Twitter and then the system that tey built to replace *Storm*-*Heron*. +Twitter is one of the 'go-to' exmaples that people would think of when considering large scale stream processing system, since it has a huge amount of data that needed to be processed in real-time. Twitter bought the company that created *Storm* and used *Storm* as its real-time analysis tool for several years {% cite toshniwal2014storm --file streaming %}. However, as the data volume along with the more complex use cases increased, Twitter needed to build a new real-time stream data processing system as *Storm* can no longer satisfies the new requirements. We would talk about how *Storm* was used at Twitter and then the system that they built to replace *Storm*-*Heron*. - Storm@Twitter |