![]() ![]() In a follow-up discussion with me, McCandless stressed that the decision wasn’t trivial given our “very large, high-velocity catalog with exceptionally strong latency requirements and extremely peaky query rates.” Against such stringent demands, the product search team was unsure whether Lucene could keep up.įirst off, McCandless said, Lucene has attracted a massive community of passionate people who are constantly iterating on the technology. In a Berlin Buzzwords 2019 talk, McCandless (and Amazon search colleague Mike Sokolov) walked through the reasons that Amazon, after years of success with a homegrown search engine, elected to embrace Lucene. …so long as he could continue to contribute changes upstream, back to the open source Lucene project. McCandless, who joined Amazon in 2017, says that “the incredible challenge” of configuring Apache Lucene to run at Amazon scale was “too hard to resist”… To get a deeper appreciation for Amazon’s embrace of Lucene, I caught up with Mike McCandless, a 12-year veteran of the Lucene community. Although Amazon has powered its product search for years with a homegrown C++ search engine, today when you search for a new book or dishwasher on Amazon (or when you ask Alexa to search for you), you’re tapping the power of Apache Lucene (“Lucene”), an open source full-text search engine. It becomes dramatically harder, however, when searching at Amazon scale: think billions of products, complicated by millions of sellers constantly changing those products on a daily basis, with hundreds of millions of customers searching through that inventory at all hours. ![]() At pretty much any scale, search is hard. ![]()
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