Ah - politics. It’s frustrating, it’s funny, it’s serious business. It is perhaps one of the best windows we have into the nature of the human condition. So we think it’s fitting that we combine politics with another window into human nature - search data. In particular, Yelp’s PR team was interested in looking at how the Republican and Democratic National Conventions affected what people looked for on Yelp. Could we confirm certain political stereotypes? Would there be surprises? Methodology From a data analysis perspective, we first need to precisely state the question before we can get to tackling it....

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This post is part of a series covering Yelp's real-time streaming data infrastructure. Our series explores in-depth how we stream MySQL and Cassandra data at real-time, how we automatically track & migrate schemas, how we process and transform streams, and finally how we connect all of this into data stores like Redshift, Salesforce, and Elasticsearch. Read the posts in the series: Billions of Messages a Day - Yelp's Real-time Data Pipeline Streaming MySQL tables in real-time to Kafka More Than Just a Schema Store PaaStorm: A Streaming Processor Data Pipeline: Salesforce Connector Streaming Messages from Kafka into Redshift in near...

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Yelp is known for useful, funny, and cool reviews of all kinds of businesses, so it’s no surprise that they often get shared in other places. While we love seeing screenshots of these reviews shared on other websites, they don’t make for a great user experience. Their image formats make it easy to create and share but they become outdated, load slower than text, and make it hard for users to find out more about the business. We wanted to build something that retains screenshots’ ease of sharing while solving some their biggest shortcomings, so we created embedded reviews. Now,...

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This post is part of a series covering Yelp's real-time streaming data infrastructure. Our series explores in-depth how we stream MySQL and Cassandra data at real-time, how we automatically track & migrate schemas, how we process and transform streams, and finally how we connect all of this into data stores like Redshift, Salesforce, and Elasticsearch. Read the posts in the series: Billions of Messages a Day - Yelp's Real-time Data Pipeline Streaming MySQL tables in real-time to Kafka More Than Just a Schema Store PaaStorm: A Streaming Processor Data Pipeline: Salesforce Connector Streaming Messages from Kafka into Redshift in near...

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Yelp is now entirely on HTTPS! While several pages have been secured for quite some time (we began securing pages with sensitive information like passwords, credit card numbers, and even the reviews you submit, in 2008), we’ve finally made the transition to using TLS across the entirety of our website. To some, this will sound like quite the accomplishment while others may wonder why it took until mid-2016 to complete this migration. Why Now? Brief History of HTTPS Netscape created SSL in 1994 and by 2000, TLS became the default encryption protocol and the modern HTTPS spec was created. But...

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For the past two years we’ve been running a private bug-bounty program. We worked with academic researchers and bug hunters from all over the world and, as a result, we have fixed over a hundred potential vulnerabilities, and have paid bug bounties to dozens of security experts. Today we’re launching our public bug-bounty program as our next step towards improving the security of Yelp’s systems and services. Our vulnerability reward payouts will go up to $15,000 USD for the most impactful exploits. Since getting familiar with our infrastructure may be a bit intimidating, we’ve put together some information below to...

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This post is part of a series covering Yelp's real-time streaming data infrastructure. Our series explores in-depth how we stream MySQL and Cassandra data at real-time, how we automatically track & migrate schemas, how we process and transform streams, and finally how we connect all of this into data stores like Redshift, Salesforce, and Elasticsearch. Read the posts in the series: Billions of Messages a Day - Yelp's Real-time Data Pipeline Streaming MySQL tables in real-time to Kafka More Than Just a Schema Store PaaStorm: A Streaming Processor Data Pipeline: Salesforce Connector Streaming Messages from Kafka into Redshift in near...

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Peter Seibel wrote that to maximize engineering effectiveness, “Let a thousand flowers bloom. Then rip 999 of them out by the roots.” Flowers, in how the metaphor applies to us, are code patterns — the myriad different functions, classes, styles, and idioms that developers use when writing code. At first, new flowers are welcome — maybe the new pattern seems easier to use, more scalable, more efficient, or more suited to some particular task than the old. As a code base grows, and the flowers proliferate, however, it becomes clear which patterns work and which don’t. Suddenly, code patterns that...

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