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How Zalando Used Bayesian Statistics to Save Loads of Money

By Calvin Seward on Apr 30, 2015 03:58 pm
zalandoEveryone likes to save money–and when you’re running a huge business like Zalando, saving money by making your systems more efficient can mean saving millions of Euros. That’s why I’m excited to tell you that the Zalando Data Intelligence team recently found a way to save us piles of money. In this post, I’ll tell you how. THE GOAL Until recently, the only way that Zalando’s warehouse workers were able to determine the weights of our hundreds of thousands of items was by weighing each item manually. As you can imagine, this was a labor-intensive, time-consuming and expensive process. It recently occurred to us that we could greatly simplify our operations by replacing our manual weight estimation process with highly refined data from another, automatic process. Here’s where those huge...
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Presto versus Hive: What You Need to Know

By Kiyoto Tamura on Apr 28, 2015 02:57 pm
Hive vs Presto what you need to knowThere is much discussion in the industry about analytic engines and, specifically, which engines best meet various analytic needs. This post looks at two popular engines, Hive and Presto, and assesses the best uses for each. How Hive Works Hive translates SQL queries into multiple stages of MapReduce and it is powerful enough to handle huge numbers of jobs (Although as Arun C Murthy pointed out, modern Hive runs on Tez whose computational model is similar to Spark’s). MapReduce is fault-tolerant since it stores the intermediate results into disks and enables batch-style data processing. Many of our customers issue thousands of Hive queries to our service on a daily basis. A key advantage of Hive over newer SQL-on-Hadoop engines is robustness: Other engines like Cloudera’s Impala and Presto require careful...
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