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Hadoop Playlist at Spotify

| Posted in Tips, Troubleshooting |

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A typical day of a data engineer at Spotify revolves around Hadoop and music. However after some time of simultaneous developing MapReduce jobs, maintaining a large cluster and listening to perfect music for every moment, something surprising might happen…!

What?

Well, after some time, a data engineer starts discovering Hadoop (and its related concepts) in the lyrics of many popular songs. How can Coldplay, Black Eyed Peas, Michael Jackson or Justin Timberlake sing about Hadoop?

Maybe it is some kind of illness? Definitely! A doctor could call it “inlusio elephans” ;)

Mysterious Mass Murder In The Hadoopland

| Posted in Monitoring, Troubleshooting |

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Mysterious Mass Murder

This is one of the most bloodcurling (and my favorites) stories, that we have recently seen in our 190-square-meter Hadoopland. In a nutshell, some jobs were surprisingly running extremely long, because thousands of their tasks were constantly being killed for some unknown reasons by someone (or something).

For example, a photo, taken by our detectives, shows a job running for 12hrs:20min that spawned around 13,000 tasks until that moment. However (only) 4,118 of map tasks had finished successfully, while 8,708 were killed (!) and … surprisingly only 1 task failed (?) – obviously spreading panic in the Hadoopland.

JobTracker slowness, guesstimation and a data-driven answer

| Posted in Monitoring, Troubleshooting |

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JobTracker slowness issue

The problem

A couple of weeks ago, we got a JIRA ticket complaining about JobTracker being super slow (while it used to be super snappy most of the time). Obviously in such a situation, developers and analysts are a bit annoyed because it results in difficulties in submitting and tracking status of MapReduce jobs (however, the side effect is having a time for unplanned coffee break, what should not be so bad ;)) Anyway, we are also a bit ashamed and sad, because we aim for a perfect Hadoop cluster and no unplanned coffee breaks interruptions.