Posts Tagged
‘hadoop’

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While a lot of problems can be solved in batch, the stream-processing approach can give you even more benefits. In this blog post series, we’ll discuss a real-world example of user session analytics to give you a use-case driven overview of business and technical problems that modern stream processing technologies like Apache Flink help you [...]

In this blog post, we share motivation, current status, and challenges for our new project, called AirHadoop. AirHadoop follows the sharing economy model and it aims to allow companies to use idle Hadoop clusters that belong to somebody else to temporarily gain more computing power and storage. Shared economy A sharing economy is an economic […]

Geospatial analytics on Hadoop A few months ago I was working on a project with a lot of geospatial data. Data was stored in HDFS, easily accessible through Hive. One of the tasks was to analyze this data and the first step was to join two datasets on columns which were geographical coordinates. I wanted […]

  Data Pipeline Evolution The LinkedIn Engineering blog is a great resource of technical blog posts related to building and using large-scale data pipelines with Kafka and its “ecosystem” of tools. In this post, I provide several pictures and diagrams (including quotes) that summarise how data pipeline has evolved at LinkedIn over the years. The […]

Avoiding the mess in the Hadoop cluster In the first part of this blog series, I described a few challenges that I had to face to quickly implement a simple Hive query and schedule it periodically on the Hadoop cluster. These challenges include data cataloguing, data discovery, data lineage and process scheduling. I also explained […]

Avoiding the mess in the Hadoop Cluster This blog series is based on the talk “Simplified Data Management and Process Scheduling in Hadoop” that we gave at the Big Data Technical Conference in Poland in February 2015. Because the talk was very well received by the audience, we decided to convert it into a blog […]

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