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We share our knowledge happily

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 […]

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 first step was to join two datasets on columns which were geographical coordinates. I wanted some easy and efficient solution. But […]

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 actual content is based […]

Nov 20, 2015

Adam Kawa

Blog

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Go to Big Data Weekly Quiz #10 to start playing this week’s edition. The quiz covers topic from the last issue of Hadoop Weekly and it contains questions about Spark, Succinct Spark, Zeppelin, S3 and EMR. Remember to share your score on Twitter or Facebook! đŸ™‚

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 how they can be addressed using existing […]

When properly deployed, Spark Streaming 1.2 provides zero data loss guarantee. To enjoy this mission-critical feature, you need to fulfil following prerequisites: The input data comes from reliable source and reliable receivers Application metadata is checkpointed by the application driver Write ahead log is enabled Let’s briefly describe these prerequisites. In this blog post, we […]

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