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When we’re talking about conventional IT systems, we rarely question the idea of geo-distributed systems and redundancy. And we don’t usually challenge the notion that load balancing among servers and farms is a smart thing to do. So why don’t we routinely think this way about Hadoop?

Customers can set up multiple Hadoop clusters and use each one for a different workload. Companies can then site these clusters in different geographies, for redundancy, load balancing and/or content distribution. The data can be segregated or, using replication technology, it can be synchronized between sites to create a “logical data lake.” Is utilizing multiple Hadoop clusters in this way is folly, or is it just pragmatism?

In this webinar, our panel will discuss:

  • Does Apache YARN make all tasks equal or does dedicating clusters to specific workloads make more sense?
  • Is the data lake concept best for all, or is partitioning…

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