Five Pitfalls to Avoid with Hadoop

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Tips to avoid this pitfall:

Hadoop ETL requires organizations to acquire a completely new set of advanced programming skills that are expensive and difficult to find. To overcome this pitfall, it’s critical to choose a data integration tool that both complements Hadoop and also leverages skills organizations already have.

  • Select a tool with a graphical user interface (GUI) that abstracts the complexities of MapReduce programming.
  • Look for pre-built templates specifically to create MapReduce jobs without manually writing code.
  • Insist on the ability to re-use previously created MapReduce flows as means to increase developers’ productivity.
  • Avoid code generation since it frequently requires tuning and maintenance.
  • Visually track data flows with metadata and lineage.

The emergence of Hadoop as the de facto Big Data operating system has brought on a flurry of beliefs and expectations that are sometimes simply untrue. Organizations embarking on their Hadoop journey face multiple pitfalls that, if not proactively addressed, will lead to wasted time, runaway expenditures and performance bottlenecks. By proactively anticipating these issues and utilizing smarter tools, the full potential of Hadoop may be realized. Syncsort has identified five pitfalls that should be avoided with Hadoop.

 

Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

 
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