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Debugger is detailed data flow analysis for the various MapReduce code levels, which helps the developer to fine-tune the algorithm and detect faults.It provides developers to code level control flow statistics of MapReduce job. User may apply regex validations or its own user defined validation classes.

The "Analyze Job" feature gives the cluster level correlation of data with execution flow inside the code. It can bring down hours of execution logic debugging trials by identification of root causes within minutes.

Jumbune provides a comprehensive table/chart view depicting the flow of input records through the job.User may apply regex validations or user defined validation classes,As per the applied validation, Flow Debugger checks the flow of input data tuples essentially <key, value> pair data for each mapper and reducer in the submitted job.The flow is displayed at job level, MapReduce level, and instance level.Unmatched keys/values represent the number of unexpected flow of key/value data through the job.Debugger drills down into the code to examine the flow of data through various counters like loops and if-conditions, else-if, etc.MapReduce job profiler module gives the correlation between the individual execution phases, resource consumption and throughput, for identification and rectification of bottlenecks.

About Us

Jumbune, a product from Impetus Technologies, that helps to optimize and analyze Big Data applications running on enterprise clusters. It is built on open source and highly scalable with deep insights into performance of Hadoop applications and clusters.