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MapReduce framework consists of two primitive functions defined by the user: Map and Reduce.
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The figure illustrates how the information introduced by the user maps to the WSDL definitions.
Each map task processes one data block of the input file, and outputs intermediate key/value pairs generated by the user defined map function.
Mappers turn their given chunk into a sequence of key–value pairs; exactly how these key–value pairs are generated from the input data depends on the particular computing task and is determined by the code written by the user for the map function.
Phoenix provides two distinct types of APIs: the first set is defined by the user such as Map, Reduce, and Partition.
The multiplication factor γ 2 and the model parameter η are determined by the user-specified mapping of the two input pixels denoted (x 1,x 2) to the corresponding two output pixels (y 1,y 2) by solving the following equations: y_{1}=gamma_{2}otimes x_{1} (4).
Transcripts, which correspond to criteria defined by the user, can be mapped on-the-fly onto the KEGG metabolic maps, which are accessible as GIF images [ 7].
Additional nodes of the MappingGraph can be created by the user and represent mappings (so-called mapping nodes).
In this step, some centers are selected by the user in the GIS map layer.
Query data supplied by the user is parsed and mapped to the corresponding gene context data using python scripts.
It is important to note that SNP annotations to genes will not change from source to source, SNP identifiers will either map to genes (depending on the gene boundaries set by the user), or SNPs will not map to genes.
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