source code is the input that tells the computer which task to execute.
source code is the input that tells the computer which task to execute.
input that tells the computer which task to execute is?
source code
computers can only directly execute the machine code instructions which are part of their instruction set. because these instructions are difficult for humans to read, and writing good programs in machine code or other low-level programming languages is a time-consuming task, most programmers write in the source code of a high-level programming language. this source code is translated into machine code by a compiler or interpreter so that the computer can execute it to perform its tasks. a compiler produces object code which is usually in machine language but may also be in an intermediate language which is at a lower level than the source. a runtime system is often used to execute object code by linking it with commonly used libraries. bytecode is a lower level of source which is designed for more efficient interpretation by interpreters.
computer code
the programming model for mapreduce architecture is a simple abstraction where the computation takes a set of input key-value pairs associated with the input data and produces a set of output key-value pairs. in the map phase, the input data is partitioned into input splits and assigned to map tasks associated with processing nodes in the cluster. the map task typically executes on the same node containing its assigned partition of data in the cluster. these map tasks perform user-specified computations on each input key-value pair from the partition of input data assigned to the task, and generates a set of intermediate results for each key. the shuffle and sort phase then takes the intermediate data generated by each map task, sorts this data with intermediate data from other nodes, divides this data into regions to be processed by the reduce tasks, and distributes this data as needed to nodes where the reduce tasks will execute. the reduce tasks perform additional user-specified operations on the intermediate data possibly merging values associated with a key to a smaller set of values to produce the output data. for more complex data processing procedures, multiple mapreduce calls may be linked together in sequence.
data-intensive computing