July 2017
Intermediate to advanced
796 pages
18h 55m
English
Content preview from Scala and Spark for Big Data Analytics
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Spark architecture in a cluster
Hadoop-based MapReduce framework has been widely used for the last few years; however, it has some issues with I/O, algorithmic complexity, low-latency streaming jobs, and fully disk-based operation. Hadoop provides the Hadoop Distributed File System (HDFS) for efficient computing and storing big data cheaply, but you can only do the computations with a high-latency batch model or static data using the Hadoop-based MapReduce framework. The main big data paradigm that Spark has brought for us is the introduction of in-memory computing and caching abstraction. This makes Spark ideal for large-scale data processing and enables the computing nodes to perform multiple operations by accessing the same input data. ...
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