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Browse CoursesBasic Filesystem operations The information returned is very similar to that returned by the Unix command ls l, with a few minor differences. The first column shows the file mode. The secord column is the replication factor of the file (something a traditional Unix filesystem do not have). Remember we set the default replication factor […]
Blocks A disk has a block size, which is the minimum amount of data that it can read or write. Filesystems for a single disk build on this by dealing with data in blocks, which are an integral multiple of the disk block size. Filesystem blocks are typically a few kilobytes in size, whereas disk […]
Scaling Out Map Reduce works for small inputs; now it’s time to take a bird’s-eye view of the system and look at the data flow for large inputs. For simplicity, the examples so far have used files on the local filesystem. However, to scale out, we need to store the data in a distributed filesystem […]
Java MapReduce Having run through how the MapReduce program works, the next step is to express it in code. We need three things: a map function, a reduce function, and some code to run the job. The map function is represented by the Mapper class, which declares an abstract map() method. Java MapReduce if (airTemperature […]
MapReduce is a programming model for data processing. The model is simple, yet not too simple to express useful programs in. Hadoop can run MapReduce programs written in various languages; we look at the same program expressed in Java. Ruby, and Python. Most importantly, MapReduce programs are inherently parallel, thus putting very large-scale data analysis […]
Data The volume of data being made publicly available increases every year. Organizations no longer have to merely their own data; success in the feature will be dictated to a large extent by their ability to extract value from other organizations data. A Brief History of Apache Hadoop Hadoop was created by Doug Cutting, the […]
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