Spark GraphX in Action

List of Figures

Chapter 1. Two important technologies: Spark and graphs

Figure 1.1. Big Data is data that is too big to fit on a single machine. Hadoop and Spark are technologies that distribute Big Data across a cluster of nodes. Spark is faster than Hadoop alone because it distributes data across the RAM in the cluster instead of the disks.

Figure 1.2. Three data blocks distributed with replication factor 2 across a Hadoop Distributed File System (HDFS)

Figure 1.3. MapReduce is the processing paradigm used by both Hadoop and Spark. Shown is a MapReduce operation to count the number of times “error” appears in a server log. The Map is (normally) a one-to-one operation that produces one transformed data item for each source data item. The Reduce ...