CSRUD for Big Data
Abstract
This chapter describes how a distributed processing environment such as Hadoop Map/Reduce can be used to support the CSRUD Life Cycle for Big Data. The examples shown in this chapter use the match key blocking described in Chapter 9 as a data partitioning strategy to perform ER on large datasets. The chapter includes an algorithm for finding the transitive closure of multiple match keys in a distributed processing environment using an iterative algorithm that minimizes the amount of local memory required for each processor. It also outlines a structure for an identity knowledge base in a distributed key-value data store, and describes strategies and distributed processing workflows for capture and update phases ...
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