Abstract
Hash functions are an integral part of MapReduce software, both in Apache Hadoop and Spark. If the hash function performs badly, the load in the reduced part will not be balanced and access times will spike. To investigate this problem further, we ran the Wordcount program with numerous different hash functions on Amazon AWS. In particular, we will leverage the Amazon Elastic MapReduce framework. The paper investigates the general purpose, cryptographic, checksum, and special hash functions. Through the analysis, we present the corresponding runtime results.
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