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Data processing on the cloud is increasingly used for offering cost effective services. In this paper, we present a method for resource allocation for data processing services over the cloud taking into account not just the processing power and memory requirements, but the network speed, reliability and data throughput. We also present algorithms for partitioning data, for doing parallel block data transfer to achieve better throughput and allocated cloud resources. We also present methods for optimal pricing and determination of Service Level Agreements for a given data processing job. The usefulness of our approach is shown through experiments performed under different resource allocation conditions.