Nt1330 Unit 7 Igm

Satisfactory Essays
Based on the comparison Table 1, Table 2 and Table 3, we identified following set of categories on which we would like to evaluate the above tools and computing paradigm in subsequent sub-sections: 4.1.1. Distributed Computation, Scalability and Parallel Computation As we can see from the comparison tables, all computing tools provide these facilities. Hadoop distributes data as well as computing via transferring it to various storage nodes. Also, it linearly scales by adding a number of nodes to computing clusters but shows a single point failure. Cloudera Impala also quits execution of the entire query if a single part of it stops. IBM Netezza and Apache Giraph whereas does not have single point failure. In terms of parallel computation IBM Netezza is fastest due to hardware built parallelism. 4.1.2. Real Time Query, Query Speed, Latency Time The Hadoop employs MapReduce paradigm of computing which targets batch-job processing. It does not directly support the real time query execution i.e OLTP. Hadoop can be integrated with Apache Hive that supports HiveQL query language which supports query firing, but still not provide OLTP tasks (such as updates and deletion at row level) and has late response time (in minutes) due to absence of pipeline…show more content…
Also, since Clouera and Giraph perform in memory computation they do not require data input and data output that saves a lot of processing cost involved in I/O. None of the tools require the ETL (Extract, Transform and Load) service, thereby they save a major cost involved in data preprocessing. Hadoop is highly fault tolerant that is achieved by maintaining multiple replicas of data sets, and its architecture that facilitates dealing with frequent hardware malfunctions. Giraph achieves fault tolerance using barrier checkpoints.
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