Interactive Big Data Analytics Platform for Healthcare and Clinical Services - Engineering Sciences
A Big Data Platform (BDA) with
Hadoop/MapReduce technologies distributed over HBase (key-value NoSQL database
storage) and generate hospitalization metadata was established for testing
functionality and performance. Performance tests retrieved results from
simulated patient records with Apache tools in Hadoop’s ecosystem. At optimized
iteration, Hadoop distributed file system (HDFS) ingestion with HBase exhibited
sustained database integrity over hundreds of iterations; however, to complete
its bulk loading via MapReduce to HBase required a month. The framework over
generated HBase data files took a week and a month for one billion (10TB) and
three billion (30TB), respectively. Apache Spark and Apache Drill showed high
performance. However, inconsistencies of Map Reduce limited the capacity to
generate data. Hospital system based on a patient encounter-centric database was
very difficult to establish because data profiles have complex relationships.
Recommendations for key-value storage should be considered for healthcare when
analyzing large volumes of data over simplified clinical event models.
Read more...PDF in Iris Publishers
Read more...PDF in Iris Publishers
No comments:
Post a Comment