Data analytics is increasingly being brought to bear to treat human disease, but as more and more health data is stored in computer databases, one significant challenge is how to perform analyses across these disparate databases. In this post I take a look at the Observational Health Data Sciences and Informatics (or OHDSI, pronounced “Odyssey”) program that was formed to address this challenge, and which today accounts for 1.26 billion patient records collectively stored across 64 databases in 17 countries.
Learn about BigBench, the new industrywide effort to create a sorely needed Big Data benchmark.
Benchmarking Big Data systems is an open problem. To address this concern, numerous hardware and software vendors are working together to create a comprehensive end-to-end big data benchmark suite called BigBench. BigBench builds upon and borrows elements from existing benchmarking efforts in the Big Data space (such as YCSB, TPC-xHS,
Apache Hive is a fantastic tool for performing SQL-style queries across data that is often not appropriate for a relational database. For example, semistructured and unstructured data can be queried gracefully via Hive, due to two core features: The first is Hive’s support of complex data types, such as structs, arrays, and unions, in addition to many of the common data types found in most relational databases. The second feature is the SerDe.
The beta release of Cloudera Impala, the first (and open source) real-time query engine for Apache Hadoop, has been out in the wild (in binary as well as VM forms) for over a month now, and users have had time to get up-close and hands-on. Consequently, we’re beginning to see some fascinating self-published observations and guides.
Here are just a few examples; you may know of more that we’ve missed:
This is the third article in a series about analyzing Twitter data using some of the components of the Apache Hadoop ecosystem that are available in CDH (Cloudera’s open-source distribution of Apache Hadoop and related projects). If you’re looking for an introduction to the application and a high-level view, check out the first article in the series.
In the previous article in this series, we saw how Flume can be utilized to ingest data into Hadoop.