Big data is a big challenge in semantic web. We need to store trillion of triples/quads in a store. It is more than data warehouse as data are connected to each other to form a graph. So, semantic data lake is coined. Then query/inferencing is a real challenge to achieve scalability. Hadoop is a good choice of achieving scalability using commodity hardware. But, my question focuses on the concrete technique of implementing semantic data lake using Hadoop.
I agree with Mirko question, on scalability will be a side where one can rely on the HADOOP. the primary challenge lies on creation of cluster and define the map reduce job.
Hi Haneef,
Hadoop can definitely help you out in this.
Please go through this link - This article talks about possible solution.
http://www.datanami.com/2015/05/26/hadoop-triple-stores-and-the-semantic-data-lake/
Hello Mr. Pankaj Singh,
I read the link before. However, it is rather likely a news than addressing technical howto's. Anyway, thank you for the answer. I really need a concrete way out like pigSPARQL.
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