May 2017
Beginner to intermediate
596 pages
15h 2m
English
While we have seen Apache HIVE more as a Data Lake storage and query component, this can as well play a role into the serving layer, if the data exposed via HIVE views is a modelled data and meant for consumption by other applications. Both types of paradigms may exist here, that is, push and pull. Since HIVE supports access via JDBC driver, other application can pull the processed information over JDBC channel. Also, since it is a part of Hadoop storage layer required ETL mechanisms can be put in place for pushing the data out of the HIVE views containing modelled data.
Apache Impala is general purpose SQL query engine (also known as interactive SQL for Hadoop), quite an apt addition to our Data Lake implementation. ...