Oracle offers dedicated BI Server DB GB to
support HiveQL query generation against Hadoop Hive interface. Specific DB
Features are tuned to the capabilities of HiveQL. An example of using Hadoop
sources in BI Model is shown as below. I
have taken this from the Oracle published document.
Hive Queries – High
Latency
One of the biggest challenges with Hive
Queries is that these queries will have high query latency; hence these queries
are not suitable for ad hoc analysis. This blog is an attempt to explain number
of measures to make sure that ad hoc analysis should generated Hive Queries
which will perform.
Tools to Improve Performance of Hive Queries
Summary Advisor and Aggregate Persistence can
be used to vastly improve overall query performance. Some federated queries are not well suited for
Hadoop sources, particularly those requiring large volumes of data to be
“stitched” by the BI Server, instead aggregate source can vastly improve
performance of federated query.
Query latency can be reduced from minutes to
sub-seconds when leveraging Exalytics in-memory cache. By loading data into
Times Ten can improve the performance of the queries. E.g. a report directly
against Hadoop and federating relational table takes multiple minutes, but same
report against in-memory cache has sub-second response.
I believe for Hive Queries Exalytics might be
a better option.
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