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What is Impala alternative in HDP?

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What is Impala alternative in HDP?

New Contributor

Hi

We have one product which runs on CDH and uses Impala in on of its module. I need to know what are alternatives of Impala in HDP. Also ,we need to connect to Pentaho using that.

Ankit

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Re: What is Impala alternative in HDP?

Explorer
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Re: What is Impala alternative in HDP?

Explorer
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Re: What is Impala alternative in HDP?

Super Guru

@Ankit Jindal LLAP which comes with HDP 2.5. Or Apache HAWQ, which is also known as HDB. Both are fast sql engines and faster then impala. Both run on yarn. LLAP has terabyte scale. HDB is virtually limitless by adding nodes based on your usage. Lastly for known query patterns or access patterns, apache phoenix should be considered. Using primary row key along with secondary index is simply fast. Here is article on how to use phoenix secondary indexes. https://community.hortonworks.com/content/kbentry/61705/art-of-phoenix-secondary-indexes.html

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Re: What is Impala alternative in HDP?

Cloudera Employee
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Re: What is Impala alternative in HDP?

Super Guru

Apache Phoenix

https://phoenix.apache.org/faq.html

SparkSQL is probably what you are looking for.

http://spark.apache.org/sql/

Hortonworks is 100% open source apache.

It can run Apache Impala, Apache Drill, Hive LLAP, Phoenix, Apache HAWQ, SparkSQL, Presto.

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Re: What is Impala alternative in HDP?

Explorer

Good point Tim.

Each "SQL on Hadoop" implementation obviously has pros and cons... general rule of thumbs:

  • SparkSQL --> good for iterative processing, access existing Hive tables, given results fits in memory
  • HAWQ --> good for "traditional" BI-like queries, star schemas, cubes OLAP
  • HIVE-LLAP --> good for petabyte scale mixed with smaller tables requiring sub-second queries.
  • Phoenix --> A good way to interact with HBase tables, good with time series, good indexing
  • Drill, Presto --> Query federation-like capabilities but limited SQL syntax. Performance varies quite a bit.
Highlighted

Re: What is Impala alternative in HDP?

Explorer

Good point Tim.

Each "SQL on Hadoop" implementation obviously has pros and cons... general rule of thumbs:

  • SparkSQL --> good for iterative processing, access existing Hive tables, given results fits in memory
  • HAWQ --> good for "traditional" BI-like queries, star schemas, cubes OLAP
  • HIVE-LLAP --> good for petabyte scale mixed with smaller tables requiring sub-second queries.
  • Phoenix --> A good way to interact with HBase tables, good with time series, good indexing
  • Drill, Presto --> Query federation-like capabilities but limited SQL syntax. Performance varies quite a bit.
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