Hi,
Thanks for the info. I understand ELT (Extract, Load, Transform) is more
appropriate for big data compared to traditional ETL. What are the major
advantages of this in Big Data space.
Example. if I started using Sqoop to get data from traditional transactional
and Data Warehouse databases an
co.com]
Sent: 18 December 2015 21:51
To: user@hive.apache.org; Ashok Kumar
Subject: Re: The advantages of Hive/Hadoop comnpared to Data Warehouse
Yes, that is what I meant.
In practice, it is often not possible to reach a 100% perfectly denormalized
fact table (for instance, if you need
I think you should draw more the attention that Hive is just one component in
the ecosystem. You can have many more components, such as ELT, integrating
unstructured data, machine learning, streaming data etc. however usually
analysts are not aware about the technologies and it staff is not much
15 at 4:22 PM
To: "user@hive.apache.org<mailto:user@hive.apache.org>"
mailto:user@hive.apache.org>>
Subject: Re: The advantages of Hive/Hadoop comnpared to Data Warehouse
Thank you sir.
Can you please describe a bit more detail your vision of "A fully denormalized
columnar s
t), please contact the sender by reply
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From: Ashok Kumar
Reply-To: User , Ashok Kumar
Date: Friday, December 18, 2015 at 4:01 PM
To: User
Subject: The advantages of Hive/Hadoop comnpar
18, 2015 at 4:01 PM
To: User mailto:user@hive.apache.org>>
Subject: The advantages of Hive/Hadoop comnpared to Data Warehouse
Gurus,
Some analysts keep asking me the advantages of having Hive tables when the star
schema in Data Warehouse (DW) does the same.
For example if you have fact and di
Gurus,
Some analysts keep asking me the advantages of having Hive tables when the star
schema in Data Warehouse (DW) does the same.
For example if you have fact and dimensions table in DW and just import them
into Hive via a say SQOOP, what are we going to gain.
I keep telling them storage econo
