Historically, many orgs. have replaced data warehouses with Hadoop clusters
and used Hive along with Impala (on Cloudera deployments) or Drill (on MapR
deployments) for SQL. Hive is older and slower, while Impala and Drill are
newer and faster, but you typically need both for their complementary
works best for you. HDInsights works well for mixing
matching tools.
HTH,
- SteveN
-Original Message-
From: Dean Wampler [mailto:deanwamp...@gmail.com]
Sent: Thursday, 26 February, 2015 8:54
To: Vikram Kone
Cc: dev@spark.apache.org
Subject: Re: Need advice for Spark newbie
Dean
Thanks for the info. Are you saying that we can create star/snowflake data
models using spark so they can be queried from tableau ?
On Thursday, February 26, 2015, Dean Wampler deanwamp...@gmail.com wrote:
Historically, many orgs. have replaced data warehouses with Hadoop
clusters and
','dev@spark.apache.org');
Subject: Re: Need advice for Spark newbie
Historically, many orgs. have replaced data warehouses with Hadoop
clusters and used Hive along with Impala (on Cloudera deployments) or Drill
(on MapR
deployments) for SQL. Hive is older and slower, while Impala and Drill
There's no support for star or snowflake models, per se. What you get with
Hadoop is access to all your data and the processing power to build the ad
hoc queries you want, when you need them, rather than having to figure out
a schema/model in advance.
I recommend that you also ask your questions
Hi,
I'm a newbie when it comes to Spark and Hadoop eco system in general. Our
team has been predominantly a Microsoft shop that uses MS stack for most of
their BI needs. So we are talking SQL server for storing relational data
and SQL Server Analysis services for building MOLAP cubes for
