![Hadoop: Denormalization of many-to-many data by using multiple map keys for a single value. | Gluster Hadoop: Denormalization of many-to-many data by using multiple map keys for a single value. | Gluster](https://4.bp.blogspot.com/-3kZvhuPKVkI/UA25gHVQyPI/AAAAAAAABJE/70__xqx2SVw/s1600/chart-1.png)
Hadoop: Denormalization of many-to-many data by using multiple map keys for a single value. | Gluster
![How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org](https://i1.wp.com/andreafabrizi.org/wp-content/uploads/2019/01/Slide3.jpg?fit=990%2C557)
How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org
![How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org](https://i2.wp.com/andreafabrizi.org/wp-content/uploads/2019/01/Slide4.png?fit=990%2C557)
How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org
When migrating a data warehouse to a Spark/Hive/Hadoop stack, how necessary is it to maintain the OLAP schema? Is it possible to 'flatten' the schema out and still provide equivalent performance? -
![How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org](https://i1.wp.com/andreafabrizi.org/wp-content/uploads/2019/01/Slide1.jpg?fit=990%2C557)
How to exploit the full use of Hadoop and Data Lakes – Part 2: How to create Hadoop-Friendly data schema – AndreaFabrizi.org
![Figure 2 from SQL-to-NoSQL Schema Denormalization and Migration: A Study on Content Management Systems | Semantic Scholar Figure 2 from SQL-to-NoSQL Schema Denormalization and Migration: A Study on Content Management Systems | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/a4c7eed69558ba96ea2d0e8cb2810fc359b43175/3-Figure2-1.png)
Figure 2 from SQL-to-NoSQL Schema Denormalization and Migration: A Study on Content Management Systems | Semantic Scholar
![Modeling: Denormalized Dimension Tables with Materialized Views for Business Users · Advanced SQL · SILOTA Modeling: Denormalized Dimension Tables with Materialized Views for Business Users · Advanced SQL · SILOTA](http://www.silota.com/docs/images/recipes/denormalized-table/facts_dimensions.png)