Lightning talk at RailsConf 2011 about mondrian-olap gem

1. Multidimensional
Data Analysis
with JRuby
Raimonds Simanovskis
github.com/rsim
@rsim

2. Relational
data model

3. SQL is good for detailed
data queries
Get all sales transactions in
USA, California
SELECT customers.fullname, products.product_name,
sales.sales_date, sales.unit_sales, sales.store_sales
FROM sales
LEFT JOIN products ON sales.product_id = products.id
LEFT JOIN customers ON sales.customer_id = customers.id
WHERE customers.country = 'USA' AND customers.state_province = 'CA'

4. SQL becomes complex
for analytical queries
Get total sales in USA, California
in Q1, 2011 by main product groups
SELECT product_class.product_family,
SUM(sales.unit_sales) unit_sales_sum,
SUM(sales.store_sales) store_sales_sum
FROM sales
LEFT JOIN product ON sales.product_id = product.product_id
LEFT JOIN product_class
ON product.product_class_id = product_class.product_class_id
LEFT JOIN time_by_day ON sales.time_id = time_by_day.time_id
LEFT JOIN customer ON sales.customer_id = customer.customer_id
WHERE time_by_day.the_year = 2011 AND time_by_day.quarter = 'Q1'
AND customer.country = 'USA' AND customer.state_province = 'CA'
GROUP BY product_class.product_family

5. Maybe write distributed
map reduce function?

6. Multidimensional
Data Model
Multidimensional cubes
Dimensions
Hierarchies and levels
Measures

7. OLAP technologies
On-Line Analytical Processing

8. http://github.com/rsim/mondrian-olap

9. MDX query language
Get total units sold and sales amount
in USA, California in Q1, 2011
by main product groups
SELECT {[Measures].[Unit Sales], [Measures].[Store Sales]} ON COLUMNS,
[Product].children ON ROWS
FROM [Sales]
WHERE ( [Time].[2011].[Q1], [Customers].[USA].[CA] )

10. Or in Ruby like this
Get total units sold and sales amount
in USA, California in Q1, 2011
by main product groups
olap.from('Sales').
columns('[Measures].[Unit Sales]',
'[Measures].[Store Sales]').
rows('[Product].children').
where('[Time].[2011].[Q1]', '[Customers].[USA].[CA]').
execute

11. Also more complex
queries
Get sales amount and profit %
of top 50 products sold in USA and Canada
during Q1, 2011
olap.from('Sales').
with_member('[Measures].[ProfitPct]').
as('(Measures.[Store Sales] - Measures.[Store Cost]) / Measures.[Store Sales]',
:format_string => 'Percent').
columns('[Measures].[Store Sales]', '[Measures].[ProfitPct]').
rows('[Product].children').crossjoin('[Customers].[Canada]', '[Customers].[USA]').
top_count(50, '[Measures].[Store Sales]')
where('[Time].[2011].[Q1]').
execute

12. OLAP schema
(mapping cube to tables)
schema = Mondrian::OLAP::Schema.define do
cube 'Sales' do
table 'sales'
dimension 'Gender', :foreign_key => 'customer_id' do
hierarchy :has_all => true, :primary_key => 'customer_id' do
table 'customer'
level 'Gender', :column => 'gender', :unique_members => true
end
end
dimension 'Time', :foreign_key => 'time_id' do
hierarchy :has_all => false, :primary_key => 'time_id' do
table 'time_by_day'
level 'Year', :column => 'the_year', :type => 'Numeric', :unique_members => true
level 'Quarter', :column => 'quarter', :unique_members => false
level 'Month',:column => 'month_of_year',:type => 'Numeric',:unique_members => false
end
end
measure 'Unit Sales', :column => 'unit_sales', :aggregator => 'sum'
measure 'Store Sales', :column => 'store_sales', :aggregator => 'sum'
end
end

13. mondrian-olap gem
eazybi.com