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Multidimensionāla
  (Oracle un MySQL)
 datu analīze ar
     JRuby
Agile
                                      Open-
Tehnoloģijas                          source
                                      Ruby



               Raimonds Simanovskis
                                      JavaScript
                                         github.com/rsim



                        @rsim
Relacionālais datu
     modelis
SQL ir labs detalizētu datu
        atlasīšanai
           Atlasīt visas pārdošanas transakcijas
           ASV, Kalifornijā

SELECT customer.fullname, product.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'
SQL kļūst sarežģīts
analītiskiem pieprasījumiem
           Kāds ir pārdošanas kopsavilkums
           ASV, Kalifornijā,
           2011. gada pirmajā kvartālā
           pa galvenajām produktu grupām
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
Multidimensionālais
        datu modelis
Multi-dimensionāli “kubi” (cubes)

Dimensijas, hierarhijas un līmeņi
(dimensions, hierarchies, levels)

Mērījumi (measures)
OLAP tehnoloģijas
  On-Line Analytical Processing
MDX pieprasījumu
             valoda
         Kāds ir pārdošanas kopsavilkums
         2011. gada pirmajā kvartālā
         ASV, Kalifornijā,
         pa galvenajām produktu grupām

SELECT {[Measures].[Unit Sales], [Measures].[Store Sales]} ON COLUMNS,
           [Product].children ON ROWS
     FROM [Sales]
     WHERE ([Time].[2011].[Q1], [Customers].[USA].[CA])
http://github.com/rsim/mondrian-olap
(R)OLAP shēma
Dimensional model:
 cubes
 dimensions (hierarchies & levels)
 measures, calculated measures


                   Mapping


Relational model:
 fact tables, dimension tables
 joined by foreign keys
OLAP shēmas
                      definēšana
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
Multidimensionālie
   pieprasījumi no Ruby
      Kāds ir pārdošanas kopsavilkums
      2011. gada pirmajā kvartālā
      ASV, Kalifornijā,
      pa galvenajām produktu grupām


olap.from('Sales').
columns('[Measures].[Unit Sales]', '[Measures].[Store Sales]').
rows('[Product].children').
where('[Time].[2011].[Q1]', '[Customers].[USA].[CA]')
Demo

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Multidimensionāla datu analīze ar JRuby

  • 1. Multidimensionāla (Oracle un MySQL) datu analīze ar JRuby
  • 2. Agile Open- Tehnoloģijas source Ruby Raimonds Simanovskis JavaScript github.com/rsim @rsim
  • 4. SQL ir labs detalizētu datu atlasīšanai Atlasīt visas pārdošanas transakcijas ASV, Kalifornijā SELECT customer.fullname, product.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'
  • 5. SQL kļūst sarežģīts analītiskiem pieprasījumiem Kāds ir pārdošanas kopsavilkums ASV, Kalifornijā, 2011. gada pirmajā kvartālā pa galvenajām produktu grupām 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
  • 6. Multidimensionālais datu modelis Multi-dimensionāli “kubi” (cubes) Dimensijas, hierarhijas un līmeņi (dimensions, hierarchies, levels) Mērījumi (measures)
  • 7. OLAP tehnoloģijas On-Line Analytical Processing
  • 8.
  • 9.
  • 10.
  • 11. MDX pieprasījumu valoda Kāds ir pārdošanas kopsavilkums 2011. gada pirmajā kvartālā ASV, Kalifornijā, pa galvenajām produktu grupām SELECT {[Measures].[Unit Sales], [Measures].[Store Sales]} ON COLUMNS, [Product].children ON ROWS FROM [Sales] WHERE ([Time].[2011].[Q1], [Customers].[USA].[CA])
  • 12.
  • 14. (R)OLAP shēma Dimensional model: cubes dimensions (hierarchies & levels) measures, calculated measures Mapping Relational model: fact tables, dimension tables joined by foreign keys
  • 15. OLAP shēmas definēšana 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
  • 16. Multidimensionālie pieprasījumi no Ruby Kāds ir pārdošanas kopsavilkums 2011. gada pirmajā kvartālā ASV, Kalifornijā, pa galvenajām produktu grupām olap.from('Sales'). columns('[Measures].[Unit Sales]', '[Measures].[Store Sales]'). rows('[Product].children'). where('[Time].[2011].[Q1]', '[Customers].[USA].[CA]')
  • 17. Demo