[第2回 Azure Cosmos DB 勉強会] Data modelling and partitioning in Azure Cosmos DB (Azure Cosmos DB でのデータモデリングとパーティション分割)

Transcript

1. Data modelling and partitioning in Azure Cosmos DB (Azure Cosmos

   DB でのデータ モデリングとパーティション分割)

2. Session's objectives

3. What is Azure Cosmos DB? Non-relational and horizontally scalable

4. What is Azure Cosmos DB? horizontally scalable

5. What is Azure Cosmos DB? non-relational

6. What is Azure Cosmos DB? non-relational and horizontally scalable

7. So is Azure Cosmos DB suitable for relational workloads?

8. Let's look at a concrete example

9. Identifying the operations we have to serve

10. Now let's implement this model on Azure Cosmos DB!

11. Starting with the Customer entity

12. Starting with the Customer entity

13. To embed or to reference?

14. To embed or to reference? - - - - -

    -

15. Our first entity: Customer

16. Customer customers PK: ?

17. What is partitioning?

18. What is partitioning? logical partitions

19. What is partitioning? Andrew Theo Mark Tim Deborah Luis

20. What is partitioning? Max size: 20 GB Max size: 2

    MB

21. What is partitioning?

22. What is partitioning?

23. What is partitioning?

24. What is partitioning? Andrew Theo Mark Tim Deborah Luis SELECT

    * FROM c WHERE c.username = 'Mark' our partition key

25. What is partitioning? Andrew Theo Mark Tim Deborah Luis SELECT

    * FROM c WHERE c.favoriteColor = 'orange' ?

26. Choosing a partition key for customers customers PK: ?

27. Choosing a partition key for customers customers PK: ?

28. Choosing a partition key for customers customers PK: id

29. Choosing a partition key for customers customers PK: id

30. Next: product categories

31. Product categories

32. Product categories productCategories PK: ?

33. Product categories productCategories PK: ? SELECT * FROM c

34. Product categories productCategories PK: type

35. Next: product tags

36. Product tags

37. Product tags productTags PK: ?

38. Product tags productTags PK: ?

39. Product tags productTags PK: type

40. Next: products

41. Products

42. Products

43. Products products PK: ?

44. Products products PK: ? CategoryA CategoryC CategoryB SELECT * FROM

    c WHERE c.categoryId = 'CategoryA'

45. Products products PK: categoryId category name? tag names?

46. Products: how to return category and tag names? products SELECT

    * FROM c WHERE c.categoryId = 'CategoryA' productCategories SELECT c.name FROM c WHERE c.id = 'CategoryA' productTags SELECT * FROM c WHERE c.id IN ('<tagId1>', '<tagId2>', '<tagId3>')

47. Introducing denormalization

48. Products: denormalizing category and tag names products PK: categoryId

49. Products: keeping everything in sync productCategories productTags products

50. Cosmos DB's change feed

51. Products: keeping everything in sync productCategories productTags products

52. Next: sales orders

53. Sales orders

54. Sales orders

55. Sales orders salesOrders PK: ?

56. Sales orders salesOrders PK: ?

57. Sales orders salesOrders PK: ? CustomerA CustomerC CustomerB SELECT *

    FROM c WHERE c.customerId = 'CustomerA'

58. Sales orders salesOrders PK: customerId

59. Sales orders salesOrders PK: customerId customers PK: id

60. Mixing entities in the same container?

61. Sales orders salesOrders PK: customerId customers PK: id

62. Sales orders: mixing with customers customers PK: id

63. Sales orders: mixing with customers customers PK: customerId

64. Sales orders: mixing with customers customers PK: customerId

65. Sales orders: mixing with customers CustomerA CustomerC CustomerB customer sales

    orders customers PK: customerId

66. Sales orders customers PK: customerId SELECT * FROM c WHERE

    c.customerId = 'CustomerA' AND c.type = 'salesOrder'

67. Sales orders customers PK: customerId

68. Denormalizing the count of sales orders per customer

69. Denormalizing the count of sales orders per customer

70. Denormalizing the count of sales orders per customer CustomerA CustomerC

    CustomerB customer sales orders customers PK: customerId

71. Denormalizing the count of sales orders per customer CustomerA CustomerC

    CustomerB update the customer add a sales order customers PK: customerId

72. Denormalizing the count of sales orders per customer CustomerA CustomerC

    CustomerB update the customer add a sales order

73. Sales orders customers PK: customerId SELECT * FROM c WHERE

    c.type = 'customer' ORDER BY c.salesOrderCount DESC

74. Our final design customers PK: customerId productCategories PK: type productTags

    PK: type products PK: categoryId

75. Our final design, optimized! customers PK: customerId productMeta PK: type

    products PK: categoryId

76. Key takeaways

77. Going further https://docs.microsoft.com/azure/cosmos-db/modeling-data https://docs.microsoft.com/azure/cosmos-db/how-to-model-partition-example https://devblogs.microsoft.com/cosmosdb/data-modeling-and-partitioning-for-relational-workloads/ https://github.com/AzureCosmosDB/labs/blob/master/readme.md https://github.com/AzureCosmosDB/labs/blob/master/decks/Data-Modeling.pptx