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Using Spring and MongoDB with Cloud Foundry Chris Harris, Architect
Spring Data
Data Access Challenge #1: Scale Horizontally
Data Access Challenge #2: Heterogeneous data access needs
New demands on data access ,[object Object],[object Object],[object Object]
NoSQL offers several data store categories Column Key-Value Document Graph
Spring Framework built-in data access support ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Spring Data Building Blocks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Spring MongoDB
Spring Data Document Mongo ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Simple Domain Class
Mongo Template Direct Usage of the Mongo Template:
Generic Repository  Interface for generic CRUD operations on a repository for a specific type
Paging and Sorting Repository Extends “ CrudRepository ”   Usage: Paging and Sorting Repository:
Custom Repository  Custom Repository:  Keywords :  Keyword Sample Logical result GreaterThan findByAgeGreaterThan(int age) {"age" : { "$gt"  : age}} LessThan findByAgeLessThan(int age) {"age" : { "$lt"  : age}} Between findByAgeBetween(int from, int to) {"age" : { "$gt"  : from,  "$lt"  : to}} NotNull findByFirstnameNotNull() { ” firstname" : {" $ne"  : null}} Null findByFirstnameNull() { ” firstname" : null} Like findByFirstnameLike(String name) " firstname " :  firstname } ( regex ) etc….
Cross Store
JPA and MongoDB  JPA “Customer” with a “ SurveyInfo ”  Document
Using a Cross-Store Saving a Customer with a SurveryInfo Mongo Document:
Cloud Foundry
Choice of clouds Cloud  Provider Interface Application Service Interface Data Services Private  Clouds  Public Clouds Micro Clouds .js Other Services Msg Services .COM …
Cloud Foundry MongoDB Demo

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Using Spring Data and MongoDB with Cloud Foundry

  • 1. Using Spring and MongoDB with Cloud Foundry Chris Harris, Architect
  • 3. Data Access Challenge #1: Scale Horizontally
  • 4. Data Access Challenge #2: Heterogeneous data access needs
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  • 6. NoSQL offers several data store categories Column Key-Value Document Graph
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  • 13. Mongo Template Direct Usage of the Mongo Template:
  • 14. Generic Repository Interface for generic CRUD operations on a repository for a specific type
  • 15. Paging and Sorting Repository Extends “ CrudRepository ” Usage: Paging and Sorting Repository:
  • 16. Custom Repository Custom Repository: Keywords : Keyword Sample Logical result GreaterThan findByAgeGreaterThan(int age) {"age" : { "$gt" : age}} LessThan findByAgeLessThan(int age) {"age" : { "$lt" : age}} Between findByAgeBetween(int from, int to) {"age" : { "$gt" : from, "$lt" : to}} NotNull findByFirstnameNotNull() { ” firstname" : {" $ne" : null}} Null findByFirstnameNull() { ” firstname" : null} Like findByFirstnameLike(String name) " firstname " : firstname } ( regex ) etc….
  • 18. JPA and MongoDB JPA “Customer” with a “ SurveyInfo ” Document
  • 19. Using a Cross-Store Saving a Customer with a SurveryInfo Mongo Document:
  • 21. Choice of clouds Cloud Provider Interface Application Service Interface Data Services Private Clouds Public Clouds Micro Clouds .js Other Services Msg Services .COM …

Notas do Editor

  1. Oracle RAC clustering is very expensive. $70K/CPU according to list. Even at ½ the cost, it’s still really expensive to build out a horizontal data access grid.
  2. The amount of log data amassed in Facebook’s operations is staggering. Rothschild said Facebook manages more than 25 terabytes of data per day in logging data, which he said was the equivalent of about 1,000 times the volume of mail delivered daily by the U.S. Postal Service. BASE (basically available, soft state, eventually consistent)