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Easy ORM-ness with Objectify-Appengine Meetu Maltiar Inphina Technologies
Overall Presentation Goal Google Datastore Basics Options available for managing persistence Objectify-Appengine Demo of an application using Objectify
Enough About Me Senior Software Engineer at Inphina Technologies that interest me:      Cloud Computing      Scala      Hadoop
Datastore Basics Entities Operations Keys Transactions
Entities An Entity is an object’s worth of data in the datastore In datastore an Entity is like HashMap-like object of type Entity  Datastore is conceptually a HashMap of keys to entities, and an Entity is conceptually a HashMap of name/value pairs
Operations Get() an entity as a whole from datastore Put() an entity as whole in datastore Delete() an entity from datastore Query() for entities matching criteria you define
Keys In the datastore, entities are identified by the id (or name) and a kind, which corresponds to the type of Object you are storing.  So, to get Employee #111 from datastore, we need to call something like get_from_datastore (“Employee”, 111)
Keys Continued There is actually a third parameter required to identify an entity and it is called parent Parent places the child in the same entity group as the parent Parent (which can be null for the un-parented, root entity) is also required to uniquely identify an Entity.
Keys Continued So, to get Employee #111 from datastore we need to call something equivalent to: get_from_datastore (“Employee”, 111, null) or, get_from_datastore (“Employee”, 111, the_parent).  Instead of passing three parameters datastore wraps it in a single Object called Key.
Transactions Data gets stored in gigantic form of thousands of machines In order to perform an atomic transaction datastore requires that entities lie on same servers. To give us more control over where our data is stored, the datastore has a concept of an entity group To give us more control over where our data is stored, the datastore has a concept of an entity group
Transactions Continued Within a Transaction we can access data from a single entity group Choose entity groups carefully Why not have everything in a single entity group? Google restricts number of requests per second per entity group
Executing Transactions When we execute get(), put(), delete() or query() in transaction We must operate it on single entity group All operations will either fail or succeed completely If another process modifies the data before commit datastore operation will fail
Tools
Persistence Options JPA/JDO Google Datastore Persistence Frameworks on GAE   Objectify-Appengine   Twig   Simple Datastore   Slim3
Google Datastore Challenges Supports just four operations It persists GAE-Specific entity classes rather than POJO’s Datastore Keys are untyped
JPA/JDO Challenges Extra Cruft Fetch Groups    Detaching    Owned/Unownedrelationships Leaky Abstraction Keys    Entity Groups    Indexes
Developers Dilemma
Objectify It lets you persist, retrieve, delete and query typed objects All native datastore features are supported It provides type safe key and query classes
Objectify Design Considerations Minimally impacts cold start time. It is light weight No external dependencies apart from GAE SDK
Working With Datastore Entity ent = new Entity(“car”); ent.setProperty(“color”, “red”); ent.setProperty(“doors”, 2); service.put(ent);
Objectify ORMNess Objects! Employee emp = new Employee(); emp.setFirstName(“John”); emp.setLastName(“Smith”); service.put(emp);
An Objectify Entity public class Employee {   @Id Long id;    private String firstName;    private String lastName; }
get() Operation Objectify ofy = Objectifyservice.begin(); Employee emp = ofy.get(Employee.class, 123); Map<Long, Employee> employees =  ofy.get(Employee.class, 123, 124, 125);
put() Operation Objectify ofy = Objectifyservice.begin(); Employee emp = new Employee(“John”, “adams”); ofy.put(emp); System.out.println(“Id Generated is ” + emp.getId()); List<Employee> employees = createEmployees(); ofy.put(employees);
delete() Operation Objectify ofy = Objectifyservice.begin(); ofy.delete(Employee.class, 123); Employee emp = // get Employee from some where ofy.delete(emp);
query() Operation Objectify ofy = Objectifyservice.begin(); List<Employee> employees =        ofy.query(Employee.class).filter(“firstName =”, “John”)
Demo     get()     put()     delete()     query()
Objectify Best Practices Use a DAO to register entities Automatic Scanning not advised adds to initialization time     will require dependency jars apart from GAE     will require changes in web.xml GAE spins down the instance when not in use. When it comes up the request is slow because of added initialization time. This is called cold start.
Objectify Best Practices … Use Batch Gets Instead of Queries Use Indexes sparingly By default every field of object will be indexed. It comes with heavy computational price. Use @Unindexed  on entity level and @Indexed at fields required for query Avoid @Parent In JPA “owned” entity relationship provides referential integrity checking and cascading deletes and saves. Not so here.
Happy Developer
Conclusion JDO/JPA learning curve is steep due to App Engine’s non-relational nature and unique concepts such as entity groups, owned and un-owned relationships. Google Datastore is low level. It makes no pretense of being relational but also does not allow working with objects. It just stores the objects of type com.google.appengine.api.datastore.Entity Objectify is light weight and it preserves the simplicity and transparency of low level API and does all work converting to and from POJOS to Entity Objects.
mmaltiar@inphina.com www.inphina.com http://thoughts.inphina.com
References Objectify-Appengine http://code.google.com/p/objectify-appengine/ Google IO 2011 Session on highly productive gwt rapid development with app-engine objectify-requestfactory and gwt-platform Twitter mining with Objectify-Appengine http://www.ibm.com/developerworks/java/library/j-javadev2-14/?ca=drs-

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Easy ORMness with Objectify-Appengine

  • 1. Easy ORM-ness with Objectify-Appengine Meetu Maltiar Inphina Technologies
  • 2. Overall Presentation Goal Google Datastore Basics Options available for managing persistence Objectify-Appengine Demo of an application using Objectify
  • 3. Enough About Me Senior Software Engineer at Inphina Technologies that interest me: Cloud Computing Scala Hadoop
  • 4. Datastore Basics Entities Operations Keys Transactions
  • 5. Entities An Entity is an object’s worth of data in the datastore In datastore an Entity is like HashMap-like object of type Entity Datastore is conceptually a HashMap of keys to entities, and an Entity is conceptually a HashMap of name/value pairs
  • 6. Operations Get() an entity as a whole from datastore Put() an entity as whole in datastore Delete() an entity from datastore Query() for entities matching criteria you define
  • 7. Keys In the datastore, entities are identified by the id (or name) and a kind, which corresponds to the type of Object you are storing. So, to get Employee #111 from datastore, we need to call something like get_from_datastore (“Employee”, 111)
  • 8. Keys Continued There is actually a third parameter required to identify an entity and it is called parent Parent places the child in the same entity group as the parent Parent (which can be null for the un-parented, root entity) is also required to uniquely identify an Entity.
  • 9. Keys Continued So, to get Employee #111 from datastore we need to call something equivalent to: get_from_datastore (“Employee”, 111, null) or, get_from_datastore (“Employee”, 111, the_parent). Instead of passing three parameters datastore wraps it in a single Object called Key.
  • 10. Transactions Data gets stored in gigantic form of thousands of machines In order to perform an atomic transaction datastore requires that entities lie on same servers. To give us more control over where our data is stored, the datastore has a concept of an entity group To give us more control over where our data is stored, the datastore has a concept of an entity group
  • 11. Transactions Continued Within a Transaction we can access data from a single entity group Choose entity groups carefully Why not have everything in a single entity group? Google restricts number of requests per second per entity group
  • 12. Executing Transactions When we execute get(), put(), delete() or query() in transaction We must operate it on single entity group All operations will either fail or succeed completely If another process modifies the data before commit datastore operation will fail
  • 13. Tools
  • 14. Persistence Options JPA/JDO Google Datastore Persistence Frameworks on GAE Objectify-Appengine Twig Simple Datastore Slim3
  • 15. Google Datastore Challenges Supports just four operations It persists GAE-Specific entity classes rather than POJO’s Datastore Keys are untyped
  • 16. JPA/JDO Challenges Extra Cruft Fetch Groups Detaching Owned/Unownedrelationships Leaky Abstraction Keys Entity Groups Indexes
  • 18. Objectify It lets you persist, retrieve, delete and query typed objects All native datastore features are supported It provides type safe key and query classes
  • 19. Objectify Design Considerations Minimally impacts cold start time. It is light weight No external dependencies apart from GAE SDK
  • 20. Working With Datastore Entity ent = new Entity(“car”); ent.setProperty(“color”, “red”); ent.setProperty(“doors”, 2); service.put(ent);
  • 21. Objectify ORMNess Objects! Employee emp = new Employee(); emp.setFirstName(“John”); emp.setLastName(“Smith”); service.put(emp);
  • 22. An Objectify Entity public class Employee { @Id Long id; private String firstName; private String lastName; }
  • 23. get() Operation Objectify ofy = Objectifyservice.begin(); Employee emp = ofy.get(Employee.class, 123); Map<Long, Employee> employees = ofy.get(Employee.class, 123, 124, 125);
  • 24. put() Operation Objectify ofy = Objectifyservice.begin(); Employee emp = new Employee(“John”, “adams”); ofy.put(emp); System.out.println(“Id Generated is ” + emp.getId()); List<Employee> employees = createEmployees(); ofy.put(employees);
  • 25. delete() Operation Objectify ofy = Objectifyservice.begin(); ofy.delete(Employee.class, 123); Employee emp = // get Employee from some where ofy.delete(emp);
  • 26. query() Operation Objectify ofy = Objectifyservice.begin(); List<Employee> employees = ofy.query(Employee.class).filter(“firstName =”, “John”)
  • 27. Demo get() put() delete() query()
  • 28. Objectify Best Practices Use a DAO to register entities Automatic Scanning not advised adds to initialization time will require dependency jars apart from GAE will require changes in web.xml GAE spins down the instance when not in use. When it comes up the request is slow because of added initialization time. This is called cold start.
  • 29. Objectify Best Practices … Use Batch Gets Instead of Queries Use Indexes sparingly By default every field of object will be indexed. It comes with heavy computational price. Use @Unindexed on entity level and @Indexed at fields required for query Avoid @Parent In JPA “owned” entity relationship provides referential integrity checking and cascading deletes and saves. Not so here.
  • 31. Conclusion JDO/JPA learning curve is steep due to App Engine’s non-relational nature and unique concepts such as entity groups, owned and un-owned relationships. Google Datastore is low level. It makes no pretense of being relational but also does not allow working with objects. It just stores the objects of type com.google.appengine.api.datastore.Entity Objectify is light weight and it preserves the simplicity and transparency of low level API and does all work converting to and from POJOS to Entity Objects.
  • 33. References Objectify-Appengine http://code.google.com/p/objectify-appengine/ Google IO 2011 Session on highly productive gwt rapid development with app-engine objectify-requestfactory and gwt-platform Twitter mining with Objectify-Appengine http://www.ibm.com/developerworks/java/library/j-javadev2-14/?ca=drs-