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Accelerating Development.pptx

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Uraz Pokharel

JPAstreamer allows efficient and intuitive database queries using Java streams by integrating the Java stream API with JPA. It works by generating a metamodel at compile time and using an annotation processor and stream renderer to convert stream queries into optimized JPA queries that can be executed by the underlying JPA provider.

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JPAstreamer
Problems Mixing Hibernate/JPA and Java for Database actions is neither completely type-sage nor intuitive. Tedious process to switch between two languages and HQL and JPQL syntax is wordy.
Solution The Java Stream API is efficient, terse and type-safe intuitive to express application logic with java streams Adding JPAstreamer make Your database application efficient, terse and type-safe intuitive to express application logic with java streams
How it fits? JPAstreamer is added as a lightweight dependency to the Maven/Gradle build. It integrates with the JPA layer by rendering the Stream queries to JPA and passing them to the underlying JPA provider for execution.
How it works? This enriches the API of an existing JPA provider to include Java Streams to express queries. Key parts: The annotation processor Generates metamodel used to compose predicates that can be interpreted by the Stream renderer The Stream renderer Inspects the Stream pipelines and renders optimized JPA queries.
Under the hood JPAstreamer uses and annotation processor to form a metamodel at compile time It inspects any classes marked with the standard JPA annotation @Entity For every entity Foo.class, a corresponsing Foo$.class is generated Classes can take the form Foo$.firstName.startWith() that can ne interpreted by JPAstreamers query optimizer.
The Annotation Processor Meta model
The Stream renderer The StreamRenderer interface in JPAStreamer is responsible for converting the result set of a JPA query into a stream of objects that can be processed using Java Streams.
Thanks
MapStruct
The problem Need to map between different models View models vs DB models 3rd party REST api vs DB model Types are similar, but not quite the same
Problem Solutions Manually Boring Error prone (might miss mapping) Reflection-based libraries Lack of type-safe Performance penalty Difficult debugging
MapStruct Mappings are defined as interfaces Mapping java code generated at compile time using annotation processor No reflection No runtime dependencies
Advantages of code generation Type-safe Quick feedback loop Easy to debug Plain method calls -> very fast No runtime dependencies Works on CLI or in your IDE

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Accelerating Development.pptx

  • 2. Problems Mixing Hibernate/JPA and Java for Database actions is neither completely type-sage nor intuitive. Tedious process to switch between two languages and HQL and JPQL syntax is wordy.
  • 3. Solution The Java Stream API is efficient, terse and type-safe intuitive to express application logic with java streams Adding JPAstreamer make Your database application efficient, terse and type-safe intuitive to express application logic with java streams
  • 4. How it fits? JPAstreamer is added as a lightweight dependency to the Maven/Gradle build. It integrates with the JPA layer by rendering the Stream queries to JPA and passing them to the underlying JPA provider for execution.
  • 5. How it works? This enriches the API of an existing JPA provider to include Java Streams to express queries. Key parts: The annotation processor Generates metamodel used to compose predicates that can be interpreted by the Stream renderer The Stream renderer Inspects the Stream pipelines and renders optimized JPA queries.
  • 6. Under the hood JPAstreamer uses and annotation processor to form a metamodel at compile time It inspects any classes marked with the standard JPA annotation @Entity For every entity Foo.class, a corresponsing Foo$.class is generated Classes can take the form Foo$.firstName.startWith() that can ne interpreted by JPAstreamers query optimizer.
  • 8. The Stream renderer The StreamRenderer interface in JPAStreamer is responsible for converting the result set of a JPA query into a stream of objects that can be processed using Java Streams.
  • 11. The problem Need to map between different models View models vs DB models 3rd party REST api vs DB model Types are similar, but not quite the same
  • 12. Problem Solutions Manually Boring Error prone (might miss mapping) Reflection-based libraries Lack of type-safe Performance penalty Difficult debugging
  • 13. MapStruct Mappings are defined as interfaces Mapping java code generated at compile time using annotation processor No reflection No runtime dependencies
  • 14. Advantages of code generation Type-safe Quick feedback loop Easy to debug Plain method calls -> very fast No runtime dependencies Works on CLI or in your IDE