Refactoring to Java 8 Trisha Gee (@trisha_gee) Developer & - - PowerPoint PPT Presentation

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Refactoring to Java 8 Trisha Gee (@trisha_gee) Developer & - - PowerPoint PPT Presentation

Dec 07, 2022 643 likes •1.4k views

Refactoring to Java 8 Trisha Gee (@trisha_gee) Developer & Technical Advocate, JetBrains Why Java 8? Its Faster Performance Improvements in Common Data Structures Fork/Join Speed Improvements Changes to Support Concurrency

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Trisha Gee (@trisha_gee) Developer & Technical Advocate, JetBrains

Refactoring to Java 8

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Why Java 8?

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It’s Faster

  • Performance Improvements in Common Data

Structures

  • Fork/Join Speed Improvements
  • Changes to Support Concurrency
  • …and more

http://bit.ly/refJ8

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Easy to Parallelize

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Fewer Lines of Code

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New Solutions to Problems

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Minimizes Errors

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Safety Check

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Test Coverage

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Performance Tests

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Decide on the Goals

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Limit the Scope

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Morphia

https://github.com/mongodb/morphia

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Refactoring!

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Lambda Expressions

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Automatic Refactoring

  • Predicate
  • Comparator
  • Runnable
  • etc…
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Abstract classes

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Advanced Search

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Collections & Streams API

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Automatic Refactoring

  • For loop to collect
  • For loop to forEach
  • …with and without Streams
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Manual Refactoring

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Optional

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But what about performance?

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Lambdas

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20 40 60 80 100 120 140 160 180

Ops/ms

Anonymous Inner Classes vs Lambdas

Anonymous Inner Class Lambda

 

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http://www.oracle.com/technetwork/java/jvmls2013kuksen-2014088.pdf

2 4 6 8 10 12 14 16 18 20

single thread max threads nsec/op

Performance of Capture

anonymous(static) anonymous(non-static) lambda

 

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 

50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000

Constant message Variable message Ops/ms

Logging Performance

Direct call Lambda

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Streams vs Iteration

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1 2 3 4 5 6 7 8 9

Ops/ms

Iterator vs Stream (1000 elements)

for loop forEach()

 

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1000 2000 3000 4000 5000 6000 7000

1 10 100 1000 Ops/ms

IterHelper

  • riginal

simplified refactored

 

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1 2 3 4 5 6 7 8 9

1000 10000 100000 Ops/ms

IterHelper

  • riginal

simplified refactored

 

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BasicDAO – map & collect

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5000 10000 15000 20000 25000

1 10 100 1000

Ops/ms

BasicDAO

  • riginal

simplified refactored

 

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DuplicatedAttributeNames – filter, map & collect

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200 400 600 800 1000 1200

Ops/ms

DuplicatedAttributeNames

  • riginal

refactored

 

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EntityScanner– forEach

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 

0.01 0.02 0.03 0.04 0.05 0.06

Ops/ms

EntityScanner

  • riginal

refactored

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DatastoreImpl – filter & forEach

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0.1 0.2 0.3 0.4 0.5 0.6 0.7

Ops/ms

DatastoreImpl

  • riginal

refactored

 

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MappingValidator – single stream operation

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 

100 200 300 400 500 600 700 800 900

EntityWithOneError EntityWith10Errors EntityWith20Errors Ops/ms

MappingValidator

  • riginal

refactored

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QueryImpl – multiple operations

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500 1000 1500 2000 2500 3000 3500

Ops/ms

QueryImpl

  • riginal

simplified refactored

 

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Going parallel

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0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Serial Parallel Time Taken (seconds)

map()

MacBook Surface

 

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20 40 60 80 100 120 140 160 Serial Parallel Time Taken (millis)

findAny()

MacBook Surface

 

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Optional

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50,000 100,000 150,000 200,000 250,000 300,000 350,000

Value not null Value null Ops/ms

Compare Constant Field Value with Null

Null check Optional

 

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50,000 100,000 150,000 200,000 250,000 300,000

Value not null Value null Ops/ms

Compare Variable Field Value with Null

Null check Optional

 

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Summary

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Sometimes new idioms decrease clutter

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…but sometimes they don’t

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Sometimes the new features improve performance

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20 40 60 80 100 120 140 160 180

Ops/ms

Anonymous Inner Classes vs Lambdas

Anonymous Inner Class Lambda

 

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…and sometimes they don’t

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200 400 600 800 1000 1200

Ops/ms

DuplicatedAttributeNames

  • riginal

refactored

 

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Sometimes a new feature makes life easier

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…sometimes not so much

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Some refactoring can safely be done automatically

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…often you need a human brain

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Conclusion

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Should you migrate your code to Java 8?

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It Depends

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Always remember what your goal is

And compare results to it

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Understand what may impact performance

And if in doubt, measure

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Code may magically improve

Or you may expose areas for improvement

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Your tools can help you

But you need to apply your brain too

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http://bit.ly/refJ8

@trisha_gee