Some principles to keep in mind when optimizing Java application performance.

1. Optimizing Java Performance
When App is on Fire
by Konstantin Pavlov
blog.konstantinpavlov.net
kpavlov

2. What’s the High Load?
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There is no exact definition of “High Load”
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Let's say, over 10000+ incoming events per second, over 1000
events per one seconds on peak
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Example: Market quotes processing

3. “20% efforts gives 80% of success”
– Pareto Principle

4. How to Optimize
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Measure, not guess
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Consider Not Doing Things
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Minimize I/O
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Reduce database operations
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Reduce network operations
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Reduce memory allocations and garbage collection
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Use logging judiciously
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Optimizing is iterative process

5. Measure, Not Guess
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Record and compare throughput before and after changes
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Samplers and profilers are your best friends: jvisualVM, JProfiler, etc.
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Different environments have different results
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Try to test on production-like environment
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If production-like environment is not available, compare relative
performance change on single environment

6. Consider Not Doing
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Use caching proxies for web applications
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Review your algorithms
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In some cases exit earlier. e.g. No need to prepare a data which will
not be used later

7. Minimize I/O
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If CPU is idle then I/O is likely a bottleneck
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File system operations
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Network operations, data serialization/deserialization.
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Logging
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Database operations

8. Distributing Objects
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Main rule of distributing objects: "Do not distribute objects. If
possible” (Martin Fowler, “Enterprise Integration Patterns”)
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CAP Theorem: "It's impossible in distributed system to achieve
Consistency, Availability and Partition Tolerance at the same time"
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Pros: Less I/O and serialization, simpler interfaces, no coping data
between POJOs
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Cons: Higher resource consumption on single node, may not scale
well, temptation to make architectural mess

9. Reduce Database I/O
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Make sure your DBMS has enough resources
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Minimize DB access. Cache objects in-memory, if possible
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Consider using stored procedures to reduce communication
between server and DB. DBMS is designed to process data
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Find the slowest query, optimize it, then take next and so on…
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Read/write only necessary columns

10. Use Logging Judiciously
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Consider what to log. Review toString() methods
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Consider when to log. Decision to log or not takes time itself.
Logger.isDebugEnabled() takes time
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Choose appropriate log levels
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When using {}-placeholders don’t evaluate expressions

11. Reduce GC
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Do not create unnecessary objects
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Use builders carefully. HashCodeBuilder and EqualsBuilder may
produce GC overhead in collections
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Review comparators used in TreeSets
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Reduce boxing/unboxing

12. Reduce CPU Load
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HashCode and Equals when called frequently may be a bottleneck

13. Iterative Optimization
Result p = measurePerformance();
while (!satisfied(p)) {
optimize();
p = measurePerformance();
}

14. Thank you!