UPortal Performance Optimization Faizan Ahmed Architect and Engineering Group Enterprise Systems & Services RUTGERS faizan@rutgers.edu@rutgers.edu.

uPortal Performance Optimization

Faizan AhmedArchitect and Engineering GroupEnterprise Systems & ServicesRUTGERSfaizan@rutgers.edu

04/21/23 2

GC History Garbage Collection (GC) has been

around for a while (1960’s LISP, Smalltalk, Eiffel, Haskell, ML, Scheme and Modula-3)

Went mainstream in the 1990’s with Java (then C#)

JVM implementations have improved on GC algorithms/speed over the past decade

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GC Benefits/Cost Benefits

Increased reliability Decoupling of memory mgmt from program

design Less time spent debugging memory errors Dangling points/memory leaks do not occur

(Note: Java programs do NOT have memory leaks; “unintentional object retention” is more accurate)

Costs Length of GC pause CPU/memory utilization

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GC Options

Sun’s 1.3 JDK included 3 GC strategies

1.4 JDK includes 6 and over a dozen command line options

Application type will demand strategy: Real-time – short and bounded pauses Enterprise – may tolerate longer or less

predictable pauses in favor of higher throughput

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GC Phases

GC has two main phases: Detection Reclamation

Steps are either distinct: Mark-Sweep, Mark-Compact

… or interleaved Copying

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Fundamental GC Property

“When an object becomes garbage, it stays garbage.”

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Reachability

Roots – reference to object in a static variable or local variable on an active stack frame

Root Objects – directly reachable from roots

Live Objects – all objects transitively reachable from roots

Garbage Objects – all other objects

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Reachability Example

RuntimeStack

ref

ref

Heap

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GC Algorithms

Two basic approaches: Reference Counting – keep a count of

references to an object; when a count of zero, object is garbage

Tracing – trace out the graph of objects starting from roots and mark; when complete, unmarked objects are garbage

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Reference Counting

An early GC strategy Advantages:

can be run in small chunks of time Disadvantages:

does not detect cycles overhead in incrementing/decrementing

counters Reference Counting is currently out-of

favor

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Tracing

Basic tracing algorithm is known as mark and sweep mark phase – GC traverses reference

tree, marking objects sweep phase – umarked objects are

finalized/freed

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Mark-Sweep Example

Root

1. mark-sweep start

Root

2. end of marking

Root

3. end of sweeping

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Mark-Sweep

Problem is fragmentation of memory Two strategies include:

Mark-Compact Collector – After mark, moves live objects to a contiguous area in the heap

Copy Collector – moves live objects to a new area

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Mark-Compact Collector Example

Root

1. end of marking

Root

2. end of compacting

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Copy Collector Example

Root

1. copying start

Root

2. end of copying

UnusedUnused

UnusedUnused

From

From

To

To

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Performance Characteristics

Mark-Compact collection is roughly proportional to the size of the heap

Copy collection time is roughly proportional to the number of live objects

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Copying

Advantages: Very fast…if live object count is low No fragmentation Fast allocation

Disadvantages: Doubles space requirements – not

practical for large heaps

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Observations

Two very interesting observations: Most allocated objects will die young Few references from older to younger

objects will exist These are known as the weak

generational hypothesis

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Generations

Heap is split into generations, one young and one old Young generation – all new objects are

created here. Majority of GC activity takes place here and is usually fast (Minor GC).

Old generation – long lived objects are promoted (or tenured) to the old generation. Fewer GC’s occur here, but when they do, it can be lengthy (Major GC).

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Sun HotSpot Heap Layout

Young Old Permanent

Eden From To

Survivor Spaces

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Before Minor GC

Old Permanent

Eden From To

Survivor Spaces

UnusedUnused

Young

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After Minor GC

EmptyEmpty

Old Permanent

Eden To From

Survivor Spaces

UnusedUnused

Young

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GC Notes

Algorithm used will vary based on VM type (e.g., client/server)

Algorithm used varies by generation Algorithm defaults change between

VM releases (e.g., 1.4 to 1.5)

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Young Generation Collectors Serial Copying Collector

All J2SEs (1.4.x default) Stop-the-world Single threaded

Parallel Copying Collector -XX:+UseParNewGC JS2E 1.4.1+ (1.5.x default) Stop-the-world Multi-threaded

Parallel Scavenge Collector -XX:UseParallelGC JS2E 1.4.1+ Like Parallel Copying Collector Tuned for very large heaps (over 10GB) w/ multiple CPUs Must use Mark-Compact Collector in Old Generation

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Serial vs. Parallel Collector

stop-the-worldpause

SerialCollector

ParallelCollector

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Old Generation Collectors Mark-Compact Collector

All J2SEs (1.4.x default) Stop-the-world Single threaded

Train (or Incremental) Collector -Xincgc About 10% performance overhead All J2SEs To be replaced by CMS Collector

Concurrent Mark-Sweep (CMS) Collector -XX:+UseConcMarkSweepGC J2SE 1.4.1+ (1.5.x default (-Xincgc)) Mostly concurrent Single threaded

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Mark-Compact vs. CMS Collector

stop-the-worldpause

Mark-CompactCollector

Concurrent Mark-SweepCollector

initial mark

concurrentmarking

remark

concurrent sweeping

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JDK 1.4.x Heap Option Summary

Low Pause Collectors Throughput Collectors Heap SizesGeneration

Young

Old

Permanent

1 CPU 2+ CPUs

Serial Copying Collector (default)

Parallel Copying Collector

-XX:+UseParNewGC

1 CPU 2+ CPUs

Copying Collector (default)

Parallel Scavenge Collector

-XX:+UseParallelGC-XX:+UseAdaptiveSizePolicy

-XX:+AggressiveHeap

-XX:NewSize-XX:MaxNewSize

-XX:SurvivorRatio

Mark-Compact Collector (default)

Concurrent Collector

-XX:+UseConcMarkSweepGC

Mark-Compact Collector (default)

Mark-Compact Collector (default)

-Xms-Xmx

Can be turned off with –Xnoclassgc (use with care)-XX:PermSize

-XX:MaxPermSize

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Heap Tuning

Analyze application under realistic load

Run with –verbose:gc and other options to identify GC information

Select GC engine based on need Size areas of heap based on

application profile – e.g., an app that creates many temporary objects may need a large eden area

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Verbose Minor GC Example62134.872: [GC {Heap before GC invocations=1045:Heap def new generation total 898816K, used 778761K eden space 749056K, 100% used from space 149760K, 19% used to space 149760K, 0% used tenured generation total 1048576K the space 1048576K, 24% used compacting perm gen total 32768K, used 26906K the space 32768K, 82% used62134.880: [DefNewDesired survivor size 138018816 bytes, new threshold 16 (max 16)- age 1: 3718312 bytes, 3718312 total- age 2: 5935096 bytes, 9653408 total- age 3: 2614616 bytes, 12268024 total- age 4: 1426056 bytes, 13694080 total- age 5: 2095808 bytes, 15789888 total- age 6: 3996288 bytes, 19786176 total- age 7: 550448 bytes, 20336624 total- age 8: 4058384 bytes, 24395008 total: 778761K->23823K(898816K), 0.1397140 secs] 1035112K->280173K(1947392K) Heap after GC invocations=1046:Heap def new generation total 898816K, used 23823K eden space 749056K, 0% used from space 149760K, 15% used to space 149760K, 0% used tenured generation total 1048576K, used 256350K the space 1048576K, 24% used compacting perm gen total 32768K, used 26906K the space 32768K, 82% used} , 0.1471464 secs]

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Verbose Major GC Example199831.706: [GC {Heap before GC invocations=9786:Heap def new generation total 898816K, used 749040K eden space 749056K, 99% used from space 149760K, 0% used to space 149760K, 0% used tenured generation total 1048576K, used 962550K the space 1048576K, 91% used compacting perm gen total 32768K, used 27040K the space 32768K, 82% used199831.706: [DefNew: 749040K->749040K(898816K), 0.0000366 secs]199831.707:

[Tenured: 962550K->941300K(1048576K), 3.6172827 secs] 1711590K->1653534K(1947392K) Heap after GC invocations=9787:

Heap def new generation total 898816K, used 712233K eden space 749056K, 95% used from space 149760K, 0% used to space 149760K, 0% used tenured generation total 1048576K, used 941300K the space 1048576K, 89% used compacting perm gen total 32768K, used 27007K the space 32768K, 82% used} , 3.6185589 secs]

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Demonstrate Heap tuning

JVM heap tuning was demonstrated for uPortal running on local machine using JDK 1.5.06 . (one hour)

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Programming Tips No need to call System.gc() Finalizers must be used with care! The use of Object pools can be debated Learn to use ThreadLocal for large Objects

(but use with care) Be cognizant of the number/size of Objects

being created Use caches judiciously (e.g.,

WeakHashMap’s make bad caches under a heavily loaded system)

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Techniques for production env.

lsof command File descriptors Verbose gc Kill -3 Tune gc

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Conclusions

GC can be your friend (or enemy) Put your app on an Object diet Should always monitor an app with -

verbose:gc -XX:+PrintGCDetails Tune your heap only if there is a

problem A large heap may slow an app (more

memory is not always good)

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References

Garbage Collection in Java - http://www.cs.usm.maine.edu/talks/05/printezis.pdf

A brief history of garbage collection – http://www-128.ibm.com/developerworks/java/library/j-jtp10283/

Garbage collection in the HotSpot JVM - http://www-128.ibm.com/developerworks/java/library/j-jtp11253/

Diagnosing a GC problem -

http://java.sun.com/docs/hotspot/gc1.4.2/example.html