Garbage Collection

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Garbage Collection

• Danny Angus

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Introduction

• Student loans, amongst other things, run B2B
  applications implementing government policy in
  the UK.
• We process 900,000 complex loan applications in
  the six months from March to September every year.

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Introduction

• We have to tune performance, our funding
  stakeholders demand we provide value for money.
  (As a tax payer so do I).
• You should tune for performance too.

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Myth

• Memory management is one of the things Java is
  supposed to do for us.
• We do have to be good citizens
• And sometimes it still fails to live up to our
  expectations.

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Just take a look at these comments from APR, and
imagine the code. Glad you dont have to write
it? I know I am.

• / Round up the block size to the next boundary,
  but always
• allocate at least a certain size (MIN_ALLOC).
• /
• / Find the index for this node size by
• dividing its size by the boundary size
• /
• / First see if there are any nodes in the area
  we know
• our node will fit into.
• /
• / Walk the free list to see if there are
• any nodes on it of the requested size
• NOTE an optimization would be to check
• allocator-gtfreeindex first and if no
• node is present, directly use
• allocator-gtfreemax_index. This seems
• like overkill though and could cause
• memory waste.
• /

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So what do we have

• A load of theory but no silver bullet (but I
  think Sun would like the AgressiveHeap option
  to work for most of us)
• No API which we (the hardworking geeks in the
  field) can use to even hint about what our
  applications are going to be doing.
• A few general heap options
• A lot of secret knowledge

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How to keep up with the work

• Suns JVM uses generational heap management
• Partions for old young
• Java can create a lot of new objects,
• For long running processes under steady heavy
  load that means a real lot.

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The Generations

• Young generation
• New space, when you create an object memory here
  is allocated.
• Tenured generation
• If it last longer than a wee while it is moved
  here
• Permanent generation
• Stuff (classes loaded mainly) that wont be
  thrown away

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And theres more to the young

• Creation space
• Two survivor spaces
• Objects are promoted from survivor space when
  they survive a certain number of collections. You
  can set this number.

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A Generalisation about types

• Mark and sweep
• Start in the VM and follow all of the object
  references you can reach,
• mark each object
• Remove the ones you cant reach
• Stop and copy
• Stop execution
• Copy all the objects you can reach into a new
  space

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Mark and sweep

• Lots of work to do all that marking
• Leads to fragmentation
• You can sweep concurrent with execution
• This is good if you have plenty of CPU and want
  to avoid pauses.
• Still need to defrag now and then though.
• More garbage more work

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Stop and copy

• You need twice as much memory
• Pauses everything for the whole time it takes
• De-fragments the space every time
• More survivors more work

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JRE 1.4

• Copying collector default for the young space
  aka minor collection
• Parallel copying XXUseParNewGC
• Parallel scavenge XXUseParallelGC
• Mark compact default for tenured space
  major collection
• Concurrent collector XXUseConcMarkSweepGC

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What is your goal?

• They expect you to choose betweenThroughput
  Response time, or speed v no pauses.
• But if youre like me youll want everything.

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The compromise

• Balance the time spent in collections against the
  number of collections.
• Get the maximum benefit from each collection.

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Some more clues

• Space fills to its threshold, and is cleaned
  right out.
• In a steady state process there will be an
  apparent base load in a newly cleaned space, you
  can measure this and size the spaces.
• Then you can pick the collector that least
  intrusively keeps up with the rate at which you
  use the space.

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So how do you measure?

• -loggcltfilepathgt
• -XXPrintGCDetails
• -verbosegcGC 0.000 DefNew 512K-gt64K(576K),
  0.0051493 secs 512K-gt155K(1984K), 0.0053630
  secs
• Draw the graph
• Youre looking for a sawtooth shape
• The peaks and troughs should reach the same point
  every time.

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Illustration

• Pink is before, blue after
• See the small amount cleaned at each small
  collection
• And the big amount cleaned in the major
  collection
• What does this suggest? Young space is too small
• Time line there is no time on this graph
• If the whole think took a day do we have too few
  major collections
• If this whole thing is a minute do we have too
  many
• Context is important

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If the heap in use grows

• Reduce the frequency of collections by increasing
  the young space

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Another example

• This time the young generation is more cleaned
• Fewer promotions
• Tenured space in use after the major collection
• If this continues the size of the heap will
  increase
• And pauses will be bigger

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Tie it back to real events

• Logarythmic early growth
• Steady young size and promotion
• Would we want the lines to be more horizontal?
• Only you can tell, balance memory use vs CPU
• Is this under load or is your normal peak load
  worse?
• Optimise for normal peak efficient
• Optimise for occasional peak robust

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If major collections are too frequent

• Increase the size of the heap a bit..

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Dont overdo it

• If the tenured space is too big youll have
  longer pauses for the tenured collection
• Reduce the number of promtions by sizing the
  young generation.
• -XXNewSize
• -XXMaxNewSize
• -XXSurvivorRatio

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Size the young gen
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Use Subtraction

• GC 83473.842 DefNew 98814K-gt7027K(104832K),
  0.0829770 secs 704440K-gt612653K(1036928K),
  0.0831090 secs
• GC 83475.633 DefNew 100210K-gt3604K(104832K),
  0.0963160 secs 705836K-gt613349K(1036928K),
  0.0964500 secs
• 696k promoted.

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Time, dont forget it
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A real default profile
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Heres one I prepared earlier
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Myth exploded

• Make Xmx and Xms the same size
• If you have plenty of RAM make Xmx big to cope
  with the unexpected
• But keep Xms small to manage collection
  frequency and size

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Tip

• Never let the OS swap out the Java heap
• This is because marking involves traversing the
  whole heap in unpredictable patterns

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Size the Young generation

• Make those collections work for you
• New size, new ratio balance the eden space and
  the survivor spaces
• You want as many of your short lived objects to
  live and die in one collection, without letting
  the collection get too onerous of course

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Size the permanent space

• Size it just a bit bigger than you need

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Myth exploded

• allocations which cant be made in permanent
  space will be made from tenured space
• In practice a compacting collection occurs, and
  if it doesnt release enough concurrent memory in
  the perm space the jvm spins up to 100 re-trying
  the compaction.

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Parallel and concurrent

• Might make sense if you have plenty of cpu
• Uses more cpu, but no pauses
• Except that you still get de-fragmentation
  pauses, threads have to be parked before objects
  can be moved and references re-written.
• Marking takes a while, and then you have to
  collect. This may be too slow to clear down
  during peaks.

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Aggressive heap

• The silver bullet?

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Some more stuff

• -Xincgc / -Xnoincgc
• -XXParallelGCThreadsltdesired numbergt
• -XXUseCMSCompactAtFullCollection
• -XXMaxTenuringThreshold0
• -XXSurvivorRatio1024
• -XXSoftRefLRUPolicyMSPerMB10000
• -XXPretenureSizeThresholdltbyte sizegt
• -XXDisableExplicitGC
• -XXCMSInitiatingOccupancyFractionltpercentgt
• -XXUseCMSInitiatingOccupancyOnly
• -XXCMSFullGCsBeforeCompaction1

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Sizes

• Xmsvalue
• -Xmxvalue
• -Xmnvalue
• -XXMinHeapFreeRatiominimum
• -XXMaxHeapFreeRatiomaximum
• -XXNewRatioratio
• -XXNewSizesize
• -XXMaxNewSizesize
• -XXMaxPermSizeltdesired sizegt
• -XXAggressiveHeap
• -XXUseAdaptiveSizePolicy

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Conclusion

• If you spend too much time doing this you
  probably need to buy hardware.
• But it is worth doing now and again.
• Thanks to Student Loans for letting me talk
  frankly about our problems.

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Questions?

• http//people.apache.org/danny

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