In this session we review the design of the newly released off heap storage feature in Apache Geode, and discuss use cases and potential direction for additional capabilities of this feature.

1. Off-heap Storage
•
Edin Zulich

2. Agenda
• Motivation and goals for off-heap storage
• Off-heap features and usage
• Implementation overview
• Preliminary benchmarks: off-heap vs. heap
• Tips and best practices
• Future Directions

3. Motivation and goals for
off-heap storage

4. Why Off-heap
•
• Increase data density and reduce memory overhead
• 128+ GB user data in one JVM
• 10+ TB user data in one cluster
• Usable out-of-box without extensive GC tuning of JVM
• Maintain existing throughput performance

5. Off-heap Usage and
Features

6. Off-heap: How Do I Use It?
• Set the off-heap memory size for the process
– Using the new property: off-heap-memory-size
• Mark regions whose entry values should be stored off-heap
– Using the new region attribute: off-heap (false | true)
• Adjust the JVM heap memory size down accordingly
– The smaller the better; at least try to keep it below 32G
• Optionally
– Configure Resource Manager
– Lock the off-heap memory

7. Off-heap Features
• Startup options
• Interaction with other features
• Resource Manager
• Monitoring & Management
• Limitations

8. Startup Options
• --off-heap-memory-size
specifies amount of off-heap memory to allocate
• --lock-memory
specifies whether to lock the off-heap memory
• Example:
gfsh start server –initial-heap=10G –max-heap=10G –off-heap-
memory-size=200G –lock-memory=true

9. Off-heap Interaction with Other Features
• Deltas: values have to be copied (the clone option is ON,
and cannot be turned off)
• EntryEvents
– Limited availability of oldValue, newValue
• Indexes
– Functional range indexes not supported (too expensive)
• Region operations that compare the value do not call
object equals, but either PDXInstance or serialized bytes
– In order to do equality check without having to deserialize data

10. More Expensive with Off-heap
• PDX
– Values currently copied from off-heap to create a PDXInstance
• Deltas: to apply a delta you have to serialize/deserialize
every time
• Compression: there is an extra copy on decompression
• Querying: deserialize on every query

11. Off-heap and Resource Manager
• Out of Memory Semantics
• Eviction and Critical Thresholds
• Resource Manager API

12. “Out of Memory” Occurs When...
• Java heap runs out of memory
– Threads start throwing OutOfMemoryError
• Off-heap runs out of memory
– Threads start throwing OutOfOffHeapMemoryException
• => causing the Geode member to close and disconnect
– Closes the Cache to prevent reading inconsistent data
– Disconnects from the Geode cluster to prevent distribution problems
or hangs

13. Eviction and Critical Thresholds for Off-heap
• CriticalOffHeapPercentage
– triggers LowMemoryException for puts into off-heap regions
– critical member informs other members that it is critical
• EvictionOffHeapPercentage
– triggers eviction of entries in off-heap regions configured with
LRU_HEAP
• Semantics the same as with the equivalent heap
thresholds

14. Startup Options
• Existing:
• -critical-heap-percentage
• -eviction-heap-percentage
• New:
• -critical-off-heap-percentage
• -eviction-off-heap-percentage
• Example:
start server –initial-heap=10G –max-heap=10G –off-heap-memory-
size=200G –lock-memory=true –critical-off-heap-percentage=99

15. ResourceManager API
• GemFireCache#getResourceManager()
• com.gemstone.gemfire.cache.control.ResourceManager
– exposes getters/setters for all of the heap and off-heap threshold
percentages
– Examples:
▪ public void setCriticalOffHeapPercentage(float offHeapPercentage);
▪ public float getCriticalOffHeapPercentage();

16. Monitoring & Management
• Statistics
• Mbeans
• gfsh

17. Statistics
name description
defragmentations The total number of times off-heap memory has been defragmented.
defragmentationTime The total time spent defragmenting off-heap memory.
fragmentation The percentage of off-heap memory fragmentation. Updated every time a defragmentation is
performed.
fragments The number of fragments of free off-heap memory. Updated every time a defragmentation is
done.
freeMemory The amount of off-heap memory, in bytes, that is not being used.
largestFragment The largest fragment of memory found by the last compaction of off heap memory. Updated
every time a defragmentation is done.
maxMemory The maximum amount of off-heap memory, in bytes. This is the amount of memory allocated at
startup and does not change.
objects The number of objects stored in off-heap memory.
reads The total number of reads of off-heap memory.
usedMemory The amount of off-heap memory, in bytes, that is being used to store data.

18. MBeans
MemberMXBean
getOffHeapDefragmentationTime -- provides the value of the defragmentationTime statistic
getOffHeapFragmentation -- provides the value of the fragmentation statistic
getOffHeapFreeMemory -- provides the value of the freeMemory statistic
getOffHeapObjects -- provides the value of the objects statistic
getOffHeapUsedMemory -- provides the value of the usedMemory statistic
getOffHeapMaxMemory -- provides the value of freeMemory + usedMemory
RegionMXBean
listRegionAttributes (operation)
enableOffHeapMemory (true | false)

19. Gfsh Support for Off-heap Memory
• alter disk-store: new option "--off-heap" for setting off-heap for each
region in the disk-store
• create region: new option "--off-heap" for setting off-heap
• describe member: now displays the off-heap size
• describe offline-disk-store: now shows if a region is off-heap
• describe region: now displays the off-heap region attribute
• show metrics: Now has an offheap category. The offheap metrics
are: maxMemory, freeMemory, usedMemory, objects, fragmentation,
and defragmentationTime
• start server: added --lock-memory, --off-heap-memory-size, --critical-
off-heap-percentage, and --eviction-off-heap-percentage

20. Off-heap Limitations
• Maximum object size limited to slightly less than 2 GB
• All data nodes must consistently configure a region to be off-
heap
• Functional Range Indexes not supported
• Keys, subscription queue entries not stored off-heap
• Fragmentation statistic is only updated during off-heap
compactions

21. Implementation Overview

22. Off-heap: How are We Doing It?
• Using memory that is separate from the Java heap
– Built our own Memory Manager
– Memory Manager is very finely tuned and specific to our usage
– Avoid GC overhead
▪ Avoid copying of objects for promotion between generations
▪ Garbage Collector is a major performance killer
– Use sun.misc.Unsafe API for performance
• Optimizing code to minimize usage of heap memory
• Using off-heap as primary store instead of overflowing to it

23. Off-heap
Memory
Management

24. Off-heap Implementation
• Memory allocated in 2GB slabs
– Max data value size: ~2GB
– Object values stored serialized; blobs stored as byte arrays
– Allocation faster for values < 128KB
▪ Controlled by a system property: gemfire.OFF_HEAP_FREE_LIST_COUNT
▪ First try to allocate from the free list; if that fails, allocate from unused memory
▪ Small values (< 8B) inlined (not using any off-heap space)
• Defragmentation consolidates free memory to minimize
fragmentation
– Blocks writes; best to avoid by minimizing fragmentation

25. Off-heap Implementation (cont’d)
• Allocated chunks
– Header
▪ isSerialized
▪ isCompressed
▪ Size
▪ Padding size
• Free chunks
– Header
▪ Size
▪ Address of next chunk in the list

26. What is Stored On-heap vs. Off-heap
Always Stored On-heap Stored Off-heap
Region Meta-Data Values
Entry Meta-Data Reference Counts
- Off-Heap Addresses Lists of Free Memory Blocks
Keys WAN Queue Elements
Indexes
Subscription Queue Elements

27. Preliminary Benchmarks:
Off-heap vs. Heap

28. Off-heap: Initial Testing Results
• 256 GB user data per node across 8 nodes for total of 2 TB
of user data
• Heap-only test worked twice as hard to produce 1/3 the
updates as test using Off-Heap
– Details on the next slide
• Succeeded in scaling up to much larger in-memory data
• Increased throughput of operations for large data sets

29. Heap vs. Off-Heap Comparison
Java Heap Off-Heap
creates/sec 30,000 45,000
updates/sec 17,000 (std dev: 2130) 51,000 (std dev: 737)
Java RSS size 50 GB 32 GB
CPU load 70% (load avg 10 cpus) 32% (load avg 5 cpus)
JVM GC ConcurrentMarkSweep ConcurrentMarkSweep
GC ms/sec 777 ms 24 ms
GC marks (GC pauses) 1 per 30 sec never

30. Recommendations and
Best Practices

31. Off-heap Rules of Thumb
• Try to minimize fragmentation
– In order to avoid defragmentation
– Beware of usage patterns that lead to fragmentation
▪ Many updates of varying value size
▪ Use cases that require a lot of serialization/deserialization
• Beware of more expensive features
– Deltas
– Querying
– Compression
– PDX

32. Off-heap Recommendations
• Recommended when
– The values are relatively uniform in size
– The values are mostly less than 128K in size (configurable)
– The usage patterns involve cycles of many creates followed by
destroys or clear
– The values do not need to be frequently deserialized
• Configure all data nodes with the same off-heap-memory-
size

33. Future

34. How about...
• Storing keys, indexes, subscription queues off-heap?
• An API to invoke a defragmentation?
• A way to configure the slab size?
• A way to configure the max value size for the most efficient
off-heap allocation, or maybe the size increment?
• A different defragmentation algorithm/policy?
• Anything else?

35. Questions?

36. Feedback Welcome!
Full spec at:
https://cwiki.apache.org/confluence/display/GEODE/Off-
Heap+Memory+Spec

37. Join the Apache Geode Community!
• Check out: http://geode.incubator.apache.org
• Subscribe: user-subscribe@geode.incubator.apache.org
• Download: http://geode.incubator.apache.org/releases/

38. Thank You!