The document introduces JStorm, an open source distributed real-time computation framework. It was created by Alibaba to address issues with Apache Storm and improve performance for real-time applications. JStorm has been used by Alibaba to process over 3 trillion messages per day across 3000+ servers. Key features discussed include high throughput, fault tolerance, horizontal scalability, and more powerful scheduling capabilities compared to Storm.

1. Company
LOGO
An Introduction of JStorm
LongdaFeng(zhongyan.feng@alibaba-inc.com)

2. Longda Feng
Alibaba
Agenda
Background
Basic Concept & Scenarios
Why start JStorm?
JStorm vs Storm
Question and Answer.

3. Who are we?
JStorm Team was among one of the
earliest that uses Storm in China.
 Storm 0.5.1/0.5.4/0.6.0/0.6.2/0.7.0/0.7.1
 JStorm 0.7.1/0.9.0/0.9.1/0.9.2/0.9.3/…
Our Duties
 Application Development
 JStorm System Development
 JStorm System Operation
Longda Feng
Alibaba

4. Who are Using JStorm
Many small Chinese companies are using
JStorm
Longda Feng
Alibaba

5. How Big?
More than 3000 servers
More than 3 trillion messages per day
Longda Feng
Alibaba

6. What is JStorm?
JStorm is a distributed programming
framework
 Similar to Hadoop MapReduce but designed
for real-time/in-memory scenarios
 Users can build powerful distributed
applications from very simple APIs
Longda Feng
Alibaba

7. What is JStorm?
Redesigned Storm in Java.
 Proved stable running in huge clusters.
 Much faster
 Much more powerful
Longda Feng
Alibaba

8. Basic Conception
Pipe-lined data processing
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Alibaba

9. Advantage 1
Easy learning:
 Simple Building Blocks: Topology/Spout/Bolt
APIs
 Out of Box RPC/Fault-tolerance/Real-time
Data Grouping & Combining
Longda Feng
Alibaba

10. Advantage 2
Excellent Scalability
 Horizontally Scalable
 DAG-based
 Adjustable parallelism of each component
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Alibaba

11. Stable
Guarantees Fault-Tolerance
 No Single Point of Failure
• Nimbus HA
• Any Supervisor can be shutdown
 New worker will be spawned and replace the
failed one automatically
Longda Feng
Alibaba

12. Accuracy
Acking framework guarantees no lost of
data
Transaction framework guarantees data
accuracy.
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Alibaba

13. Scenarios
Stateless Computation
 All data come from Tuple
Use Cases：
 Log Analysis
 Pipe-lined System
 Message converter
 Statistical Analysis
 Real-time Recommendation Algorithm
Longda Feng
Alibaba

14. Longda Feng
Alibaba
Why start JStorm
Storm community is not as active as we’ve
expected
 Tailored for enterprise environment
 Fixed critical bugs in Storm
 Provided professional technical support,
improved app development pace.
 Reduced operational cost.


15. How Many Versions?
https://github.com/alibaba/JStorm/releases
 0.9.6(2014/9/22)
 0.9.5.1(2014/9/14)
 0.9.5 (2014/8/27)
 0.9.4.1 (2014/8/15)
 0.9.4(2014/7/18)
 0.9.3.1 (2014/5/31)
 0.9.3 (2014/5/10)
 0.9.2 (2014/4/8)
 0.9.1(2014/1/24)
 0.9.0(2013/12/30)
 0.7.1(2013/4/28)
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Alibaba

16. JStorm is a superset of Storm
The program run in Storm can run in
JStorm without changing code
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Alibaba

17. More stable (1) -- nimbus HA
Nimbus HA
 Dual-Nimbus HA
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Alibaba

18. More stable (2) -- RPC
Netty supports 2 RPC modes
 Async
 Sync
• Sending speed keeps up with the receiving speed,
therefore the data flow is more stable.
Longda Feng
Alibaba

19. More stable(3) – resource isolation
Malicious Worker won’t mess up with
others
 Supported CPU Isolation with cgroups
 Supported Memory Isolation
Resources quota can be enforced on each
group (before 0.9.5)
Longda Feng
Alibaba

20. More stable(4) -- Monitor
Monitor every component in your
Topology
 Many more metrics(70+) than storm
Supported user-defined metrics
Supported user-defined alerts
Longda Feng
Alibaba

21. More stable (5) – CPU usage
Better utilizing CPU resource
 Improved disruptor implementation
• Drop CPU usage from 300% to 10% when
processing queue is full
 Avoid CPU spin-waiting
• Relocating nextTuple/ack/fail work to a different
thread
Longda Feng
Alibaba

22. More stable(6) -- more catch
Add try-catch in any place.
 Nimbus/supervisor main thread
 Spout/bolt initialization/cleanup
 All IO operation, serialization/deserialization
 All ZK operation
Longda Feng
Alibaba

23. More stable(7) -- ZK
Reduced unnecessary ZK usage：
 Removed useless watcher
 Increased ZK heartbeat frequency
 Detect failed worker without a full scan of the
entire ZK directory
Longda Feng
Alibaba

24. More stable（8） -- other
Improved GC Tuning.
Guaranteed that all workers killed after kill
command is issued
Guaranteed single supervisor/nimbus per
instance
Avoid excessive use of local ports by
Netty client
。。。
Longda Feng
Alibaba

25. More powerful scheduler
Balancing Tasks with regard of ：
 CPU
 Memory
 Net
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Alibaba

26. CPU assignment
By default assign each worker a single
CPU slot
Application can be configured to utilize
more slots
Why：
 Some task creates extra threads to do other
things in Alimama, one CPU slot doesn’t meet
requirement
Longda Feng
Alibaba

27. Memory Usage
Default worker memory is 2G
Application can be configured to utilize
more memory slots
Why:
 In Alipay Mdrill application, Solr bolt will apply
much more memory
Longda Feng
Alibaba

28. Smarter Balancing
With JStorm Scheduler:
 Tasks that exchange data heavily tend to be
assigned to the same worker to avoid
networking cost.
Longda Feng
Alibaba

29. User Defined Scheduler
User define task run one designated
worker
 User can setting how many CPU slot /memory
slot will be used
Why：
 In Taobao TAE project, some bolts want to
run in user defined-nodes
Longda Feng
Alibaba

30. Task on Different Node
Task of one component can be scheduled
to run on different nodes
Why：
 In ALIPAY Mdrill, Solr bolt must run different
node
Longda Feng
Alibaba

31. Task on Single Node
All tasks can be scheduled to run on a
single node.
Why:
 In Taobao TLog, there are many small jobs, in
order to reduce network cost, all task of one
job must run on single node.
Longda Feng
Alibaba

32. Old Assignment
“Last Assignment Policy”
 By default , a task will run on the machine it
runs previous time
Why：
 In Alibaba CDO, When restart one application,
user wanted to reuse old workers
Longda Feng
Alibaba

33. Pluginable
Be able to run on:
Hadoop yarn(more stable than storm)
Alibaba Apsara Clould System
Alibaba Elastic Resource Pool
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Alibaba

34. Classloader
Resolved application jar-confliction with
JStorm
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Alibaba

35. More convenient UI
More useful stats collected and displayed.
Browse Worker Log in UI
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Alibaba

36. Support libjar
Don’t need assembly all dependency jars
into one jar
 Submit libjar with libjar parameter
 Support worker.classpath
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Alibaba

37. Faster
6 Servers (24core/98G)
18 Spout/18 Bolt/18 Acker
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Alibaba
9280598
10818815
Throughput vs workers
9065965
6819139
5610201
6243680
6830500
5595900 5474180
3379800
12000000
10000000
8000000
6000000
4000000
2000000
0
0 10 20 30 40 50 60
polltuples/10s
workers
jstorm
storm

38. JStorm 41W/S Sending Speed
Longda Feng
Alibaba

39. Storm 41W/S Sending Speed
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Alibaba

40. Why Faster
Reduce memory-copying by zeroMq
Dedicated Deserializing Thread
Better Tuned Sampling Logic
Better Tuned Acking Framework
Better Tuned GC
Longda Feng
Alibaba

41. Other Improvement
 More than 100 improvements
 https://github.com/alibaba/JStorm/blob/master/history.md
 Fixed assign topology competition
 Reset rebalance/reassigned worker timeout as 4 minutes
 Graceful worker shutdown
 Improvement on thrift server
 Avoid mistakenly killing of worker while rebalancing jobs.
 。。。。
Longda Feng
Alibaba

42. More document
https://github.com/alibaba/JStorm/wiki
Google-group:JStorm-user@googlegroups.com
Wangwang：JStorm
QQ：228374502
Laiwang: JStorm
Longda Feng
Alibaba

43. Join us
Welcome to Join us
 zhongyan.feng@alibaba-inc.com
Longda Feng
Alibaba

44. Company
LOGO
纪君祥（Longda Feng）