Apache Pulsar: How a Segment-Oriented Architecture Delivers Bett
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This talk introduces Apache Pulsar, a durable, distributed messaging system. Pulsar uses Apache BookKeeper as its storage layer for message persistence. In this talk, Jia will discuss how this layered architecture allows Pulsar to achieve a high level of scalability and performance. In particular, It will cover:
- Pulsar’s segment oriented architecture. This architecture allows easy elasticity for your messaging cluster without having to do cumbersome rebalancing operations.
- The benefits that this segment oriented architecture brings.
- A benchmark of throughput and latency of Pulsar messaging system.
In short, this talk will be a deep dive into the storage internals of a large scale, production validated distributed messaging system.
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1. Fast, Durable, Flexible Pub/Sub based on
Segment-Oriented Architecture
演讲者／streamlio 翟佳
2.What is Apache Pulsar?
Durability Ordering Delivery Guarantees
Data replicated and Guaranteed ordering At least once, at most
synced to disk once and effectively once
Geo-replication Multi-tenancy Low Latency
Out of box support for A single cluster can Low publish latency of
geographically support many tenants 5ms at 99pct
distributed and use cases
applications
Unified messaging High throughput Highly scalable
model Can reach 1.8 M Can support millions of
Support both Topic & messages/s in a topics
Queue semantic in a single partition
single model
!2
4. Architecture view
- Separate layers between brokers bookies
4
6.Bookies - Apache BookKeeper
\ Durable and Consistent
- I/O Isola3on
! High Throughput
2 Low Latency
!6
7.Bookies - Apache BookKeeper
!7
8.Architecture view
• Unbounded topic
partition storage
• Instant scaling
without data
rebalance
• Independent
scalability
11.Seamless - broker failure
12.Seamless - bookie failure
13.Seamless - cluster expand
14. Conclusion
• Unbounded topic partition storage
• Instant scaling without data rebalance
• Seamless - broker failure recovery
• Seamless- bookie failure recovery
• Seamless - cluster expansion
• Independent scalability
15. Benchmark
https://github.com/openmessaging/openmessaging-benchmark
19. Pulsar Functions
- Lightweight stream processing
- New in Pulsar 2.0
- Currently supports Java and Python
Python
def process(input):
return input.replace(“jia”, “anonymous”)
Java
import java.util.function.Function;
public class Anon implements Function<String,String> {
@Override
public String apply(String input) {
return input.replace(“jia”, “anonymous”);
}
}
20. Pulsar Functions
Input Function
Output
Topic Topic
# pulsar-admin functions create \
—py anon.py --className anon \
--fqfn lc3-tenant/demo/anony \
Python --inputs persistent://lc3-tenant/demo/input \
--output persistent://lc3-tenant/demo/output
# pulsar-admin functions create \
—jar anon.jar --className Anon \
--fqfn lc3-tenant/demo/anony \
Java --inputs persistent://lc3-tenant/demo/input \
--output persistent://lc3-tenant/demo/output
21. Curious to Get More
• Apache Pulsar : http://pulsar.incubator.apache.org
• Apache BookKeeper : http://bookkeeper.apache.org
• Technical Blog : https://streaml.io/blog/
• Twitter: @apache_pulsar @asfbookkeeper
• slack:
• https://apache-pulsar.herokuapp.com/
• https://apachebookkeeper.herokuapp.com/
