architecture patterns and practices
Post on 13-Jan-2015
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trait Speaker { val name:String val aliases:Set[String]}
trait Organization{ val bu = "tmall" val group = "alibaba"}
object WangFuqiang extends Speaker with Organization{ val name = "王福强"
val aliases = Set("千任", "@囚千任") val blog = “http://afoo.me”}
架构模式与实践漫谈
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Architecture
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Architecture Principles• Abstraction
• Modularity
• Scalability
• Robustness
• Security
• Availability
• Reusability
• name it more...
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Exciting?
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Don’t Be Silly!
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Overload
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How About Practices + Patterns
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Roadmap First
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Consistency
Layering
Isolation
Immutability
Clustering
Buffering
Async
Throttling单结点 多结点
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So Far, So Good
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Consistency
Layering
Caching
Isolation
Immutability
Clustering
Async
Throttling
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What we do?
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Sure, 1. Scale Up!
纵向扩展
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“I try so hard, I got so far...”
‘cause hardware can’t work well without proper software
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Buffering缓冲
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Queuesfucking simple idea, right?
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Queue Everywhere• cpu task run queue
• thread pool task queue
• actors’ mailbox
• TCP stack send buffer /receive buffer
• MOM
• etc.
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Batching分批处理when they slowly move
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When to batchWhen to flush
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Problem With Nagle Algorithm
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Latency VS.
Throughput
It’s your choice!
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Smart Batchingfocus on the whole pipeline
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http://mechanical-sympathy.blogspot.com/2011/10/smart-batching.html
• Lock-free
• 100K+ TPS
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DisruptorStart 2 use it today
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--------割--------
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Throttling限流|flow control
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Rate ControlBackpressure
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Rate Control
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Semaphore
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僵硬 灵活
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Let’s apply
BackPressureButterfly Effect
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表征
位置(反馈)方式
what
where how
BackPressure
load, rt, etc.
ack, nack, etc.hardware, os, app, etc.
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--------割--------
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2 + 2 = ?
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Caching缓存
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Why Caching?
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Cache Everywhere• CPU Level1-3 cache
• Browser-side cache
• Server-side cache
• Business-layer cache
• DAL-layer cache
• Database-level cache
• Reverse Proxy
• DNS
• Name it more...
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Cache Types• Local Cache
• Map
• Ehcache * (BigHeap)
• Redis
• Remote Cache
• Tair *
• Memcached
• In-Memory Data Grid - IMDG
• Coherence
• GemFire
* means Hybrid
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Cache Strategy
Dimension Synchronous Asynchronous
READ Read-Through Refresh-Ahead
WRITE Write-Through Write-Behind
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Caching Tricks• Dummy Value
• non-exist entities in storage
• Versioning
• long-period-cached files
K1
K2
K3
K1
K2
K3
K4 K4
K5 K5
Cache Storage
file1.v1
file1.v2index.html <=> file1
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Case Study - 支付宝双11预充值
我爬...
我也爬...
我跟着爬...
我等？！
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--------割--------
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Async异步
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give me the quote of EUR/USD
here u arebuy 2 lots
transaction result
Story Background...
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Future<Double> rateQuoteFuture = executor.submit(new Callable<Double>() { @Override public Double call() throws Exception { connection.getCurrentValue(USD); } });
try { Double rateQuote = rateQuoteFuture.get(5, TimeUnit.SECONDS); // Blocking wait Future<Integer> future = executor.submit(new Callable<Object>() { @Override public Integer call() throws Exception { if(isProfitable(rateQuote)) connection.buy(amount, rateQuote) else throw new Exception("not profitable"); } }); Integer amount = future.get(5, TimeUnit.SECONDS); // Blocking wait System.out.println("Purchased "+ amount + " USD"); } catch (InterruptedException e) { e.printStackTrace(); //To change body of catch statement use File | Settings | File Templates. } catch (ExecutionException e) { e.printStackTrace(); //To change body of catch statement use File | Settings | File Templates. } catch (TimeoutException e) { e.printStackTrace(); //To change body of catch statement use File | Settings | File Templates. }
Go Async
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The Pain In The Neckblocking wait
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1. val rateQuote = future {2. connection.getCurrentValue(USD)3. }
5. rateQuote onSuccess { case quote =>6. val purchase = future {7. if (isProfitable(quote)) connection.buy(amount, quote)8. else throw new Exception("not profitable")9. }10. 11. purchase onSuccess {12. case _ => println("Purchased " + amount + " USD")13. }14.}
Go Reactive
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Behind The Pretty Face blocking still exists
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Task Scheduling Matters
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Async & Task Schedule Granularity
•Process•Thread•Actor•Coroutine•Continuation
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Go Non-Blocking
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And Think In Big Picture
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Sir, Yes, Sir.Sunday, July 14, 13
R All Async Good?
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“Trade A For A” AsyncAnti-Pattern
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A yelled ‘get it done’
B working...
A looking/waiting/smoking...
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Future<Double> rateQuoteFuture = executor.submit(new Callable<Double>() { @Override public Double call() throws Exception { connection.getCurrentValue(USD); } });
Double rateQuote = rateQuoteFuture.get(5, TimeUnit.SECONDS);// Nothing more to do, just wait and return
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Future<Double> rateQuoteFuture = executor.submit(new Callable<Double>() { @Override public Double call() throws Exception { connection.getCurrentValue(USD); } });
Double rateQuote = rateQuoteFuture.get(5, TimeUnit.SECONDS);// Nothing more to do, just wait and return
Why don’t U do it in current thread?
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It’s All About
RESOURCE UTILITY资源利用率是关键
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SEDAA grand master of buffering + async
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--------割--------
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Layering
Isolation
Immutability
Clustering
Buffering
Async
ThrottlingManage Dependencies
Wisely明智地管理依赖
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WhereWeStand Service2
Service1
Service3
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ExceptionStart Small, But Basic!
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What we do after catch?retry?
ignore?throw up?
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Timeout Everywhere• Thread.join(long)
• Future.get(long, TimeUnit)
• ExecutorService.awaitTermination(long, TimeUnit)
• CountDownLatch.await(long, TimeUnit)
• RPC Framework, say, HSF or Dubbo
• IO timeout
• you name it...
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Circuit Breaker Pattern
I want it to be automatic!
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SwitchesI don’t need you here!
开关
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trait PartialFunction[-A, +B] extends (A => B) { self => import PartialFunction._
/** Checks if a value is contained in the function's domain. * * @param x the value to test * @return `'''true'''`, iff `x` is in the domain of this function, `'''false'''` otherwise. */ def isDefinedAt(x: A): Boolean ...}
trait Function1[@specialized(..) -T1, @specialized(..) +R] extends AnyRef { self => /** Apply the body of this function to the argument. * @return the result of function application. */ def apply(v1: T1): R
http://www.infoq.com/cn/articles/function-switch-realize-better-continuous-implementations
Switch.reduce{
}Sunday, July 14, 13
Hard Enough
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2. Scale Out横向扩展
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We r gonna Cluster it.
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Symmetric
Stateful
State
Asymmetric
Stateless
ComputationSunday, July 14, 13
Replicas 复制品, 副本
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Replica means Symmetric
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When It Goes Stateless
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Computational Replicas
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Master-Workers Pattern
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Most of the time, Computation and state are so close...
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State Replicas
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Read ScalesRedundancy
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Replication
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Replication Types• Consistency Concerning Replication
• Synchronous Replication
• Asynchronous Replication
• Bandwidth Concerning Replication
• Intra-IDC Replication
• Inter-IDC Replication
• Other Views...
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Load-Balancing
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So short？ Just Stay with me
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--------割--------
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Shards分片,分区aka. Partitioning
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Write ScalesStorage Scales
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Routing
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Lookup Table
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Hashing
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Consistent Hashing
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Sharding Strategy Matters• Capacity Planning
• Capacity Expanding
• State Transferring
• State Access Pattern
• Fault-Tolerance
• etc.
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L.B. Vs. Routing
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--------割--------
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ShitHappens
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Isolation隔离性
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Bulkhead Pattern
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One Tab, One Process
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Linux Container
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Single Box In A Cluster
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A Whole Cluster Goes Bad...
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So When you deploy clusters of• Search Service
• HSF/Dubbo Service
• Data Storage Service
• Caching Service(Tair, Redis, memcached...)
• Whatever that’s important or have higher priority, NO Share!
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What Do U Think?
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--------割--------
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Redundancy冗余
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Symmetric Cluster?
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Symmetric Cluster?
What A Lucky Boy!
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What About Asymmetric Cluster?
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BinaryStar Pattern
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--------割--------
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Way&Style
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Consistency一致性
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Why Consistency?
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Consistency Everywhere• Religion
• Bible
• Brotherhood initiation
• Psychology
• Gambling
• Debating
• Industry
大众就一款⻋车高尔夫，拍窄点就是菠萝，加个屁股就是新桑塔纳和新捷达，继续拍一拍就是速腾和朗逸、再捏一把就是新宝来，扩大一圈就是新帕萨特，再拍一拍就是迈腾，再加大一圈就是辉腾，拍成方的就是途安，加多三个后座就是夏朗，加高底盘就是途观，再撑大点就是途锐，拍扁就是尚酷，搓圆了就是甲壳虫。
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Show Time...
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统一构建原则
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In Framework Design like Spring
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-- Haskell is a pure functional language and even the I/O system can't break this purity.
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Go Consistency When Necessary
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Layering分层
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Why Layering?
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impact
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Layer Patterns Everywhere
Can U Name More?
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Cake Pattern
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Stackable Traits Pattern Decorator Pattern In Scala
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--------割--------
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Immutability不变性
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Persistent Data Structure
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Familiar?
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Event Sourcing
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Capture all changes to an application state as a sequence of events.
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Real World ES• Binlog, HLog . . .
• Kafka’s Storage Strategy
• MetaQ - Java Clone of Kafka,
• LMAX Platform
• Many home-brew tools
• Ultra Messaging Stream Edition(UMS) - Informatica
• Available Projects/Solutions
• https://github.com/eligosource/eventsourced
• https://github.com/sbtourist/Journal.IO
• https://github.com/fusesource/hawtjournalSunday, July 14, 13
案例分析•TMS编辑和发布的并发控制与潜在冲突
•模板中变量名变更的追踪无案底可查
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Lambda Pattern
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Does Lambda’s face inspire U?
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http://www.infoq.com/presentations/High-Performance-Network-Applications-in-the-Capital-Markets
Todd-Montgomery
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Log VS. JMXYour Opinion?
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--------割--------
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ComposabilityYes, This is a principle :0)
组合
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灵活运用工具的能力比工具质量要重要的多
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It’sNot The Ending, It’s The Beginning...
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推荐书目
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Have Fun & Happy
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