Thinkings of Architecture Design

Thinkings of Architecture Design
by Lin Shiding (An Top Architect @ Baidu.com)
Online View(in Chinese): http://wenku.baidu.com/view/8f7a79dcad51f01dc281f127.html

Translated & Transcript by fcicq

Page 2
Begin with Examples:

• Storage
• Distributed
• Service Architecture
• Computation Models

Page 3
Storage(1):

• Structure: File, Object, Table
• Characteristics of Data
  • mutable or not
  • size
  • data layout
• Access Pattern
  • Realtime Read(Query)/Write
  • Batched Write, Realtime Query
  • Stream Read
  • Scan / Range Query
• "Realtimeness"
  • Realtimeness
  • Freshness
  • Consistency

Page 4
Storage(2):

• Conflicts (fcicq: or trade-offs)
  • Latency / Throughput
  • Random / Sequential
  • Scale / Freshness (Realtimeness / Latency)
• Model
  • B+ Tree (Realtime, Random)
  • Log-based (Batched, Sequential)
• Solve the conflicts:
  • Weaken the requirements
  • Exploit the locality
  • Combine models

Page 5
Storage Model: B+ tree
(pic)

Page 6
Storage Model: Log-based structure
(pic)

Page 7
Storage (Model): Combined(/Hybrid) Model
(S: Sequential Read performance High, High storage capacity)
(R: Random Read performace High, Low storage capacity)

Page 8
Distributed

• Goal
  • Scaling (capacity): scalability
  • Fault Tolerance: availability
• Methods
  • Partition
  • Replication

(P = p^k => P = 1-(1-p)^k)

• Point
  • Protocol Design
  • Debugging

Page 9
Distributed: Partition

• Static hashing
  • cant modify/tune (after build)
• Consistent hashing
  • K/n (fractional of total data) affected
• Mapping
  • Split and Combine/Merge

Page 10
Distributed: Replication

• Granularity
  • Machine
  • Record
  • Group

(Pic Translation:
粒度: Granularity, 开销: Cost,
并行度: Degree of parallelism, 可靠性: Reliability)

Page 11
Replication is not omnipotent (fcicq: cant solve every problem)

(Pic Translation:
故障率: Failure Rate)

Page 12
(Pic Translation:
时间: Time, 吞吐: Throughput, 输入: Load, 极限: Designed maximum throughput,
文艺模型: Well-designed / Optimal Model, 普通模型: Typical / poor-designed Model)

Page 13
Service Architecture

• Goal
  • High throughput
  • Stable throughput/serving under extreme load
• Model
  • Basic: threadpool + queue
  • Complex/Advanced: event-driven
• Ensure the stablity
  • Reduce the granularity for resource allocation, active scheduling
  • Flow control
    • Load (data/metrics) feedback, Throttling (fcicq: on high load)
    • (Response) Latency deadline, multi-leveled queue (fcicq: looks like QoS)

Page 14
Computation

• Data Intensive
  • MapReduce
  • Scan-Filter
• Compute Intensive (CPU-Bound)
  • seti@home
• Communication Intensive (Traditional HPC)
  • Machine Learning
  • Matrix related calculation

Page 15
Scan-Filter

• Example: Calculate the Intersection of the 2 sets.
• Input: list1 + list2, |list1|>>|list2|
• Output: {}
• MapReduce
  • Sort + Partition + Reduce
• Scan-Filter (Model)

Page 16
How to make a Storage System?
How to make a High Performance Services?
How to make a Data Warehouse?

What is Architechure?
What does An Architect need?

Page 17-19
Three methods for An Architect

Understand the requirements

• Tradeoff
  • Cant satisfy all the requirements
  • Dont have to treat all the requirements the same. (fcicq: the important ones have high priority)

(Yellow word on the right side:
Say No to unreasonable requirements! but still give end-to-end solutions)

• Find the root requirements
  • Divide(breaking down a problem), Abstract, Dimensional(or scale) Reduction

(fcicq: "Dimensional Reduction" here means solve a simplified and/or scale-reduced problem?)

• • Define primitives and combine rules.
• Understand the requirement changes as time goes by

Choose the methods

• Estimate, Stimulation, Implement

(Yellow word:
Back-of-the-Envelope Calculation
Monte-Carlo Simulation
Discrete Event Simulation
Emulation)

• Divide vs Iteration
• Design Patterns

Maintaining appropriate pace

• Planning the reachable path
• Produce/Deliver periodically / on a regular basis

(Pic Translation:
迭代: Iteration)