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公开课笔记
CMU 15-445/645 Database Systems
Relational Data Model
Advanced SQL
Database Storage
Buffer Pools
Hash Tables
Tree Indexes
Index Concurrency Control
Query Processing
Sorting&Aggregations
Join Algorithms
Query Optimization
Parallel Execution
Embedded Database Logic
Concurrency Control Theory
Two Phase Locking
Timestamp Ordering Concurrency Control
Multi-Version Concurrency Control
Logging Schemes
Database Recovery
Introduction to Distributed Databases
Distributed OLTP Databases
Distributed OLAP Databases
UCB - CS162
OS intro
Introduction to the Process
Processes, Fork, I/O, Files
I/O Continued, Sockets, Networking
Concurrency: Processes & Threads
Cooperating Threads, Synchronization
Semaphores, Condition Variables, Readers/Writers
Scheduling
Resource Contention & Deadlock
Address Translation, Caching
File System (18,19,20)
Distributed Systems, Networking, TCP/IP, RPC (21,22)
Distributed Storage, Key-Value Stores, Security (23)
Security & Cloud Computing (24)
Topic: Ensuring Data Reaches Disk
MIT - 6.006
Sequence and Set Interface
Data Structure for Dynamic Sequence Interface
Computation Complexity
Algorithms and Computation
Structure Of Computation
Graph & Search
Tree & Search
Weighted Shortest Paths
String Matching, Karp-Rabin
Priority Queue Interface & Implementation
Dictionary Problem & Implementation
Sorting
Dynamic Programming
Backtracking
Self-Balancing Tree
MIT - 6.824
2PC & 3PC
Introduction and MapReduce
RPC and Threads
Primary/Backup Replication
Lab: Primary/Backup Key/Value Service
Google File System (GFS)
Raft
Lab: Raft - Leader Election
Lab: Raft - Log Replication
Stanford-CS107
原始数据类型及相互转化
指鹿为马
泛型函数
泛型栈
运行时内存结构
从 C 到汇编
函数的活动记录
C 与 C++ 代码生成
编译的预处理过程
编译的链接过程
函数的活动记录续、并发
从顺序到并发和并行
信号量与多线程 1
信号量与多线程 2
复杂多线程问题
函数式编程 - Scheme 1
函数式编程 - Scheme 2
函数式编程 - Scheme 3
函数式编程 - Scheme 4
函数式编程 - Scheme 5
Python 基础
MIT - 6.001 - SICP
什么是程序
程序抽象
替代模型
时间/空间复杂度
数据抽象
高阶函数
Symbol
数据驱动编程与防御式编程
数据抽象中的效率与可读性
数据修改
环境模型
面向对象-消息传递
面向对象 - Scheme 实现
构建 Scheme 解释器
Eval-Apply Loop
Normal Order (Lazy) Evaluation
通用机
寄存器机器
子程序、栈与递归
在寄存器机器中执行
内存管理
MIT - 6.046
Randomized Algorithms
Skip Lists
System Design
Twitter
Cache Consistency & Coherence
DDIA 笔记
Replication
Transactions
The Trouble with Distributed Systems
Consistency & Consensus
Papers We Love
Consistent Hashing and Random Trees (1997)
Dynamic Hash Tables (1988)
LFU Implementation With O(1) Complexity (2010)
Time, Clocks, and the Ordering of Events in a Distributed System (1978)
Dapper, a Large-Scale Distributed Systems Tracing Infrastructure (2010)
Gorilla: A Fast, Scalable, In-Memory Time Series Database (2015)
Release It 笔记
Anti-patterns & Patterns in Microservice Architecture
Database Design
Log Structured Merge (LSM) Tree & Usages in KV Stores
Prometheus
Powered By
GitBook
函数式编程 - Scheme 3
第二十一课
map
一种常见的操作就是将一个 sequence 转化成另一个 sequence,其中对 sequence 的每个元素都执行同样的操作,如:
>
(
double-all
'(
1
2
3
4
))
(
2
4
6
8
)
>
(
incr-all
'(
1
2
3
4
))
(
2
3
4
5
)
其实这就是我们在其它语言中常见的 map。在 Scheme 中,我们希望这样:
>
(
define
(
double
x
)
(
*
x
2
))
>
(
define
(
incr
x
)
(
+
x
1
))
; map unary functions
>
(
map
double
'(
1
2
3
4
))
(
2
4
6
8
)
>
(
map
incr
'(
1
2
3
4
))
(
2
3
4
5
)
>
(
map
car
'((
1
2
)
(
4
8
2
)
(
11
)))
(
1
4
11
)
>
(
map
cdr
'((
1
2
)
(
4
8
2
)
(
11
)))
((
2
)
(
8
2
)
())
; map binary functions
>
(
map
cons
'(
1
2
8
)
'((
4
)
()
(
2
5
)))
((
1
4
)
(
2
)
(
8
2
5
))
>
(
map
+
'(
1
2
)
'(
3
4
)
'(
6
10
))
(
10
16
)
实现 map
(
define
(
my-unary-map
fn seq
)
(
if
(
null?
seq
)
'()
(
cons
(
fn
(
car
seq
))
(
my-unary-map
fn
(
cdr
seq
)))))
apply & eval
eval 接收一个参数,这个参数是程序员输入的原始表达式字符串,之后 eval 会 tokenize、parse 原始表达式字符串,然后再用 evaluator 来处理解析后的 list structure,最终得到输出:
>>
(
eval
'(
+
1
2
3
))
6
apply 总是接受两个参数,procedure 的 symbol 和 argument list,apply 会用 cons 把 symbol 和 argument list 合成一个 list 作为输入交给 eval 执行:
>
(
apply
+
'(
1
2
3
))
6
>
(
define
(
average
num-list
)
(
/
(
apply
+ num-list
)
(
length
num-list
)))
>
(
average
'(
1
2
3
4
))
5/2
了解了 eval 和 apply 我们可以回顾一下 flatten
(
define
(
flatten
seq
)
(
if
(
not
(
list?
seq
))
(
list
seq
)
(
apply
append
(
map
flatten seq
))))
translate
>
(
define
(
translate
points delta
)
(
map
(
lambda
(
x
)
(
+
x delta
))
points
))
>
(
translate
'(
2
5
8
11
25
)
100
)
(
102
105
108
111
125
)
这里利用 lambda 在 translate procedure 内部定义 anonymous procedure,后者中的自由变量 delta 可以在它的外环境找到 binding。更直接地,我们也可以使用 named procedure:
(
define
(
translate
seq delta
)
(
define
(
shift-by
x
)
(
+
x delta
))
(
map
shift-by seq
))
define named procedure
(
define
(
sum
x y
)
(
+
x y
))
(
define
sum
(
lambda
(
x y
)
(
+
x y
)))
第一种写法实际上是第二种写法的 syntactic sugar。
参考
Stanford-CS107-lecture-21
Stanford-CS107 - Previous
函数式编程 - Scheme 2
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3yr ago
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