mirror of
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poriting to noat.cards
This commit is contained in:
Vu
@@ -1,6 +1,6 @@
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# 设计一个键-值缓存来存储最近 web 服务查询的结果
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**注意：这个文档中的链接会直接指向[系统设计主题索引](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#系统设计主题的索引)中的有关部分，以避免重复的内容。你可以参考链接的相关内容，来了解其总的要点、方案的权衡取舍以及可选的替代方案。**
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**注意：这个文档中的链接会直接指向[系统设计主题索引](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#系统设计主题的索引) 中的有关部分，以避免重复的内容。你可以参考链接的相关内容，来了解其总的要点、方案的权衡取舍以及可选的替代方案。**
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## 第一步：简述用例与约束条件
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@@ -58,7 +58,7 @@
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> 列出所有重要组件以规划概要设计。
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## 第三步：设计核心组件
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@@ -70,7 +70,7 @@
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由于缓存容量有限，我们将使用 LRU（近期最少使用算法）来控制缓存的过期。
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* **客户端**向运行[反向代理](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#反向代理web-服务器)的 **Web 服务器**发送一个请求
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* **客户端**向运行[反向代理](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#反向代理web-服务器) 的 **Web 服务器**发送一个请求
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* 这个 **Web 服务器**将请求转发给**查询 API** 服务
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* **查询 API** 服务将会做这些事情：
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* 分析查询
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@@ -98,33 +98,33 @@
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实现**查询 API 服务**：
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```python
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class QueryApi(object):
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class QueryApi(object) :
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def __init__(self, memory_cache, reverse_index_service):
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def __init__(self, memory_cache, reverse_index_service) :
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self.memory_cache = memory_cache
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self.reverse_index_service = reverse_index_service
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def parse_query(self, query):
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def parse_query(self, query) :
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"""移除多余内容，将文本分割成词组，修复拼写错误，
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规范化字母大小写，转换布尔运算。
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"""
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...
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def process_query(self, query):
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query = self.parse_query(query)
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results = self.memory_cache.get(query)
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def process_query(self, query) :
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query = self.parse_query(query)
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results = self.memory_cache.get(query)
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if results is None:
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results = self.reverse_index_service.process_search(query)
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self.memory_cache.set(query, results)
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results = self.reverse_index_service.process_search(query)
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self.memory_cache.set(query, results)
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return results
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```
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实现**节点**：
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```python
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class Node(object):
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class Node(object) :
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def __init__(self, query, results):
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def __init__(self, query, results) :
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self.query = query
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self.results = results
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```
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@@ -132,34 +132,34 @@ class Node(object):
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实现**链表**：
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```python
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class LinkedList(object):
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class LinkedList(object) :
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def __init__(self):
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def __init__(self) :
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self.head = None
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self.tail = None
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def move_to_front(self, node):
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def move_to_front(self, node) :
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...
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def append_to_front(self, node):
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def append_to_front(self, node) :
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...
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def remove_from_tail(self):
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def remove_from_tail(self) :
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...
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```
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实现**缓存**：
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```python
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class Cache(object):
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class Cache(object) :
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def __init__(self, MAX_SIZE):
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def __init__(self, MAX_SIZE) :
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self.MAX_SIZE = MAX_SIZE
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self.size = 0
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self.lookup = {} # key: query, value: node
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self.linked_list = LinkedList()
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self.linked_list = LinkedList()
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def get(self, query)
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def get(self, query)
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"""从缓存取得存储的内容
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将入口节点位置更新为 LRU 链表的头部。
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@@ -167,10 +167,10 @@ class Cache(object):
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node = self.lookup[query]
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if node is None:
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return None
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self.linked_list.move_to_front(node)
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self.linked_list.move_to_front(node)
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return node.results
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def set(self, results, query):
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def set(self, results, query) :
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"""将所给查询键的结果存在缓存中。
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当更新缓存记录的时候，将它的位置指向 LRU 链表的头部。
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@@ -181,18 +181,18 @@ class Cache(object):
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if node is not None:
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# 键存在于缓存中，更新它对应的值
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node.results = results
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self.linked_list.move_to_front(node)
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self.linked_list.move_to_front(node)
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else:
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# 键不存在于缓存中
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if self.size == self.MAX_SIZE:
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# 在链表中查找并删除最老的记录
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self.lookup.pop(self.linked_list.tail.query, None)
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self.linked_list.remove_from_tail()
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self.lookup.pop(self.linked_list.tail.query, None)
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self.linked_list.remove_from_tail()
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else:
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self.size += 1
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# 添加新的键值对
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new_node = Node(query, results)
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self.linked_list.append_to_front(new_node)
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new_node = Node(query, results)
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self.linked_list.append_to_front(new_node)
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self.lookup[query] = new_node
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```
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@@ -206,13 +206,13 @@ class Cache(object):
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解决这些问题的最直接的方法，就是为缓存记录设置一个它在被更新前能留在缓存中的最长时间，这个时间简称为存活时间（TTL）。
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参考 [「何时更新缓存」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#何时更新缓存)来了解其权衡取舍及替代方案。以上方法在[缓存模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存模式)一章中详细地进行了描述。
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参考 [「何时更新缓存」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#何时更新缓存) 来了解其权衡取舍及替代方案。以上方法在[缓存模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存模式) 一章中详细地进行了描述。
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## 第四步：架构扩展
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> 根据限制条件，找到并解决瓶颈。
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**重要提示：不要从最初设计直接跳到最终设计中！**
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@@ -222,16 +222,16 @@ class Cache(object):
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我们将会介绍一些组件来完成设计，并解决架构扩张问题。内置的负载均衡器将不做讨论以节省篇幅。
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**为了避免重复讨论**，请参考[系统设计主题索引](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#系统设计主题的索引)相关部分来了解其要点、方案的权衡取舍以及可选的替代方案。
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**为了避免重复讨论**，请参考[系统设计主题索引](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#系统设计主题的索引) 相关部分来了解其要点、方案的权衡取舍以及可选的替代方案。
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* [DNS](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#域名系统)
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* [负载均衡器](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#负载均衡器)
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* [水平拓展](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#水平扩展)
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* [反向代理（web 服务器）](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#反向代理web-服务器)
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* [API 服务（应用层）](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#应用层)
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* [缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存)
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* [一致性模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#一致性模式)
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* [可用性模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#可用性模式)
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* [DNS](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#域名系统)
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* [负载均衡器](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#负载均衡器)
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* [水平拓展](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#水平扩展)
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* [反向代理（web 服务器）](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#反向代理web-服务器)
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* [API 服务（应用层）](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#应用层)
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* [缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存)
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* [一致性模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#一致性模式)
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* [可用性模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#可用性模式)
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### 将内存缓存扩大到多台机器
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@@ -239,7 +239,7 @@ class Cache(object):
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* **缓存集群中的每一台机器都有自己的缓存** - 简单，但是它会降低缓存命中率。
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* **缓存集群中的每一台机器都有缓存的拷贝** - 简单，但是它的内存使用效率太低了。
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* **对缓存进行[分片](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#分片)，分别部署在缓存集群中的所有机器中** - 更加复杂，但是它是最佳的选择。我们可以使用哈希，用查询语句 `machine = hash(query)` 来确定哪台机器有需要缓存。当然我们也可以使用[一致性哈希](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#正在完善中)。
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* **对缓存进行[分片](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#分片) ，分别部署在缓存集群中的所有机器中** - 更加复杂，但是它是最佳的选择。我们可以使用哈希，用查询语句 `machine = hash(query) ` 来确定哪台机器有需要缓存。当然我们也可以使用[一致性哈希](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#正在完善中) 。
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## 其它要点
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@@ -247,58 +247,58 @@ class Cache(object):
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### SQL 缩放模式
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* [读取复制](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#主从复制)
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* [联合](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#联合)
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* [分片](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#分片)
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* [非规范化](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#非规范化)
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* [SQL 调优](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#sql-调优)
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* [读取复制](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#主从复制)
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* [联合](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#联合)
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* [分片](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#分片)
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* [非规范化](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#非规范化)
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* [SQL 调优](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#sql-调优)
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#### NoSQL
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* [键-值存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#键-值存储)
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* [文档类型存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#文档类型存储)
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* [列型存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#列型存储)
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* [图数据库](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#图数据库)
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* [SQL vs NoSQL](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#sql-还是-nosql)
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* [键-值存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#键-值存储)
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* [文档类型存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#文档类型存储)
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* [列型存储](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#列型存储)
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* [图数据库](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#图数据库)
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* [SQL vs NoSQL](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#sql-还是-nosql)
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### 缓存
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* 在哪缓存
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* [客户端缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#客户端缓存)
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* [CDN 缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#cdn-缓存)
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* [Web 服务器缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#web-服务器缓存)
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* [数据库缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#数据库缓存)
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* [应用缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#应用缓存)
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* [客户端缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#客户端缓存)
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* [CDN 缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#cdn-缓存)
|
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* [Web 服务器缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#web-服务器缓存)
|
||||
* [数据库缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#数据库缓存)
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* [应用缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#应用缓存)
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* 什么需要缓存
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* [数据库查询级别的缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#数据库查询级别的缓存)
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* [对象级别的缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#对象级别的缓存)
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* [数据库查询级别的缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#数据库查询级别的缓存)
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* [对象级别的缓存](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#对象级别的缓存)
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* 何时更新缓存
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* [缓存模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存模式)
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* [直写模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#直写模式)
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* [回写模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#回写模式)
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* [刷新](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#刷新)
|
||||
* [缓存模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#缓存模式)
|
||||
* [直写模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#直写模式)
|
||||
* [回写模式](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#回写模式)
|
||||
* [刷新](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#刷新)
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### 异步与微服务
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||||
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||||
* [消息队列](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#消息队列)
|
||||
* [任务队列](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#任务队列)
|
||||
* [背压](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#背压)
|
||||
* [微服务](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#微服务)
|
||||
* [消息队列](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#消息队列)
|
||||
* [任务队列](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#任务队列)
|
||||
* [背压](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#背压)
|
||||
* [微服务](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#微服务)
|
||||
|
||||
### 通信
|
||||
|
||||
* 可权衡选择的方案：
|
||||
* 与客户端的外部通信 - [使用 REST 作为 HTTP API](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#表述性状态转移rest)
|
||||
* 服务器内部通信 - [RPC](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#远程过程调用协议rpc)
|
||||
* [服务发现](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#服务发现)
|
||||
* 与客户端的外部通信 - [使用 REST 作为 HTTP API](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#表述性状态转移rest)
|
||||
* 服务器内部通信 - [RPC](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#远程过程调用协议rpc)
|
||||
* [服务发现](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#服务发现)
|
||||
|
||||
### 安全性
|
||||
|
||||
请参阅[「安全」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#安全)一章。
|
||||
请参阅[「安全」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#安全) 一章。
|
||||
|
||||
### 延迟数值
|
||||
|
||||
请参阅[「每个程序员都应该知道的延迟数」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#每个程序员都应该知道的延迟数)。
|
||||
请参阅[「每个程序员都应该知道的延迟数」](https://github.com/donnemartin/system-design-primer/blob/master/README-zh-Hans.md#每个程序员都应该知道的延迟数) 。
|
||||
|
||||
### 持续探讨
|
||||
|
||||
|
||||
@@ -58,7 +58,7 @@ Handy conversion guide:
|
||||
|
||||
> Outline a high level design with all important components.
|
||||
|
||||
|
||||
|
||||
|
||||
## Step 3: Design core components
|
||||
|
||||
@@ -70,7 +70,7 @@ Popular queries can be served from a **Memory Cache** such as Redis or Memcached
|
||||
|
||||
Since the cache has limited capacity, we'll use a least recently used (LRU) approach to expire older entries.
|
||||
|
||||
* The **Client** sends a request to the **Web Server**, running as a [reverse proxy](https://github.com/donnemartin/system-design-primer#reverse-proxy-web-server)
|
||||
* The **Client** sends a request to the **Web Server**, running as a [reverse proxy](https://github.com/donnemartin/system-design-primer#reverse-proxy-web-server)
|
||||
* The **Web Server** forwards the request to the **Query API** server
|
||||
* The **Query API** server does the following:
|
||||
* Parses the query
|
||||
@@ -98,33 +98,33 @@ The cache can use a doubly-linked list: new items will be added to the head whil
|
||||
**Query API Server** implementation:
|
||||
|
||||
```python
|
||||
class QueryApi(object):
|
||||
class QueryApi(object) :
|
||||
|
||||
def __init__(self, memory_cache, reverse_index_service):
|
||||
def __init__(self, memory_cache, reverse_index_service) :
|
||||
self.memory_cache = memory_cache
|
||||
self.reverse_index_service = reverse_index_service
|
||||
|
||||
def parse_query(self, query):
|
||||
def parse_query(self, query) :
|
||||
"""Remove markup, break text into terms, deal with typos,
|
||||
normalize capitalization, convert to use boolean operations.
|
||||
"""
|
||||
...
|
||||
|
||||
def process_query(self, query):
|
||||
query = self.parse_query(query)
|
||||
results = self.memory_cache.get(query)
|
||||
def process_query(self, query) :
|
||||
query = self.parse_query(query)
|
||||
results = self.memory_cache.get(query)
|
||||
if results is None:
|
||||
results = self.reverse_index_service.process_search(query)
|
||||
self.memory_cache.set(query, results)
|
||||
results = self.reverse_index_service.process_search(query)
|
||||
self.memory_cache.set(query, results)
|
||||
return results
|
||||
```
|
||||
|
||||
**Node** implementation:
|
||||
|
||||
```python
|
||||
class Node(object):
|
||||
class Node(object) :
|
||||
|
||||
def __init__(self, query, results):
|
||||
def __init__(self, query, results) :
|
||||
self.query = query
|
||||
self.results = results
|
||||
```
|
||||
@@ -132,34 +132,34 @@ class Node(object):
|
||||
**LinkedList** implementation:
|
||||
|
||||
```python
|
||||
class LinkedList(object):
|
||||
class LinkedList(object) :
|
||||
|
||||
def __init__(self):
|
||||
def __init__(self) :
|
||||
self.head = None
|
||||
self.tail = None
|
||||
|
||||
def move_to_front(self, node):
|
||||
def move_to_front(self, node) :
|
||||
...
|
||||
|
||||
def append_to_front(self, node):
|
||||
def append_to_front(self, node) :
|
||||
...
|
||||
|
||||
def remove_from_tail(self):
|
||||
def remove_from_tail(self) :
|
||||
...
|
||||
```
|
||||
|
||||
**Cache** implementation:
|
||||
|
||||
```python
|
||||
class Cache(object):
|
||||
class Cache(object) :
|
||||
|
||||
def __init__(self, MAX_SIZE):
|
||||
def __init__(self, MAX_SIZE) :
|
||||
self.MAX_SIZE = MAX_SIZE
|
||||
self.size = 0
|
||||
self.lookup = {} # key: query, value: node
|
||||
self.linked_list = LinkedList()
|
||||
self.linked_list = LinkedList()
|
||||
|
||||
def get(self, query)
|
||||
def get(self, query)
|
||||
"""Get the stored query result from the cache.
|
||||
|
||||
Accessing a node updates its position to the front of the LRU list.
|
||||
@@ -167,10 +167,10 @@ class Cache(object):
|
||||
node = self.lookup[query]
|
||||
if node is None:
|
||||
return None
|
||||
self.linked_list.move_to_front(node)
|
||||
self.linked_list.move_to_front(node)
|
||||
return node.results
|
||||
|
||||
def set(self, results, query):
|
||||
def set(self, results, query) :
|
||||
"""Set the result for the given query key in the cache.
|
||||
|
||||
When updating an entry, updates its position to the front of the LRU list.
|
||||
@@ -181,18 +181,18 @@ class Cache(object):
|
||||
if node is not None:
|
||||
# Key exists in cache, update the value
|
||||
node.results = results
|
||||
self.linked_list.move_to_front(node)
|
||||
self.linked_list.move_to_front(node)
|
||||
else:
|
||||
# Key does not exist in cache
|
||||
if self.size == self.MAX_SIZE:
|
||||
# Remove the oldest entry from the linked list and lookup
|
||||
self.lookup.pop(self.linked_list.tail.query, None)
|
||||
self.linked_list.remove_from_tail()
|
||||
self.lookup.pop(self.linked_list.tail.query, None)
|
||||
self.linked_list.remove_from_tail()
|
||||
else:
|
||||
self.size += 1
|
||||
# Add the new key and value
|
||||
new_node = Node(query, results)
|
||||
self.linked_list.append_to_front(new_node)
|
||||
new_node = Node(query, results)
|
||||
self.linked_list.append_to_front(new_node)
|
||||
self.lookup[query] = new_node
|
||||
```
|
||||
|
||||
@@ -204,15 +204,15 @@ The cache should be updated when:
|
||||
* The page is removed or a new page is added
|
||||
* The page rank changes
|
||||
|
||||
The most straightforward way to handle these cases is to simply set a max time that a cached entry can stay in the cache before it is updated, usually referred to as time to live (TTL).
|
||||
The most straightforward way to handle these cases is to simply set a max time that a cached entry can stay in the cache before it is updated, usually referred to as time to live (TTL) .
|
||||
|
||||
Refer to [When to update the cache](https://github.com/donnemartin/system-design-primer#when-to-update-the-cache) for tradeoffs and alternatives. The approach above describes [cache-aside](https://github.com/donnemartin/system-design-primer#cache-aside).
|
||||
Refer to [When to update the cache](https://github.com/donnemartin/system-design-primer#when-to-update-the-cache) for tradeoffs and alternatives. The approach above describes [cache-aside](https://github.com/donnemartin/system-design-primer#cache-aside) .
|
||||
|
||||
## Step 4: Scale the design
|
||||
|
||||
> Identify and address bottlenecks, given the constraints.
|
||||
|
||||
|
||||
|
||||
|
||||
**Important: Do not simply jump right into the final design from the initial design!**
|
||||
|
||||
@@ -224,14 +224,14 @@ We'll introduce some components to complete the design and to address scalabilit
|
||||
|
||||
*To avoid repeating discussions*, refer to the following [system design topics](https://github.com/donnemartin/system-design-primer#index-of-system-design-topics) for main talking points, tradeoffs, and alternatives:
|
||||
|
||||
* [DNS](https://github.com/donnemartin/system-design-primer#domain-name-system)
|
||||
* [Load balancer](https://github.com/donnemartin/system-design-primer#load-balancer)
|
||||
* [Horizontal scaling](https://github.com/donnemartin/system-design-primer#horizontal-scaling)
|
||||
* [Web server (reverse proxy)](https://github.com/donnemartin/system-design-primer#reverse-proxy-web-server)
|
||||
* [API server (application layer)](https://github.com/donnemartin/system-design-primer#application-layer)
|
||||
* [Cache](https://github.com/donnemartin/system-design-primer#cache)
|
||||
* [Consistency patterns](https://github.com/donnemartin/system-design-primer#consistency-patterns)
|
||||
* [Availability patterns](https://github.com/donnemartin/system-design-primer#availability-patterns)
|
||||
* [DNS](https://github.com/donnemartin/system-design-primer#domain-name-system)
|
||||
* [Load balancer](https://github.com/donnemartin/system-design-primer#load-balancer)
|
||||
* [Horizontal scaling](https://github.com/donnemartin/system-design-primer#horizontal-scaling)
|
||||
* [Web server (reverse proxy) ](https://github.com/donnemartin/system-design-primer#reverse-proxy-web-server)
|
||||
* [API server (application layer) ](https://github.com/donnemartin/system-design-primer#application-layer)
|
||||
* [Cache](https://github.com/donnemartin/system-design-primer#cache)
|
||||
* [Consistency patterns](https://github.com/donnemartin/system-design-primer#consistency-patterns)
|
||||
* [Availability patterns](https://github.com/donnemartin/system-design-primer#availability-patterns)
|
||||
|
||||
### Expanding the Memory Cache to many machines
|
||||
|
||||
@@ -239,7 +239,7 @@ To handle the heavy request load and the large amount of memory needed, we'll sc
|
||||
|
||||
* **Each machine in the cache cluster has its own cache** - Simple, although it will likely result in a low cache hit rate.
|
||||
* **Each machine in the cache cluster has a copy of the cache** - Simple, although it is an inefficient use of memory.
|
||||
* **The cache is [sharded](https://github.com/donnemartin/system-design-primer#sharding) across all machines in the cache cluster** - More complex, although it is likely the best option. We could use hashing to determine which machine could have the cached results of a query using `machine = hash(query)`. We'll likely want to use [consistent hashing](https://github.com/donnemartin/system-design-primer#under-development).
|
||||
* **The cache is [sharded](https://github.com/donnemartin/system-design-primer#sharding) across all machines in the cache cluster** - More complex, although it is likely the best option. We could use hashing to determine which machine could have the cached results of a query using `machine = hash(query) `. We'll likely want to use [consistent hashing](https://github.com/donnemartin/system-design-primer#under-development) .
|
||||
|
||||
## Additional talking points
|
||||
|
||||
@@ -247,58 +247,58 @@ To handle the heavy request load and the large amount of memory needed, we'll sc
|
||||
|
||||
### SQL scaling patterns
|
||||
|
||||
* [Read replicas](https://github.com/donnemartin/system-design-primer#master-slave-replication)
|
||||
* [Federation](https://github.com/donnemartin/system-design-primer#federation)
|
||||
* [Sharding](https://github.com/donnemartin/system-design-primer#sharding)
|
||||
* [Denormalization](https://github.com/donnemartin/system-design-primer#denormalization)
|
||||
* [SQL Tuning](https://github.com/donnemartin/system-design-primer#sql-tuning)
|
||||
* [Read replicas](https://github.com/donnemartin/system-design-primer#master-slave-replication)
|
||||
* [Federation](https://github.com/donnemartin/system-design-primer#federation)
|
||||
* [Sharding](https://github.com/donnemartin/system-design-primer#sharding)
|
||||
* [Denormalization](https://github.com/donnemartin/system-design-primer#denormalization)
|
||||
* [SQL Tuning](https://github.com/donnemartin/system-design-primer#sql-tuning)
|
||||
|
||||
#### NoSQL
|
||||
|
||||
* [Key-value store](https://github.com/donnemartin/system-design-primer#key-value-store)
|
||||
* [Document store](https://github.com/donnemartin/system-design-primer#document-store)
|
||||
* [Wide column store](https://github.com/donnemartin/system-design-primer#wide-column-store)
|
||||
* [Graph database](https://github.com/donnemartin/system-design-primer#graph-database)
|
||||
* [SQL vs NoSQL](https://github.com/donnemartin/system-design-primer#sql-or-nosql)
|
||||
* [Key-value store](https://github.com/donnemartin/system-design-primer#key-value-store)
|
||||
* [Document store](https://github.com/donnemartin/system-design-primer#document-store)
|
||||
* [Wide column store](https://github.com/donnemartin/system-design-primer#wide-column-store)
|
||||
* [Graph database](https://github.com/donnemartin/system-design-primer#graph-database)
|
||||
* [SQL vs NoSQL](https://github.com/donnemartin/system-design-primer#sql-or-nosql)
|
||||
|
||||
### Caching
|
||||
|
||||
* Where to cache
|
||||
* [Client caching](https://github.com/donnemartin/system-design-primer#client-caching)
|
||||
* [CDN caching](https://github.com/donnemartin/system-design-primer#cdn-caching)
|
||||
* [Web server caching](https://github.com/donnemartin/system-design-primer#web-server-caching)
|
||||
* [Database caching](https://github.com/donnemartin/system-design-primer#database-caching)
|
||||
* [Application caching](https://github.com/donnemartin/system-design-primer#application-caching)
|
||||
* [Client caching](https://github.com/donnemartin/system-design-primer#client-caching)
|
||||
* [CDN caching](https://github.com/donnemartin/system-design-primer#cdn-caching)
|
||||
* [Web server caching](https://github.com/donnemartin/system-design-primer#web-server-caching)
|
||||
* [Database caching](https://github.com/donnemartin/system-design-primer#database-caching)
|
||||
* [Application caching](https://github.com/donnemartin/system-design-primer#application-caching)
|
||||
* What to cache
|
||||
* [Caching at the database query level](https://github.com/donnemartin/system-design-primer#caching-at-the-database-query-level)
|
||||
* [Caching at the object level](https://github.com/donnemartin/system-design-primer#caching-at-the-object-level)
|
||||
* [Caching at the database query level](https://github.com/donnemartin/system-design-primer#caching-at-the-database-query-level)
|
||||
* [Caching at the object level](https://github.com/donnemartin/system-design-primer#caching-at-the-object-level)
|
||||
* When to update the cache
|
||||
* [Cache-aside](https://github.com/donnemartin/system-design-primer#cache-aside)
|
||||
* [Write-through](https://github.com/donnemartin/system-design-primer#write-through)
|
||||
* [Write-behind (write-back)](https://github.com/donnemartin/system-design-primer#write-behind-write-back)
|
||||
* [Refresh ahead](https://github.com/donnemartin/system-design-primer#refresh-ahead)
|
||||
* [Cache-aside](https://github.com/donnemartin/system-design-primer#cache-aside)
|
||||
* [Write-through](https://github.com/donnemartin/system-design-primer#write-through)
|
||||
* [Write-behind (write-back) ](https://github.com/donnemartin/system-design-primer#write-behind-write-back)
|
||||
* [Refresh ahead](https://github.com/donnemartin/system-design-primer#refresh-ahead)
|
||||
|
||||
### Asynchronism and microservices
|
||||
|
||||
* [Message queues](https://github.com/donnemartin/system-design-primer#message-queues)
|
||||
* [Task queues](https://github.com/donnemartin/system-design-primer#task-queues)
|
||||
* [Back pressure](https://github.com/donnemartin/system-design-primer#back-pressure)
|
||||
* [Microservices](https://github.com/donnemartin/system-design-primer#microservices)
|
||||
* [Message queues](https://github.com/donnemartin/system-design-primer#message-queues)
|
||||
* [Task queues](https://github.com/donnemartin/system-design-primer#task-queues)
|
||||
* [Back pressure](https://github.com/donnemartin/system-design-primer#back-pressure)
|
||||
* [Microservices](https://github.com/donnemartin/system-design-primer#microservices)
|
||||
|
||||
### Communications
|
||||
|
||||
* Discuss tradeoffs:
|
||||
* External communication with clients - [HTTP APIs following REST](https://github.com/donnemartin/system-design-primer#representational-state-transfer-rest)
|
||||
* Internal communications - [RPC](https://github.com/donnemartin/system-design-primer#remote-procedure-call-rpc)
|
||||
* [Service discovery](https://github.com/donnemartin/system-design-primer#service-discovery)
|
||||
* External communication with clients - [HTTP APIs following REST](https://github.com/donnemartin/system-design-primer#representational-state-transfer-rest)
|
||||
* Internal communications - [RPC](https://github.com/donnemartin/system-design-primer#remote-procedure-call-rpc)
|
||||
* [Service discovery](https://github.com/donnemartin/system-design-primer#service-discovery)
|
||||
|
||||
### Security
|
||||
|
||||
Refer to the [security section](https://github.com/donnemartin/system-design-primer#security).
|
||||
Refer to the [security section](https://github.com/donnemartin/system-design-primer#security) .
|
||||
|
||||
### Latency numbers
|
||||
|
||||
See [Latency numbers every programmer should know](https://github.com/donnemartin/system-design-primer#latency-numbers-every-programmer-should-know).
|
||||
See [Latency numbers every programmer should know](https://github.com/donnemartin/system-design-primer#latency-numbers-every-programmer-should-know) .
|
||||
|
||||
### Ongoing
|
||||
|
||||
|
||||
@@ -1,59 +1,59 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
|
||||
class QueryApi(object):
|
||||
class QueryApi(object) :
|
||||
|
||||
def __init__(self, memory_cache, reverse_index_cluster):
|
||||
def __init__(self, memory_cache, reverse_index_cluster) :
|
||||
self.memory_cache = memory_cache
|
||||
self.reverse_index_cluster = reverse_index_cluster
|
||||
|
||||
def parse_query(self, query):
|
||||
def parse_query(self, query) :
|
||||
"""Remove markup, break text into terms, deal with typos,
|
||||
normalize capitalization, convert to use boolean operations.
|
||||
"""
|
||||
...
|
||||
|
||||
def process_query(self, query):
|
||||
query = self.parse_query(query)
|
||||
results = self.memory_cache.get(query)
|
||||
def process_query(self, query) :
|
||||
query = self.parse_query(query)
|
||||
results = self.memory_cache.get(query)
|
||||
if results is None:
|
||||
results = self.reverse_index_cluster.process_search(query)
|
||||
self.memory_cache.set(query, results)
|
||||
results = self.reverse_index_cluster.process_search(query)
|
||||
self.memory_cache.set(query, results)
|
||||
return results
|
||||
|
||||
|
||||
class Node(object):
|
||||
class Node(object) :
|
||||
|
||||
def __init__(self, query, results):
|
||||
def __init__(self, query, results) :
|
||||
self.query = query
|
||||
self.results = results
|
||||
|
||||
|
||||
class LinkedList(object):
|
||||
class LinkedList(object) :
|
||||
|
||||
def __init__(self):
|
||||
def __init__(self) :
|
||||
self.head = None
|
||||
self.tail = None
|
||||
|
||||
def move_to_front(self, node):
|
||||
def move_to_front(self, node) :
|
||||
...
|
||||
|
||||
def append_to_front(self, node):
|
||||
def append_to_front(self, node) :
|
||||
...
|
||||
|
||||
def remove_from_tail(self):
|
||||
def remove_from_tail(self) :
|
||||
...
|
||||
|
||||
|
||||
class Cache(object):
|
||||
class Cache(object) :
|
||||
|
||||
def __init__(self, MAX_SIZE):
|
||||
def __init__(self, MAX_SIZE) :
|
||||
self.MAX_SIZE = MAX_SIZE
|
||||
self.size = 0
|
||||
self.lookup = {}
|
||||
self.linked_list = LinkedList()
|
||||
self.linked_list = LinkedList()
|
||||
|
||||
def get(self, query):
|
||||
def get(self, query) :
|
||||
"""Get the stored query result from the cache.
|
||||
|
||||
Accessing a node updates its position to the front of the LRU list.
|
||||
@@ -61,10 +61,10 @@ class Cache(object):
|
||||
node = self.lookup[query]
|
||||
if node is None:
|
||||
return None
|
||||
self.linked_list.move_to_front(node)
|
||||
self.linked_list.move_to_front(node)
|
||||
return node.results
|
||||
|
||||
def set(self, results, query):
|
||||
def set(self, results, query) :
|
||||
"""Set the result for the given query key in the cache.
|
||||
|
||||
When updating an entry, updates its position to the front of the LRU list.
|
||||
@@ -75,16 +75,16 @@ class Cache(object):
|
||||
if node is not None:
|
||||
# Key exists in cache, update the value
|
||||
node.results = results
|
||||
self.linked_list.move_to_front(node)
|
||||
self.linked_list.move_to_front(node)
|
||||
else:
|
||||
# Key does not exist in cache
|
||||
if self.size == self.MAX_SIZE:
|
||||
# Remove the oldest entry from the linked list and lookup
|
||||
self.lookup.pop(self.linked_list.tail.query, None)
|
||||
self.linked_list.remove_from_tail()
|
||||
self.lookup.pop(self.linked_list.tail.query, None)
|
||||
self.linked_list.remove_from_tail()
|
||||
else:
|
||||
self.size += 1
|
||||
# Add the new key and value
|
||||
new_node = Node(query, results)
|
||||
self.linked_list.append_to_front(new_node)
|
||||
new_node = Node(query, results)
|
||||
self.linked_list.append_to_front(new_node)
|
||||
self.lookup[query] = new_node
|
||||
|
||||
Reference in New Issue
Block a user