Facebook Distributed System Optimization via Asynchronization -- Big Data Queries

Asynchronization Query

• Asynchronization Query
• Each query is asynchronous, all functions return “Future Object"
• Every DB query are divided into two parts
• Set request
• Receive response
• Future Object tree

• Each future object has two states
• Waiting for execution
• Finished execution
• Once the tree structure is constructed, the execution will start from the bottom to the root. 
• When the root finishes execution, it means the page loading is completed.
• Lazy manner
• The execution process is lazy, since it first construct the trees and then execute. This is similar with Spark map-reduce, the functions forms a DAG structure, only when a node is being needed will its predecessor be executed.

Memcache

• In terms of the problem of which query should be executed first, it should not be depended in the coding process.
• But, there should be an extra phase to determine such kind of schedule. 
• Importance of which query to be executed first
• "比如我们现在有两个查询需求。一个是查询你在淘宝上买过东西的朋友，另一个是查询你在淘宝上买过保时捷的朋友。常理来说，我们会先想到查询你在淘宝上的朋友，再进行另一个条件的查询，比如这样：”

  IdList friends = waitFor(getFriends(myId));
  yield return getTaoBaoBuyers(friends);
  

  但是对于保时捷这个查询而言，这是不对的，因为淘宝上买保时捷的人是很少的，可能就一两个，而淘宝上的好友数可能有上百。因此保时捷的查询应该是这个次序比较优化：

  IdList buyers = waitFor(getPorscheBuyer());
  yield return getFriends(buyers);

Reference
[1] http://www.infoq.com/cn/news/2015/04/async-distributed-haiping