# Chapter 11:  Next?

* **Tree**
  * Binary Search Tree
  * B-trees
  * Red-black trees
  * Heaps
  * Splay trees
* **Inverted indexes**
  * search engine works
* **The Fourier transform**
  * given a song, the transform can separate it into individual frequencies.
* **Parallel algorithms**
  * *Overhead of managing the parallelism*
  * *Load balancing*
* **MapReduce**
  * the *distributed algorithm*
  * Suppose you have a table with billions or trillions of rows, and you want to run a complicated SQL query on it. You can’t run it on MySQL, because it struggles after a few billion rows. Use MapReduce through Hadoop!
  * MapReduce in particular is built up from two simple ideas: the **map function** and the **reduce function**
* **Bloom filters and HyperLogLog**
* **The SHA algorithms**
  * **Comparing files**
  * **Checking passwords**
* **Locality-sensitive hashing**
* **Diffie-Hellman key exchange**
  * RSA
* **Linear programming**