Hi guys, I'm back after a long time without writing anything. Today, I want to share about how to create a Spark Streaming pipeline that consumes data from Kafka, everything is built on Docker.

Lately, I've spent a lot of time teaching myself how to build Hadoop clusters, Spark, Hive integration, and more. This article will write about how you can build a Spark cluster for data processing using Docker, including 1 master node and 2 worker nodes, the cluster type is standalone cluster (maybe the upcoming articles I will do about Hadoop cluster and integrated resource manager is Yarn). Let's go to the article.

In the previous post, I talked about the binary search tree. With efficiency in search, insert, delete,... binary search tree can be done in logrithmic time (${\Theta(logn)}$) in the average case. In this article, I will talk about AVL tree, which is a type of binary search tree, ensuring that in all cases, the time complexity of the above operations is the same ${\Theta(logn)}$.

In the process of learning programming, you will encounter many types of data structures such as arrays, linked lists, maps, etc. Each type of data structure has its own advantages and disadvantages. Today, I will talk about an interesting type of data structure called a binary search tree, a very convenient data structure for the search problem.

In these early blogs, I will only write about the most basic algorithms when I'm just starting to learn programming. First, let me relearn the basics (because I'm extremely forgetful). Second, for those who are new to programming, you can refer to it. This article will talk about the basic sorting algorithms I learned in school, and also taught myself.

Today I will talk about an extremely basic algorithm that I and most of you who are starting to learn about algorithmic programming have done. That is the Peak Finding algorithm.