What is a Big data architect? A system-level developer of a big data platform is skilled in the core framework of mainstream big data platforms such as Hadoop, Spark and Storm. Have an in-depth knowledge of how to write MapReduce jobs and manage job flows, complete data calculation, and be able to use general algorithms provided by Hadoop, and master components of the entire Hadoop ecosystem, such as: Yarn, HBase, Hive, Pig and other important components can realize the development of platform monitoring and auxiliary o&M system.
What techniques do Big Data architects need to learn?
First, programming language
Java.Python.R .Ruby .Scala
Ii. General big data processing platform
Spark.Flink.Hadoop
Distributed storage
HDFS
Fourth, resource scheduling
Yarn.Mesos
5. Data structure
Stack, queue, linked list, hash table, binary tree, red black tree, B tree
Architecture diagram
What are the recruitment requirements for big data architects?
salary
1. Familiar with big data solutions including Hadoop, Spark, Storm, machine learning, deep learning and other big data solutions;
2. Have a deep understanding of big data processing (stream computing, distributed computing, distributed file system, distributed storage and other related technologies and implementation methods, with practical experience in architecture and design;
3. Familiar with Oracle/Redis and other mainstream data database operation and optimization technology;
4. Proficient in one or more languages of Java, Scala, Python, and R;
5. Familiar with container, virtualization, microservice framework and other related technologies;
6. Sensitive to data, rigorous working ideas, good communication skills, and team work spirit;
7. Familiar with R, Python, SAS, SPSS data mining experience is preferred;
8. High scalability, high performance and distributed system practice and operation experience is preferred;
9. Experience in large-scale data warehouse implementation and big data platform data development, familiar with operators’ business is preferred.
To sum up, no matter what profession you are in, you should love what you do and love what you do. Don’t complain, but put yourself in others’ shoes, love your company, love your boss, and love your money. I am a big data engineer. The so-called artificial intelligence is to collect a large amount of data to find out the rules of the operation of things and get the best route service. In short, we need a large amount of data, that is, big data is the blood of artificial intelligence. It is similar to oil in the industrial era, which means that all learning Java development in the future will develop towards big data. I am a big data programmer, and I set up a big data resource sharing group 593188212 to share big data learning materials and learning methods every day
Former Ali Cloud Big data architect: What skills do I need to master to join Ali Cloud
Big data engineer AH Fu
Ali cloud
What is a Big data architect? A system-level developer of a big data platform is skilled in the core framework of mainstream big data platforms such as Hadoop, Spark and Storm. Have an in-depth knowledge of how to write MapReduce jobs and manage job flows, complete data calculation, and be able to use general algorithms provided by Hadoop, and master components of the entire Hadoop ecosystem, such as: Yarn, HBase, Hive, Pig and other important components can realize the development of platform monitoring and auxiliary o&M system.
What techniques do Big Data architects need to learn?
First, programming language
Java.Python.R .Ruby .Scala
Ii. General big data processing platform
Spark.Flink.Hadoop
Distributed storage
HDFS
Fourth, resource scheduling
Yarn.Mesos
5. Data structure
Stack, queue, linked list, hash table, binary tree, red black tree, B tree
Architecture diagram
What are the recruitment requirements for big data architects?
salary
1. Familiar with big data solutions including Hadoop, Spark, Storm, machine learning, deep learning and other big data solutions;
2. Have a deep understanding of big data processing (stream computing, distributed computing, distributed file system, distributed storage and other related technologies and implementation methods, with practical experience in architecture and design;
3. Familiar with Oracle/Redis and other mainstream data database operation and optimization technology;
4. Proficient in one or more languages of Java, Scala, Python, and R;
5. Familiar with container, virtualization, microservice framework and other related technologies;
6. Sensitive to data, rigorous working ideas, good communication skills, and team work spirit;
7. Familiar with R, Python, SAS, SPSS data mining experience is preferred;
8. High scalability, high performance and distributed system practice and operation experience is preferred;
9. Experience in large-scale data warehouse implementation and big data platform data development, familiar with operators’ business is preferred.
To sum up, no matter what profession you are in, you should love what you do and love what you do. Don’t complain, but put yourself in others’ shoes, love your company, love your boss, and love your money. I am a big data engineer. The so-called artificial intelligence is to collect a large amount of data to find out the rules of the operation of things and get the best route service. In short, we need a large amount of data, that is, big data is the blood of artificial intelligence. It’s like oil in the industrial age, which means that everyone learning Java development is going to move to big data,