Author: Zen and the Art of Computer Programming
1 Introduction
ClickHouse is an open-source, high-performance database system that supports distributed computing and is used to quickly process very large-scale data sets. The database has a disk-based storage engine and a memory-based computing engine, which can quickly respond to complex queries and utilize multi-core CPUs for parallel computing. It also has the following characteristics:
- Flexible data modeling: raw data can be flexibly converted into table structures in different formats.
- High-performance query processing: Support the query optimizer to automatically generate query plans and automatically optimize query execution efficiency.
- High scalability: Through distributed query processing, real-time analysis of massive data can be easily realized.
- High Availability: Ensure data security and availability through redundant replication.
For enterprise-level big data analysis, ClickHouse is completely sufficient. This article will discuss how to perform high-throughput, low-latency workloads such as data analysis, machine learning, and graph exploration in ClickHouse, as well as a real-time monitoring system for data centers.
2. Explanation of basic concepts and terms
2.1 What is ClickHouse?
ClickHouse is an open source distributed database management system developed by Russian Malevich Alexander Leonil and Russian Otto Mikhailov. It is written in C++ and its purpose is to provide a fast and efficient Analytical data warehouse.
Key features of ClickHouse include:
- Flexible framework: expression-based query language, supports SQL syntax, can dynamically load various plug-ins, and can customize data access strategies.
- Support high performance: Support disk-based storage engine and memory-based calculation index SISTENCY, which can efficiently run complex queries and real-time analysis tasks.
- Strong adaptability: able to support input data in multiple formats, such as CSV, Parq