introduce
ClickHouse is a fast, highly available, distributed columnar database management system (DBMS) designed for Online Analytical Processing (OLAP) workloads. It was developed by the Yandex team, initially for its own internal data analysis tasks, and later open-sourced in 2016.
ClickHouse uses a columnar storage engine, which stores data on disk in columns instead of rows. This storage method enables ClickHouse to perform aggregation queries quickly, especially for large amounts of data and complex query statements, and its query speed is very fast. At the same time, ClickHouse also supports vectorized query and data compression technology, which further improves query performance and storage efficiency.
ClickHouse's distributed architecture is very flexible, and the cluster size can be expanded as needed. At the same time, it also provides some high-availability functions, such as data backup and data redundancy, to ensure data security and availability.
In addition to OLAP workloads, ClickHouse can also be used in scenarios such as time series data, log analysis, and data warehouses. It supports a variety of data sources and data formats, including CSV, JSON, Apache Parquet, and more.
In short, ClickHouse is a high-performance, highly available, and flexible columnar database management system, especially suitable for large-scale data analysis and processing scenarios.
The performance of ClickHouse is very good, mainly in the following aspects:
高速查询
ClickHouse uses a columnar storage engine, which can compress and encode columnar data, thereby reducing disk IO and memory usage. At the same time, ClickHouse adopts vectorized query technology, which can operate on multiple data at the same time, further improving query efficiency. These optimization technologies enable ClickHouse to have extremely high query speed when processing large-scale data.
高并发
ClickHouse adopts a distributed architecture, which can distribute data and query tasks to multiple nodes for processing. This distributed processing method makes ClickHouse have high concurrency and can process multiple query tasks at the same time. At the same time, ClickHouse also supports horizontal expansion and load balancing, and can freely expand the cluster size and load capacity according to demand.
高可用性
ClickHouse supports data backup and redundancy mechanisms, and can automatically switch to a standby node when a data node fails to ensure data availability. At the same time, ClickHouse also supports high-availability solutions such as remote backup and cross-data center replication, which can ensure data security and availability when data center-level failures occur.
灵活的数据模型
ClickHouse supports a variety of data models, including relational models, time series models, log analysis models, etc., and can adapt to different data scenarios. At the same time, ClickHouse also supports a variety of data sources and data formats, including CSV, JSON, Apache Parquet, etc., allowing users to easily import and export data.
In short, ClickHouse has the advantages of high-speed query, high concurrency, high availability and flexible data model, which is very suitable for large-scale data processing and analysis scenarios.
The performance of ClickHouse has been verified in the actual production environment:
TPC-H测试
In the TPC-H test, ClickHouse showed excellent performance. Taking the test results of a single node as an example, the query performance of ClickHouse at a scale of 100GB has surpassed that of big data processing engines such as Apache Spark and Google BigQuery. At a scale of 300GB, the query performance of ClickHouse is still very good.
Yandex Metrica的使用案例
ClickHouse was originally developed by Yandex and is one of the core technologies of Yandex Metrica. Yandex Metrica is a service for website analysis that needs to process trillions of log data every day. By adopting ClickHouse, Yandex Metrica is able to process this data with very low latency and high availability, achieving high concurrent processing of hundreds of thousands of queries per second.
CloudFlare的使用案例
CloudFlare is a cloud computing service provider that provides security and performance optimization services for more than two million websites around the world. In order to improve the performance and stability of the service, CloudFlare uses ClickHouse to store and analyze a large amount of network traffic data. By adopting ClickHouse, CloudFlare can analyze data at a very high query speed, achieving high concurrent processing of hundreds of thousands of queries per second.
In short, ClickHouse has been verified in multiple large-scale production environments and has achieved excellent performance.
The steps to install ClickHouse are as follows:
Download and install dependencies
Before installing ClickHouse, you need to ensure that the following dependencies have been installed in the system:
C++编译器
zlib库
lz4库
OpenSSL库
These dependencies can be installed with the following commands:
sudo apt-get update
sudo apt-get install -y g++ zlib1g-dev liblz4-dev libssl-dev
The steps to install ClickHouse are as follows:
下载并安装依赖
Before installing ClickHouse, you need to ensure that the following dependencies have been installed in the system:
C++编译器
zlib库
lz4库
OpenSSL库
These dependencies can be installed with the following commands:
sudo apt-get update
sudo apt-get install -y g++ zlib1g-dev liblz4-dev libssl-dev
1. Download and install ClickHouse
You can download the ClickHouse installation package from the ClickHouse official website at https://clickhouse.tech/docs/en/getting-started/install/#official-packages.
Select the appropriate installation package according to the type and version of the operating system, download and decompress it to the specified directory. Taking Ubuntu 20.04 as an example, the command to download and decompress is as follows:
wget https://repo.clickhouse.tech/tgz/clickhouse-server-21.3.7.33-all-deb.tgz
tar -xzvf clickhouse-server-21.3.7.33-all-deb.tgz
After decompression, you will get a directory named clickhouse-server-21.3.7.33, which contains the ClickHouse server program and client program.
2. Start the ClickHouse service
The ClickHouse service can be started with the following command:
sudo /etc/init.d/clickhouse-server start
At this point, the ClickHouse service has been started, and the ClickHouse database can be accessed and managed through the command line client or the web interface.
3. Visit ClickHouse
The ClickHouse command line client can be started with the following command:
clickhouse-client
The ClickHouse database can also be accessed and managed through the web interface. By default, the ClickHouse web interface listens on port 8123. Enter http://localhost:8123 in the browser to access the web interface.
The above are the brief steps to install ClickHouse, the actual installation process may vary depending on the operating system version and environment. You can refer to the official ClickHouse documentation for more detailed installation instructions.