ClickHouse Application Development Overview

Introduction

ClickHouse is a column-based database oriented to online analysis and processing. It supports SQL query and provides good query performance. The aggregation analysis and query performance based on large and wide tables is excellent, which is one order of magnitude faster than other analytical databases.

Advantages:

• High data compression ratio
• Multi-core parallel computing
• Vectorized computing engine
• Nested data structure
• Sparse indexes
• INSERT and UPDATE

Application scenarios:

• Real-time data warehouse

  The streaming computing engine (such as Flink) is used to write real-time data to ClickHouse. With the excellent query performance of ClickHouse, multi-dimensional and multi-mode real-time query and analysis requests can be responded within subseconds.

• Offline query

  Large-scale service data is imported to ClickHouse to construct a large wide table with hundreds of millions to tens of billions of records and hundreds of dimensions. It supports personalized statistics collection and continuous exploratory query and analysis at any time to assist business decision-making and provide excellent query experience.

ClickHouse Application Development APIs

ClickHouse is developed using C++ and positioned as a DBMS. It supports HTTP and Native TCP network interface protocols and multiple driver modes such as JDBC and ODBC. clickhouse-jdbc of the community edition is recommended for application development.

Concepts

• Cluster

  Cluster is a logical concept in ClickHouse. It can be defined by users as required, which is different from the general understanding of cluster. Multiple ClickHouse nodes are loosely coupled and deployed independently.

• Shard

  A shard is a horizontal division of a cluster. A cluster can consist of multiple shards.

• Replica

  Multiple replicas can be created for one shard.

• Partition

  Partitions vertically divide local replicas into different parts.

• MergeTree

  ClickHouse has a huge table engine system. As the basic table engine of the family system, MergeTree provides functions such as data partitioning, primary indexes, and secondary indexes. When creating a table, you need to specify the table engine. Different table engines determine the characteristics of a data table, for example, the features of a data table, in what format data is stored, and how data is loaded.