Five steps to using GaussDB(DWS)
Five steps to using GaussDB(DWS)
01 Sign up for Huawei Cloud and complete real-name authentication.
Open the Huawei Cloud website and create an account.
02 Create a cluster.
Select a standard data warehouse, hybrid data warehouse, or stream data warehouse, and select data storage capacity based on your analysis scenarios and service scales. To prevent single points of failure (SPOFs), Elastic Load Balance ELB must be used.
03 Connect to the cluster.
You can use a SQL client tool or a third-party driver, such as JDBC (Java database connectivity) or ODBC (Open Database Connectivity), to connect to a cluster and access databases in the cluster.
04 Import data.
Data can be imported from multiple data sources by using various import tools and methods, such as OBS and GDS foreign tables, CDM, DRS, and DLI real-time import, accessing remote MRS data sources, exporting and importing metadata, and using DSC to migrate SQL scripts.
05 Perform data analysis.
After data is imported, run SQL commands to analyze the data in various service scenarios.
Get Started with GaussDB(DWS) in 10 Minutes
Get Started with GaussDB(DWS) in 10 Minutes
Planning a Storage Model
GaussDB(DWS) supports hybrid row and column storage. Each storage method applies to specific scenarios. Select an appropriate model when creating a table.
Creating and Managing Schemas
Schemas allow you to organize database objects into logical groups that are easy to manage. You can add third-party applications to schemas to avoid conflicts.
Getting Started with Common Practices
This section provides you with four independent examples. You can practice with one or more, based on your requirements.
Planning a Storage Model
GaussDB(DWS) supports hybrid row and column storage. Each storage method applies to specific scenarios. Select an appropriate model when creating a table.
Creating and Managing Schemas
Schemas allow you to organize database objects into logical groups that are easy to manage. You can add third-party applications to schemas to avoid conflicts.
Getting Started with Common Practices
This section provides you with four independent examples. You can practice with one or more, based on your requirements.
Best Practices
Best Practices
Migration Process
Oracle migration, MySQL real-time synchronization, and Kafka real-time writing to GaussDB(DWS).
Table Structure Design
This section describes how to optimize table performance in GaussDB(DWS) through table structure design (for example, by configuring the table storage mode, compression level, distribution mode, distribution column, partitioned tables, and local clustering).
Excellent Practices for SQL Queries
SQL statement optimization enables a database to execute SQL statements more quickly while still obtaining correct results.
Best Practices for Automatic Partition Management
GaussDB (DWS) provides the automatic partition management feature. You can set the table-level parameters period and ttl to enable automatic partition management, which automatically creates new partitions and deletes expired partitions, reducing partition table maintenance costs and improving query performance.
Best Practices of Hot and Cold Data Management
The need for data may vary in different time periods, therefore, data is managed in a hierarchical manner, improving data analysis performance and reducing service costs. In some data usage scenarios, data can be classified into hot data and cold data by accessing frequency.
Best Practices of Resource Management
This section demonstrates the resource management feature of GaussDB(DWS), which can resolve performance bottlenecks caused by multi-user query jobs during data analysis and implement independently execution of SQL jobs of many users, reducing resource consumption.