Preparing data source and compute source
Before utilizing Dataphin, select a suitable database or data warehouse as the data source to match your business scenario requirements. This source will facilitate the reading of raw data and the writing of constructed data. Concurrently, prepare MaxCompute and Flink projects as compute sources to provide the necessary computing resources for data development within Dataphin.
Preparing data source
Dataphin integrates with various data sources, including big data storage, files, message queues, relational databases, and NoSQL databases. For a detailed list of supported data sources and guidance on operations, refer to Data Sources Supported by Dataphin.
Ensure network connectivity between Dataphin and your chosen data source before creating it in Dataphin. This connectivity is crucial for Dataphin to access raw data and return processed data.
Preparing compute source
Prior to establishing a project space, finalize the preparation of the compute source. This includes offline compute sources like MaxCompute and real-time compute sources such as Flink, chosen based on your specific business requirements:
For guidance on creating a MaxCompute project, see Create a MaxCompute project.
To enhance query speeds for the MaxCompute compute engine's offline data warehouse, consider adding Hologres as an accelerated compute source. For activation details, see Purchase a Hologres instance.
For instructions on creating a Flink project, consult Getting started with an SQL deployment of Realtime Compute for Apache Flink.
ImportantNote that Dataphin currently only supports the Blink exclusive cluster version of Flink as a compute source.
What to do next
Once the data and compute sources are ready, proceed to create a project space for data development. For step-by-step instructions, visit Create a general project.