Related Services

OBS works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI provides an API for you to import data from corresponding OBS paths to DLI tables.

  For details about the API, see Resource-related APIs > Table-related APIs > Importing Data in the Data Lake Insight API Reference.

• Data storage: You can create OBS tables on DLI. However, such tables only store metadata while data content is stored in corresponding OBS paths.

  For details, see Creating an OBS Table Using the DataSource Syntax and Creating an OBS Table Using the Hive Syntax in the Data Lake Insight SQL Syntax Reference.

• Data backup: DLI provides an API for you to export the data in DLI to OBS for backup.

  For details about the API, see Resource-related APIs > Table-related APIs > Exporting Data in the Data Lake Insight API Reference.

• Query result storage: DLI provides an API for you to save routine query result data on OBS.

  For details about the API, see "SQL Job related APIs" > "Exporting Query Results" in Data Lake Insight API Reference.

Identity and Access Management (IAM) authenticates access to DLI.

For details, see Creating an IAM User and Granting Permissions and Using IAM Roles or Policies to Grant Access to DLI.

Cloud Trace Service (CTS) audits performed DLI operations.

For details about DLI operations that can be recorded by CTS, see DLI Operations That Can Be Recorded by CTS.

Cloud Eye helps monitor job metrics for DLI, delivering status information in a concise and efficient manner.

For details, see Monitoring DLI Using Cloud Eye.

Simple Message Notification (SMN) can send notifications to users when a job running exception occurs on DLI.

For details, see Creating an SMN Topic.

Relational Database Service (RDS) works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import RDS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to RDS tables.

For how to access RDS data through a DLI datasource connection, see Common Development Methods for DLI Cross-Source Analysis.

DWS works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import DWS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to DWS tables.

CSS works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import CSS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to CSS tables.

For how to access CSS data through a DLI datasource connection, see Common Development Methods for DLI Cross-Source Analysis.

Distributed Cache Service (DCS) works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import DCS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to DCS tables.

For how to access DCS data through a DLI datasource connection, see Common Development Methods for DLI Cross-Source Analysis.

Document Database Service (DDS) works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import DDS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to DDS tables.

For how to access DDS data through a DLI datasource connection, see Common Development Methods for DLI Cross-Source Analysis.

MapReduce Service (MRS) works as the data source and data storage system for DLI, and delivers the following capabilities:

• Data source: DLI allows you to import MRS data using DataFrame or SQL.
• Query result storage: DLI uses the SQL INSERT syntax to store query result data to MRS tables.

For how to access MRS data through a DLI datasource connection, see Common Development Methods for DLI Cross-Source Analysis.

DataArts Studio is a one-stop big data development platform for collaborations and provides fully-managed big data scheduling capabilities. It manages various big data services, making big data more accessible than ever before and helping you effortlessly build big data processing centers.

• The DLI SQL node in DataArts Studio transfers SQL statements to DLI for execution.
• The DLI Spark node in DataArts Studio is used to execute a predefined Spark job.

For details about how to submit DLI jobs using DataArts Studio, see DataArts Studio User Guide.