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Stream Compute Service

문서Stream Compute ServiceOperation GuideOverview of Upstream and Downstream Data

Overview of Upstream and Downstream Data

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마지막 업데이트 시간: 2026-08-06 15:17:00
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Introduction to Upstream and Downstream Data for SQL Jobs

A data source (Source) refers to the upstream data input to a stream computing system. In current SCS SQL-mode jobs, data sources can include message queues such as Kafka and databases such as MySQL.
A data destination (Sink) refers to the destination where a stream computing system outputs processed results. In current SCS SQL-mode jobs, data destinations can include message queues such as Kafka, databases such as MySQL, and data analysis engines such as ES.
Users can also upload custom Connector packages to support more data sources and destinations.
For the concepts mentioned in this document, such as the differences between Tuple and Upsert data destinations, see the Glossary.
Upstream/Downstream
As a Streaming Data Source
As a Batch Data Source
As a Dimension Table
As an Append Data Destination
As an Upsert Data Destination
Supported
Supported (JAR Jobs)
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Supported
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Supported (JAR Jobs)
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Supported
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Supported (Flink-1.11)
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Supported
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Supported (version 9.6 and above)
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Supported (Flink-1.13)
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Supported
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Supported
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Supported
Note:
Elasticsearch supports versions 6.x and 7.x, but does not support version 5.x.
The mysql-cdc connector can be used with TDSQL-C.
Note
For information on developing and using Sources and Sinks for SQL jobs, refer to the Upstream and Downstream Development Guide.

Introduction to Upstream and Downstream Data for JAR Jobs

After the VPC of a dedicated cluster establishes a peering connection with a user-specified VPC, JAR-mode jobs can access all network-accessible resources within that user-specific VPC. This not only supports the upstream and downstream components compatible with SQL jobs mentioned above, but also enables the use of various Tencent Cloud services within that VPC, such as message queues, databases, API services, and CVMs.
Additionally, you can purchase a NAT Gateway within this specific VPC and configure the routing table to access external internet addresses (such as APIs on the public network or externally self-built services), further enhancing the processing capability of stream computing jobs.
For information on developing and using Sources and Sinks for JAR jobs, refer to the DataStream Connectors section in the Flink official documentation.
이전 주제: Flink Dynamic CEP Quick Start다음 주제: Job Overview

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