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Stream Compute Service
DocumentationStream Compute ServiceProduct IntroductionOverview
Overview
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Last updated: 2023-11-07 15:26:47
Overview
Last updated: 2023-11-07 15:26:47
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Stream Compute Service is a powerful enterprise-grade real-time big data analytics platform based on Apache Flink. It features one-stop development, seamless connection, sub-second latency, low costs, high security, and high stability, helping businesses maximize the value of their data and accelerate their move to real-time data processing.

Category
Item
Description
Stream Compute Service
Open-Source Apache Flink
Development and debugging
Data connection
Connection to various upstream and downstream data services through connectors, quickly aggregating real-time data and applying output data
Supported
Partially supported
Cloud data products
Seamless integration with mainstream Tencent Cloud data products, including Cloud Data Warehouse, EMR, CDB, CKafka, TDMQ, and COS
Supported
Partially supported
Self-built data services
Custom connectors for connecting to various external data systems, including those in the cloud and IDC
Supported
Supported
Web IDE
Provides Web IDE as a one-stop development and debugging platform that integrates graphical development, multi-language development, metadata management, code debugging, and dependency management
Supported
Not supported
Low-code development
Real-time ETL graphical development
Supported
Not supported
Multiple languages
SQL, Java, and Scala
Supported
Not supported
Metadata
Built-in metadata management that allows users to manage the variables of metadata parameters
Supported
Partially supported
Automatic DDL
Intelligent detection of connected external data systems and automatic generation of table creation statements for data sources and data sinks
Supported
Not supported
Custom functions
Custom functions such as UDF, UDTF, and UDAF
Supported
Supported
Job debugging
Online SQL syntax check
Supported
Not supported
Online SQL debugging that does not affect the production environment
Dependencies
Management of packages, and management and dynamic distribution of external dependencies (configuration files, dependent libraries, etc.)
Supported
Not supported
Compute resources
Configuration of fine-grained resources and operator parallelism for JobManager and TaskManager
Supported
Partially supported
Job versions
Historical version management of jobs and resources to facilitate business upgrade and development
Supported
Not supported
Development using TencentCloud API
TencentCloud API provides all the APIs required for Web IDE development, through which business platforms and Stream Compute Service can be seamlessly connected.
Supported
Not supported
Deployment and Ops
Job deployment
Deployment management of jobs throughout the lifecycle (including start, stop, suspend, and resume) using Web IDE and TencentCloud API
Supported
Not supported
Monitoring
Visualization of running parameters and status of jobs
Supported
Partially supported
Running parameters
Visualization of the logic and parameters of running jobs, such as SQL statement details and parameter configurations
Supported
Not supported
Running status events
Visualization of events such as unexpected job restarts, snapshot failures, and CPU or memory exceptions of JobManager/TaskManager
Supported
Not supported
Metrics and alarms
Comprehensive job monitoring and alerting based on dynamic metrics defined at task granularity and over 65 monitoring metrics. The monitoring metrics are related to healthy running of cluster jobs and upstream and downstream systems and aggregated using functions such as sum, max, min, and avg.
Supported
Partially supported
Monitoring metrics
Display of metrics at job, JobManager, TaskManager, and Task granularity, as well as accurate CPU/memory metrics for container Pods
Supported
Partially supported
Monitoring alarms
Alarm rule (including AI-based dynamic threshold alarms) configuration for over 65 monitoring metrics using Tencent Cloud Observability Platform
Supported
Not supported
Smart diagnosis
Intelligently diagnoses and analyzes the exception information by collecting and analyzing exception logs and provides recommended solutions
Supported
Partially supported
Exception information collection
Ships the exception logs generated during job running to Tencent Cloud Log Service (CLS) in real time
Supported
Not supported
Exception information search
Allows users to view job instance exception logs, which can be aggregated and searched by instance ID, process role, and process ID
Supported
Not supported
Exception diagnosis
Allows users to quickly identify the causes of job exceptions using the exception log-based quick diagnosis feature and provides recommended solutions
Supported
Not supported
Black window diagnosis
Automatically uploads the underlying OOM Dump, JFR, exception logs, and other exception information from actual jobs to the user's Object Storage Service (COS)
Supported
Not supported
Information collection
Provides a list of files (including OOM Dump and JFR files) in the log directory for user analysis after the job process is ended
Supported
Not supported
High availability
SLA guarantee
Distributed cluster design without any single point of failure, full-linkage monitoring, and rapid self-healing capabilities to ensure the availability of 99.9%
Supported
Not supported
Cost
Resource cost
Reduces computing resource costs by allocating and utilizing resources on demand based on actual business load
Supported
Not supported
Auto scaling
Auto scaling based on the business load to ensure normal business operations and avoid resource waste
Supported
Not supported
Fine-grained resources
Selection of fine-grained resources (e.g. 0.5 CU/process) for jobs to avoid resource waste
Supported
Partially supported
Security
Security isolation
Multi-dimensional isolation of the resource environment to ensure data security across tenants
Supported
Partially supported
Space isolation
Exclusive tenant access to network space, computing resources, and storage resources, ensuring physical isolation between tenants
Supported
Partially supported
Process isolation
Isolates job processes by container deployment to ensure process stability and security
Supported
Partially supported
Access control
Ensures account security using the Tencent Cloud account system and SAML authentication mechanism, and achieves fine-grained access control
Supported
Not supported
Account system
Connects to the Tencent Cloud account system and supports SAML authentication
Supported
Partially supported
Fine-grained access control
Fine-grained permission management at cluster or job level to meet the needs of collaborative development by multiple persons
Supported
Not supported

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