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Stream Compute Service
    Documentation
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    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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