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    Realtime Compute for Apache Flink

    • Realtime Compute for Apache Flink
    • Updates and Announcements
      • Document updates
    • Introduction
      • What is Alibaba Cloud Realtime Compute for Apache Flink?
      • Architecture of Realtime Compute for Apache Flink in exclusive mode
      • Service types
      • Scenarios
    • Fully Managed Flink
      • Announcements
      • Pricing
      • Overview
        • Overview
        • Introduction to the console of fully managed Flink
        • Upstream and downstream storage
      • Preparations
        • Assign a role to an account
        • Configure a whitelist
        • Grant permissions to an account
      • Procedure for activating the service
      • Manage projects
      • Configure a session cluster
      • Flink SQL Reference
        • Overview
        • Keywords
        • Create a data view
        • DDL statements
          • Create a source table
            • Create a Log Service source table
            • Create a Message Queue for Apache Kafka source table
            • Create a full MaxCompute source table
            • Create an incremental MaxCompute source table
            • Create a Message Queue for Apache RocketMQ source table
            • Create a Hologres source table
            • Create a full Elasticsearch source table
            • Create a PostgreSQL CDC source table (public preview)
            • Create a MySQL CDC source table (public preview)
            • Create an Upsert Kafka source table
            • Create a Datagen source table
          • Create a result table
            • Create a Log Service result table
            • Create a Message Queue for Apache Kafka result table
            • Create a Tablestore result table
            • Create a MaxCompute result table
            • Create a Message Queue for Apache RocketMQ result table
            • Create an ApsaraDB for HBase result table
            • Create an ApsaraDB for Redis result table
            • Create a Hologres result table
            • Create an ApsaraDB for MongoDB result table
            • Create an Elasticsearch result table
            • Create a Phoenix5 result table
            • Create an ApsaraDB RDS for MySQL result table
            • Create an AnalyticDB for MySQL V3.0 result table
            • Create a ClickHouse result table
            • Create a print result table
            • Create an Upsert Kafka result table
            • Create a blackhole result table
            • Create an InfluxDB result table
          • Create a dimension table
            • Create an ApsaraDB for HBase dimension table
            • Create a Tablestore dimension table
            • Create a MaxCompute dimension table
            • Create an ApsaraDB for Redis dimension table
            • Create an Elasticsearch dimension table
            • Create a Hologres dimension table
            • Create an ApsaraDB RDS for MySQL dimension table
            • Create an AnalyticDB for MySQL V3.0 dimension table
            • Create a FileSystem dimension table
        • INSERT INTO statement
        • DQL statements
        • Window functions
          • Overview
          • Tumbling windows
          • Sliding windows
          • Session windows
          • OVER windows
        • Built-in functions
          • Overview
          • Scalar functions
            • BITAND
            • BITNOT
            • BITOR
            • BITXOR
            • CONV
            • DATEDIFF
            • DATE_ADD
            • DATE_FORMAT
            • DATE_FORMAT_TZ
            • DATE_SUB
            • FROM_UNIXTIME
            • ISNAN
            • JSON_VALUE
            • KEYVALUE
            • MURMUR_HASH
            • MURMUR_HASH_64
            • PARSE_URL
            • REGEXP
            • REGEXP_REPLACE
            • SPLIT_INDEX
            • TO_DATE
            • TO_TIMESTAMP_TZ
            • UNIX_TIMESTAMP
          • Table-valued functions
            • GENERATE_SERIES
            • JSON_TUPLE
            • MULTI_KEYVALUE
            • STRING_SPLIT
          • Aggregate functions
            • APPROX_COUNT_DISTINCT
            • FIRST_VALUE
            • LAST_VALUE
          • CLUSTER_SERVING
        • User-defined functions
          • Java
            • Overview
            • UDFs
            • UDAFs
            • UDTFs
          • Python
            • Overview
            • UDFs
            • UDAFs
            • UDTFs
      • Flink SQL Developer Guide
        • Overview
        • Develop a job
        • Start a job
        • Suspend or terminate a job
        • Debug a job
        • Manage UDFs
        • Configure a Hive metastore
        • Manage Hologres Catalogs
        • Manage custom connectors
        • Job optimization
          • Recommended Flink SQL practices
          • Configure resources in expert mode
      • Flink DataStream Developer Guide
        • Overview
        • Develop a job
        • Publish a job
        • Start a job
        • Suspend or terminate a job
      • Flink Python Developer Guide
        • Overview
        • Develop a job
        • Publish a job
        • Start a job
        • Suspend or terminate a job
        • Python dependencies
      • O&M management
        • Job O&M
        • Manage job versions
        • Configure alert rules (on the fully managed Flink tab)
        • Configure monitoring alerts (in the ARMS console)
        • Configure job logs
        • View job logs
        • Configure Autopilot
      • Cluster configuration management
        • Reconfigure workspace resources
        • Manage components
          • Modify a vSwitch
      • Security and monitoring
        • ActionTrail logs
      • SDK Reference
        • OpenAPI SDK
      • FAQ
        • Basic concepts
        • Reference
        • Troubleshooting
        • Upstream and downstream storage
        • Common SQL errors
      • Agreements
        • Flink Serverless SLA
    • Exclusive Mode
      • Announcements
      • Release notes
        • Blink-3.7.10
        • Blink 3.7.9
        • Blink-3.6.8
        • Blink-3.6.5
        • Blink 3.6.2
        • Blink-3.6.0
        • Blink-3.5.0-hotfix
        • Blink 3.4.4
        • Blink 3.4.3
        • Blink 3.3.0
        • Blink 3.2.3
        • Blink 3.2.1
          • Blink 3.2.1 release notes
          • API compatibility report: Blink 3.2 and Flink 1.5.1
          • Incompatible SQL items: Blink 3.0 and Blink 2.0
      • Product Introduction
        • Overview
        • Development history
        • Workflow
        • Upstream and downstream data stores
        • Product security
        • Limits
      • Pricing
        • Billable items
        • Billing methods
        • Specification selection
        • Renewal
          • Manual renewal
          • Auto-renewal
        • Change resource configurations
      • Preparation
        • Alibaba Cloud account and RAM user authorization
        • Activate Realtime Compute for Apache Flink and create a project
        • Role authorization
          • Assign a RAM role to an account that uses Realtime Compute for Apache Flink in exclusive mode
      • Flink SQL
        • Overview
        • Keywords
        • Basic concepts
          • Time zone
          • Time attributes
          • Watermark
          • Computed column
        • Data types
          • Data type conversion
          • Mathematical and logical operations between data types
        • Create a data view
        • DDL statements
          • Overview
          • Create a source table
          • Create a result table
          • Create a dimension table
        • DML statement
          • INSERT INTO statements
          • EMIT statements
        • Query statements
          • SELECT statements
          • WHERE statement
          • HAVING statement
          • GROUP BY statement
          • JOIN statements
          • JOIN statements for dimension tables
          • IntervalJoin statement
          • UNION ALL
          • TopN
          • GROUPING SETS clause
          • CEP statements
          • Deduplication statements
        • Window functions
          • Overview
          • Tumbling window
          • Sliding windows
          • Session window
          • OVER window
        • Built-in functions
          • String functions
          • Mathematical functions
          • Date functions
          • Logical functions
          • Conditional functions
          • Table-valued functions
          • Type conversion function
          • Aggregate functions
          • Other functions
        • UDX
          • Overview
          • UDF
          • UDAF
          • UDTF
          • Develop a UDX by using IntelliJ IDEA
      • Flink SQL Development Guide
        • Overview
        • Data storage
          • Overview
          • Data storage resource registration
          • Authorize Realtime Compute for Apache Flink to access a VPC
          • Configure a whitelist for accessing storage resources
        • Data development
          • Develop a job
          • Publish a job
          • Start a job
          • Suspend a job
          • Terminate a job
        • Job debugging
          • Local debugging
          • Online debugging
        • Data administration
          • Go to the Job Administration page
          • Running information
          • Curve charts
          • Timeline
          • Failover
          • Checkpoints
          • JobManager
          • TaskExecutor
          • Data lineage
          • Properties and parameters
          • Job diagnosis
        • Configuration optimization
          • Overview
          • Recommended Flink SQL practices
          • Performance optimization by using automatic configuration
          • Performance optimization by using auto scaling
          • Optimize performance by manual configuration
          • Typical backpressure scenarios and optimization ideas
          • SQL Tuning Advisor
            • Asynchronous mode
            • Cache policy
            • Local-global optimization
            • ROW_NUMBER OVER WINDOW
            • miniBatch and microBatch
            • Partial-final optimization
            • APPROX_COUNT_DISTINCT
            • Partitioned All Cache
        • Monitoring and alerting
        • Manage Blink versions of a Realtime Compute for Apache Flink cluster deployed in exclusive mode
        • Customize log levels and download paths
      • Flink Datastream Development Guide
        • Overview
        • Configure a whitelist for accessing storage resources
        • Set custom parameters
        • Monitoring and alerts
        • Develop a job
        • Publish a job
        • Example of DataStream jobs
          • Read data from DataHub
          • Read data from Message Queue for Apache Kafka
          • Read data from DataHub and write data to ApsaraDB for HBase
          • Read data from Log Service
      • Best Practices
        • Best practices of Realtime Compute in the e-commerce industry
          • Latest transaction records in e-commerce scenarios
          • Real-time situation awareness and geographic distribution of orders in e-commerce scenarios
          • Marketing coupons in e-commerce scenarios
          • Real-time PV and UV curves in e-commerce scenarios
        • Best practices of Realtime Compute in the IoT industry
          • Multidimensional analysis of data from IoT sensors
        • Best practices of Realtime Compute in the live streaming industry
          • Core video metric monitoring for live streaming
          • Digital operations for live streaming
      • Agreements
        • Realtime Compute for Apache Flink Service Level Agreement
 
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    Realtime Compute for Apache Flink Service Level Agreement

    Document Center

    Realtime Compute for Apache Flink Service Level Agreement

    Last Updated: Apr 10, 2021

    For more information about the Realtime Compute for Apache Flink Service Level Agreement (SLA), see Alibaba Cloud Realtime Compute for Apache Flink Service Level Agreement.

    Previous: Digital operations for live streaming

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