- Product Introduction
- Purchase Guide
- Getting Started
- Complete Process for New User Activation
- DLC Data Import Guide
- Quick Start with Data Analytics in Data Lake Compute
- Quick Start with Permission Management in Data Lake Compute
- Quick Start with Partition Table
- Enabling Data Optimization
- Cross-Source Analysis of EMR Hive Data
- Standard Engine Configuration Guide
- Operation Guide
- Data Exploration
- Data Management
- Data Job
- Task History
- Insight Management
- Engine Management
- Data Engine Introduction
- SuperSQL Engine
- SuperSQL Engine Overview
- Purchasing Private Data Engine
- Renewing SuperSQL Engine
- Managing Private Data Engine
- Engine-Level Parameter Settings
- Disaster Recovery Cluster
- Engine Kernel Version
- Engine Network Configuration
- Associating Tag with Private Engine Resource
- Engine Local Cache
- Custom Task Scheduling Pool
- Standard Engine
- Ops Management
- Query Script Management
- Development Guide
- Client Access
- Practical Tutorial
- SQL Statement
- SuperSQL Statement
- Overview of SuperSQL Statement
- Unified Statement
- Common Data Types
- DDL Statement
- CREATE DATABASE
- SHOW DATABASES
- DESCRIBE DATABASE
- ALTER DATABASE
- DROP DATABASE
- CREATE TABLE
- REPLACE TABLE AS SELECT
- SHOW TABLES
- SHOW CREATE TABLE
- SHOW TBLPROPERTIES
- DESCRIBE TABLE
- SHOW COLUMNS IN TABLE
- ALTER TABLE
- ALTER TABLE ADD COLUMNS
- ALTER TABLE ADD COLUMN AFTER/FIRST
- ALTER TABLE DROP COLUMN
- ALTER TABLE ADD PARTATION
- SHOW PARTITIONS
- ALTER TABLE DROP PARTITION
- ALTER TABLE ADD PARTITION FIELD
- ALTER TABLE DROP PARTITION FIELD
- ALTER TABLE ... RENAME COLUMN
- ALTER TABLE SET TBLPROPERTIES
- ALTER TABLE SET LOCATION
- ALTER TABLE ... WRITE ORDERED BY
- ALTER TABLE ... WRITE DISTRIBUTED BY PARTITION
- ALTER TABLE ... SET IDENTIFIER FIELDS
- ALTER TABLE ... DROP IDENTIFIER FIELDS
- MSCK REPAIR TABLE
- ANALYZE TABLES
- DROP TABLE
- EXPLAIN
- CALL STATEMENT
- CREATE VIEW AS
- SHOW VIEWS
- DESCRIBE VIEW
- SHOW CREATE VIEW
- SHOW COLUMNS IN VIEW
- ALTER VIEW
- DROP VIEW
- CREATE FUNCTION
- SHOW FUNCTION
- DROP FUNCTION
- DML Statement
- DQL Statement
- Iceberg Table Statement
- Materialized View Statement
- SQL Implicit Conversion
- Functions
- Overview of Standard Spark Statement
- Overview of Standard Presto Statement
- Reserved Words
- SuperSQL Statement
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- Data Table APIs
- Task APIs
- CreateSparkSessionBatchSQL
- CancelSparkSessionBatchSQL
- CancelTask
- CreateResultDownload
- CreateSparkAppTask
- CreateTask
- CreateTasks
- DeleteSparkApp
- DescribeEngineUsageInfo
- DescribeResultDownload
- DescribeSparkAppTasks
- DescribeTaskResult
- DescribeTasks
- QueryTaskCostDetail
- CreateSparkApp
- DescribeSparkAppJob
- DescribeSparkSessionBatchSqlLog
- ModifySparkApp
- DescribeSparkAppJobs
- ModifySparkAppBatch
- DescribeTaskStatistics
- DescribeQuery
- DescribeJobs
- DescribeJob
- Metadata APIs
- Service Configuration APIs
- CreateCHDFSBindingProduct
- DeleteCHDFSBindingProduct
- DescribeOtherCHDFSBindingList
- CreateStoreLocation
- DescribeStoreLocation
- ModifyDataEngineDescription
- RollbackDataEngineImage
- SwitchDataEngine
- SwitchDataEngineImage
- UpgradeDataEngineImage
- DeleteThirdPartyAccessUser
- DescribeDataEngineImageVersions
- DescribeSubUserAccessPolicy
- DescribeThirdPartyAccessUser
- RegisterThirdPartyAccessUser
- RestartDataEngine
- UpdateUserDataEngineConfig
- UpdateDataEngineConfig
- Permission Management APIs
- AddUsersToWorkGroup
- AttachUserPolicy
- AttachWorkGroupPolicy
- BindWorkGroupsToUser
- CreateUser
- CreateWorkGroup
- DeleteUser
- DeleteUsersFromWorkGroup
- DeleteWorkGroup
- DescribeUserInfo
- DescribeUserRoles
- DescribeUserType
- DescribeUsers
- DescribeWorkGroupInfo
- DescribeWorkGroups
- DetachUserPolicy
- DetachWorkGroupPolicy
- ModifyUser
- ModifyUserType
- ModifyWorkGroup
- UnbindWorkGroupsFromUser
- UpdateRowFilter
- CheckGrantedPermission
- Database APIs
- Data Source Connection APIs
- Data Optimization APIs
- Data Engine APIs
- Data Types
- Error Codes
- General Reference
- DLC Policy
- Service Level Agreement
- Contact Us
- Product Introduction
- Purchase Guide
- Getting Started
- Complete Process for New User Activation
- DLC Data Import Guide
- Quick Start with Data Analytics in Data Lake Compute
- Quick Start with Permission Management in Data Lake Compute
- Quick Start with Partition Table
- Enabling Data Optimization
- Cross-Source Analysis of EMR Hive Data
- Standard Engine Configuration Guide
- Operation Guide
- Data Exploration
- Data Management
- Data Job
- Task History
- Insight Management
- Engine Management
- Data Engine Introduction
- SuperSQL Engine
- SuperSQL Engine Overview
- Purchasing Private Data Engine
- Renewing SuperSQL Engine
- Managing Private Data Engine
- Engine-Level Parameter Settings
- Disaster Recovery Cluster
- Engine Kernel Version
- Engine Network Configuration
- Associating Tag with Private Engine Resource
- Engine Local Cache
- Custom Task Scheduling Pool
- Standard Engine
- Ops Management
- Query Script Management
- Development Guide
- Client Access
- Practical Tutorial
- SQL Statement
- SuperSQL Statement
- Overview of SuperSQL Statement
- Unified Statement
- Common Data Types
- DDL Statement
- CREATE DATABASE
- SHOW DATABASES
- DESCRIBE DATABASE
- ALTER DATABASE
- DROP DATABASE
- CREATE TABLE
- REPLACE TABLE AS SELECT
- SHOW TABLES
- SHOW CREATE TABLE
- SHOW TBLPROPERTIES
- DESCRIBE TABLE
- SHOW COLUMNS IN TABLE
- ALTER TABLE
- ALTER TABLE ADD COLUMNS
- ALTER TABLE ADD COLUMN AFTER/FIRST
- ALTER TABLE DROP COLUMN
- ALTER TABLE ADD PARTATION
- SHOW PARTITIONS
- ALTER TABLE DROP PARTITION
- ALTER TABLE ADD PARTITION FIELD
- ALTER TABLE DROP PARTITION FIELD
- ALTER TABLE ... RENAME COLUMN
- ALTER TABLE SET TBLPROPERTIES
- ALTER TABLE SET LOCATION
- ALTER TABLE ... WRITE ORDERED BY
- ALTER TABLE ... WRITE DISTRIBUTED BY PARTITION
- ALTER TABLE ... SET IDENTIFIER FIELDS
- ALTER TABLE ... DROP IDENTIFIER FIELDS
- MSCK REPAIR TABLE
- ANALYZE TABLES
- DROP TABLE
- EXPLAIN
- CALL STATEMENT
- CREATE VIEW AS
- SHOW VIEWS
- DESCRIBE VIEW
- SHOW CREATE VIEW
- SHOW COLUMNS IN VIEW
- ALTER VIEW
- DROP VIEW
- CREATE FUNCTION
- SHOW FUNCTION
- DROP FUNCTION
- DML Statement
- DQL Statement
- Iceberg Table Statement
- Materialized View Statement
- SQL Implicit Conversion
- Functions
- Overview of Standard Spark Statement
- Overview of Standard Presto Statement
- Reserved Words
- SuperSQL Statement
- API Documentation
- History
- Introduction
- API Category
- Making API Requests
- Data Table APIs
- Task APIs
- CreateSparkSessionBatchSQL
- CancelSparkSessionBatchSQL
- CancelTask
- CreateResultDownload
- CreateSparkAppTask
- CreateTask
- CreateTasks
- DeleteSparkApp
- DescribeEngineUsageInfo
- DescribeResultDownload
- DescribeSparkAppTasks
- DescribeTaskResult
- DescribeTasks
- QueryTaskCostDetail
- CreateSparkApp
- DescribeSparkAppJob
- DescribeSparkSessionBatchSqlLog
- ModifySparkApp
- DescribeSparkAppJobs
- ModifySparkAppBatch
- DescribeTaskStatistics
- DescribeQuery
- DescribeJobs
- DescribeJob
- Metadata APIs
- Service Configuration APIs
- CreateCHDFSBindingProduct
- DeleteCHDFSBindingProduct
- DescribeOtherCHDFSBindingList
- CreateStoreLocation
- DescribeStoreLocation
- ModifyDataEngineDescription
- RollbackDataEngineImage
- SwitchDataEngine
- SwitchDataEngineImage
- UpgradeDataEngineImage
- DeleteThirdPartyAccessUser
- DescribeDataEngineImageVersions
- DescribeSubUserAccessPolicy
- DescribeThirdPartyAccessUser
- RegisterThirdPartyAccessUser
- RestartDataEngine
- UpdateUserDataEngineConfig
- UpdateDataEngineConfig
- Permission Management APIs
- AddUsersToWorkGroup
- AttachUserPolicy
- AttachWorkGroupPolicy
- BindWorkGroupsToUser
- CreateUser
- CreateWorkGroup
- DeleteUser
- DeleteUsersFromWorkGroup
- DeleteWorkGroup
- DescribeUserInfo
- DescribeUserRoles
- DescribeUserType
- DescribeUsers
- DescribeWorkGroupInfo
- DescribeWorkGroups
- DetachUserPolicy
- DetachWorkGroupPolicy
- ModifyUser
- ModifyUserType
- ModifyWorkGroup
- UnbindWorkGroupsFromUser
- UpdateRowFilter
- CheckGrantedPermission
- Database APIs
- Data Source Connection APIs
- Data Optimization APIs
- Data Engine APIs
- Data Types
- Error Codes
- General Reference
- DLC Policy
- Service Level Agreement
- Contact Us
The billing of Data Lake Compute consists of two parts: compute resources and storage resources. Compute resources have private and public engines, and storage resources are charged only when the managed storage service of Data Lake Compute is used.
Billing of Compute Resources
Performance description
Data Lake Compute private engines are billed by compute unit (CU). Each CU contains 1 CPU core and 4 GB memory. You can estimate the number of required CUs based on your actual business conditions or submit a ticket for assistance.
Data Lake Compute public engines are billed by scanned data volume. Public engines are suitable for scenarios with a small amount of data and are recommended.
Billing modes
Data Lake Compute supports pay-as-you-go and monthly subscription billing modes as detailed below. For more information, see Postpaid Billing and Prepaid Billing respectively.
Data Engine Type | Billing Mode | Description |
Public engine | Pay-as-you-go | Requires no configuration management. Incurs no fees when idle and is billed by scanned data volume. Works well in temporary computing scenarios with a small amount of data. |
Private engine | Pay-as-you-go | Scales private resources elastically as needed. Supports suspension when there is no task and incurs no fees when suspended; is billed by CU Works well in irregular computing scenarios with a medium amount of data. |
| Monthly subscription | Scales private resources elastically as needed. Is billed by CU and becomes available at any time with no need of startup. The elastically scaled resources are pay-as-you-go. Works well in stable computing tasks with a large amount of data. |
Pricing
Public engine
A public engine is billed by scanned data volume in successful query tasks, with a bill generated every clock-hour. You can view specific bills in the Billing Center.
Public engine fees = Scanned data volume * Unit price
Billable Item | Price (USD/GB) |
Scanned data volume | 0.0045 |
Note
Fees will be incurred if the query task succeeds or the task is manually canceled but data is scanned. No fees will be incurred when resources are being scheduled or if the query task fails.
If less than 34 MB of data is scanned for a single SQL task, it will be billed as 34 MB (about 0.00015 USD).
When you use a public engine, since Data Lake Compute adopts serverless architecture, it needs to schedule compute resources for task execution for the first time over a period of time, which may take a longer time.
Private engine
Note
To purchase a data engine with more than 256 CUs, submit a ticket for assistance, and we will reserve resources for you.
Pay-as-you-go
A pay-as-you-go data engine is elastically scalable. When you purchase it, the system will freeze the fees for 1-hour usage of the minimum cluster specification. A bill will be generated every clock-hour. You can view specific bills in the Billing Center.
Pay-as-you-go private engine fees = Hourly number of used CUs * Unit price
Note
In pay-as-you-go billing mode, the engine will keep running at the purchased minimum cluster count. You can suspend the engine when you don't need to use clusters in order to avoid fees.
Monthly subscription
In monthly subscription billing mode, the engine will keep running at the purchased minimum cluster count. If elastic scaling is triggered, added cluster resources will be pay-as-you-go. You can view specific bills in the Billing Center. A monthly subscribed engine won't incur pay-as-you-go fees if it is not scaled.
Monthly subscription fees = Cluster specification Minimum cluster count Number of purchase months * Monthly subscription unit price
Monthly subscription scaling fees = Cluster specification Number of added clusters Pay-as-you-go unit price
Example: If you purchase a monthly subscribed private data engine with a specification of 16 CUs, a minimum cluster count of 2, and a maximum cluster count of 5 for one month, the monthly subscription fees will be 16 2 1 22 = 704 USD, and the engine will run for one month with two 16-CU clusters without incurring additional fees. If the engine is scaled out to five clusters for one hour, then three added 16-CU clusters will incur pay-as-you-go fees of 16 (5 - 2) 1 0.05 = 2.4 USD.
Unit price
Note
The available regions on the purchase page apply.
The prices of Data Lake Compute CU in different regions are as follows:
Region | Monthly Subscription Price (USD/CU/Month) | Pay-As-You-Go Price (USD/CU/Hour) |
Hong Kong (China) | 22 | 0.05 |
Singapore | 22 | 0.05 |
Virginia | 22 | 0.05 |
Billing of Storage Resources
Data Lake Compute provides the data storage capability. After you enable the native table feature, the native table data is stored under managed storage of Data Lake Compute.
Managed storage is used to store data including native table data, adaptive shuffle data, query result data, and program packages.
Billing modes
Managed storage fees are pay-as-you-go. They consist of storage usage fees and request fees, as detailed below.
Billable Item | Description | Billing Formula |
Storage usage fees | Calculated based on the storage usage at a unit price that varies by storage class. | Daily storage usage fees = Monthly storage usage unit price / 30 * Daily storage usage Daily storage usage = Sum of "5-minute storage usage" for the day / 288 (number of statistical points) |
Request fees | Calculated based on the number of requests at a unit price that varies by storage class. | Request fees = Unit price per 10,000 requests * Daily accumulated number of requests / 10,000 |
Pricing
Region | Storage Usage Fees (USD/GB/month) | Request Fees (USD/10k requests) |
Hong Kong (China) | 0.022 | 0.002 |
Singapore | 0.022 | 0.003 |
Virginia | 0.02 | 0.002 |
Example:
Assume that on November 1, 2020, user A uploaded 10 GB of data to a Data Lake Compute managed storage bucket residing in Hong Kong (China) region in the STANDARD storage class, generating 100 requests. As fees for a day were settled the next day:
STANDARD storage usage fees: Settled daily starting from November 2, 2020.
STANDARD request fees: Settled on November 2, 2020.
An analysis is performed as follows based on the two billing modes:
STANDARD storage usage fees = 0.022 USD/GB/month / 30 10 GB 30 days = 0.22 USD
STANDARD request fees = 0.002 USD/10,000 requests * 100 requests / 10,000 = 0.00002 USD
In summary, the total bill for user A in November is calculated as follows: 0.22 + 0.00002 = 0.22002 USD.
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