Benefits for Serverless Infrastructure
Benefits for Serverless Infrastructure
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Independent Scaling
Save money by scaling storage and compute resources independently of each other. -
Auto Scaling
Make sure you always have enough capacity on hand no matter what sort of traffic spikes come your way. -
Pay-per-Use
Pay only for what you actually use (scanned data volume/CUH packages). When no jobs are running, you pay nothing. -
HA Dual-AZ Deployment
Free yourself from the hassle of complicated O&M and upgrade operations while you enjoy high data availability with dual-AZ deployment.
Functions
Functions
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Full SQL Compatibility
You don't need to have a background in big data to do big data analysis. If you know SQL, you are good to go. The SQL syntax is fully compatible with the standard ANSI SQL 2003.You don't need to a background in big data to do big data analysis. If you know SQL, you are good to go. The SQL syntax is fully compatible with the standard ANSI SQL 2003. -
Serverless Spark/Flink/openLooKeng
Seamlessly migrate your offline applications to the cloud with serverless technology. DLI is fully compatible with Apache Spark, Apache Flink, and Presto ecosystems and APIs.Seamlessly migrate your offline applications to the cloud with serverless technology. DLI is fully compatible with Apache Spark, Apache Flink, and Presto ecosystems and APIs.
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Cross-source Analysis
Analyze your data across databases. No migration required. A unified view of your data gives you a comprehensive understanding of your data and helps you innovate faster. There are no restrictions on data formats, cloud data sources, or whether the database is created online or off.Analyze your data across databases. No migration required. A unified view of your data gives you a comprehensive understanding of your data and helps you innovate faster. There are no restrictions on data formats, cloud data sources, or whether the database is created online or off. -
Enterprise Multi-tenant
Manage compute or resource related permissions by project or by user. Enjoy fine-grained control that makes it easy to maintain data independence for separate tasks.Manage compute or resource related permissions by project or by user. Enjoy fine-grained control that makes it easy to maintain data independence for separate tasks.
Application Scenarios
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Database Analysis
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E-commerce
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Gaming
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Large Enterprises
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Genetics
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Finance
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Government
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Geography
Database Analysis
Application data (such as registration details) is stored in a relational database and needs analysis.
Pain points
•Complicated queries are not supported for larger relational databases.
•Comprehensive analysis is not possible because database and table partitions are spread in multiple relational databases.
•Business data analysis might overload available resources and impact business operations.
Advantages
Hit the ground running with new services. DLI supports standard ANSI SQL 2003 relational database syntax so there is almost no learning curve.
Use DLI, powered by distributed in-memory computing models, to easily process massive data.
Precision Marketing
Information from multiple channels needs to be combined for associative analysis to improve the conversion rate.
Advantages
When advertisement CTR data is stored in OBS and user registration data in RDS, you can query and analyze it directly. There is no need to migrate it to DLI.
With multiple data sources interconnected, you can map them together by creating a table using just SQL statements.
Related Services
Log Analysis
Running a gaming company calls for a quality data analysis platform to improve ad placements, improve new player retention, improve operations, and get better feedback for future game iterations.
PainPoints
•Log analysis is usually performed by period. During the idle periods between each task, resources are wasted.
Advantages
Reduce costs by more than 50% compared with purchasing exclusive clusters. We only bill you for the resources actually used for scheduling.
You only need a single copy of metadata for real-time cleaning, offline ETL processing, and interactive analysis. You can directly use the data processing result for data mining.
Related Services
Log Analysis
If you run a large enterprise, different departments in the company may need to manage resources independently. You need fine-grained permissions management for data security and improved management efficiency.
Advantages
Grant permissions by column or by specific operations, such as insert and overwrite; and control read and write permissions for the metadata.
Use a single IAM account to manage the multiple employees in your company.
Gene Data Management
Third-party analysis libraries based on the Spark distributed framework, such as ADAM and Hail, are necessary for genome analysis.
Pain Points
•High technical skills are required to install analysis libraries such as ADAM and Hail.
•Every time you create a cluster, you have to install these analysis libraries again.
Advantages
You can package third-party analysis libraries, like ADAM and Hail, into custom images and upload them directly to the Software Repository for Container (SWR). When using DLI, custom images in SWR are automatically pulled.
Huawei enhanced Spark and Flink images in multiple versions and open-source AI images (Tensorflow/Keras/PyTorch) are built in to DLI for your convenience.
Related Services
Real-time Risk Control
Almost every aspect of financial services involves some sort of risk control. A comprehensive system is required.
Pain Points
•There is very little tolerance for excessive latency when it comes to risk control.
Advantages
You can perform real-time data analysis in DLI with the help of an Apache Flink dataflow model. A single CPU can process 1,000 to 20,000 messages per second.
You can save real-time data streams to multiple cloud services such as CloudTable and SMN.
Related Services
Real-time Large Screen
With epidemics like COVID-19 raging across the globe, governments need to be able to monitor key data in real-time on a large screen display, so they can scientifically manage epidemic control.
Pain Points
•Government employees do not necessarily have a background in big data. SQL is usually far more familiar.
Advantages
Based on the powerful in-memory computing framework, the built-in openLooKeng engine optimizes query performance to achieve interactive analysis in milliseconds.
You only need SQL syntax for DLI queries. The syntax is fully compatible with standard ANSI SQL 2003.
Geographic Big Data Analysis
Geographic big data can involve massive volumes of data, for example petabytes of satellite imaging data. It also includes many different types of data. There is, for example, structured remote sensing image raster data, vector data, unstructured spatial location data, and 3D modeling data. An efficient mining tool is a must for geographic data analysis.
Advantages
Spark spatial data analysis algorithm operators in DLI enable real-time stream processing and offline batch processing. You can import massive data types, including structured remote sensing image data, unstructured 3D modeling, and laser point cloud data in DLI.
SQL statements are all that is needed for yaw detection and geo-fencing.
You can quickly migrate terabytes,or even exabytes, of remote sensing images to the cloud and slice the images to data sources for distributed batch processing.
Comparison Between DLI and Self-built Hadoop
Cost
Billing is based on the actual amount of data scanned or used CUH. Up to 50% costs saved.
High cost due to long-term resource occupation; wastage of resources
Elastic scalability
Container-based Kubernetes, intelligent elastic scaling
N/A
O&M availability
Strong technical capabilities are required for configuration and O&M
Learning cost
Low.
The optimization parameters are standardized based on 10 years' experience in thousands of projects. In addition, DLI provides a GUI for intelligent optimization.
High.
Hundreds of tuning parameters need to be learned.
Supported data sources
Cloud: OBS/RDS/DWS/CSS/MongoDB/Redis;
On-premises: self-built database/MongoDB/Redis
Cloud: OBS;
On-premises: HDFS
