Learn how to use MaxCompute to query and process data across data lakes with DLF, OSS, Paimon, Hive, and Hologres.
Tutorials
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Tutorial |
Description |
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Data transformation and multi-scenario orchestration on a data lake using MaxCompute |
Ingest IoV data into a data lake and warehouse with MaxLake. Analyze vehicle GPS mileage and speed, then orchestrate multiple engines for real-time reports, cross-team collaboration, desensitized sharing, and AI training — deriving multiple values from a single dataset. |
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Extract metadata from OSS with DLF, then run federated queries through a MaxCompute external schema. |
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Create a Paimon DLF catalog with Flink, read MySQL CDC data into OSS, sync metadata to DLF, and query the data lake through a MaxCompute external schema. |
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Use a schemaless query in MaxCompute to read Parquet files from an E-MapReduce serverless Spark cluster. Write results back to OSS with the UNLOAD command. |
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Create an external schema in MaxCompute to query Hive table data on E-MapReduce. |
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Create metadata mapping and data synchronization for Hologres |
Create metadata mapping and synchronize data between MaxCompute and Hologres. |
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Read and write Paimon data on a data lake using an external project and a FileSystem Catalog |
Create a Paimon catalog with Flink and generate data, then use a MaxCompute external project with a FileSystem Catalog to read Paimon table data. |
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Create a Paimon DLF catalog with Flink, read MySQL CDC data into DLF, and run federated queries through a MaxCompute external project. Results are written back to DLF. This tutorial uses the new version of DLF, not DLF 1.0. |