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Updated on 2024-05-29 GMT+08:00

Using the HetuEngine Cross-Source Function

Using the HetuEngine Cross-Source Function

Enterprises usually store massive data, such as from various databases and warehouses, for management and information collection. However, diversified data sources, hybrid dataset structures, and scattered data storage rise the development cost for cross-source query and prolong the cross-source query duration.

HetuEngine provides unified standard SQL statements to implement cross-source collaborative analysis, simplifying cross-source analysis operations.
Figure 1 HetuEngine cross-source function

Key Technologies and Advantages

  • Compute pushdown: When HetuEngine is used for cross-source collaborative analysis, HetuEngine enhances the compute pushdown capability from the dimensions listed in the following table to improve access efficiency.
    • Basic pushdown: predicate, projection, subquery, and limit
    • Aggregate pushdown: GROUP BY, ORDER BY, COUNT, SUM, MIN, and MAX
    • Operator pushdown: <, >, LIKE, and OR.
  • Multi-source heterogeneous data: Collaborative analysis supports both structured data sources such as Hive, GaussDB, and ClickHouse, and unstructured data sources such as HBase and Elasticsearch.
  • Global metadata: A mapping table is provided to map unstructured schemas to structured schemas, enabling HetuEngine to access HBase using SQL statements. Global management for data source information is provided.
  • Global permission control: Data source permissions can be opened to Ranger through HetuEngine for centralized management and control.

Usage Guide of Cross-Source Function

HetuEngine supports quick joint query of multiple data sources and GUI-based data source configuration and management. You can quickly add the following data sources on the HSConsole page by referring to Before You Start:

Process of Using Cross-Source Collaborative Analysis

  1. Log in to the HetuEngine client by referring to Using the HetuEngine Client.
  2. Register data sources such as Hive, HBase, and GaussDB A.
    hetuengine> show catalogs;
      Catalog  
    ----------  
    dws                
    hive         
    hive_dg
    hbase
    system       
    systemremote 
    (6 rows)
  3. Compile SQL statements for cross-source collaborative analysis.
    select * from hive_dg.schema1.table1 t1 join hbase.schema3.table3 t2 join dws.schema02.table4 t3 on t1.name = t2.item and t2.id = t3.cardNo;