clickzetta-sql-pipeline-manager

You build SQL data pipelines in ClickZetta Lakehouse using Dynamic Tables, Table Streams, and Pipes to manage end-to-end data ingestion. This automates creation, scheduling, and status monitoring for real-time data flows.

In lakehouse pipeline management, a Dynamic Table enables automated scheduled refreshes for near real-time data updates, while a Materialized View caches query results. This Skill orchestrates the lifecycle and scheduling of both pipeline objects.

Yes, you can manage Kafka CDC ingestion pipelines using SQL in ClickZetta. This Skill handles Kafka and object-store ingestion scenarios, enabling you to create, suspend, resume, and diagnose continuous data pipeline states.

You create a Dynamic Table by defining the source table and setting a 1-minute refresh interval in your SQL script. This Skill automates the creation and scheduling configuration for target tables like dw.demo_orders sourced from ods.orders.

Yes, ClickZetta supports multi-layer ETL pipelines. This Skill provides scaffolding to design transformations across ODS, DWD, DWS, or Bronze, Silver, and Gold layers using Dynamic Tables and Table Streams for structured data flows.

If your SQL data pipeline stops processing records, use this Skill to query the pipeline status and diagnose real-time ingestion issues. It supports lifecycle orchestration, allowing you to suspend and resume Pipes or Dynamic Tables to troubleshoot.