timeplus-sql-guide

Name: timeplus-sql-guide
Availability: InStock
Author: Timeplus

Author and execute real-time streaming SQL against Timeplus Proton via the ClickHouse-compatible HTTP API.

1|Updated Mar 4, 2026

Search Tags:#real-time #streaming #sql #ingestion #materialized-views #udf #timeplus

Ready to run

npx skills add https://github.com/timeplus-io/AgentSkills --skill timeplus-sql-guide

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: timeplus-sql-guide
Source: https://github.com/timeplus-io/AgentSkills/tree/main/timeplus-sql-guide
Command: npx skills add https://github.com/timeplus-io/AgentSkills --skill timeplus-sql-guide

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Timeplus SQL Guide helps data teams author and run real-time streaming SQL against Timeplus Proton via a ClickHouse-compatible HTTP API, enabling end-to-end streaming analytics workflows.

Core Features & Use Cases

Write and execute Timeplus streaming SQL including DDL/DML, window functions, joins, and UDFs.
Build pipelines with streams, materialized views, ingestion, and sinks; simulate data with random streams for testing.
Real-world use cases include real-time dashboards, alerting, data enrichment, and streaming ETL.

Quick Start

Install the skill, configure TIMEPLUS_HOST, TIMEPLUS_USER, TIMEPLUS_PASSWORD, and run a sample streaming SQL against your Timeplus server to validate the setup.

Frequently Asked Questions about timeplus-sql-guide

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I execute real-time streaming SQL queries against Timeplus Proton?▼

To execute real-time streaming SQL against Timeplus Proton, configure curl with TIMEPLUS_HOST, TIMEPLUS_USER, and TIMEPLUS_PASSWORD environment variables, then send queries via the ClickHouse-compatible HTTP API on port 8123.

What's the best way to build streaming ETL pipelines with materialized views in Timeplus?▼

Build streaming ETL pipelines by creating streams, defining materialized views to continuously transform data, and configuring ingestion and sinks to route results, using random streams to simulate data for testing before deploying.

Can I use Python or JavaScript UDFs in Timeplus streaming SQL?▼

Yes, Timeplus streaming SQL supports Python and JavaScript UDFs to apply custom logic within your streaming queries, enabling advanced data enrichment and transformations directly in the pipeline.

How do I ingest streaming data into Timeplus Proton?▼

Ingest streaming data into Timeplus Proton by sending it to port 3218 for streaming ingest, ensuring your environment has curl installed and the required host and password variables configured.

Does Timeplus streaming SQL support window functions and joins for real-time analytics?▼

Yes, Timeplus streaming SQL supports window functions and joins to aggregate and enrich real-time data, enabling use cases like live dashboards, alerting, and continuous data transformation workflows.

Do I need curl to use Timeplus SQL for streaming queries?▼

Yes, curl is required to interact with the Timeplus Proton HTTP API, serving as the client to execute DDL, DML, and streaming SQL queries once your environment variables are set.