📄️ Real-time Insights for GitHub
In this tutorial, you will process real-time data from GitHub. We have setup a public accessible Kafka cluster for you to consume data from Kafka topic. If you are on Timeplus Cloud, you can also build real-time dashboards and alerts.
📄️ Connect to Kafka, Confluent, Redpanda, Aiven, WarpStream, Upstash, etc.
Connect to local Kafka or Redpanda
📄️ Query Kafka with SQL
This tutorial is mainly for Timeplus Proton users. For Timeplus Cloud users, please check the guide for connecting Timeplus with Confluent Cloud with web UI. SQL in this guide can be ran both in Timeplus Proton and Timeplus Cloud/Enterprise.
📄️ Streaming JOIN
1. This tutorial is mainly for Timeplus Proton users. For Timeplus Cloud users, please check the guide for connecting Timeplus with Confluent Cloud with web UI. SQL in this guide can be ran both in Timeplus Proton and Timeplus Cloud/Enterprise.
📄️ Streaming ETL: Kafka to Kafka
You can quickly build streaming ETL pipelines with Timeplus. For example, the original web access logs in Kafka topics contain the raw IP address. To further protect user privacy, you can build a data pipeline to read new data from Kafka, masking the IP address and send to a different Kafka topic.
📄️ Streaming ETL: Kafka to ClickHouse
This video demonstrates how to read live data from Redpanda, apply stream processing and send results to ClickHouse. Related blog.
📄️ Streaming ETL: MySQL to ClickHouse
A Docker Compose stack is provided at https://github.com/timeplus-io/proton/tree/develop/examples/cdc, to demonstrate how to mirror the data from MySQL to ClickHouse. The common use case is to keep MySQL as the transactional database, while using ClickHouse for the analytics workload.
📄️ Read Avro Message in Kafka
Example: Read Avro Encoded Data in Confluent Cloud
📄️ Connect to local ClickHouse, ClickHouse Cloud, Aiven, etc.
You can define the external table and use it to read data from the ClickHouse table, or write to it.
📄️ Use Primary Key For Update and Delete
By default, streams in Timeplus are in append-only mode. When you create a stream with the mode versioned_kv, you can update the data with same primary key(s). When you query the stream with table function, only the latest version for the same primary key(s) will be shown. 当您在与其他流的 JOIN 中将这个流用作 “右表” 时，Timeplus 会自动选择最接近的版本。
📄️ Top-N
您可以根据条件在 Timeplus 流或视图中获得最顶部或最底部的事件。
📄️ More Query Examples
This document demonstrates some typical query patterns that you can achieve in Timeplus to solve various use cases.