Let's say you are looking to explore the relationship between extreme weather and people's conversations about it on Twitter, you can gather and analyze weather and Twitter event data streams.
You will need the following (both in JSON format):
- a Weather API to obtain real-time & forecasted weather data,
- a Twitter API to also get real-time tweets & mentions.
The National Weather Service API can be accessed here
The Twitter API can be accessed here
Create a weather topic and Twitter topic in a Kafka cluster with some partitions and replications.
Create a weather producer and Twitter producer to publish the JSON data to the two topics, respectively.
Create a weather consumer and Twitter consumer to read the events from the two topics, and the bytes stored in the Kafka topics into event JSON data.
Use a DB writer to parse the JSON files and create database records, which can be written into the database with SQL insert statements.
Finally, you can query and visualize the database records in a dashboard to complete the end-to-end pipeline.
Additional infos:
What is a Kafka DB Writer:
A Kafka DB writer is a type of software that enables a user to write data from a database into a Kafka topic. It can be used for data integration, stream processing, or data ingestion. Kafka DB writers are often used for large-scale distributed systems, such as streaming analytics and real-time decision making.
KAFKA TOOL - ksqlDB:
KSQLDB is an open-source, cloud-native streaming SQL database built on Apache Kafka. It enables you to easily develop streaming applications that process data in real-time and respond to events as they occur. KSQLDB supports a wide range of operations including stream processing, time-based event-driven processing, windowed operations, joins, and more. It also provides a high-performance SQL query engine for accessing and analyzing data from Apache Kafka and other sources. With KSQLDB, developers can quickly build and deploy powerful streaming applications with a few lines of code.
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