Spark Structured Streaming with Kafka: Understanding the startingOffset=“earliest” Issue
Spark Structured Streaming is a powerful tool for processing large volumes of data in real-time. However, many data scientists have encountered an issue where the startingOffset="earliest" setting is not honored when using Kafka as a source. This blog post will delve into this issue, providing a comprehensive understanding and potential solutions.
Understanding the Issue When using Spark Structured Streaming with Kafka, the startingOffset option allows you to specify where Spark should start reading data. The two options are "latest", which reads only new data, and "earliest", which reads from the beginning of the topic. However, some users have reported that Spark does not always honor the "earliest" setting. Instead of starting from the beginning, Spark starts reading from the latest offset, leading to data loss.
Read more : https://saturncloud.io/blog/spark-structured-streaming-with-kafka-understanding-the-startingoffsetearliest-issue/
Credit: https://saturncloud.io/blog/spark-structured-streaming-with-kafka-understanding-the-startingoffsetearliest-issue/
Understanding the Issue When using Spark Structured Streaming with Kafka, the startingOffset option allows you to specify where Spark should start reading data. The two options are "latest", which reads only new data, and "earliest", which reads from the beginning of the topic. However, some users have reported that Spark does not always honor the "earliest" setting. Instead of starting from the beginning, Spark starts reading from the latest offset, leading to data loss.
Read more : https://saturncloud.io/blog/spark-structured-streaming-with-kafka-understanding-the-startingoffsetearliest-issue/
Credit: https://saturncloud.io/blog/spark-structured-streaming-with-kafka-understanding-the-startingoffsetearliest-issue/
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