Hi dev: Currently CarbonData 1.3(will be released soon) just support to integrate with Spark Structured Streaming which requires Kafka's version must be >= 0.10. I think there are still many users integrating Spark Streaming with kafka 0.8, at least our cluster is, but the cost of upgrading kafka is too much. So should CarbonData need to integrate with Spark Streaming too? I think there are two ways to integrate with Spark Streaming, as following: 1). CarbonData batch data loading + Auto compaction Use CarbonSession.createDataFrame to convert rdd to DataFrame in InputDStream.foreachRDD, and then save rdd data into CarbonData table which support auto compaction. In this way, it can support to create pre-aggregate tables on this main table too (Streaming table does not support to create pre-aggregate tables on it). I can test with this way in our QA env and add example to CarbonData. 2). The same as integration with Structured Streaming With this way, Structured Streaming append every mini-batch data into stream segment which is row format, and then when the size of stream segment is greater than 'carbon.streaming.segment.max.size', it will auto convert stream segment to batch segment(column format) at the begin of each batch and create a new stream segment to append data. However, I have no idea how to integrate with Spark Streaming yet, *any suggestion for this*?
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