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In the use case of using Kafka for data lake ingestion, if we can produce the segment with Parquet, which is the native format in a data lake, the consumer application (e.g., Spark jobs for ingestion) can directly dump the segments as raw byte buffer into the data lake without unwrapping each record individually and then writing to the Parquet file one by one with expensive steps of encoding and compression again. This would provide additional savings for both data freshness of ingestion and resource consumption, as the ingestion job would be lighter weight and finishes significantly faster.

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