[ https://issues.apache.org/jira/browse/SPARK-25937?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-25937: ---------------------------------- Affects Version/s: (was: 2.4.0) 3.0.0 > Support user-defined schema in Kafka Source & Sink > -------------------------------------------------- > > Key: SPARK-25937 > URL: https://issues.apache.org/jira/browse/SPARK-25937 > Project: Spark > Issue Type: Improvement > Components: Structured Streaming > Affects Versions: 3.0.0 > Reporter: Jackey Lee > Priority: Major > > Kafka Source & Sink is widely used in Spark and has the highest frequency > in streaming production environment. But at present, both Kafka Source and > Link use the fixed schema, which force user to do data conversion when > reading and writing Kafka. So why not we use fileformat to do this just like > hive? > Flink has implemented Kafka's Json/Csv/Avro extended Source & Sink, we > can also support it in Spark. > *Main Goals:* > 1. Provide a Source and Sink that support user defined Schema. Users can read > and write Kafka directly in the program without additional data conversion. > 2. Provides read-write mechanism based on FileFormat. User's data conversion > is similar to FileFormat's read and write process, we can provide a mechanism > similar to FileFormat, which provide common read-write format conversion. It > also allow users to customize format conversion. -- This message was sent by Atlassian JIRA (v7.6.14#76016) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org