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https://issues.apache.org/jira/browse/SPARK-24768?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Gengliang Wang updated SPARK-24768:
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Description: Apache Avro (https://avro.apache.org) is a popular data
serialization format. It is widely used in the Spark and Hadoop ecosystem,
especially for Kafka-based data pipelines. Using the external package
[https://github.com/databricks/spark-avro], Spark SQL can read and write the
avro data. Making spark-Avro built-in can provide a better experience for
first-time users of Spark SQL and structured streaming. We expect the built-in
Avro data source can further improve the adoption of structured streaming. The
proposal is to inline code from spark-avro package
([https://github.com/databricks/spark-avro]). The target release is Spark 2.4.
(was: Apache Avro (https://avro.apache.org) is a popular data serialization
format. It is widely used in the Spark and Hadoop ecosystem, especially for
Kafka-based data pipelines. Using the external package, Spark SQL can read and
write the avro data. Making spark-Avro built-in can provide a better experience
for first-time users of Spark SQL and structured streaming. We expect the
built-in Avro data source can further improve the adoption of structured
streaming. The proposal is to inline code from spark-avro package (https://
github.com/databricks/spark-avro). The target release is Spark 2.4.
)
> Have a built-in AVRO data source implementation
> -----------------------------------------------
>
> Key: SPARK-24768
> URL: https://issues.apache.org/jira/browse/SPARK-24768
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 2.4.0
> Reporter: Gengliang Wang
> Priority: Major
>
> Apache Avro (https://avro.apache.org) is a popular data serialization format.
> It is widely used in the Spark and Hadoop ecosystem, especially for
> Kafka-based data pipelines. Using the external package
> [https://github.com/databricks/spark-avro], Spark SQL can read and write the
> avro data. Making spark-Avro built-in can provide a better experience for
> first-time users of Spark SQL and structured streaming. We expect the
> built-in Avro data source can further improve the adoption of structured
> streaming. The proposal is to inline code from spark-avro package
> ([https://github.com/databricks/spark-avro]). The target release is Spark
> 2.4.
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