spark-instrumented-optimizer/external/avro/pom.xml
Gengliang Wang 395860a986 [SPARK-24768][SQL] Have a built-in AVRO data source implementation
## What changes were proposed in this pull request?

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.

[Built-in AVRO Data Source In Spark 2.4.pdf](https://github.com/apache/spark/files/2181511/Built-in.AVRO.Data.Source.In.Spark.2.4.pdf)

## How was this patch tested?

Unit test

Author: Gengliang Wang <gengliang.wang@databricks.com>

Closes #21742 from gengliangwang/export_avro.
2018-07-12 13:55:25 -07:00

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XML

<?xml version="1.0" encoding="UTF-8"?>
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~ distributed under the License is distributed on an "AS IS" BASIS,
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-parent_2.11</artifactId>
<version>2.4.0-SNAPSHOT</version>
<relativePath>../../pom.xml</relativePath>
</parent>
<artifactId>spark-sql-avro_2.11</artifactId>
<properties>
<sbt.project.name>avro</sbt.project.name>
</properties>
<packaging>jar</packaging>
<name>Spark Avro</name>
<url>http://spark.apache.org/</url>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-catalyst_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-tags_${scala.binary.version}</artifactId>
</dependency>
</dependencies>
<build>
<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
</build>
</project>