395860a986
## 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. |
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create-release | ||
deps | ||
sparktestsupport | ||
tests | ||
.gitignore | ||
.rat-excludes | ||
appveyor-guide.md | ||
appveyor-install-dependencies.ps1 | ||
change-scala-version.sh | ||
check-license | ||
checkstyle-suppressions.xml | ||
checkstyle.xml | ||
github_jira_sync.py | ||
lint-java | ||
lint-python | ||
lint-r | ||
lint-r.R | ||
lint-scala | ||
make-distribution.sh | ||
merge_spark_pr.py | ||
mima | ||
pip-sanity-check.py | ||
README.md | ||
requirements.txt | ||
run-pip-tests | ||
run-tests | ||
run-tests-jenkins | ||
run-tests-jenkins.py | ||
run-tests.py | ||
sbt-checkstyle | ||
scalastyle | ||
test-dependencies.sh | ||
tox.ini |
Spark Developer Scripts
This directory contains scripts useful to developers when packaging, testing, or committing to Spark.
Many of these scripts require Apache credentials to work correctly.