This project contains some basic runnable tools that can help with various tasks around an Apache Spark based project.
Spark Tools alternatives and similar packages
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This project contains some basic runnable tools that can help with various tasks around a Spark based project.
The main tools available:
- [FormatConverter](docs/format-converter.md) Converts any acceptable file format into a different file format, providing also partitioning support.
- [SimpleSqlProcessor](docs/sql-processor.md) Applies a given SQL to the input files which are being mapped into tables.
- [StreamingFormatConverter](docs/streaming-format-converter.md) Converts any acceptable data stream format into a different data stream format, providing also partitioning support.
- [SimpleFileStreamingSqlProcessor](docs/file-streaming-sql-processor.md) Applies a given SQL to the input files streams which are being mapped into file output streams.
This project is also trying to create and encourage a friendly yet professional environment for developers to help each other, so please do no be shy and join through gitter, twitter, issue reports or pull requests.
- Java 8 or higher
- Scala 2.11 or 2.12
- Apache Spark 2.4.X
Getting Spark Tools
where the latest artifacts can be found.
- Group id / organization:
- Artifact id / name:
- Latest version is
Usage with SBT, adding a dependency to the latest version of tools to your sbt build definition file:
libraryDependencies += "org.tupol" %% "spark-tools" % "0.4.1"
Include this package in your Spark Applications using
with Scala 2.11
$SPARK_HOME/bin/spark-shell --packages org.tupol:spark-tools_2.11:0.4.1
or with Scala 2.12
$SPARK_HOME/bin/spark-shell --packages org.tupol:spark-tools_2.12:0.4.1
- The project compiles with both Scala
- Updated Apache Spark to
- Updated the
- Removed the
com.databricks:spark-avrodependency, as avro support is now built into Apache Spark
- Updated the
spark-utilsdependency to the latest available snapshot
For previous versions please consult the [release notes](RELEASE-NOTES.md).
This code is open source software licensed under the [MIT License](LICENSE).
*Note that all licence references and agreements mentioned in the Spark Tools README section above are relevant to that project's source code only.