A library built in Scala 2.12 that utilizes Apache POI to parse Excel Workbooks based on a flexible JSON configuration. It seamlessly integrates with Apache Spark, allowing you to load Excel data into Spark DataFrames for further processing.
- JSON-Based Configuration: Easily define how to extract data from Excel sheets, including ranges, columns, and virtual columns using a simple JSON config.
- Virtual Columns: Add computed or derived columns that don't exist in the original Excel sheet.
- Download the
xlparsec-${VERSION}.jar. - Place the JAR file in your
${SPARK_HOME}/jars/directory.
import de.fxttr.scala.xlparsec.Xlparsec
import org.apache.spark.sql.SparkSession
implicit val spark: SparkSession = SparkSession.builder()
.appName("ExcelParserExample")
.master("local[*]")
.getOrCreate()
val configJson = """{...}"""
val result = Xlparsec.toDFs(configJson)
result match {
case Right(dataFrames) =>
dataFrames.foreach { case (sheetName, scopes) =>
scopes.foreach { case (scopeName, dfEither) =>
dfEither match {
case Right(df) => df.show()
case Left(error) => println(s"Error parsing scope $scopeName: $error")
}
}
}
case Left(error) => println(s"Error parsing file: $error")
}For more examples, refer to the /examples directory.
Comprehensive documentation can be found in the /docs directory, including detailed configuration instructions, supported JSON schema, and advanced usage scenarios.
Feel free to open issues or submit pull requests for improvements or bug fixes. Contributions are always welcome!
This project is licensed under the Apache-2.0 License.