Lire Excel Spark
import org.apache.spark.sql._
val spark: SparkSession = ???
val df = spark.read
.format("com.crealytics.spark.excel")
.option("sheetName", "Daily") // Required
.option("useHeader", "true") // Required
.option("treatEmptyValuesAsNulls", "false") // Optional, default: true
.option("inferSchema", "false") // Optional, default: false
.option("addColorColumns", "true") // Optional, default: false
.option("startColumn", 0) // Optional, default: 0
.option("endColumn", 99) // Optional, default: Int.MaxValue
.option("timestampFormat", "MM-dd-yyyy HH:mm:ss") // Optional, default: yyyy-mm-dd hh:mm:ss[.fffffffff]
.option("maxRowsInMemory", 20) // Optional, default None. If set, uses a streaming reader which can help with big files
.option("excerptSize", 10) // Optional, default: 10. If set and if schema inferred, number of rows to infer schema from
.schema(myCustomSchema) // Optional, default: Either inferred schema, or all columns are Strings
.load("Worktime.xlsx")
Sore Stork
