bio.ferlab.datalake.spark3.publictables.normalized.TopMed.scala Maven / Gradle / Ivy
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Library built on top of Apache Spark to speed-up data lakes development..
package bio.ferlab.datalake.spark3.publictables.normalized
import bio.ferlab.datalake.commons.config.{DatasetConf, RepartitionByColumns, RuntimeETLContext}
import bio.ferlab.datalake.spark3.etl.v4.SimpleETLP
import bio.ferlab.datalake.spark3.implicits.DatasetConfImplicits._
import bio.ferlab.datalake.spark3.implicits.GenomicImplicits.columns._
import mainargs.{ParserForMethods, main}
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.functions._
import java.time.LocalDateTime
case class TopMed(rc: RuntimeETLContext) extends SimpleETLP(rc) {
private val raw_topmed = conf.getDataset("raw_topmed_bravo")
override val mainDestination: DatasetConf = conf.getDataset("normalized_topmed_bravo")
override def extract(lastRunValue: LocalDateTime = minValue,
currentRunValue: LocalDateTime = LocalDateTime.now()): Map[String, DataFrame] = {
Map(raw_topmed.id -> raw_topmed.read)
}
override def transformSingle(data: Map[String, DataFrame],
lastRunValue: LocalDateTime = minValue,
currentRunValue: LocalDateTime = LocalDateTime.now()): DataFrame = {
import spark.implicits._
data(raw_topmed.id)
.select(
chromosome,
start,
end,
name,
reference,
alternate,
ac,
af,
an,
$"INFO_HOM"(0) as "homozygotes",
$"INFO_HET"(0) as "heterozygotes",
$"qual",
when(size($"filters") === 1 && $"filters"(0) === "PASS", "PASS")
.when(array_contains($"filters", "PASS"), "PASS+FAIL")
.otherwise("FAIL") as "qual_filter"
)
}
override val defaultRepartition: DataFrame => DataFrame = RepartitionByColumns(columnNames = Seq("chromosome"), sortColumns = Seq("start"))
}
object TopMed {
@main
def run(rc: RuntimeETLContext): Unit = {
TopMed(rc).run()
}
def main(args: Array[String]): Unit = ParserForMethods(this).runOrThrow(args)
}