spark Sql

package org.apache.spark.sql

import org.apache.spark.{SparkConf, SparkContext}

object SLA_parquetSQL {

  def main(args: Array[String]) {
    val sc = new SparkContext(new SparkConf().setAppName("SLA Filter"))
    val sqlContext = new SQLContext(sc)
    val suffix = args(0)
    sqlContext.parquetFile("/user/hive/warehouse/sla_parquet.db/e60001_shipment_exported_" + suffix).registerTempTable("e60001_shipment_exported")
    sqlContext.parquetFile("/user/hive/warehouse/sla_parquet.db/e62005_shipment_shipped_and_closed_" + suffix).registerTempTable("e62005_shipment_shipped_and_closed")
    sqlContext.parquetFile("/user/hive/warehouse/sla_parquet.db/e62006_shipment_canceled_and_closed_" + suffix).registerTempTable("e62006_shipment_canceled_and_closed")

    val e60001_shipment_exported = sqlContext.sql("select ordernumber, type_id, event_time from e60001_shipment_exported").map(line => (line(0), (line(1).toString, line(2).toString.substring(0, 19))))
    val e62005_shipment_shipped_and_closed = sqlContext.sql("select ordernumber, type_id, event_time from e62005_shipment_shipped_and_closed").map(line => (line(0), (line(1).toString, line(2).toString.substring(0, 19))))
    val e62006_shipment_canceled_and_closed = sqlContext.sql("select ordernumber, type_id, event_time from e62006_shipment_canceled_and_closed").map(line => (line(0), (line(1).toString, line(2).toString.substring(0, 19))))

    val un = e60001_shipment_exported.union(e62005_shipment_shipped_and_closed).union(e62006_shipment_canceled_and_closed)

    un.groupByKey.filter(kv => FilterSLA.filterSLA(kv._2.toSeq)).map(kv => kv._1 + "\t" + Utils.flatValues(kv._2.toSeq)).saveAsTextFile(args(1))
  }
}