spark sql join 1个driver很慢，其他很快，怀疑数据倾斜，帮解决可有偿私

问题：用spark sql 表join自身，执行过程就1个driver很慢，其他很快

代码：

      spark.sql("select /*+ MERGEJOIN(t2) */ t1.bsm,t2.bsm " +
        " from temp t1" +
        " join temp t2 on t1.index != t2.index and st_overlaps(t1.geometry,t2.geometry)").show()

结果：

import org.apache.spark.sql.SparkSession
import org.gdal.ogr.Geometry
import org.locationtech.geomesa.spark.GeoMesaSparkKryoRegistrator
import org.locationtech.geomesa.spark.jts._
import org.locationtech.jts.geom.MultiPolygon

object SparkSqlJoinTest {

  def main(args: Array[String]):Unit = {
    val spark: SparkSession = SparkSession.builder()
      .appName("testSpark")
      .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
      .config("spark.kryo.registrator", classOf[GeoMesaSparkKryoRegistrator].getName)
      .master("local[*]")
//      .config("spark.sql.adaptive.enabled",true)
//      .config("spark.sql.adaptive.coalescePartitions.enabled",true)
//      .config("spark.sql.adaptive.coalescePartitions.minPartitionNum",1)
//      .config("spark.sql.adaptive.skewJoin.enabled",true)
//      .config("spark.sql.adaptive.skewJoin.skewedPartitionFactor",5)
      .config("spark.sql.crossJoin.enabled",true)
      .getOrCreate()
      .withJTS

    val geonamesParams = Map(
      "hbase.zookeepers" -> "master",
      "hbase.catalog"  -> "test"
    )

    val geonamesDF = spark.read
      .format("geomesa")
      .options(geonamesParams)
      .option("geomesa.feature", "test2000")
      .load()

    geonamesDF.where("layername='test2000'").createOrReplaceTempView("temp")

    try{

      spark.sql("select /*+ skewjoin(t2) */ t1.bsm,t2.bsm from temp t1 join temp t2 ").rdd.saveAsTextFile("D:/test")

//      spark.sql("select /*+ skewjoin(t2) */ t1.bsm,t2.bsm " +
//        " from temp t1" +
//        " join temp t2 on t1.index != t2.index and st_overlaps(t1.geometry,t2.geometry)").show()
}finally {
  print("a")

}
  }



}

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