Sql server 计算分区火花JDBC的上下限

我使用Spark jdbc和Scala从MS SQL server读取数据，并希望按指定列对这些数据进行分区。我不想手动设置分区列的上下限。我可以读取此字段中的某种最大值和最小值，并将其设置为上限/下限吗？ 另外，使用这个查询，我想从数据库中读取所有数据。 目前，查询机制如下所示：

def jdbcOptions() = Map[String,String](
    "driver" -> "db.driver",
    "url" -> "db.url",
    "user" -> "db.user",
    "password" -> "db.password",
    "customSchema" -> "db.custom_schema",
    "dbtable" -> "(select * from TestAllData where dayColumn > 'dayValue') as subq",
    "partitionColumn" -> "db.partitionColumn",
    "lowerBound" -> "1",
    "upperBound" -> "30",
    "numPartitions" -> "5"
}

    val dataDF = sparkSession
      .read
      .format("jdbc")
      .options(jdbcOptions())
      .load()

---

如果

dayColumn

是数字或日期字段，则可以使用下一个代码检索边界：

def jdbcBoundOptions() = Map[String,String]{
    "driver" -> "db.driver",
    "url" -> "db.url",
    "user" -> "db.user",
    "password" -> "db.password",
    "customSchema" -> "db.custom_schema",
    "dbtable" -> "(select max(db.partitionColumn), min(db.partitionColumn) from TestAllData where dayColumn > 'dayValue') as subq",
    "numPartitions" -> "1"
}

val boundRow = sparkSession
    .read
    .format("jdbc")
    .options(jdbcBoundOptions())
    .load()
    .first()

val maxDay = boundRow.getInt(0)
val mimDay = boundRow.getInt(1)

请注意，

numPartitions

必须为1，在这种情况下，我们不需要像Spark中所描述的那样指定分区细节

最后，您可以将检索到的边界用于原始查询：

def jdbcOptions() = Map[String,String]{
    "driver" -> "db.driver",
    "url" -> "db.url",
    "user" -> "db.user",
    "password" -> "db.password",
    "customSchema" -> "db.custom_schema",
    "dbtable" -> "(select * from TestAllData where dayColumn > 'dayValue') as subq",
    "partitionColumn" -> "db.partitionColumn",
    "lowerBound" -> minDay.toString,
    "upperBound" -> maxDay.toString,
    "numPartitions" -> "5"
}

---

Hi@Cassie是db.partitionColumn的数字列吗？@AlexandrosBiratsis是的，partitionColumn的数据类型是int