将 Cassandra 行映射到 Spark RDD 中的参数化类型

Question

我正在尝试使用 spark-cassandra-connector 将 cassandra 行映射到参数化类型。我一直在尝试使用隐式定义的 columnMapper 来定义映射，因此：

class Foo[T<:Bar:ClassTag:RowReaderFactory] {
  implicit object Mapper extends JavaBeanColumnMapper[T](
    Map("id" -> "id",
        "timestamp" -> "ts"))

  def doSomeStuff(operations: CassandraTableScanRDD[T]): Unit = {
    println("do some stuff here")
  }
}

但是，我运行遇到了以下错误，我认为这是因为我传入了 RowReaderFactory 而没有正确指定 [=13] 的映射=].知道如何为 RowReaderFactory 指定映射信息吗？

Exception in thread "main" java.lang.IllegalArgumentException: Failed to map constructor parameter timestamp in Bar to a column of MyNamespace
    at com.datastax.spark.connector.mapper.DefaultColumnMapper$$anonfun$$anonfun$apply.apply(DefaultColumnMapper.scala:78)
    at com.datastax.spark.connector.mapper.DefaultColumnMapper$$anonfun$$anonfun$apply.apply(DefaultColumnMapper.scala:78)
    at scala.Option.getOrElse(Option.scala:120)
    at com.datastax.spark.connector.mapper.DefaultColumnMapper$$anonfun.apply(DefaultColumnMapper.scala:78)
    at com.datastax.spark.connector.mapper.DefaultColumnMapper$$anonfun.apply(DefaultColumnMapper.scala:76)
    at scala.collection.TraversableLike$WithFilter$$anonfun$map.apply(TraversableLike.scala:722)
    at scala.collection.immutable.List.foreach(List.scala:318)
    at scala.collection.TraversableLike$WithFilter.map(TraversableLike.scala:721)
    at com.datastax.spark.connector.mapper.DefaultColumnMapper.columnMapForReading(DefaultColumnMapper.scala:76)
    at com.datastax.spark.connector.rdd.reader.GettableDataToMappedTypeConverter.<init>(GettableDataToMappedTypeConverter.scala:56)
    at com.datastax.spark.connector.rdd.reader.ClassBasedRowReader.<init>(ClassBasedRowReader.scala:23)
    at com.datastax.spark.connector.rdd.reader.ClassBasedRowReaderFactory.rowReader(ClassBasedRowReader.scala:48)
    at com.datastax.spark.connector.rdd.reader.ClassBasedRowReaderFactory.rowReader(ClassBasedRowReader.scala:43)
    at com.datastax.spark.connector.rdd.CassandraTableRowReaderProvider$class.rowReader(CassandraTableRowReaderProvider.scala:48)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.rowReader$lzycompute(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.rowReader(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableRowReaderProvider$class.verify(CassandraTableRowReaderProvider.scala:147)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.verify(CassandraTableScanRDD.scala:59)
    at com.datastax.spark.connector.rdd.CassandraTableScanRDD.getPartitions(CassandraTableScanRDD.scala:143)

Answer 1

事实证明，columnMapper 必须在创建 Foo 实例的范围内创建，而不是在 Foo 本身。

Answer 2

可以在Foo的伴生对象中隐式定义，如下：

object Foo {
  implicit object Mapper extends JavaBeanColumnMapper[T](
    Map("id" -> "id",
        "timestamp" -> "ts"))
}

Scala 将在 class 试图找到 class 的隐式实例时查看 class 的伴生对象。如果你愿意，你可以在需要隐式的范围内定义它，但你可能想添加伴随对象，这样你就不需要在需要时重复它。

将 Cassandra 行映射到 Spark RDD 中的参数化类型

Mapping cassandra row to parametrized type in Spark RDD

scala

apache-spark

spark-cassandra-connector