【发布时间】:2018-03-05 05:34:26
【问题描述】:
我有 JSON 输入文件:
{"a": "abc", "b": "bcd", "d": 3},
{"a": "ezx", "b": "hdg", "c": "ssa"},
...
每个对象的某些字段丢失,而不是放置 null 值。
在使用 Scala 的 Apache Spark 中:
import SparkCommons.sparkSession.implicits._
private val inputJsonPath: String = "resources/input/input.json"
private val schema = StructType(Array(
StructField("a", StringType, nullable = false),
StructField("b", StringType, nullable = false),
StructField("c", StringType, nullable = true),
StructField("d", DoubleType, nullable = true)
))
private val inputDF: DataFrame = SparkCommons.sparkSession
.read
.schema(schema)
.json(inputJsonPath)
.cache()
inputDF.printSchema()
val dataRdd = inputDF.rdd
.map {
case Row(a: String, b: String, c: String, d: Double) =>
MyCaseClass(a, b, c, d)
}
val dataMap = dataRdd.collectAsMap()
MyCaseClass 代码:
case class MyCaseClass(
a: String,
b: String,
c: String = null,
d: Double = Predef.Double2double(null)
)
我得到以下模式作为输出:
root
|-- a: string (nullable = true)
|-- b: string (nullable = true)
|-- c: string (nullable = true)
|-- d: double (nullable = true)
程序可以编译,但在运行时 Spark 完成工作后,我会收到以下异常:
[error] - org.apache.spark.executor.Executor - Exception in task 3.0 in stage 4.0 (TID 21)
scala.MatchError: [abc,bcd,null,3] (of class org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema)
at com.matteoguarnerio.spark.SparkOperations$$anonfun$1.apply(SparkOperations.scala:62) ~[classes/:na]
at com.matteoguarnerio.spark.SparkOperations$$anonfun$1.apply(SparkOperations.scala:62) ~[classes/:na]
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410) ~[scala-library-2.11.11.jar:na]
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410) ~[scala-library-2.11.11.jar:na]
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410) ~[scala-library-2.11.11.jar:na]
at org.apache.spark.util.random.SamplingUtils$.reservoirSampleAndCount(SamplingUtils.scala:42) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.RangePartitioner$$anonfun$9.apply(Partitioner.scala:261) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.RangePartitioner$$anonfun$9.apply(Partitioner.scala:259) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:820) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:820) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.scheduler.Task.run(Task.scala:86) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274) ~[spark-core_2.11-2.0.2.jar:2.0.2]
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) [na:1.8.0_144]
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) [na:1.8.0_144]
at java.lang.Thread.run(Thread.java:748) [na:1.8.0_144]
Spark 版本:2.0.2
Scala 版本:2.11.11
- 即使在RDD匹配和创建对象中某些字段为
null或缺失,如何解决此异常并进行迭代? - 为什么架构,即使我在某些字段上明确定义不可为空和可空,一切都可以为空?
更新
我刚刚在dataRdd 上使用了一种解决方法来避免这个问题:
private val dataRdd = inputDF.rdd
.map {
case r: GenericRowWithSchema => {
val a = r.getAs("a").asInstanceOf[String]
val b = r.getAs("b").asInstanceOf[String]
var c: Option[String] = None
var d: Option[Double] = None
try {
c = if (r.isNullAt(r.fieldIndex("c"))) None: Option[String] else Some(r.getAs("c").asInstanceOf[String])
d = if (r.isNullAt(r.fieldIndex("d"))) None: Option[Double] else Some(r.getAs("d").asInstanceOf[Double])
} catch {
case _: Throwable => None
}
MyCaseClass(a, b, c, d)
}
}
并以这种方式更改MyCaseClass:
case class MyCaseClass(
a: String,
b: String,
c: Option[String],
d: Option[Double]
)
【问题讨论】:
标签: json scala apache-spark nullpointerexception pattern-matching