如何从 parquet 文件读取和写入自定义 class

Question

我正在尝试使用 DataFrame/datasets

为特定 class 类型编写镶木地板 read/write class

class 架构：

class A {
  long count;
  List<B> listOfValues;
}
class B {
  String id;
  long count;
}

代码：

  String path = "some path";
  List<A> entries = somerandomAentries();
  JavaRDD<A> rdd = sc.parallelize(entries, 1);
  DataFrame df = sqlContext.createDataFrame(rdd, A.class);

  df.write().parquet(path);
  DataFrame newDataDF = sqlContext.read().parquet(path);
  newDataDF.show();

当我尝试运行时，它会抛出一个错误。我在这里错过了什么？创建数据框时是否需要为整个 class 提供架构错误：

    Caused by: scala.MatchError: B(Id=abc, count=0) (of class B)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:255)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$StructConverter.toCatalystImpl(CatalystTypeConverters.scala:250)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:169)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$ArrayConverter.toCatalystImpl(CatalystTypeConverters.scala:153)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$CatalystTypeConverter.toCatalyst(CatalystTypeConverters.scala:102)
    at org.apache.spark.sql.catalyst.CatalystTypeConverters$$anonfun$createToCatalystConverter.apply(CatalystTypeConverters.scala:401)
    at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$$anonfun$apply.apply(SQLContext.scala:1358)
    at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows$$anonfun$apply.apply(SQLContext.scala:1358)
    at scala.collection.TraversableLike$$anonfun$map.apply(TraversableLike.scala:244)
    at scala.collection.TraversableLike$$anonfun$map.apply(TraversableLike.scala:244)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
    at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows.apply(SQLContext.scala:1358)
    at org.apache.spark.sql.SQLContext$$anonfun$org$apache$spark$sql$SQLContext$$beansToRows.apply(SQLContext.scala:1356)
    at scala.collection.Iterator$$anon.next(Iterator.scala:328)
    at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:263)
    ... 8 more

Answer 1

您收到错误消息是因为 Spark 1.6 版本不支持嵌套的 JavaBeans。请参阅 https://spark.apache.org/docs/1.6.0/sql-programming-guide.html#inferring-the-schema-using-reflection

Currently, Spark SQL does not support JavaBeans that contain nested or contain complex types such as Lists or Arrays.

如何从 parquet 文件读取和写入自定义 class

How to read and write a custom class from parquet file

java

apache-spark

parquet

apache-spark-sql

spark-dataframe