Apache Spark中的数据集

时间:2018-04-29 19:58:23

标签: java apache-spark spark-dataframe

Dataset<Tweet> ds = sc.read().json("path").as(Encoders.bean(Tweet.class));
ds.show();
JavaRDD<Tweet> dstry = ds.toJavaRDD();
System.out.println(dstry.first().getClass());
Caused by: java.util.concurrent.ExecutionException: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 50, Column 16: failed to compile: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 50, Column 16: No applicable constructor/method found for actual parameters "org.apache.spark.unsafe.types.UTF8String"; candidates are: "public void sparkSQL.Tweet.setId(long)"
    at org.spark_project.guava.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:306)
    at org.spark_project.guava.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:293)
    at org.spark_project.guava.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
    at org.spark_project.guava.util.concurrent.Uninterruptibles.getUninterruptibly(Uninterruptibles.java:135)
    at org.spark_project.guava.cache.LocalCache$Segment.getAndRecordStats(LocalCache.java:2410)
    at org.spark_project.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2380)
    at org.spark_project.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342)
    at org.spark_project.guava.cache.LocalCache$Segment.get(LocalCache.java:2257)
    at org.spark_project.guava.cache.LocalCache.get(LocalCache.java:4000)
    at org.spark_project.guava.cache.LocalCache.getOrLoad(LocalCache.java:4004)
    at org.spark_project.guava.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4874)
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.compile(CodeGenerator.scala:1369)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateSafeProjection$.create(GenerateSafeProjection.scala:197)
    at org.apache.spark.sql.catalyst.expressions.codegen.GenerateSafeProjection$.create(GenerateSafeProjection.scala:36)
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1325)
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator.generate(CodeGenerator.scala:1322)
    at org.apache.spark.sql.execution.DeserializeToObjectExec$$anonfun$2.apply(objects.scala:90)
    at org.apache.spark.sql.execution.DeserializeToObjectExec$$anonfun$2.apply(objects.scala:89)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:818)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 50, Column 16: failed to compile: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 50, Column 16: No applicable constructor/method found for actual parameters "org.apache.spark.unsafe.types.UTF8String"; candidates are: "public void sparkSQL.Tweet.setId(long)"
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.org$apache$spark$sql$catalyst$expressions$codegen$CodeGenerator$$doCompile(CodeGenerator.scala:1435)
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1497)
    at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$$anon$1.load(CodeGenerator.scala:1494)
    at org.spark_project.guava.cache.LocalCache$LoadingValueReference.loadFuture(LocalCache.java:3599)
    at org.spark_project.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2379)

当我仔细观察时,我唯一怀疑的是:

  

找不到适用于实际参数的构造函数/方法“org.apache.spark.unsafe.types.UTF8String”;候选人是:“public void sparkSQL.Tweet.setId(long)”

2 个答案:

答案 0 :(得分:1)

由于类型不匹配,它会给您一个错误:

  • Tweet类将id字段定义为Long
  • 您的数据idString

您必须投射输入或调整类定义。

答案 1 :(得分:1)

正如@ user9718686所写,id字段有不同的类型:json文件中有String,类定义中有long。当您将其读入Dataset<Row>时,Spark会从文件中推断出架构并检测到该类型为String,这就是为什么当您尝试打印时它起作用的原因(正如您所要求的那样)在你的一条评论中)。如果您希望将数据框设置为Dataset<Tweet>,那么您必须将json文件更改为使用long ID而不是String,或者当您尝试执行时,可以让Spark转换此id

。数据框上的任何action operation

Dataset<Row> rowDataset = sc.read().json("path");
Dataset<Tweet> tweetDataset = rowDataset
                .withColumn("id", rowDataset.col("id").cast(DataTypes.LongType))
                .as(Encoders.bean(Tweet.class));
tweetDataset.printSchema();
System.out.println(tweetDataset.head().getId());