Java apachespark中的数据集

当我仔细观察时，唯一引起我怀疑的是：

未找到适用于实际参数“org.apache.spark.unsafe.types.UTF8String”的构造函数/方法；候选项为：“public void sparkSQL.Tweet.setId（long）”

---

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

• 您的数据具有

  id

  作为

  String

---

您必须转换输入或调整类定义。

正如@user9718686所写，id字段有不同的类型：

String

在json文件中，以及

long

在类定义中。当您将其读入

数据集

时，Spark会从文件中推断出模式，并检测到id的类型为

字符串

，这就是为什么您试图打印它时它会起作用（正如您在一条注释中要求的那样）。如果您想将数据帧设置为

数据集

，则必须将json文件更改为使用

长

id而不是

字符串

，或者您可以在尝试对数据帧执行任何操作时让Spark强制转换此id

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)

Dataset rowDataset=sc.read（）.json（“路径”）；
数据集tweetDataset=rowDataset
.withColumn（“id”，rowDataset.col（“id”）.cast（DataTypes.LongType））
.as（Encoders.bean（Tweet.class））；
tweetDataset.printSchema（）；
System.out.println（tweetDataset.head（）.getId（））；

Tweets定义：-这是一个包含getter和setter的类，具有长id、字符串名称、字符串文本。是的，我更改了类定义，然后键入了它，但它为什么与dataframe一起工作dataframe的代码：-Dataset df=sc.read（）.json（path）；JavaRDD dftry=df.JavaRDD（）.map（s->s.toString（））；系统输出println（dftry.take（2））；有人能回答我吗？我终于明白了，耶

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)

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());