我试图将dataframe保存到spark shell中的tfrecord文件中,该文件需要spark tensorflow connector jar的依赖关系,因此我运行
spark-shell --jars xxx/xxx/spark-tensorflow-connector_2.11-1.11.0.jar
然后在spark shell中运行以下代码:
scala> import org.apache.spark.sql.{DataFrame, SaveMode, SparkSession}
import org.apache.spark.sql.{DataFrame, SaveMode, SparkSession}
scala> val df = Seq((8, "bat"),(8, "abc"), (1, "xyz"), (2, "aaa")).toDF("number", "word")
df: org.apache.spark.sql.DataFrame = [number: int, word: string]
scala> df.show
+------+----+
|number|word|
+------+----+
| 8| bat|
| 8| abc|
| 1| xyz|
| 2| aaa|
+------+----+
scala> var s = df.write.mode(SaveMode.Overwrite).format("tfrecords").option("recordType", "Example")
s: org.apache.spark.sql.DataFrameWriter[org.apache.spark.sql.Row] = org.apache.spark.sql.DataFrameWriter@da1382f
scala> s.save("tmp/tfrecords")
java.lang.NoClassDefFoundError: scala/Product$class
at org.tensorflow.spark.datasources.tfrecords.TensorflowRelation.<init>(TensorflowRelation.scala:29)
at org.tensorflow.spark.datasources.tfrecords.DefaultSource.createRelation(DefaultSource.scala:78)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:175)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:213)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:210)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:171)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:122)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:121)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:944)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:763)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:944)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:396)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:380)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:269)
... 47 elided
Caused by: java.lang.ClassNotFoundException: scala.Product$class
at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:355)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
... 70 more
spark版本是3.0.0,使用scala版本2.12.10(java hotspot(tm)64位服务器虚拟机,java 1.8.0旸261)
1条答案
按热度按时间xkrw2x1b1#
问题是您使用的是用scala 2.11编译的tensorflow连接器(注意
_2.11
使用scala 2.12编译的spark 3.0。到目前为止,还没有为spark3.0编译的tensorflow连接器,因此需要使用scala2.11编译的spark2.4.6。