Hi Abhinav,
Using ReadStream or Read will not mind.
The following error
java.lang.NoSuchMethodError:
org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkFieldNames(
states that you are using different version of Spark at someplace of your
project or you are using an older component
Please check your Spark Binaries and as well as your pom that you are
indeed using the same versions.
On Fri, 17 Dec 2021 at 15:11, Abhinav Gundapaneni
<agundapan...@microsoft.com.invalid> wrote:
> Hello Spark community,
>
>
>
> I’m using Apache spark(version 3.2) to read a CSV file to a dataframe
> using ReadStream, process the dataframe and write the dataframe to Delta
> file using WriteStream. I’m getting a failure during the WriteStream
> process. I’m trying to run the script locally in my windows 11 machine.
> Below is the stack trace of the error I’m facing. Please let me know if
> there’s anything that I’m missing.
>
>
>
>
>
>
>
>
>
>
>
> java.lang.NoSuchMethodError:
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkFieldNames(Lscala/collection/Seq;)V
>
> at
> org.apache.spark.sql.delta.schema.SchemaUtils$.checkFieldNames(SchemaUtils.scala:958)
>
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.verifyNewMetadata(OptimisticTransaction.scala:216)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.verifyNewMetadata$(OptimisticTransaction.scala:214)
>
> at
> org.apache.spark.sql.delta.OptimisticTransaction.verifyNewMetadata(OptimisticTransaction.scala:80)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.updateMetadata(OptimisticTransaction.scala:208)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.updateMetadata$(OptimisticTransaction.scala:195)
>
> at
> org.apache.spark.sql.delta.OptimisticTransaction.updateMetadata(OptimisticTransaction.scala:80)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata(ImplicitMetadataOperation.scala:101)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata$(ImplicitMetadataOperation.scala:62)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.updateMetadata(DeltaSink.scala:37)
>
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata(ImplicitMetadataOperation.scala:59)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata$(ImplicitMetadataOperation.scala:50)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.updateMetadata(DeltaSink.scala:37)
>
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.$anonfun$addBatch$1(DeltaSink.scala:80)
>
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.$anonfun$addBatch$1$adapted(DeltaSink.scala:54)
>
> at
> org.apache.spark.sql.delta.DeltaLog.withNewTransaction(DeltaLog.scala:188)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.addBatch(DeltaSink.scala:54)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:600)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
>
> at
> org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:598)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:598)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:228)
>
> at
> scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:193)
>
> at
> org.apache.spark.sql.execution.streaming.OneTimeExecutor.execute(TriggerExecutor.scala:39)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:187)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:303)
>
> at
> scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
>
> at
> org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
>
> at org.apache.spark.sql.execution.streaming.StreamExecution.org
> $apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:286)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:209)
>
> Exception in thread "stream execution thread for [id =
> aafe131a-0785-4285-8b5e-7735b30959a7, runId =
> effac477-1036-498e-961b-41e9b76c68df]" java.lang.NoSuchMethodError:
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkFieldNames(Lscala/collection/Seq;)V
>
>
> at
> org.apache.spark.sql.delta.schema.SchemaUtils$.checkFieldNames(SchemaUtils.scala:958)
>
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.verifyNewMetadata(OptimisticTransaction.scala:216)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.verifyNewMetadata$(OptimisticTransaction.scala:214)
>
> at
> org.apache.spark.sql.delta.OptimisticTransaction.verifyNewMetadata(OptimisticTransaction.scala:80)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.updateMetadata(OptimisticTransaction.scala:208)
>
> at
> org.apache.spark.sql.delta.OptimisticTransactionImpl.updateMetadata$(OptimisticTransaction.scala:195)
>
> at
> org.apache.spark.sql.delta.OptimisticTransaction.updateMetadata(OptimisticTransaction.scala:80)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata(ImplicitMetadataOperation.scala:101)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata$(ImplicitMetadataOperation.scala:62)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.updateMetadata(DeltaSink.scala:37)
>
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata(ImplicitMetadataOperation.scala:59)
>
> at
> org.apache.spark.sql.delta.schema.ImplicitMetadataOperation.updateMetadata$(ImplicitMetadataOperation.scala:50)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.updateMetadata(DeltaSink.scala:37)
>
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.$anonfun$addBatch$1(DeltaSink.scala:80)
>
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.$anonfun$addBatch$1$adapted(DeltaSink.scala:54)
>
> at
> org.apache.spark.sql.delta.DeltaLog.withNewTransaction(DeltaLog.scala:188)
>
> at
> org.apache.spark.sql.delta.sources.DeltaSink.addBatch(DeltaSink.scala:54)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$17(MicroBatchExecution.scala:600)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
>
> at
> org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
>
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$16(MicroBatchExecution.scala:598)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:598)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:228)
>
> at
> scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:375)
>
> at
> org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:373)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:69)Traceback
> (most recent call last):
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate\tests\test_mdefbasic.py",
> line 60, in <module>
>
>
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:193)
>
> at
> org.apache.spark.sql.execution.streaming.OneTimeExecutor.execute(TriggerExecutor.scala:39)
>
> at
> org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:187)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:303)
>
> at
> scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
>
> at
> org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
>
> at org.apache.spark.sql.execution.streaming.StreamExecution.org
> $apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:286)
>
> at
> org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:209)
>
> obj.test_ingest_incremental_data_batch1()
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate\tests\test_mdefbasic.py",
> line 56, in test_ingest_incremental_data_batch1
>
> mdef.ingest_incremental_data('example', entity,
> self.schemas['studentattendance'], 'school_year')
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate/src\MDEFBasic.py", line
> 109, in ingest_incremental_data
>
> query.awaitTermination() # block until query is terminated, with
> stop() or with error; A StreamingQueryException will be thrown if an
> exception occurs.
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate\.tox\default\lib\site-packages\pyspark\sql\streaming.py",
> line 101, in awaitTermination
>
> return self._jsq.awaitTermination()
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate\.tox\default\lib\site-packages\py4j\java_gateway.py",
> line 1309, in __call__
>
> return_value = get_return_value(
>
> File
> "C:\Users\agundapaneni\Development\ModernDataEstate\.tox\default\lib\site-packages\pyspark\sql\utils.py",
> line 117, in deco
>
> raise converted from None
>
> pyspark.sql.utils.StreamingQueryException:
> org.apache.spark.sql.execution.datasources.parquet.ParquetSchemaConverter$.checkFieldNames(Lscala/collection/Seq;)V
>
> === Streaming Query ===
>
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