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https://issues.apache.org/jira/browse/SPARK-29764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16967800#comment-16967800
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Felix Kizhakkel Jose commented on SPARK-29764:
----------------------------------------------
The Spark Schema generated for the POJO is:
message spark_schema {
optional group address {
optional binary city (UTF8);
optional binary streetName (UTF8);
optional group zip {
required int32 ext;
required int32 zip;
}
}
required int32 age;
optional group dob {
optional group chronology {
optional binary calendarType (UTF8);
optional binary id (UTF8);
}
required int32 dayOfMonth;
optional binary dayOfWeek (UTF8);
required int32 dayOfYear;
optional group era {
required int32 value;
}
required boolean leapYear;
optional binary month (UTF8);
required int32 monthValue;
required int32 year;
}
optional group id {
required int64 leastSignificantBits;
required int64 mostSignificantBits;
}
optional binary name (UTF8);
optional binary phone (UTF8);
optional group startDateTime {
required int32 dayOfMonth;
optional binary dayOfWeek (UTF8);
required int32 dayOfYear;
required int32 hour;
required int32 minute;
optional binary month (UTF8);
required int32 monthValue;
required int32 nano;
required int32 second;
required int32 year;
}
}
Also I don't know why its not recognized as int96 [timestamptype] or int
i[datetype] instead its represented as group. I dont know whether thats the
reason to get negativeArrayException when I have large data set to persist to
parquet. Any help is very much appreciated
> Error on Serializing POJO with java datetime property to a Parquet file
> -----------------------------------------------------------------------
>
> Key: SPARK-29764
> URL: https://issues.apache.org/jira/browse/SPARK-29764
> Project: Spark
> Issue Type: Bug
> Components: Java API, Spark Core, SQL
> Affects Versions: 2.4.4
> Reporter: Felix Kizhakkel Jose
> Priority: Blocker
>
> Hello,
> I have been doing a proof of concept for data lake structure and analytics
> using Apache Spark.
> When I add a java java.time.LocalDateTime/java.time.LocalDate properties in
> my data model, the serialization to Parquet start failing.
> *My Data Model:*
> @Data
> public class Employee
> { private UUID id = UUID.randomUUID(); private String name; private int age;
> private LocalDate dob; private LocalDateTime startDateTime; private String
> phone; private Address address; }
>
> *Serialization Snippet*
> {color:#0747a6}public void serialize(){color}
> {color:#0747a6}{ List<Employee> inputDataToSerialize =
> getInputDataToSerialize(); // this creates 100,000 employee objects
> Encoder<Employee> employeeEncoder = Encoders.bean(Employee.class);
> Dataset<Employee> employeeDataset = sparkSession.createDataset(
> inputDataToSerialize, employeeEncoder ); employeeDataset.write()
> .mode(SaveMode.Append) .parquet("/Users/felix/Downloads/spark.parquet");
> }{color}
> +*Exception Stack Trace:*
> +
> *java.lang.IllegalStateException: Failed to execute
> CommandLineRunnerjava.lang.IllegalStateException: Failed to execute
> CommandLineRunner at
> org.springframework.boot.SpringApplication.callRunner(SpringApplication.java:803)
> at
> org.springframework.boot.SpringApplication.callRunners(SpringApplication.java:784)
> at
> org.springframework.boot.SpringApplication.afterRefresh(SpringApplication.java:771)
> at
> org.springframework.boot.SpringApplication.run(SpringApplication.java:316) at
> org.springframework.boot.SpringApplication.run(SpringApplication.java:1186)
> at
> org.springframework.boot.SpringApplication.run(SpringApplication.java:1175)
> at com.felix.Application.main(Application.java:45)Caused by:
> org.apache.spark.SparkException: Job aborted. at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:198)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:170)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:131)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:155)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
> at
> org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:676)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:78)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
> at
> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676) at
> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:290)
> at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271) at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:229) at
> org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:566) at
> com.felix.SparkParquetSerializer.serialize(SparkParquetSerializer.java:24) at
> com.felix.Application.run(Application.java:63) at
> org.springframework.boot.SpringApplication.callRunner(SpringApplication.java:800)
> ... 6 moreCaused by: org.apache.spark.SparkException: Job aborted due to
> stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost
> task 0.0 in stage 0.0 (TID 0, localhost, executor driver):
> org.apache.spark.SparkException: Task failed while writing rows. at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:257)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:177)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at
> org.apache.spark.scheduler.Task.run(Task.scala:123) at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:411)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:748)Caused by:
> java.lang.NegativeArraySizeException at
> org.apache.spark.unsafe.types.UTF8String.getBytes(UTF8String.java:297) at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$makeWriter$8(ParquetWriteSupport.scala:164)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$makeWriter$8$adapted(ParquetWriteSupport.scala:162)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$writeFields$1(ParquetWriteSupport.scala:124)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.consumeField(ParquetWriteSupport.scala:435)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.writeFields(ParquetWriteSupport.scala:124)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$makeWriter$16(ParquetWriteSupport.scala:196)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.consumeGroup(ParquetWriteSupport.scala:429)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$makeWriter$15(ParquetWriteSupport.scala:196)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$makeWriter$15$adapted(ParquetWriteSupport.scala:194)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$writeFields$1(ParquetWriteSupport.scala:124)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.consumeField(ParquetWriteSupport.scala:435)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.writeFields(ParquetWriteSupport.scala:124)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.$anonfun$write$1(ParquetWriteSupport.scala:114)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.consumeMessage(ParquetWriteSupport.scala:423)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.write(ParquetWriteSupport.scala:114)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.write(ParquetWriteSupport.scala:50)
> at
> org.apache.parquet.hadoop.InternalParquetRecordWriter.write(InternalParquetRecordWriter.java:128)
> at
> org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:182)
> at
> org.apache.parquet.hadoop.ParquetRecordWriter.write(ParquetRecordWriter.java:44)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.write(ParquetOutputWriter.scala:40)
> at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.write(FileFormatDataWriter.scala:137)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$1(FileFormatWriter.scala:245)
> at
> org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1394)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:242)
> ... 9 more*
> Could you please help me to identify on what am I doing wrong? This is
> blocking me from proceeding further with Apache Spark + Parque
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