[Java] PySpark3 with pandas 1.1.5 and pyarrow 2.0.0 getting the below error

While running pyspark3 with pandas 1.1.5 and pyarrow 2.0.0 getting the below error:

**Spark Code:**
```java

import pyarrow
import pandas as pd

df = pd.DataFrame({'col1' : [1,2,3], 'col2': [4,5,6]})
df_sp = spark.createDataFrame(df)
df_sp.cache().count()
schema = df_sp.schema

def dummy_udf(data):
return data

res = df_sp.groupby('col1').applyInPandas(dummy_udf, schema=schema)
print(res.cache().count())
print(res.toPandas())
```

**Exception:**
```java

21/09/17 07:28:10 ERROR util.Utils: Uncaught exception in thread stdout writer for python3
java.lang.NoSuchMethodError: com.google.flatbuffers.FlatBufferBuilder.createString(Ljava/lang/CharSequence;)I
at org.apache.arrow.vector.types.pojo.Field.getField(Field.java:204)
at org.apache.arrow.vector.types.pojo.Schema.getSchema(Schema.java:178)
at org.apache.arrow.vector.ipc.message.MessageSerializer.serializeMetadata(MessageSerializer.java:187)
at org.apache.arrow.vector.ipc.message.MessageSerializer.serialize(MessageSerializer.java:165)
at org.apache.arrow.vector.ipc.ArrowWriter.ensureStarted(ArrowWriter.java:159)
at org.apache.arrow.vector.ipc.ArrowWriter.start(ArrowWriter.java:112)
at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.$anonfun$writeIteratorToStream$1(ArrowPythonRunner.scala:86)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.writeIteratorToStream(ArrowPythonRunner.scala:103)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:397)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1996)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:232)
21/09/17 07:28:10 ERROR util.SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[stdout writer for python3,5,main]
java.lang.NoSuchMethodError: com.google.flatbuffers.FlatBufferBuilder.createString(Ljava/lang/CharSequence;)I
at org.apache.arrow.vector.types.pojo.Field.getField(Field.java:204)
at org.apache.arrow.vector.types.pojo.Schema.getSchema(Schema.java:178)
at org.apache.arrow.vector.ipc.message.MessageSerializer.serializeMetadata(MessageSerializer.java:187)
at org.apache.arrow.vector.ipc.message.MessageSerializer.serialize(MessageSerializer.java:165)
at org.apache.arrow.vector.ipc.ArrowWriter.ensureStarted(ArrowWriter.java:159)
at org.apache.arrow.vector.ipc.ArrowWriter.start(ArrowWriter.java:112)
at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.$anonfun$writeIteratorToStream$1(ArrowPythonRunner.scala:86)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.sql.execution.python.ArrowPythonRunner$$anon$1.writeIteratorToStream(ArrowPythonRunner.scala:103)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.$anonfun$run$1(PythonRunner.scala:397)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1996)
at org.apache.spark.api.python.BasePythonRunner$WriterThread.run(PythonRunner.scala:232)
21/09/17 07:28:10 WARN storage.BlockManager: Putting block rdd_25_69 failed due to exception org.apache.spark.SparkException: Python worker exited unexpectedly (crashed).
21/09/17 07:28:10 INFO memory.MemoryStore: MemoryStore cleared
21/09/17 07:28:10 INFO storage.BlockManager: BlockManager stopped
21/09/17 07:28:10 INFO util.ShutdownHookManager: Shutdown hook called
```

**Reporter**: [Ranga Reddy](https://issues.apache.org/jira/browse/ARROW-14038)

_{**Note**: *This issue was originally created as [ARROW-14038](https://issues.apache.org/jira/browse/ARROW-14038). Please see the [migration documentation](https://github.com/apache/arrow/issues/14542) for further details.*}

Reproduisez l’exemple PySpark fourni avec pandas 1.1.5 et pyarrow 2.0.0, puis retracez l’échec depuis ArrowPythonRunner via ArrowWriter jusqu’à org.apache.arrow.vector.types.pojo.Field.getField. Comparez la dépendance Java FlatBuffers impliquée dans createString avec la documentation de migration liée dans l’issue ; le travail est considéré comme terminé lorsque le problème de compatibilité et le chemin de migration applicable sont documentés ou vérifiés.

Rédigé par le modèle d'indexation à partir du texte de l'issue.