[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.*}

Reproduzieren Sie das bereitgestellte PySpark-Beispiel mit pandas 1.1.5 und pyarrow 2.0.0 und verfolgen Sie anschließend den Fehler von ArrowPythonRunner über ArrowWriter bis zu org.apache.arrow.vector.types.pojo.Field.getField zurück. Vergleichen Sie die beteiligte Java-FlatBuffers-Abhängigkeit in createString mit der im Issue verlinkten Migrationsdokumentation; abgeschlossen ist die Aufgabe, wenn das Kompatibilitätsproblem und der anwendbare Migrationspfad dokumentiert oder verifiziert sind.

Vom Indexierungsmodell aus dem Issue-Text verfasst.