[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.*}

Reproduce the supplied PySpark example with pandas 1.1.5 and pyarrow 2.0.0, then trace the failure from ArrowPythonRunner through ArrowWriter and org.apache.arrow.vector.types.pojo.Field.getField. Compare the Java FlatBuffers dependency involved in createString with the migration documentation linked in the issue; done means the compatibility problem and applicable migration path are documented or verified.

Written by the indexing model from the issue text.