This is my code, it is a class which is used to obtain near 70,000 rows from a mysql server.

class Loader:
    """Load a table with multithreading"""
    def __init__(self, table: str, connector: Connector, fields: str=None, chunk_size: int=1000, query: str=None):
        # Config the table information
        self.fields = ['all' if fields is None else fields] # Query all the fields if user do NOT indicate.
        self.table = table
        self.conn = connector.conn
        self.cursor = connector.cursor

        self.cursor.execute(f"""SELECT COUNT(*) FROM {table}""")
        self.table_size = self.cursor.fetchone()[0]

        self.chunk_size = chunk_size
        self.num_chunks = self.table_size // self.chunk_size + (1 if self.table_size % self.chunk_size > 0 else 0)
        self.query = query # user's query

    def load_large_data(self):
        all_data = pd.DataFrame()  # Store all the data from SQL

        with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
            futures = [] # tasks queue
            # Commit multithreading tasks
            for i in range(self.num_chunks):
                offset = i * self.chunk_size
                futures.append(executor.submit(self.read_chunked_data, offset))

            # Collect the result after all the tasks are completed.
            for future in concurrent.futures.as_completed(futures):
                data_chunk = future.result()
                all_data = pd.concat([all_data, data_chunk], ignore_index=True)  # Merge tasks' data.

        return all_data

    def read_chunked_data(self, offset):
        # Execute embedded query either user's modified query.
        if self.query is None:
            if self.fields == 'all':
                query = f"""SELECT * FROM {self.table} LIMIT {self.chunk_size} OFFSET {offset}"""
            else:
                fields_string = ','.join(self.fields)
                query = f"""SELECT {fields_string} FROM {self.table} LIMIT {self.chunk_size} OFFSET {offset}"""
        else: # In case of 'WHERE' etc. is added by user.
            query = f"""{self.query} LIMIT {self.chunk_size} OFFSET {offset}"""

        return pd.read_sql(query, self.conn)

And the ERROR is:

Traceback (most recent call last):
  File "D:ApplicationsAnacondaLibsite-packagespandasiosql.py", line 2674, in execute
    cur.execute(sql, *args)
  File "D:ApplicationsAnacondaLibsite-packagespymysqlcursors.py", line 153, in execute
    result = self._query(query)
             ^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespymysqlcursors.py", line 322, in _query
    conn.query(q)
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 563, in query
    self._affected_rows = self._read_query_result(unbuffered=unbuffered)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 825, in _read_query_result
    result.read()
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 1199, in read
    first_packet = self.connection._read_packet()
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 753, in _read_packet
    raise err.OperationalError(
pymysql.err.OperationalError: (2013, 'Lost connection to MySQL server during query')

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:ApplicationsAnacondaLibsite-packagespandasiosql.py", line 2678, in execute
    self.con.rollback()
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 492, in rollback
    self._execute_command(COMMAND.COM_QUERY, "ROLLBACK")
  File "D:ApplicationsAnacondaLibsite-packagespymysqlconnections.py", line 843, in _execute_command
    raise err.InterfaceError(0, "")
pymysql.err.InterfaceError: (0, '')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:UserswhalePycharmProjectsRisk Controlriskcontroltest.py", line 33, in <module>
    result = loader.load_large_data()
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:UserswhalePycharmProjectsRisk Controlriskcontroldatabase.py", line 96, in load_large_data
    data_chunk = future.result()
                 ^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibconcurrentfutures_base.py", line 449, in result
    return self.__get_result()
           ^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibconcurrentfutures_base.py", line 401, in __get_result
    raise self._exception
  File "D:ApplicationsAnacondaLibconcurrentfuturesthread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:UserswhalePycharmProjectsRisk Controlriskcontroldatabase.py", line 112, in read_chunked_data
    return pd.read_sql(query, self.conn)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespandasiosql.py", line 706, in read_sql
    return pandas_sql.read_query(
           ^^^^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespandasiosql.py", line 2738, in read_query
    cursor = self.execute(sql, params)
             ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:ApplicationsAnacondaLibsite-packagespandasiosql.py", line 2683, in execute
    raise ex from inner_exc
pandas.errors.DatabaseError: Execution failed on sql: SELECT CONTENT FROM tb_customer_info LIMIT 1000 OFFSET 2000
(2013, 'Lost connection to MySQL server during query')
unable to rollback

I suspected that the mysql server couldn’t bear the query of large data. But when I alternated the ‘LIMIT’ as ‘10,000’, my code and mysql server was able to obtain the whole rows at only one query.

It make me confused, does there anybody know how to fix it? I can’t get any information avaliable with it on the Google and from chatGPT.