# credativ-pg-migrator
# Copyright (C) 2025 credativ GmbH
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

from credativ_pg_migrator.database_connector import DatabaseConnector
from credativ_pg_migrator.migrator_logging import MigratorLogger
import ibm_db_dbi  ## install ibm_db package to use this connector
import traceback
import time
import datetime

class IbmDb2LuwConnector(DatabaseConnector):
    def __init__(self, config_parser, source_or_target):
        if source_or_target != 'source':
            raise ValueError("IBM DB2 is only supported as a source database")

        self.connection = None
        self.config_parser = config_parser
        self.source_or_target = source_or_target
        self.connectivity = self.config_parser.get_connectivity(self.source_or_target)
        self.on_error_action = self.config_parser.get_on_error_action()
        self.logger = MigratorLogger(self.config_parser.get_log_file()).logger

    def connect(self):
        connection_string = self.config_parser.get_connect_string(self.source_or_target)
        try:
            self.connection = ibm_db_dbi.connect(connection_string, "", "")
            if not self.connection:
                raise Exception("Failed to connect to the database")
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: connect: Unexpected error while connecting into the database: {e}")
            raise

    def disconnect(self):
        try:
            if self.connection:
                self.connection.close()
        except Exception as e:
            pass

    def get_sql_functions_mapping(self, settings):
        """ Returns a dictionary of SQL functions mapping for the target database """
        target_db_type = settings['target_db_type']
        if target_db_type == 'postgresql':
            return {}
        else:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_sql_functions_mapping: Unsupported target database type: {target_db_type}")

    def migrate_sequences(self, target_connector, settings):
        return True

    def fetch_table_names(self, table_schema: str):
        query = f"""
            SELECT
                TABLEID,
                TABNAME,
                REMARKS
            FROM SYSCAT.TABLES
            WHERE TABSCHEMA = upper('{table_schema}')
            ORDER BY TABNAME"""
        try:
            tables = {}
            order_num = 1
            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            for row in cursor.fetchall():
                tables[order_num] = {
                    'id': row[0],
                    'schema_name': table_schema,
                    'table_name': row[1],
                    'comment': row[2]
                }
                order_num += 1
            cursor.close()
            self.disconnect()
            return tables
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: fetch_table_names: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def fetch_table_columns(self, settings) -> dict:
        table_schema = settings['table_schema']
        table_name = settings['table_name']
        result = {}
        try:
            if self.config_parser.get_system_catalog() in ('SYSCAT','NONE'):
                query = f"""
                    SELECT
                        COLNO,
                        COLNAME,
                        TYPENAME,
                        "LENGTH",
                        "LENGTH",
                        "SCALE",
                        "NULLS",
                        "DEFAULT",
                        "REMARKS",
                        IDENTITY
                    FROM SYSCAT.COLUMNS
                    WHERE TABSCHEMA = upper('{table_schema}') AND tabname = '{table_name}' ORDER BY COLNO
                """
            elif self.config_parser.get_system_catalog() in ('SYSIBM'):
                query = f"""
                    SELECT
                        ORDINAL_POSITION,
                        COLUMN_NAME,
                        DATA_TYPE,
                        CHARACTER_MAXIMUM_LENGTH,
                        NUMERIC_PRECISION,
                        NUMERIC_SCALE,
                        IS_NULLABLE,
                        COLUMN_DEFAULT,
                        '' AS REMARKS,
                        'N' AS IDENTITY
                    FROM SYSIBM.COLUMNS
                    WHERE TABLE_NAME = '{table_name}' AND TABLE_SCHEMA = upper('{table_schema}') ORDER BY ORDINAL_POSITION
                """
            else:
                raise ValueError(f"Unsupported system catalog: {self.config_parser.get_system_catalog()}")
            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            for row in cursor.fetchall():
                ordinal_position = row[0]
                column_name = row[1]
                data_type = row[2]
                character_maximum_length = row[3]
                numeric_precision = row[4]
                numeric_scale = row[5]
                is_nullable = row[6]
                if self.config_parser.get_system_catalog() == 'SYSCAT':
                    is_nullable = 'NO' if is_nullable == 'N' else 'YES'
                column_default = row[7]
                column_comment = row[8] if len(row) > 8 else ''
                is_identity = 'YES' if (len(row) > 9 and row[9] in ('Y', 'YES')) else 'NO'

                # when column is identity, code shall ignore default value if this is set
                if is_identity == 'YES' and column_default is not None:
                    column_default = None

                column_type = data_type
                if self.is_string_type(data_type) and character_maximum_length is not None:
                    column_type = f"{data_type}({character_maximum_length})"
                elif self.is_numeric_type(data_type) and numeric_precision is not None and numeric_scale is not None:
                    column_type = f"{data_type}({numeric_precision},{numeric_scale})"
                elif self.is_numeric_type(data_type) and numeric_precision is not None:
                    column_type = f"{data_type}({numeric_precision})"

                result[ordinal_position] = {
                    'column_name': column_name,
                    'data_type': data_type,
                    'column_type': column_type,
                    'character_maximum_length': character_maximum_length,
                    'numeric_precision': numeric_precision,
                    'numeric_scale': numeric_scale,
                    'is_nullable': is_nullable,
                    'column_default_value': column_default,
                    'column_comment': column_comment,
                    'is_identity': is_identity,
                }
            cursor.close()
            self.disconnect()
            return result
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: fetch_table_columns: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def get_types_mapping(self, settings):
        target_db_type = settings['target_db_type']
        types_mapping = {}
        if target_db_type == 'postgresql':
            types_mapping = {
                'BIGDATETIME': 'TIMESTAMP',
                'DATE': 'DATE',
                'DATETIME': 'TIMESTAMP',
                'SMALLDATETIME': 'TIMESTAMP',
                'TIME': 'TIME',
                'TIMESTAMP': 'TIMESTAMP',
                'BIGINT': 'BIGINT',
                'UNSIGNED BIGINT': 'BIGINT',
                'INTEGER': 'INTEGER',
                'INT': 'INTEGER',
                'INT8': 'BIGINT',
                'UNSIGNED INT': 'INTEGER',
                'UINT': 'INTEGER',
                'TINYINT': 'SMALLINT',
                'SMALLINT': 'SMALLINT',

                'BLOB': 'BYTEA',

                'BOOLEAN': 'BOOLEAN',
                'BIT': 'BOOLEAN',

                'BINARY': 'BYTEA',
                'VARBINARY': 'BYTEA',
                'IMAGE': 'BYTEA',
                'CHAR': 'CHAR',
                'NCHAR': 'CHAR',
                'UNICHAR': 'CHAR',
                'NVARCHAR': 'VARCHAR',
                'TEXT': 'TEXT',
                'SYSNAME': 'TEXT',
                'LONGSYSNAME': 'TEXT',
                'LONG VARCHAR': 'VARCHAR',
                'LONG NVARCHAR': 'VARCHAR',
                'UNICHAR': 'CHAR',
                'UNITEXT': 'TEXT',
                'UNIVARCHAR': 'VARCHAR',
                'VARCHAR': 'VARCHAR',

                'CLOB': 'TEXT',
                'DECIMAL': 'DECIMAL',
                'DOUBLE PRECISION': 'DOUBLE PRECISION',
                'FLOAT': 'FLOAT',
                'INTERVAL': 'INTERVAL',
                'MONEY': 'MONEY',
                'NUMERIC': 'NUMERIC',
                'REAL': 'REAL',
                'SERIAL8': 'BIGSERIAL',
                'SERIAL': 'SERIAL',
                'SMALLFLOAT': 'REAL',
            }
        else:
            raise ValueError(f"Unsupported target database type: {target_db_type}")

        return types_mapping

    def get_create_table_sql(self, settings):
        return ""

    def is_string_type(self, column_type: str) -> bool:
        string_types = ['CHAR', 'VARCHAR', 'NCHAR', 'NVARCHAR', 'TEXT', 'LONG VARCHAR', 'LONG NVARCHAR', 'UNICHAR', 'UNIVARCHAR']
        return column_type.upper() in string_types

    def is_numeric_type(self, column_type: str) -> bool:
        numeric_types = ['BIGINT', 'INTEGER', 'INT', 'TINYINT', 'SMALLINT', 'FLOAT', 'DOUBLE PRECISION', 'DECIMAL', 'NUMERIC']
        return column_type.upper() in numeric_types

    def migrate_table(self, migrate_target_connection, settings):
        part_name = 'initialize'
        source_table_rows = 0
        target_table_rows = 0
        total_inserted_rows = 0
        migration_stats = {}
        batch_number = 0
        shortest_batch_seconds = 0
        longest_batch_seconds = 0
        average_batch_seconds = 0
        chunk_start_row_number = 0
        chunk_end_row_number = 0
        processing_start_time = time.time()
        order_by_clause = ''
        try:
            worker_id = settings['worker_id']
            source_schema_name = settings['source_schema_name']
            source_table_name = settings['source_table_name']
            source_table_id = settings['source_table_id']
            source_columns = settings['source_columns']
            # target_schema_name = self.config_parser.convert_names_case(settings['target_schema_name'])
            target_schema_name = settings['target_schema_name'] ## target schema is used as it is defined in config, not converted to upper/lower case
            target_table_name = self.config_parser.convert_names_case(settings['target_table_name'])
            target_columns = settings['target_columns']
            batch_size = settings['batch_size']
            migrator_tables = settings['migrator_tables']
            migration_limitation = settings['migration_limitation']
            chunk_size = settings['chunk_size']
            chunk_number = settings['chunk_number']
            resume_after_crash = settings['resume_after_crash']
            drop_unfinished_tables = settings['drop_unfinished_tables']

            source_table_rows = self.get_rows_count(source_schema_name, source_table_name, migration_limitation)
            target_table_rows = migrate_target_connection.get_rows_count(target_schema_name, target_table_name)

            total_chunks = self.config_parser.get_total_chunks(source_table_rows, chunk_size)
            if chunk_size == -1:
                chunk_size = source_table_rows + 1

            migration_stats = {
                'rows_migrated': target_table_rows,
                'chunk_number': chunk_number,
                'total_chunks': total_chunks,
                'source_table_rows': source_table_rows,
                'target_table_rows': target_table_rows,
                'finished': True if source_table_rows == 0 else False,
            }
            ## source_schema_name, source_table_name, source_table_id, source_table_rows, worker_id, target_schema_name, target_table_name, target_table_rows
            protocol_id = migrator_tables.insert_data_migration({
                'worker_id': worker_id,
                'source_table_id': source_table_id,
                'source_schema_name': source_schema_name,
                'source_table_name': source_table_name,
                'target_schema_name': target_schema_name,
                'target_table_name': target_table_name,
                'source_table_rows': source_table_rows,
                'target_table_rows': target_table_rows,
            })

            if source_table_rows == 0:
                self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Table {source_table_name} is empty - skipping data migration.")
                migrator_tables.update_data_migration_status({
                        'row_id': protocol_id,
                        'success': True,
                        'message': 'Skipped',
                        'target_table_rows': 0,
                        'batch_count': 0,
                        'shortest_batch_seconds': 0,
                        'longest_batch_seconds': 0,
                        'average_batch_seconds': 0,
                    })

                return migration_stats

            else:
                part_name = 'migrate_table in batches using cursor'
                self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Table {source_table_name} has {source_table_rows} rows - starting data migration.")

                data_conflict_action = settings.get('data_conflict_action')
                if source_table_rows > target_table_rows or data_conflict_action in ('merge_keep_target', 'merge_keep_source', 'replace'):
                    migrator_tables.update_data_migration_started(protocol_id)

                    part_name = 'migrate_table in batches using cursor'
                    self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Source table {source_table_name}: {source_table_rows} rows / Target table {target_table_name}: {target_table_rows} rows - starting data migration.")

                    select_columns_list = []
                    orderby_columns_list = []
                    insert_columns_list = []
                    for order_num, col in source_columns.items():
                        self.config_parser.print_log_message('DEBUG2',
                                                            f"Worker {worker_id}: Table {source_schema_name}.{source_table_name}: Processing column {col['column_name']} ({order_num}) with data type {col['data_type']}")

			            # if col['data_type'].lower() == 'datetime':
			            #     select_columns_list.append(f"TO_CHAR({col['column_name']}, '%Y-%m-%d %H:%M:%S') as {col['column_name']}")
			            #     select_columns_list.append(f"ST_asText(`{col['column_name']}`) as `{col['column_name']}`")
			            # elif col['data_type'].lower() == 'set':
			            #     select_columns_list.append(f"cast(`{col['column_name']}` as char(4000)) as `{col['column_name']}`")
			            # else:
                        select_columns_list.append(f'''"{col['column_name']}"''')

                        insert_columns_list.append(f'''"{self.config_parser.convert_names_case(col['column_name'])}"''')
                        orderby_columns_list.append(f'''"{col['column_name']}"''')

                    select_columns = ', '.join(select_columns_list)
                    orderby_columns = ', '.join(orderby_columns_list)
                    insert_columns = ', '.join(insert_columns_list)

                    if resume_after_crash and not drop_unfinished_tables:
                        chunk_number = self.config_parser.get_total_chunks(target_table_rows, chunk_size)
                        self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Resuming migration for table {source_schema_name}.{source_table_name} from chunk {chunk_number} with data chunk size {chunk_size}.")
                        chunk_offset = target_table_rows
                    else:
                        chunk_offset = (chunk_number - 1) * chunk_size

                    chunk_start_row_number = chunk_offset + 1
                    chunk_end_row_number = chunk_offset + chunk_size

                    self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Migrating table {source_schema_name}.{source_table_name}: chunk {chunk_number}, data chunk size {chunk_size}, batch size {batch_size}, chunk offset {chunk_offset}, chunk end row number {chunk_end_row_number}, source table rows {source_table_rows}")
                    order_by_clause = ''

                    # if table is small, skipping ordering does not make sense because it will not speed up the migration

                    query = f'''SELECT {select_columns} FROM {source_schema_name.upper()}."{source_table_name}"'''
                    if migration_limitation:
                        query += f" WHERE {migration_limitation}"
                    primary_key_columns = migrator_tables.select_primary_key({'source_schema_name': source_schema_name, 'source_table_name': source_table_name})
                    self.config_parser.print_log_message('DEBUG2', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Primary key columns for {source_schema_name}.{source_table_name}: {primary_key_columns}")
                    if primary_key_columns:
                        orderby_columns = primary_key_columns
                    order_by_clause = f""" ORDER BY {orderby_columns}"""
                    query += order_by_clause + f" LIMIT {chunk_size} OFFSET {chunk_offset}"

                    self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Fetching data with cursor using query: {query}")

                    part_name = 'execute query'
                    cursor = self.connection.cursor()
                    cursor.arraysize = batch_size

                    batch_start_time = time.time()
                    reading_start_time = batch_start_time
                    processing_start_time = batch_start_time
                    batch_end_time = None
                    batch_number = 0
                    batch_durations = []

                    cursor.execute(query)
                    while True:
                        records = cursor.fetchmany(batch_size)
                        if not records:
                            break
                        batch_number += 1
                        reading_end_time = time.time()
                        reading_duration = reading_end_time - reading_start_time
                        self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Fetched {len(records)} rows (batch {batch_number}) from source table {source_table_name}.")

                        transforming_start_time = time.time()
                        records = [
                            {column['column_name']: value for column, value in zip(source_columns.values(), record)}
                            for record in records
                        ]
                        for record in records:
                            for order_num, column in source_columns.items():
                                column_name = column['column_name']
                                column_type = column['data_type']
                                if column_type.lower() in ['binary', 'varbinary', 'image']:
                                    record[column_name] = bytes(record[column_name]) if record[column_name] is not None else None
                                elif column_type.lower() in ['datetime', 'smalldatetime', 'date', 'time', 'timestamp']:
                                    record[column_name] = str(record[column_name]) if record[column_name] is not None else None

                        # Insert batch into target table
                        self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Starting insert of {len(records)} rows from source table {source_table_name}")
                        transforming_end_time = time.time()
                        transforming_duration = transforming_end_time - transforming_start_time
                        inserting_start_time = time.time()
                        inserted_rows = migrate_target_connection.insert_batch({
                            'target_schema_name': target_schema_name,
                            'target_table_name': target_table_name,
                            'target_columns': target_columns,
                            'data': records,
                            'worker_id': worker_id,
                            'migrator_tables': migrator_tables,
                            'insert_columns': insert_columns,
                            'insert_values': settings.get('insert_values'),
                        })
                        total_inserted_rows += inserted_rows
                        inserting_end_time = time.time()
                        inserting_duration = inserting_end_time - inserting_start_time

                        batch_end_time = time.time()
                        batch_duration = batch_end_time - batch_start_time
                        batch_durations.append(batch_duration)
                        percent_done = round(total_inserted_rows / source_table_rows * 100, 2)

                        batch_start_dt = datetime.datetime.fromtimestamp(batch_start_time)
                        batch_end_dt = datetime.datetime.fromtimestamp(batch_end_time)
                        batch_start_str = batch_start_dt.strftime('%Y-%m-%d %H:%M:%S.%f')
                        batch_end_str = batch_end_dt.strftime('%Y-%m-%d %H:%M:%S.%f')
                        migrator_tables.insert_batches_stats({
                            'source_schema_name': source_schema_name,
                            'source_table_name': source_table_name,
                            'source_table_id': source_table_id,
                            'chunk_number': chunk_number,
                            'batch_number': batch_number,
                            'batch_start': batch_start_str,
                            'batch_end': batch_end_str,
                            'batch_rows': inserted_rows,
                            'batch_seconds': batch_duration,
                            'worker_id': worker_id,
                            'reading_seconds': reading_duration,
                            'transforming_seconds': transforming_duration,
                            'writing_seconds': inserting_duration,
                        })

                        msg = (
                            f"Worker {worker_id}: Inserted {inserted_rows} "
                            f"(total: {total_inserted_rows} from: {source_table_rows} "
                            f"({percent_done}%)) rows into target table '{target_table_name}': "
                            f"Batch {batch_number} duration: {batch_duration:.2f} seconds "
                            f"(r: {reading_duration:.2f}, t: {transforming_duration:.2f}, w: {inserting_duration:.2f})"
                        )
                        self.config_parser.print_log_message('INFO', msg)

                        batch_start_time = time.time()
                        reading_start_time = batch_start_time

                    target_table_rows = migrate_target_connection.get_rows_count(target_schema_name, target_table_name)
                    self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Target table {target_schema_name}.{target_table_name} has {target_table_rows} rows")

                    shortest_batch_seconds = min(batch_durations) if batch_durations else 0
                    longest_batch_seconds = max(batch_durations) if batch_durations else 0
                    average_batch_seconds = sum(batch_durations) / len(batch_durations) if batch_durations else 0
                    self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Migrated {total_inserted_rows} rows from {source_table_name} to {target_schema_name}.{target_table_name} in {batch_number} batches: "
                                                            f"Shortest batch: {shortest_batch_seconds:.2f} seconds, "
                                                            f"Longest batch: {longest_batch_seconds:.2f} seconds, "
                                                            f"Average batch: {average_batch_seconds:.2f} seconds")
                    cursor.close()

                elif source_table_rows <= target_table_rows and data_conflict_action not in ('merge_keep_target', 'merge_keep_source', 'replace'):
                    self.config_parser.print_log_message('INFO', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Source table {source_table_name} has {source_table_rows} rows, which is less than or equal to target table {target_table_name} with {target_table_rows} rows. No data migration needed.")

                migration_stats = {
                    'rows_migrated': total_inserted_rows,
                    'chunk_number': chunk_number,
                    'total_chunks': total_chunks,
                    'source_table_rows': source_table_rows,
                    'target_table_rows': target_table_rows,
                    'finished': False,
                }

                self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Migration stats: {migration_stats}")
                if source_table_rows == target_table_rows or chunk_number >= total_chunks:
                    self.config_parser.print_log_message('DEBUG3', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Setting migration status to finished for table {source_table_name} (chunk {chunk_number}/{total_chunks})")
                    migration_stats['finished'] = True
                    migrator_tables.update_data_migration_status({
                        'row_id': protocol_id,
                        'success': True,
                        'message': 'OK',
                        'target_table_rows': target_table_rows,
                        'batch_count': batch_number,
                        'shortest_batch_seconds': shortest_batch_seconds,
                        'longest_batch_seconds': longest_batch_seconds,
                        'average_batch_seconds': average_batch_seconds,
                    })

                migrator_tables.insert_data_chunk({
                    'worker_id': worker_id,
                    'source_table_id': source_table_id,
                    'source_schema_name': source_schema_name,
                    'source_table_name': source_table_name,
                    'target_schema_name': target_schema_name,
                    'target_table_name': target_table_name,
                    'source_table_rows': source_table_rows,
                    'target_table_rows': target_table_rows,
                    'chunk_number': chunk_number,
                    'chunk_size': chunk_size,
                    'migration_limitation': migration_limitation,
                    'chunk_start': chunk_start_row_number,
                    'chunk_end': chunk_end_row_number,
                    'inserted_rows': total_inserted_rows,
                    'batch_size': batch_size,
                    'total_batches': batch_number,
                    'task_started': datetime.datetime.fromtimestamp(processing_start_time).strftime('%Y-%m-%d %H:%M:%S.%f'),
                    'task_completed': datetime.datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H:%M:%S.%f'),
                    'order_by_clause': order_by_clause,
                })
                return migration_stats
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Error during {part_name} -> {e}")
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: migrate_table: Worker {worker_id}: Full stack trace: {traceback.format_exc()}")
            raise e

    def fetch_indexes(self, settings):
        source_table_id = settings['source_table_id']
        source_table_schema = settings['source_table_schema']
        source_table_name = settings['source_table_name']

        table_indexes = {}
        order_num = 1
        query = f"""
            SELECT
                INDNAME,
                COLNAMES,
                COLCOUNT,
                UNIQUERULE,
                REMARKS
            FROM SYSCAT.INDEXES I
            WHERE I.TABSCHEMA = upper('{source_table_schema}')
            AND I.TABNAME = '{source_table_name}'
            ORDER BY INDNAME
        """
        try:
            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            for row in cursor.fetchall():
                index_name = row[0]
                index_columns = ', '.join(f'"{col}"' for col in row[1].lstrip('+').split('+') if col)
                columns_count = row[2]
                index_type = row[3]
                index_comment = row[4]

                table_indexes[order_num] = {
                    'index_name': index_name,
                    'index_type': 'PRIMARY KEY' if index_type == 'P' else 'UNIQUE' if index_type == 'U' else 'INDEX',
                    'index_owner': source_table_schema,
                    'index_columns': index_columns,
                    'index_comment': index_comment,
                }
                order_num += 1

            cursor.close()
            self.disconnect()
            self.config_parser.print_log_message( 'DEBUG2', f"ibm_db2_luw_connector: fetch_indexes: Indexes for table {source_table_name} ({source_table_schema}): {index_columns}")
            return table_indexes
        except Exception as e:
            self.config_parser.print_log_message( 'ERROR', f"ibm_db2_luw_connector: fetch_indexes: Error executing query: {query}")
            self.config_parser.print_log_message( 'ERROR', str(e))
            raise

    def get_create_index_sql(self, settings):
        return ""

    def fetch_constraints(self, settings):
        source_table_id = settings['source_table_id']
        source_table_schema = settings['source_table_schema']
        source_table_name = settings['source_table_name']

        order_num = 1
        table_constraints = {}
        create_constraint_query = None
        query = f"""
            SELECT
                CONSTNAME,
                TYPE
            FROM SYSCAT.TABCONST
            WHERE TABSCHEMA = '{source_table_schema.upper()}'
            AND TABNAME = '{source_table_name}'
            AND TYPE NOT IN ('P')
            ORDER BY CONSTNAME;"""
        try:
            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            for row in cursor.fetchall():
                constraint_name = row[0]
                constraint_type = row[1]

                if constraint_type == 'F':
                    constraint_type = 'FOREIGN KEY'
                    query_fk = f"""
                        SELECT
                            PK_COLNAMES,
                            REFTABNAME,
                            FK_COLNAMES,
                            REFTABSCHEMA
                        FROM SYSCAT.REFERENCES
                        WHERE TABSCHEMA = '{source_table_schema.upper()}'
                        AND TABNAME = '{source_table_name}'
                        AND CONSTNAME = '{constraint_name}'
                    """
                    cursor.execute(query_fk)
                    fk_row = cursor.fetchone()
                    if fk_row:
                        pk_columns = fk_row[0].strip().lstrip('+').split('+')
                        pk_columns = ', '.join(f'"{col}"' for col in pk_columns)
                        ref_table_name = fk_row[1]
                        fk_columns = fk_row[2].strip().lstrip('+').split('+')
                        fk_columns = ', '.join(f'"{col}"' for col in fk_columns)
                        ref_table_schema = fk_row[3].strip() if fk_row[3] else source_table_schema
                    else:
                        ref_table_schema = source_table_schema

                    table_constraints[order_num] = {
                        'constraint_name': constraint_name,
                        'constraint_type': constraint_type,
                        'constraint_owner': source_table_schema,
                        'constraint_columns': fk_columns,
                        'referenced_table_schema': ref_table_schema,
                        'referenced_table_name': ref_table_name,
                        'referenced_columns': pk_columns,
                        'constraint_sql': '',
                        'constraint_comment': '',
                    }
                    order_num += 1

            cursor.close()
            self.disconnect()
            return table_constraints
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: fetch_constraints: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def get_create_constraint_sql(self, settings):
        return ""

    def fetch_triggers(self, table_id: int, table_schema: str, table_name: str):
        # Placeholder for fetching triggers
        return {}

    def convert_trigger(self, trig: str, settings: dict):
        # Placeholder for trigger conversion
        pass

    def fetch_funcproc_names(self, schema: str):
        # Placeholder for fetching function/procedure names
        return {}

    def fetch_funcproc_code(self, funcproc_id: int):
        # Placeholder for fetching function/procedure code
        return ""

    def convert_funcproc_code(self, settings):
        funcproc_code = settings['funcproc_code']
        target_db_type = settings['target_db_type']
        source_schema_name = settings['source_schema_name']
        target_schema_name = settings['target_schema_name']
        table_list = settings['table_list']
        view_list = settings['view_list']
        converted_code = ''
        # placeholder for actual conversion logic
        return converted_code

    def fetch_sequences(self, schema_name: str):
        # Placeholder for fetching sequences
        return {}

    def get_sequence_details(self, sequence_owner, sequence_name):
        # Placeholder for fetching sequence details
        return {}

    def get_aliases(self, settings):
        source_schema_name = settings.get('source_schema_name')
        aliases = {}
        order_num = 1
        query = ""
        try:
            if self.config_parser.get_system_catalog() in ('SYSCAT', 'NONE'):
                query = f"""
                    SELECT
                        TABNAME,
                        BASE_TABSCHEMA,
                        BASE_TABNAME,
                        TABSCHEMA,
                        REMARKS
                    FROM SYSCAT.TABLES
                    WHERE TYPE = 'A' AND TABSCHEMA = upper('{source_schema_name}')
                    ORDER BY TABNAME
                """
            elif self.config_parser.get_system_catalog() == 'SYSIBM':
                query = f"""
                    SELECT
                        NAME,
                        CREATOR,
                        NAME,
                        CREATOR,
                        REMARKS
                    FROM SYSIBM.SYSTABLES
                    WHERE TYPE = 'A' AND CREATOR = upper('{source_schema_name}')
                    ORDER BY NAME
                """
            else:
                raise ValueError(f"Unsupported system catalog: {self.config_parser.get_system_catalog()}")

            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            for row in cursor.fetchall():
                alias_name = row[0]
                aliased_schema_name = row[1] if row[1] else ''
                aliased_table_name = row[2] if row[2] else ''
                alias_owner = row[3] if row[3] else source_schema_name
                alias_comment = row[4]
                aliases[order_num] = {
                    'id': order_num,
                    'alias_schema_name': source_schema_name,
                    'alias_name': alias_name,
                    'aliased_schema_name': aliased_schema_name,
                    'aliased_table_name': aliased_table_name,
                    'alias_owner': alias_owner,
                    'alias_sql': f"CREATE ALIAS {source_schema_name}.{alias_name} FOR {aliased_schema_name}.{aliased_table_name}",
                    'alias_comment': alias_comment
                }
                order_num += 1
            cursor.close()
            self.disconnect()
            return aliases
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_aliases: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def fetch_views_names(self, source_schema_name: str):
        # Placeholder for fetching view names
        return {}

    def fetch_view_code(self, settings):
        view_id = settings['view_id']
        source_schema_name = settings['source_schema_name']
        source_view_name = settings['source_view_name']
        target_schema_name = settings['target_schema_name']
        target_view_name = settings['target_view_name']
        # Placeholder for fetching view code
        return ""

    def convert_view_code(self, settings: dict):
        view_code = settings['view_code']
        # Placeholder for view conversion
        return view_code

    def get_sequence_current_value(self, sequence_id: int):
        # Placeholder for fetching sequence current value
        return None

    def execute_query(self, query: str, params=None):
        try:
            cursor = self.connection.cursor()
            if params:
                cursor.execute(query, params)
            else:
                cursor.execute(query)
            cursor.close()
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: execute_query: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def execute_sql_script(self, script_path: str):
        try:
            with open(script_path, 'r') as file:
                script = file.read()
            cursor = self.connection.cursor()
            cursor.execute(script)
            cursor.close()
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: execute_sql_script: Error executing script: {script_path}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def begin_transaction(self):
        self.connection.jconn.setAutoCommit(False)

    def commit_transaction(self):
        self.connection.commit()
        self.connection.jconn.setAutoCommit(True)

    def rollback_transaction(self):
        self.connection.rollback()

    def get_rows_count(self, table_schema: str, table_name: str, migration_limitation: str = None):
        query = f"""SELECT COUNT(*) FROM {table_schema.upper()}."{table_name}" """
        if migration_limitation:
            query += f" WHERE {migration_limitation}"
        try:
            cursor = self.connection.cursor()
            cursor.execute(query)
            count = cursor.fetchone()[0]
            cursor.close()
            return count
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_rows_count: Error executing query: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def get_table_size(self, table_schema: str, table_name: str):
        # Placeholder for fetching table size
        return 0

    def fetch_user_defined_types(self, schema: str):
        # Placeholder for fetching user-defined types
        return {}

    def fetch_domains(self, schema: str):
        # Placeholder for fetching domains
        return {}

    def get_create_domain_sql(self, settings):
        # Placeholder for generating CREATE DOMAIN SQL
        return ""

    def fetch_default_values(self, settings) -> dict:
        # Placeholder for fetching default values
        return {}

    def get_table_description(self, settings) -> dict:
        # Placeholder for fetching table description
        self.config_parser.print_log_message('DEBUG3', f"ibm_db2_luw_connector: get_table_description: IBM DB2 connector: Getting table description for {settings['table_schema']}.{settings['table_name']}")
        return { 'table_description': '' }

    def testing_select(self):
        return "SELECT 1 FROM SYSIBM.SYSDUMMY1"

    def get_database_version(self):
        try:
            query = "SELECT SERVICE_LEVEL FROM SYSIBMADM.ENV_INST_INFO"
            cursor = self.connection.cursor()
            cursor.execute(query)
            version = cursor.fetchone()[0]
            cursor.close()
            return version
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_database_version: Error fetching database version: {e}")
            raise

    def get_database_size(self):
        query = "SELECT SUM(DATA_OBJECT_P_SIZE + INDEX_OBJECT_P_SIZE) FROM SYSIBMADM.ADMINTABINFO WHERE TABSCHEMA = 'SYSIBM'"
        try:
            cursor = self.connection.cursor()
            cursor.execute(query)
            size = cursor.fetchone()[0]
            cursor.close()
            return size
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_database_size: Error fetching database size: {e}")
            raise

    def get_top_n_tables(self, settings):
        top_tables = {}
        top_tables['by_rows'] = {}
        top_tables['by_size'] = {}
        top_tables['by_columns'] = {}
        top_tables['by_indexes'] = {}
        top_tables['by_constraints'] = {}

        source_schema_name = settings['source_schema_name']
        try:
            order_num = 1
            top_n = self.config_parser.get_top_n_tables_by_rows()
            if top_n > 0:
                query = f"""
                    SELECT
                    TABSCHEMA,
                    TABNAME,
                    STATS_ROWS_MODIFIED,
                    SUM(DATA_OBJECT_P_SIZE + INDEX_OBJECT_P_SIZE) AS TOTAL_SIZE
                    FROM SYSIBMADM.ADMINTABINFO
                    WHERE TABSCHEMA = upper('{source_schema_name}')
                    GROUP BY TABSCHEMA, TABNAME, STATS_ROWS_MODIFIED
                    ORDER BY STATS_ROWS_MODIFIED DESC
                    FETCH FIRST {top_n} ROWS ONLY
                """
                self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: get_top_n_tables: Fetching top {top_n} tables by row count for schema {source_schema_name} with query: {query}")
                cursor = self.connection.cursor()
                cursor.execute(query)
                tables = cursor.fetchall()
                cursor.close()
                order_num = 1
                for row in tables:
                    top_tables['by_rows'][order_num] = {
                        'owner': row[0].strip(),
                        'table_name': row[1].strip(),
                        'row_count': row[2],
                        'row_size': None,
                        'table_size': row[3],
                    }
                    order_num += 1
                self.config_parser.print_log_message('DEBUG2', f"ibm_db2_luw_connector: get_top_n_tables: Top {top_n} tables BY ROWS: {top_tables}")
            else:
                self.config_parser.print_log_message('DEBUG', f"ibm_db2_luw_connector: get_top_n_tables: Top N tables by rows is set to 0, skipping fetching top tables by row count.")
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: get_top_n_tables: Error fetching top {top_n} tables by row count: {e}")

        return top_tables

    def target_table_exists(self, target_schema_name, target_table_name):
        exists = False
        query = f"""
            SELECT COUNT(*)
            FROM SYSCAT.TABLES
            WHERE TABSCHEMA = upper('{target_schema_name}') AND TABNAME = '{target_table_name}'
        """
        try:
            self.connect()
            cursor = self.connection.cursor()
            cursor.execute(query)
            exists = cursor.fetchone()[0] > 0
            cursor.close()
            self.disconnect()
            return exists
        except Exception as e:
            self.config_parser.print_log_message('ERROR', f"ibm_db2_luw_connector: target_table_exists: Error checking if target table exists: {query}")
            self.config_parser.print_log_message('ERROR', e)
            raise

    def get_top_fk_dependencies(self, settings):
        top_fk_dependencies = {}
        return top_fk_dependencies

    def fetch_all_rows(self, query):
        cursor = self.connection.cursor()
        cursor.execute(query)
        rows = cursor.fetchall()
        cursor.close()
        return rows

    def convert_default_value(self, settings) -> dict:
        extracted_default_value = settings['extracted_default_value']
        return extracted_default_value

    def get_table_checksum(self, schema_name: str, table_name: str, columns: list):
        return None

    def get_random_pks(self, schema_name: str, table_name: str, pk_columns: list, sample_size: int):
        return []

    def get_row_checksums(self, schema_name: str, table_name: str, pk_columns: list, pk_values_list: list, columns: list):
        return {}

    def get_lob_sizes(self, schema_name: str, table_name: str, pk_columns: list, pk_values_list: list, lob_columns: list):
        return {}

if __name__ == "__main__":
    print("This script is not meant to be run directly")
