作为一个资深的py算法工程师，你需要对hivesql，clickhouse，mysql，sqlserver进行数据血缘分析解析得到输出表和字段级别映射，输出一套完整的python代码

以下是一个基本的 Python 代码示例，用于对 Hivesql、ClickHouse、MySQL 和 SQL Server 数据库进行数据血缘分析解析，并输出表和字段级别映射：

import sqlparse
import re
import pyodbc
import mysql.connector
from clickhouse_driver import Client

# 数据库连接配置
hiveserver2_host = 'localhost'
hiveserver2_port = 10000
clickhouse_host = 'localhost'
clickhouse_port = 9000
mysql_host = 'localhost'
mysql_port = 3306
mysql_user = 'root'
mysql_password = 'password'
mysql_database = 'test'
sqlserver_host = 'localhost'
sqlserver_port = 1433
sqlserver_user = 'sa'
sqlserver_password = 'password'
sqlserver_database = 'test'

# 数据库连接函数
def connect_to_hiveserver2():
    conn = pyodbc.connect('DSN=hive;HOST={0};PORT={1}'.format(hiveserver2_host, hiveserver2_port), autocommit=True)
    return conn.cursor()

def connect_to_clickhouse():
    client = Client(host=clickhouse_host, port=clickhouse_port)
    return client

def connect_to_mysql():
    conn = mysql.connector.connect(host=mysql_host, port=mysql_port, user=mysql_user, password=mysql_password, database=mysql_database)
    return conn.cursor()

def connect_to_sqlserver():
    conn = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server};SERVER={0},{1};DATABASE={2};UID={3};PWD={4}'.format(sqlserver_host, sqlserver_port, sqlserver_database, sqlserver_user, sqlserver_password))
    return conn.cursor()

# 解析 SQL 语句函数
def parse_sql(sql):
    parsed = sqlparse.parse(sql)
    stmt = parsed[0]
    return stmt.tokens

# 提取 SQL 语句中的表和字段函数
def extract_tables_fields(tokens):
    tables = set()
    fields = set()
    for token in tokens:
        if isinstance(token, sqlparse.sql.Identifier):
            identifier = str(token)
            if '.' in identifier:
                table, field = identifier.split('.')
                tables.add(table)
                fields.add(field)
            else:
                fields.add(identifier)
        elif isinstance(token, sqlparse.sql.IdentifierList):
            for identifier in token.get_identifiers():
                if '.' in str(identifier):
                    table, field = str(identifier).split('.')
                    tables.add(table)
                    fields.add(field)
                else:
                    fields.add(str(identifier))
        elif isinstance(token, sqlparse.sql.Where):
            where_tokens = token.tokens
            for where_token in where_tokens:
                if isinstance(where_token, sqlparse.sql.Comparison):
                    left_token, right_token = where_token.tokens[0], where_token.tokens[2]
                    if isinstance(left_token, sqlparse.sql.Identifier):
                        identifier = str(left_token)
                        if '.' in identifier:
                            table, field = identifier.split('.')
                            tables.add(table)
                            fields.add(field)
                        else:
                            fields.add(identifier)
                    if isinstance(right_token, sqlparse.sql.Identifier):
                        identifier = str(right_token)
                        if '.' in identifier:
                            table, field = identifier.split('.')
                            tables.add(table)
                            fields.add(field)
                        else:
                            fields.add(identifier)
    return tables, fields

# 建立表和字段映射关系函数
def build_mapping(tables, fields):
    mapping = {}
    for table in tables:
        if '.' in table:
            database, table_name = table.split('.')
        else:
            database = None
            table_name = table
        if database:
            columns = get_columns_from_database(database, table_name)
        else:
            columns = get_columns_from_table(table_name)
        for column in columns:
            if column in fields:
                mapping[table + '.' + column] = column
    return mapping

# 从数据库获取表字段函数
def get_columns_from_database(database, table_name):
    conn = pyodbc.connect('DRIVER={{ODBC Driver 17 for SQL Server}};SERVER={0},{1};DATABASE={2};UID={3};PWD={4}'.format(sqlserver_host, sqlserver_port, database, sqlserver_user, sqlserver_password))
    cursor = conn.cursor()
    cursor.execute('SELECT COLUMN_NAME FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = N\'' + table_name + '\'')
    columns = [column[0] for column in cursor.fetchall()]
    return columns

# 从表获取表字段函数
def get_columns_from_table(table_name):
    cursor = connect_to_mysql()
    cursor.execute('SHOW COLUMNS FROM ' + table_name)
    columns = [column[0] for column in cursor.fetchall()]
    return columns

# 主函数
def main():
    # Hivesql 数据库
    hivesql = 'SELECT a.id, a.name, b.age FROM table1 a JOIN table2 b ON a.id = b.id WHERE a.id = 1'
    hivesql_tokens = parse_sql(hivesql)
    hivesql_tables, hivesql_fields = extract_tables_fields(hivesql_tokens)
    hivesql_mapping = build_mapping(hivesql_tables, hivesql_fields)
    print('Hivesql 数据血缘分析解析：')
    print('表和字段映射关系：', hivesql_mapping)

    # ClickHouse 数据库
    clickhouse = 'SELECT id, name, age FROM table WHERE id = 1'
    clickhouse_tokens = parse_sql(clickhouse)
    clickhouse_tables, clickhouse_fields = extract_tables_fields(clickhouse_tokens)
    clickhouse_mapping = build_mapping(clickhouse_tables, clickhouse_fields)
    print('ClickHouse 数据血缘分析解析：')
    print('表和字段映射关系：', clickhouse_mapping)

    # MySQL 数据库
    mysql = 'SELECT id, name, age FROM table WHERE id = 1'
    mysql_tokens = parse_sql(mysql)
    mysql_tables, mysql_fields = extract_tables_fields(mysql_tokens)
    mysql_mapping = build_mapping(mysql_tables, mysql_fields)
    print('MySQL 数据血缘分析解析：')
    print('表和字段映射关系：', mysql_mapping)

    # SQL Server 数据库
    sqlserver = 'SELECT id, name, age FROM table WHERE id = 1'
    sqlserver_tokens = parse_sql(sqlserver)
    sqlserver_tables, sqlserver_fields = extract_tables_fields(sqlserver_tokens)
    sqlserver_mapping = build_mapping(sqlserver_tables, sqlserver_fields)
    print('SQL Server 数据血缘分析解析：')
    print('表和字段映射关系：', sqlserver_mapping)

if __name__ == '__main__':
    main()

以上代码示例仅为基本示例，实际应用中还需要考虑更多的情况，例如 SQL 方言的差异、数据库连接的异常处理、SQL 语句的优化等等。