返回超过字符长度限制的列列表- pyspark/snowflake

from pyspark.sql import SparkSession
from pyspark.sql.functions import length, when, substring

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 读取数据
df = spark.read.format("snowflake").options(**snowflake_options).option("query", "SELECT * FROM table").load()

# 获取超过字符长度限制的列列表
columns = df.columns
max_length = 100  # 假设字符长度限制为100

# 使用selectExpr函数返回超过字符长度限制的列列表
columns_list = []
for column in columns:
    column_length = df.selectExpr(f"length({column}) as length").collect()[0]["length"]
    if column_length > max_length:
        column_list = df.selectExpr(f"substring({column}, 1, {max_length}) as {column}").columns
    else:
        column_list = [column]
    columns_list.extend(column_list)

# 打印超过字符长度限制的列列表
print(columns_list)

import snowflake.connector

# 创建Snowflake连接
conn = snowflake.connector.connect(
    user='your_user',
    password='your_password',
    account='your_account',
    warehouse='your_warehouse',
    database='your_database',
    schema='your_schema'
)

# 执行SHOW COLUMNS语句
cursor = conn.cursor()
cursor.execute("SHOW COLUMNS IN your_table")

# 获取超过字符长度限制的列列表
columns_list = []
for row in cursor:
    column_name = row[1]
    column_length = row[2]
    max_length = 100  # 假设字符长度限制为100
    if column_length > max_length:
        column_list = [f"SUBSTRING({column_name}, 1, {max_length}) AS {column_name}"]
    else:
        column_list = [column_name]
    columns_list.extend(column_list)

# 打印超过字符长度限制的列列表
print(columns_list)