转换列并更新 DataFrame [英] Transforming a column and update the DataFrame

问题描述

所以，我在下面所做的是从 DataFrame 中删除一列 A 因为我想应用一个转换(这里我只是 json.加载 JSON 字符串)并用转换后的列替换旧列.转换后，我只是加入了两个结果数据帧.

So, what I'm doing below is I drop a column A from a DataFrame because I want to apply a transformation (here I just json.loads a JSON string) and replace the old column with the transformed one. After the transformation I just join the two resulting data frames.

df = df_data.drop('A').join(
    df_data[['ID', 'A']].rdd\
        .map(lambda x: (x.ID, json.loads(x.A)) 
             if x.A is not None else (x.ID, None))\
        .toDF()\
        .withColumnRenamed('_1', 'ID')\
        .withColumnRenamed('_2', 'A'),
    ['ID']
)

我不喜欢的当然是我面临的开销，因为我必须执行 withColumnRenamed 操作.

The thing I dislike about this is of course the overhead I'm faced because I had to do the withColumnRenamed operations.

使用熊猫我会做这样的事情:

With pandas All I'd do something like this:

pdf = pd.DataFrame([json.dumps([0]*np.random.randint(5,10)) for i in range(10)], columns=['A'])
pdf.A = pdf.A.map(lambda x: json.loads(x))
pdf

但以下在 pyspark 中不起作用:

but the following does not work in pyspark:

df.A = df[['A']].rdd.map(lambda x: json.loads(x.A))

那么有没有比我在第一个代码片段中所做的更简单的方法?

So is there an easier way than what I'm doing in my first code snipped?

推荐答案

我认为您不需要删除列并进行连接.以下代码应该^*与您发布的内容相同:

I do not think you need to drop the column and do the join. The following code should^* be equivalent to what you posted:

cols = df_data.columns
df = df_data.rdd\
    .map(
        lambda row: tuple(
            [row[c] if c != 'A' else (json.loads(row[c]) if row[c] is not None else None) 
             for c in cols]
        )
    )\
    .toDF(cols)

^*我还没有真正测试过这段代码，但我认为这应该可行.

但要回答您的一般问题，您可以使用 withColumn() 就地转换列.

But to answer your general question, you can transform a column in-place using withColumn().

df = df_data.withColumn("A", my_transformation_function("A").alias("A"))

其中 my_transformation_function() 可以是 udf 或 pyspark sql 函数.

Where my_transformation_function() can be a udf or a pyspark sql function.

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