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问题描述
如何使用 udfs 实现自定义爆炸功能,以便我们可以获得有关项目的额外信息?例如,除了项目,我还想拥有项目的索引.
How to implement a custom explode function using udfs, so we can have extra information on items? For example, along with items, I want to have items' indices.
我不知道该怎么做的部分是当 udf 返回多个值时,我们应该将这些值作为单独的行放置.
The part I do not know how to do is when a udf returns multiple values and we should place those values as separate rows.
推荐答案如果你需要自定义的explode函数,那么你需要写UDF来获取数组并返回数组.例如对于这个 DF:
If you need custom explode function, then you need to write UDF that gets array and returns array. For example for this DF:
df = spark.createDataFrame([(['a', 'b', 'c'], ), (['d', 'e'],)], ['array']) df.show() +---------+ | array| +---------+ |[a, b, c]| | [d, e]| +---------+添加索引和爆炸结果的函数可以是这样的:
The function that adds index and explodes the results can look like this:
from pyspark.sql.types import * value_with_index = StructType([ StructField('index', IntegerType()), StructField('letter', StringType()) ]) add_indices = udf(lambda arr: list(zip(range(len(arr)), arr)), ArrayType(value_with_index)) df.select(explode(add_indices('array'))).select('col.index', 'col.letter').show() +-----+------+ |index|letter| +-----+------+ | 0| a| | 1| b| | 2| c| | 0| d| | 1| e| +-----+------+更多推荐
PySpark DataFrame:自定义爆炸函数
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