这里的col1和col2是JSON中的顶级字段,nested_json_field是包含嵌套JSON的字段名。通过使用selectExpr函数,我们可以将嵌套的JSON字段展开为DataFrame中的多个列。 将DataFrame转换为TSV格式: 代码语言:txt 复制 tsv_data = flatten_data.selectExpr("col1", "col2", "concat_ws('\t', *) as tsv_data") 使用c...
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Assume we have below nested JSON data: [ { "data": { "city": { "addresses": [ { "id": "my-id" }, { "id": "my-id2" } ] } } } ] To hash the nested id field you need to write the following PySpark code: import pyspark.sql.functions as F hashed = df.withColumn("data...
defflatten(df:DataFrame,delimiter="_")->DataFrame:'''Flatten nested struct columns in `df` by one level separated by `delimiter`, i.e.:df = [ {'a': {'b': 1, 'c': 2} } ]df = flatten(df, '_')-> [ {'a_b': 1, 'a_c': 2} ]'''flat_cols=[nameforname,typeindf.dtyp...
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需要把数字类型转化为字符串类型，再进行连接 第一种 df1 = pd.DataFrame({'Year': ['2014', '...