Databricks Pypark使用动态键处理嵌套json

2024-09-29 00:14:34 发布

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我有一个示例json数据文件,其结构如下:

{
    "Header": {
        "Code1": "abc",
        "Code2": "def",
        "Code3": "ghi",
        "Code4": "jkl",
    },
    "TimeSeries": {
        "2020-11-25T03:00:00+00:00": {
            "UnitPrice": 1000,
            "Amount": 10000,

        },
        "2020-11-26T03:00:00+00:00": {
            "UnitPrice": 1000,
            "Amount": 10000,

        }
    }
}

当我使用命令将其解析为数据块时:

df = spark.read.json("/FileStore/test.txt") 

我得到两个输出对象:Header和TimeSeries。对于TimeSeries,我希望能够展平结构,使其具有以下模式:

Date
UnitPrice
Amount 

由于日期字段是一个键,我目前只能通过迭代列名,然后在点表示法中动态使用它来访问它:

def flatten_json(data):


  columnlist = data.select("TimeSeries.*")
  count = 0 
  for name in data.select("TimeSeries.*"):
    df1 = data.select("Header.*").withColumn(("Timeseries"), lit(columnlist.columns[count])).withColumn("join", lit("a"))
    df2 = data.select("TimeSeries." + columnlist.columns[count] + ".*").withColumn("join", lit("a"))
    if count == 0: 
      df3 = df1.join(df2, on=['join'], how="inner")
    else: 
      df3 = df3.union(df1.join(df2, on=['join'], how="inner"))
    count = count + 1
  return(df3)

这远非理想。有人知道更好的方法来创建所描述的数据帧吗


Tags: jsondatacountselectamountheaderdf1timeseries
1条回答
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1楼 · 发布于 2024-09-29 00:14:34

这个想法:

  • 步骤1:分别提取头和时间序列

  • 步骤2:对于TimeSeries对象中的每个字段,提取AmountUnitPrice,连同字段的name,将它们填充到一个结构中

  • 步骤3:将所有这些结构合并到一个数组列中,并分解它

  • 步骤4:从分解的列中提取TimeseriesAmountUnitPrice

  • 步骤5:与标题行交叉连接

import pyspark.sql.functions as F

header_df = df.select("Header.*")
timeseries_df = df.select("TimeSeries.*")
fieldNames = enumerate(timeseries_df.schema.fieldNames())
cols = [F.struct(F.lit(name).alias("Timeseries"), col(name).getItem("Amount").alias("Amount"), col(name).getItem("UnitPrice").alias("UnitPrice")).alias("ts_" + str(idx)) for idx, name in fieldNames]
combined = explode(array(cols)).alias("comb")
timeseries = timeseries_df.select(combined).select('comb.Timeseries', 'comb.Amount', 'comb.UnitPrice')
result = header_df.crossJoin(timeseries)
result.show(truncate = False)

输出:

+  -+  -+  -+  -+            -+   +    -+
|Code1|Code2|Code3|Code4|Timeseries               |Amount|UnitPrice|
+  -+  -+  -+  -+            -+   +    -+
|abc  |def  |ghi  |jkl  |2020-11-25T03:00:00+00:00|10000 |1000     |
|abc  |def  |ghi  |jkl  |2020-11-26T03:00:00+00:00|10000 |1000     |
+  -+  -+  -+  -+            -+   +    -+

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