AWS Athena将结构数组导出为JSON

Question

我有一个Athena表,其中一些字段具有相当复杂的嵌套格式.S3中的后备记录是JSON.沿着这些方向(但我们有几个级别的嵌套):

CREATE EXTERNAL TABLE IF NOT EXISTS test (
  timestamp double,
  stats array<struct<time:double, mean:double, var:double>>,
  dets array<struct<coords: array<double>, header:struct<frame:int, 
    seq:int, name:string>>>,
  pos struct<x:double, y:double, theta:double>
)
ROW FORMAT SERDE 'org.openx.data.jsonserde.JsonSerDe'
WITH SERDEPROPERTIES ('ignore.malformed.json'='true')
LOCATION 's3://test-bucket/test-folder/'

现在我们需要能够查询数据并将结果导入Python进行分析.由于安全限制,我无法直接连接到雅典娜; 我需要能够给某人查询,然后他们会给我CSV结果.

如果我们只是直接选择*,我们以不完全JSON的格式返回struct/array列.这是一个示例输入文件条目:

{"timestamp":1520640777.666096,"stats":[{"time":15,"mean":45.23,"var":0.31},{"time":19,"mean":17.315,"var":2.612}],"dets":[{"coords":[2.4,1.7,0.3], "header":{"frame":1,"seq":1,"name":"hello"}}],"pos": {"x":5,"y":1.4,"theta":0.04}}

示例输出:

select * from test

"timestamp","stats","dets","pos"
"1.520640777666096E9","[{time=15.0, mean=45.23, var=0.31}, {time=19.0, mean=17.315, var=2.612}]","[{coords=[2.4, 1.7, 0.3], header={frame=1, seq=1, name=hello}}]","{x=5.0, y=1.4, theta=0.04}"

我希望以更方便的格式导出那些嵌套字段 - 用JSON获取它们会很棒.

不幸的是,似乎转换为JSON只适用于地图而不是结构,因为它只是将所有内容展平为数组:

SELECT timestamp, cast(stats as JSON) as stats, cast(dets as JSON) as dets, cast(pos as JSON) as pos FROM "sampledb"."test"

"timestamp","stats","dets","pos"
"1.520640777666096E9","[[15.0,45.23,0.31],[19.0,17.315,2.612]]","[[[2.4,1.7,0.3],[1,1,""hello""]]]","[5.0,1.4,0.04]"

是否有一种转换为JSON(或其他易于导入的格式)的好方法,还是应该继续进行自定义解析功能？

Answer 1

我浏览了所有文档，不幸的是，到目前为止似乎没有办法做到这一点。唯一可能的解决方法是

查询 athena 时将结构转换为 json

SELECT
  my_field,
  my_field.a,
  my_field.b,
  my_field.c.d,
  my_field.c.e
FROM 
  my_table

或者我会使用后处理将数据转换为 json。下面的脚本显示了如何

#!/usr/bin/env python
import io
import re

pattern1 = re.compile(r'(?<={)([a-z]+)=', re.I)
pattern2 = re.compile(r':([a-z][^,{}. [\]]+)', re.I)
pattern3 = re.compile(r'\\"', re.I)

with io.open("test.csv") as f:
    headers = list(map(lambda f: f.strip(), f.readline().split(",")))
    for line in f.readlines():
        orig_line = line
        data = []
        for i, l in enumerate(line.split('","')):
            data.append(headers[i] + ":" + re.sub('^"|"$', "", l))

        line = "{" + ','.join(data) + "}"
        line = pattern1.sub(r'"\1":', line)
        line = pattern2.sub(r':"\1"', line)
        print(line)

输入数据的输出是

{"timestamp":1.520640777666096E9,"stats":[{"time":15.0, "mean":45.23, "var":0.31}, {"time":19.0, "mean":17.315, "var":2.612}],"dets":[{"coords":[2.4, 1.7, 0.3], "header":{"frame":1, "seq":1, "name":"hello"}}],"pos":{"x":5.0, "y":1.4, "theta":0.04}
}

哪个是有效的 JSON