AWS Athena export array of structs to JSON

Question

I\'ve got an Athena table where some fields have a fairly complex nested format. The backing records in S3 are JSON. Along these lines (but we have several more levels of nest

Answer 1

The python code from @tarun almost got me there, but I had to modify it in several ways due to my data. In particular, I have:

• json structures saved in Athena as strings
• Strings that contain multiple words, and therefore need to be in between double quotes. Some of them contain "[]" and "{}" symbols.

Here is the code that worked for me, hopefully will be useful for others:

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

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(sys.argv[1]) as f:
    headers = list(map(lambda f: f.strip(), f.readline().split(",")))
    print(headers)
    for line in f.readlines():

        orig_line = line
        #save the double quote cases, which mean there is a string with quotes inside
        line = re.sub('""', "#", orig_line)
        data = []
        for i, l in enumerate(line.split('","')):
            item = re.sub('^"|"$', "", l.rstrip())
            if (item[0] == "{" and item[-1] == "}") or (item[0] == "[" and item[-1] == "]"):
                data.append(headers[i] + ":" + item)
            else: #we have a string
                data.append(headers[i] + ": \"" + item + "\"")

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

        #restate the double quotes to single ones, once inside the json
        line = re.sub("#", '"', line)

        print(line)

Answer 2

I have skimmed through all the documentation and unfortunately there seems to be no way to do this as of now. The only possible workaround is

converting a struct to a json when querying athena

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

Or I would convert the data to json using post processing. Below script shows how

#!/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)

The output on your input data is

{"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}
}

Which is a valid JSON