Split JSON array into separate files/objects

Question

I have JSON exported from Cassandra in this format.

[
  {
    "correlationId": "2232845a8556cd3219e46ab8",
    "leg": 0,
    "tag": "received",
    "offset": 263128,
    "len": 30,
    "prev": {
      "page": {
        "file": 0,
        "page": 0
      },
      "record": 0
    },
    "data": "HEAD /healthcheck HTTP/1.1\r\n\r\n"
  },
  {
    "correlationId": "2232845a8556cd3219e46ab8",
    "leg": 0,
    "tag": "sent",
    "offset": 262971,
    "len": 157,
    "prev": {
      "page": {
        "file": 10330,
        "page": 6
      },
      "record": 1271
    },
    "data": "HTTP/1.1 200 OK\r\nDate: Wed, 14 Feb 2018 12:57:06 GMT\r\nServer: \r\nConnection: close\r\nX-CorrelationID: Id-2232845a8556cd3219e46ab8 0\r\nContent-Type: text/xml\r\n\r\n"
  }]

I would like to split it to separate documents:

{ "correlationId": "2232845a8556cd3219e46ab8", "leg": 0, "tag": "received", "offset": 263128, "len": 30, "prev": { "page": { "file": 0, "page": 0 }, "record": 0 }, "data": "HEAD /healthcheck HTTP/1.1\r\n\r\n" }

and

{ "correlationId": "2232845a8556cd3219e46ab8", "leg": 0, "tag": "sent", "offset": 262971, "len": 157, "prev": { "page": { "file": 10330, "page": 6 }, "record": 1271 }, "data": "HTTP/1.1 200 OK\r\nDate: Wed, 14 Feb 2018 12:57:06 GMT\r\nServer: \r\nConnection: close\r\nX-CorrelationID: Id-2232845a8556cd3219e46ab8 0\r\nContent-Type: text/xml\r\n\r\n" }

I wanted to use jq but didn't find way how.

Can you please advise way, how to split it by the document separator?

Thanks, Reddy

Answer 1

In case you have an array of 2 objects:

jq '.[0]' input.json > doc1.json && jq '.[1]' input.json > doc2.json

Results:

$ head -n100 doc[12].json
==> doc1.json <==
{
  "correlationId": "2232845a8556cd3219e46ab8",
  "leg": 0,
  "tag": "received",
  "offset": 263128,
  "len": 30,
  "prev": {
    "page": {
      "file": 0,
      "page": 0
    },
    "record": 0
  },
  "data": "HEAD /healthcheck HTTP/1.1\r\n\r\n"
}

==> doc2.json <==
{
  "correlationId": "2232845a8556cd3219e46ab8",
  "leg": 0,
  "tag": "sent",
  "offset": 262971,
  "len": 157,
  "prev": {
    "page": {
      "file": 10330,
      "page": 6
    },
    "record": 1271
  },
  "data": "HTTP/1.1 200 OK\r\nDate: Wed, 14 Feb 2018 12:57:06 GMT\r\nServer: \r\nConnection: close\r\nX-CorrelationID: Id-2232845a8556cd3219e46ab8 0\r\nContent-Type: text/xml\r\n\r\n"
}

Answer 2

You can do it more efficiently using Python (because you can read the entire input once, instead of once per document):

import json

docs = json.load(open('in.json'))

for ii, doc in enumerate(docs):
    with open('doc{}.json'.format(ii), 'w') as out:
        json.dump(doc, out, indent=2)

Answer 3

To split a json with many records into chunks of a desired size I simply use:

jq -c '.[0:1000]' mybig.json

which works like python slicing.

See the docs here: https://stedolan.github.io/jq/manual/

Array/String Slice: .[10:15]

The .[10:15] syntax can be used to return a subarray of an array or substring of a string. The array returned by .[10:15] will be of length 5, containing the elements from index 10 (inclusive) to index 15 (exclusive). Either index may be negative (in which case it counts backwards from the end of the array), or omitted (in which case it refers to the start or end of the array).

Answer 4

Using jq, one can split an array into its components using the filter:

.[]

The question then becomes what is to be done with each component. If you want to direct each component to a separate file, you could (for example) use jq with the -c option, and filter the result into awk, which can then allocate the components to different files. See e.g. Split JSON File Objects Into Multiple Files

Performance considerations

One might think that the overhead of calling jq+awk would be high compared to calling python, but both jq and awk are lightweight compared to python+json, as suggested by these timings (using Python 2.7.10):

time (jq -c  .[] input.json | awk '{print > "doc00" NR ".json";}')
user    0m0.005s
sys     0m0.008s

time python split.py
user    0m0.016s
sys     0m0.046s