Updating json field in Postgres

Question

Querying Postgres 9.3 by json field is really great. However i couldn\'t find a formal way to update the json object, for which i use an internal function written in plp

Answer 1

for people who want plv8 (trusted language usable on services like Heroku). I often need to do migrations or updates to json blobs and running a query directly on the db is much faster than downloading all the data, transforming it and then posting an update.

CREATE EXTENSION plv8;
CREATE OR REPLACE FUNCTION json_replace_string(obj json, path text, value text, force boolean)
RETURNS json AS $$
if (value === null && !force) {
  return obj;
}
var nestedRe = /(\.|\[)/;
var scrub = /]/g;
path = path.replace(scrub, '');
var pathBits = path.split(nestedRe);
var len = pathBits.length;
var layer = obj;
for (var i = 0; i < len; i += 2) {
  if (layer === null || layer === undefined) return obj;
  var key = pathBits[i];
  if (key === '') continue;
  if (i === len - 1) {
    layer[key] = value;
  } else {
    if (force && typeof layer[key] === 'undefined') {
      layer[key] = pathBits[i+1] === '.' ? {} : [];
    }
    layer = layer[key];
  }
}
return obj;
$$ LANGUAGE plv8 IMMUTABLE;

You can use this like so

UPDATE my_table
SET blob=json_replace_string(blob, 'some.nested.path[5].to.object', 'new value', false)
WHERE some_condition;

the force parameter serves two functions - (1) lets you set a null value. If you are dynamically generating the value based on other columns that don't exist - e.g. blob->'non_existent_value' then null will be input into the function and you probably don't mean to set the value to null. The (2) purpose is to force the creation of the nested path if it doesn't already exist in the json object you are mutating. e.g

json_replace(string('{"some_key": "some_val"}', 'other_key', 'new_val', true)

gives

{"some_key": "some_val", "other_key": "new_val"}

You can imagine similar functions to update numeric, delete keys etc. This basically enables mongo like functionality inside postgres during the early stages of new features for quick prototyping and as our schema stabilizes we break things out to independent columns and tables to get the best performance.