I have multiple JSON files. The files have two nested fields. The files are generated daily so I need to perform daily insert and update operations in the BigQuery table. I have shared Table schema in the image.
How to perform update operation on nested fields?
A little late, but in case someone else is searching. If you can use Standard SQL:
INSERT INTO your_table (optout_time, clicks, profile_id, opens, ... )
VALUES (
1552297347,
[
STRUCT(1539245347 as ts, 'url1' as url),
STRUCT(1539245341 as ts, 'url2' as url)
],
'whatever',
[
STRUCT(1539245347 as ts),
STRUCT(1539245341 as ts)
],
...
)
The BigQuery UI just provides import of JSONs to create new tables. So, to stream the content of the files into already existing tables BigQuery, you can write a small program in your favorite programming language using the client library.
I am going to assume you have your data as line-delimited JSONs looking like this:
{"optout_time": 1552297349, "clicks": {"ts": 1539245349, "url": "www.google.com"}, "profile_id": "foo", ...}
{"optout_time": 1532242949, "clicks": {"ts": 1530247349, "url": "www.duckduckgo.com"}, "profile_id": "bar", ...}
A python script to the job would look like this. It takes the json file names as command line arguments:
import json
import sys
from google.cloud import bigquery
dataset_id = "<DATASET-ID>" # the ID of your dataset
table_id = "<TABLE-ID>" # the ID of your table
client = bigquery.Client()
table_ref = client.dataset(dataset_id).table(table_id)
table = client.get_table(table_ref)
for f in sys.argv[1:]:
with open(f) as fh:
data = [json.loads(x) for x in fh]
client.insert_rows_json(table, data)
The nesting is taken care of automatically.
For pointers of how this sort of operation would look like in other languages, you can take a look at this documentation.