I wrote a python dataflow job to read data from biqquery and do some transform and save the result as bq table..
I tested with 8 days data it works fine - when I scaled to 180 days I’m getting the below error ```"message": "Request payload size exceeds the limit: 10485760 bytes.",``` ```pitools.base.py.exceptions.HttpError: HttpError accessing < https://dataflow.googleapis.com/v1b3/projects/careem-mktg-dwh/locations/us-central1/jobs?alt=json>: response: <{'status': '400', 'content-length': '145', 'x-xss-protection': '1; mode=block', 'x-content-type-options': 'nosniff', 'transfer-encoding': 'chunked', 'vary': 'Origin, X-Origin, Referer', 'server': 'ESF', '-content-encoding': 'gzip', 'cache-control': 'private', 'date': 'Wed, 10 Jan 2018 22:49:32 GMT', 'x-frame-options': 'SAMEORIGIN', 'alt-svc': 'hq=":443"; ma=2592000; quic=51303431; quic=51303339; quic=51303338; quic=51303337; quic=51303335,quic=":443"; ma=2592000; v="41,39,38,37,35"', 'content-type': 'application/json; charset=UTF-8'}>, content <{ "error": { "code": 400, "message": "Request payload size exceeds the limit: 10485760 bytes.", "status": "INVALID_ARGUMENT" } ``` In short, this is what I’m doing 1 - Reading data from bigquery table using ```beam.io.BigQuerySource ``` 2 - Partitioning each days using ``` beam.Partition ``` 3- Applying transforms each partition and combining some output P-Collections. 4- After the transforms, the results are saved to a biqquery date partitioned table.
