Request payload size exceeds the limit: 10485760 bytes

I wrote a python dataflow job to read data from Bigquery 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 : 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.

Imported from Jira [BEAM-3455](https://issues.apache.org/jira/browse/BEAM-3455). Original Jira may contain additional context.
Reported by: unais.

Start with the Python Dataflow job that uses beam.io.BigQuerySource, beam.Partition, and the date-partitioned BigQuery output, then reproduce the 180-day case against the 8-day case. No repository file or test is named; done would require identifying the cause of the Dataflow API's 10,485,760-byte request limit and documenting or validating an appropriate correction.

Written by the indexing model from the issue text.