Add support for BigQuery bulk export (to Avro, for now) #136
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389: tests/integration/***** 373: setup.py 364: records_mover/records/schema/field/__init__.py Reduce total number of bigfiles violations to 1103 or below!
vinceatbluelabs
commented
Dec 1, 2020
| @@ -1 +1 @@ | |||
| 1103 | |||
| 1125 | |||
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389: tests/integration/*****
373: setup.py
364: records_mover/records/schema/field/__init__.py
Reduce total number of bigfiles violations to 1103 or below!
vinceatbluelabs
commented
Dec 1, 2020
| @@ -87,8 +87,6 @@ def load_from_fileobj(self, schema: str, table: str, | |||
| # https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.client.Client.html#google.cloud.bigquery.client.Client.load_table_from_file | |||
| job = client.load_table_from_file(fileobj, | |||
| f"{schema}.{table}", | |||
| # Must match the destination dataset location. | |||
| location="US", | |||
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I'm not convinced this was ever needed - it's in the example code, but everything seems to run fine without it, so there must be some inference logic to figure out the dataset location based on the client object.
vinceatbluelabs
commented
Dec 1, 2020
| # support any direct conversion from an Avro type into a | ||
| # DATETIME field." | ||
| # | ||
| return records_schema.convert_datetimes_to_string() |
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This came up during the table2table integration test; BigQuery fails to load if you try to load the same string it exports from a DATETIME column into a DATETIME column.
cwegrzyn
approved these changes
Dec 1, 2020
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This is just enough code to be able to move a table from BigQuery to BigQuery via a GCS bucket.
It turns out that BigQuery doesn't export via Parquet, so the easiest path was to add the first steps of Avro support to Records Mover, and to allow Avro on BigQuery import.
In addition to that functionality, it lays the groundwork for general BigQuery export, which will be useful for moving to other places like Redshift as well.
To get BigQuery->Redshift to work for medium-sized tables, we'll probably need one of:
To get BigQuery->Redshift to work for large tables, we'll need some kind of GCS->S3 copying at scale. In typical vendor fashion, I think the GCP stuff I played around with in #132 is S3->GCS only. We might also need to teach BigQuery, Redshift and the Records spec about compressed Avro files, as well.