- Is this your first time deploying Airbyte?: Yes
- OS Version / Instance: Windows
- Memory / Disk: you can use something like 4Gb / 1 Tb
- Deployment: Docker
- Airbyte Version: * 0.39.39-alpha
- Source name/version: PostGres
- Destination name/version: Snowflake
- Step: The issue is happening during sync,
- Description: Data types for source columns not replicating in destination tables. All of the columns are being cast to a varchar. Also, all varchars are not keeping the original max value. For example, in the source there is a varchar(50) which is being rendered as a varchar(16777216), which is Snowflake’s default max value.
Any help would be appreciated, and please let me know if you need more information.
Thanks
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What version of Postgres SQL are you using?
Can you share a screenshoot of the replication tab with the catalog? (see example below)
Can you share a sync log? Which shows the catalog data type converted too.
Hello, apologize for the late reply. To answer your questions:
-Postgres version is PostgreSQL 12.12 on x86_64-pc-linux-gnu
I have also attached a copy of my most recent sync log as well as a screenshot of the replication tab.
logs-291.txt (389.3 KB)
Thanks,
Casey Douthitt
One example from your logs:
2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column address_type_id (type int8[19]) -> JsonSchemaType({type=number})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column country (type bpchar[2]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column subdivision (type varchar[50]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column city (type varchar[500]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column street1 (type varchar[500]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column street2 (type varchar[500]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column postal_code (type varchar[100]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column latitude (type float8[17]) -> JsonSchemaType({type=number})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column longitude (type float8[17]) -> JsonSchemaType({type=number})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column name (type varchar[125]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column attention (type varchar[500]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column is_primary (type bpchar[1]) -> JsonSchemaType({type=string})2022-11-27 11:07:47 e[44msourcee[0m > 2022-11-27 11:07:47 e[32mINFOe[m i.a.i.s.j.AbstractJdbcSource(lambda$discoverInternal$5):145 - Table addresses column needs_geocode (type bool[1]) -> JsonSchemaType({type=boolean})
It doesn’t look all the columns are mapped to string. Can you expand the instreg_s stream to see what data types Airbyte is reading?
Hello,
I was able to fix the problem of of having the wrong data types in the destination. The only thing left is to have the varchar max values transfer over from postgres into snowflake. For example, the varchars are listed as varchar(500) in Postgres, and are listed as varchar(16777216). Is there a way to have the varchars the same size after synching?
Thanks,
Casey Douthitt
