Lior Naim Alon
10/16/2025, 1:27 PM2025-10-16T13:05:43.487376Z [info     ] {'level': 'WARN', 'message': "Couldn't parse date/datetime string in hs_lifecyclestage_lead_date, trying to parse timestamp... Field value: 1709470649329. Ex: Unable to parse string [1709470649329]"} cmd_type=elb consumer=False job_name=staging:tap-hubspot-to-target-s3--raw-crm:eu-west-1-20251016 name=tap-hubspot producer=True run_id=0199ed1f-676c-7a87-ba25-9ddc70d8434c stdio=stderr string_id=tap-hubspot
Since the amount of data is very low and other ETLs are running fairly faster, I imagine the issue is with the amount of parsing errors and parsing attempts, logging the error, etc. it looks like there is a log entry for each row in the source data.
I tried (to no avail) to filter the specific fields using selection / custom mappers, but the errors persist.
It is crucial for me to use the airbyte variant as it is the only variant that supports custom hubspot objects out-of-the-box.
I'm looking for ways to tackle this issue - the goal is to make the ETL run as fast as a few minutes instead of 45 minutesEdgar Ramírez (Arch.dev)
10/17/2025, 9:43 PMLior Naim Alon
10/19/2025, 7:59 AM- name: tap-hubspot
    variant: airbyte
    pip_url: git+<https://github.com/MeltanoLabs/tap-airbyte-wrapper.git>
    config:
      airbyte_config:
        credentials:
          access_token: ${HUBSPOT_ACCESS_TOKEN}
          credentials_title: Private App Credentials
      force_native: true
    select:
    - companies.*
    - contacts.*
    schema:
      contacts :
        hs_lifecyclestage_lead_date:
          type: ["integer", "null"]
      companies :
        hs_lifecyclestage_lead_date:
          type: ["integer", "null"]