30 lines
1.7 KiB
SQL
30 lines
1.7 KiB
SQL
{{ config(
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indexes = [{'columns':['_airbyte_emitted_at'],'type':'btree'}],
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unique_key = '_airbyte_ab_id',
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schema = "_airbyte_unibag",
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tags = [ "top-level-intermediate" ]
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) }}
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-- SQL model to parse JSON blob stored in a single column and extract into separated field columns as described by the JSON Schema
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-- depends_on: {{ source('unibag', '_airbyte_raw_districts') }}
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select
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{{ json_extract_scalar('_airbyte_data', ['_id'], ['_id']) }} as _id,
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{{ json_extract_scalar('_airbyte_data', ['city'], ['city']) }} as city,
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{{ json_extract_scalar('_airbyte_data', ['code'], ['code']) }} as code,
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{{ json_extract_scalar('_airbyte_data', ['name'], ['name']) }} as {{ adapter.quote('name') }},
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{{ json_extract_scalar('_airbyte_data', ['slug'], ['slug']) }} as slug,
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{{ json_extract_scalar('_airbyte_data', ['tncId'], ['tncId']) }} as tncid,
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{{ json_extract_scalar('_airbyte_data', ['cityId'], ['cityId']) }} as cityid,
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{{ json_extract_scalar('_airbyte_data', ['source'], ['source']) }} as {{ adapter.quote('source') }},
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{{ json_extract_scalar('_airbyte_data', ['tncCode'], ['tncCode']) }} as tnccode,
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{{ json_extract_scalar('_airbyte_data', ['gidoCode'], ['gidoCode']) }} as gidocode,
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{{ json_extract_scalar('_airbyte_data', ['osirisId'], ['osirisId']) }} as osirisid,
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{{ json_extract_scalar('_airbyte_data', ['updatedAt'], ['updatedAt']) }} as updatedat,
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{{ json_extract_scalar('_airbyte_data', ['searchString'], ['searchString']) }} as searchstring,
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_airbyte_ab_id,
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_airbyte_emitted_at,
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{{ current_timestamp() }} as _airbyte_normalized_at
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from {{ source('unibag', '_airbyte_raw_districts') }} as table_alias
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-- districts
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where 1 = 1
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