Bug/redshift json parse

.buildkite/pipeline.yml

@@ -58,7 +58,7 @@ steps:
     commands: |
       bash .buildkite/scripts/run_models.sh redshift
 
-  - label: ":bricks: Run Tests - Databricks"
+  - label: ":databricks: Run Tests - Databricks"
     key: "run_dbt_databricks"
     plugins:
       - docker#v3.13.0:

CHANGELOG.md

@@ -1,3 +1,27 @@
+# dbt_fivetran_log v1.5.0
+[PR #114](https://github.com/fivetran/dbt_fivetran_log/pull/114) includes the following updates:
+
+## Breaking Changes
+> ⚠️ Since the following changes are breaking, we recommend running a `--full-refresh` after upgrading to this version.
+- For Bigquery and Databricks destinations, updated the `partition_by` config to coordinate with the filter used in the incremental logic.
+- For Snowflake destinations, added a `cluster_by` config for performance. 
+
+## Feature Updates
+- Updated incremental logic for `fivetran_platform__audit_table` so that it looks back 7 days to catch any late arriving records.
+- Updated JSON parsing logic in the following models to prevent run failures when incoming JSON-like strings are invalid. 
+  - `fivetran_platform__audit_table`
+  - `fivetran_platform__audit_user_activity`
+  - `fivetran_platform__connector_daily_events`
+  - `fivetran_platform__connector_status`
+  - `fivetran_platform__schema_changelog`
+- Updated `fivetran_platform__connector_status` to parse only a subset of the `message_data` field to improve compute.
+
+## Under The Hood
+- Added macros:
+  - `fivetran_log_json_parse` to handle the updated JSON parsing.
+  - `fivetran_log_lookback` for use in `fivetran_platform__audit_table`.
+- Updated seeds to test handling of invalid JSON strings.
+
 # dbt_fivetran_log v1.4.3
 [PR #112](https://github.com/fivetran/dbt_fivetran_log/pull/112) includes the following updates:
 

README.md

@@ -66,7 +66,7 @@ Include the following Fivetran Platform package version range in your `packages.
 ```yaml
 packages:
   - package: fivetran/fivetran_log
-    version: [">=1.4.0", "<1.5.0"]
+    version: [">=1.5.0", "<1.6.0"]
 ```
 
 > Note that altough the source connector is now "Fivetran Platform", the package retains the old name of "fivetran_log".

dbt_project.yml

@@ -1,6 +1,6 @@
 config-version: 2
 name: 'fivetran_log'
-version: '1.4.3'
+version: '1.5.0'
 require-dbt-version: [">=1.3.0", "<2.0.0"]
 
 models:

integration_tests/dbt_project.yml

@@ -1,5 +1,5 @@
 name: 'fivetran_log_integration_tests'
-version: '1.4.3'
+version: '1.5.0'
 
 config-version: 2
 profile: 'integration_tests'

integration_tests/seeds/connector.csv

@@ -1,3 +1,4 @@
 connector_id,_fivetran_synced,connecting_user_id,connector_name,connector_type,destination_id,paused,signed_up,_fivetran_deleted
 this_connector,2021-03-12 21:03:45.994,,this_connector,s3,ups_trampoline,true,2020-08-31 19:00:22.913630,false
 this_connector,2021-03-12 21:03:45.991,off_ence,this_connector,s3,television_trace,true,2019-03-22 18:49:12.833910,true
+aft_gleeful,2023-05-18 15:57:06.879000,intimation_awkwardly,test,s3,obtained_willow,true,2020-05-18 18:13:43.563198,false

integration_tests/seeds/destination.csv

@@ -1,3 +1,4 @@
 id,_fivetran_synced,account_id,created_at,name,region
 ups_trampoline,2021-03-12 20:20:40.650,1k56c2c4xlti6_acct,2019-07-09 07:21:03.935607,s_test,us-test
-television_trace,2021-03-12 20:20:40.624,1k56c2c4xlti6_acct,2019-07-10 08:07:48.374015,s_gcp,us-test
+television_trace,2021-03-12 20:20:40.624,1k56c2c4xlti6_acct,2019-07-10 08:07:48.374015,s_gcp,us-test
+obtained_willow,2023-05-18 15:55:02.025000,1k56c2c4xlti6_acc,2020-05-18 17:28:42.535908,dbt_package_testing_bigquery,us-test

integration_tests/seeds/log.csv

@@ -23,9 +23,10 @@ H6AsShJjRoy1n75oVRxjQ08perA=,2021-12-09 14:26:29.814,2021-12-09 20:30:53.903,int
 bCgsj8twLxBBhaiBN9N4S35grkI=,2021-12-09 14:26:29.744,2021-12-09 20:30:53.901,intrinsic_departed,INFO,"{""table"":""user_history""}",write_to_table_start,123,456abc
 UcIZasAY/eulDQF2SQM6Y5W83gU=,2021-12-09 14:26:29.719,2021-12-09 20:30:53.878,intrinsic_departed,INFO,"{""table"":""media_insights""}",write_to_table_start,123,456abc
 mm0QUb+ldnbSWknrBrF/v24YGvo=,2021-12-09 14:26:05.907,2021-12-09 20:30:53.778,intrinsic_departed,INFO,,sync_start,123,456abc
-Z/kZAi7u6DzO7UrZeWK/ZsAkbno=,2021-12-10 14:27:00.504,2021-12-10 20:30:53.959,intrinsic_departed,INFO,,sync_end,123,456abc
+Z/kZAi7u6DzO7UrZeWK/ZsAkbno=,2021-12-10 14:27:00.504,2021-12-10 20:30:53.959,intrinsic_departed,INFO,,sync_end,,456abc
 +IX63qGrDFPaTy9/6epjpppk4JI=,2021-12-10 14:26:41.875,2021-12-10 20:30:53.948,intrinsic_departed,INFO,"{""table"":""media_insights""}",write_to_table_end,123,456abc
 ZZLSXVYxirh8aKlgdCzo5fvd71g=,2021-12-10 14:26:42.029,2021-12-10 20:30:53.949,intrinsic_departed,INFO,"{""schema"":""instagram_business"",""count"":5,""operationType"":""REPLACED_OR_INSERTED"",""table"":""media_insights""}",records_modified,123,456abc
 D7UqnKYn6OT04HkUcPNjXA95ttI=,2021-12-10 14:26:29.719,2021-12-10 20:30:53.878,intrinsic_departed,INFO,"{""table"":""media_insights""}",write_to_table_start,123,456abc
 V3H62Gj5c6nB8bY+OdxMHvp/hNs=,2021-12-10 14:26:05.907,2021-12-10 20:30:53.778,intrinsic_departed,INFO,,sync_start,123,456abc
-jkLxnPUfQ/9mHaWCmxUQEhul8ZA=,2023-11-09 11:31:31.579000,2023-11-09 15:55:12.560000,protestations_mourned,INFO,"{""actor"":""[email protected]"",""properties"":{""endpoint"":""************"",""apiKey"":""************"",""customEvents"":[],""syncMode"":""AllEvents"",""isE2ETest"":false,""events"":[],""customEventSyncMode"":""AllEvents""},""id"":""iterable""}",create_connector,,
+jkLxnPUfQ/9mHaWCmxUQEhul8ZA=,2023-11-09 11:31:31.579000,2023-11-09 15:55:12.560000,protestations_mourned,INFO,"{""actor"":""[email protected]"",""properties"":{""endpoint"":""************"",""apiKey"":""************"",""customEvents"":[],""syncMode"":""AllEvents"",""isE2ETest"":false,""events"":[],""customEventSyncMode"":""AllEvents""},""id"":""iterable""}",create_connector,,
+R7UqnKYn6OT04HkUcPNjXA95qqI=,2021-12-10 16:26:29.719,2021-12-10 20:30:53.878,intrinsic_departed,INFO,says actor but not a json,status,,456abc

macros/fivetran_log_json_parse.sql

@@ -0,0 +1,42 @@
+{% macro fivetran_log_json_parse(string, string_path) -%}
+
+{{ adapter.dispatch('fivetran_log_json_parse', 'fivetran_log') (string, string_path) }}
+
+{%- endmacro %}
+
+{% macro default__fivetran_log_json_parse(string, string_path) %}
+
+  {{ fivetran_utils.json_parse(string=string, string_path=string_path) }}
+
+{% endmacro %}
+
+{% macro snowflake__fivetran_log_json_parse(string, string_path) %}
+
+  try_parse_json({{ string }}) {%- for s in string_path -%}{% if s is number %}[{{ s }}]{% else %}['{{ s }}']{% endif %}{%- endfor -%}
+
+{% endmacro %}
+
+{% macro redshift__fivetran_log_json_parse(string, string_path) %}
+
+  json_extract_path_text(
+    {{ string }}, 
+    {%- for s in string_path -%}'{{ s }}'{%- if not loop.last -%},{%- endif -%}{%- endfor -%}, 
+    true ) -- this flag sets null_if_invalid=true
+
+{% endmacro %}
+
+{% macro postgres__fivetran_log_json_parse(string, string_path) %}
+
+  case when {{ string }} ~ '^\s*[\{].*[\}]?\s*$' -- Postgres has no native json check, so this will check the string for indicators of a JSON object
+    then {{ string }}::json #>> '{ {%- for s in string_path -%}{{ s }}{%- if not loop.last -%},{%- endif -%}{%- endfor -%} }'
+    else null end
+
+{% endmacro %}
+
+{% macro sqlserver__fivetran_log_json_parse(string, string_path) %}
+
+  case when isjson({{ string }}) = 1 -- check if json string is valid
+    then json_value({{ string }}, '$.{%- for s in string_path -%}{{ s }}{%- if not loop.last -%}.{%- endif -%}{%- endfor -%} ')
+    else null end
+
+{% endmacro %}

macros/fivetran_log_lookback.sql

@@ -0,0 +1,35 @@
+{% macro fivetran_log_lookback(from_date, datepart='day', interval=7, default_start_date='2010-01-01') %}
+
+{{ adapter.dispatch('fivetran_log_lookback', 'fivetran_log') (from_date, datepart='day', interval=7, default_start_date='2010-01-01') }}
+
+{%- endmacro %}
+
+{% macro default__fivetran_log_lookback(from_date, datepart='day', interval=7, default_start_date='2010-01-01')  %}
+
+    coalesce(
+        (select {{ dbt.dateadd(datepart=datepart, interval=-interval, from_date_or_timestamp=from_date) }} 
+            from {{ this }}), 
+        {{ "'" ~ default_start_date ~ "'" }}
+        )
+
+{% endmacro %}
+
+{% macro bigquery__fivetran_log_lookback(from_date, datepart='day', interval=7, default_start_date='2010-01-01')  %}
+
+    -- Capture the latest timestamp in a call statement instead of a subquery for optimizing BQ costs on incremental runs
+    {%- call statement('date_agg', fetch_result=True) -%}
+        select {{ from_date }} from {{ this }}
+    {%- endcall -%}
+
+    -- load the result from the above query into a new variable
+    {%- set query_result = load_result('date_agg') -%}
+
+    -- the query_result is stored as a dataframe. Therefore, we want to now store it as a singular value.
+    {%- set date_agg = query_result['data'][0][0] %}
+
+    coalesce(
+        {{ dbt.dateadd(datepart='day', interval=-7, from_date_or_timestamp="'" ~ date_agg ~ "'") }}, 
+        {{ "'" ~ default_start_date ~ "'" }}
+        )
+
+{% endmacro %}

models/fivetran_platform__audit_table.sql

@@ -2,10 +2,10 @@
     materialized='incremental',
     unique_key='unique_table_sync_key',
     partition_by={
-        'field': 'sync_start',
-        'data_type': 'timestamp',
-        'granularity': 'day'
+        'field': 'sync_start_day',
+        'data_type': 'date'
     } if target.type == 'bigquery' else ['sync_start_day'],
+    cluster_by = ['sync_start_day'],
     incremental_strategy='insert_overwrite' if target.type in ('bigquery', 'spark', 'databricks') else 'delete+insert',
     file_format='parquet'
 ) }}
@@ -14,30 +14,17 @@ with sync_log as (
 
     select 
         *,
-        {{ fivetran_utils.json_parse(string='message_data', string_path=['table']) }} as table_name
+        {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['table']) }} as table_name
     from {{ ref('stg_fivetran_platform__log') }}
     where event_subtype in ('sync_start', 'sync_end', 'write_to_table_start', 'write_to_table_end', 'records_modified')
 
     {% if is_incremental() %}
 
-    -- Capture the latest timestamp in a call statement instead of a subquery for optimizing BQ costs on incremental runs
-    {%- call statement('max_sync_start', fetch_result=True) -%}
-        select cast(max(sync_start) as date) from {{ this }}
-    {%- endcall -%}
-
-    -- load the result from the above query into a new variable
-    {%- set query_result = load_result('max_sync_start') -%}
-
-    -- the query_result is stored as a dataframe. Therefore, we want to now store it as a singular value.
-    {%- set max_sync_start = query_result['data'][0][0] -%}
-
-    -- compare the new batch of data to the latest sync already stored in this model
-    and cast(created_at as date) > '{{ max_sync_start }}'
+    and cast(created_at as date) > {{ fivetran_log.fivetran_log_lookback(from_date='max(sync_start_day)', interval=7) }}
 
     {% endif %}
 ),
 
-
 connector as (
 
     select *
@@ -93,10 +80,10 @@ records_modified_log as (
     select 
         connector_id,
         created_at,
-        {{ fivetran_utils.json_parse(string='message_data', string_path=['table']) }} as table_name,
-        {{ fivetran_utils.json_parse(string='message_data', string_path=['schema']) }} as schema_name,
-        {{ fivetran_utils.json_parse(string='message_data', string_path=['operationType']) }} as operation_type,
-        cast ({{ fivetran_utils.json_parse(string='message_data', string_path=['count']) }} as {{ dbt.type_int() }}) as row_count
+        {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['table']) }} as table_name,
+        {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['schema']) }} as schema_name,
+        {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['operationType']) }} as operation_type,
+        cast ({{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['count']) }} as {{ dbt.type_int() }}) as row_count
     from sync_log 
     where event_subtype = 'records_modified'
 
@@ -146,9 +133,9 @@ final as (
     select 
         *,
         {{ dbt_utils.generate_surrogate_key(['schema_name','connector_id', 'destination_id', 'table_name', 'write_to_table_start']) }} as unique_table_sync_key, -- for incremental materialization 
-        {{ dbt.date_trunc('day', 'sync_start') }} as sync_start_day -- for partitioning in databricks
+        cast({{ dbt.date_trunc('day', 'sync_start') }} as date) as sync_start_day -- for partitioning
     from sum_records_modified
 )
 
 select *
-from final
+from final

models/fivetran_platform__audit_user_activity.sql

@@ -2,7 +2,7 @@ with logs as (
 
     select 
         *,
-        {{ fivetran_utils.json_parse(string='message_data', string_path=['actor']) }} as actor_email
+        {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path='actor') }} as actor_email
     from {{ ref('stg_fivetran_platform__log') }}
     where lower(message_data) like '%actor%'
 ),

models/fivetran_platform__connector_daily_events.sql

@@ -16,7 +16,7 @@ log_events as (
             when event_subtype in ('create_table', 'alter_table', 'create_schema', 'change_schema_config') then 'schema_change' 
             else event_subtype end as event_subtype,
 
-        sum(case when event_subtype = 'records_modified' then cast( {{ fivetran_utils.json_parse(string='message_data', string_path=['count']) }} as {{ dbt.type_int()}} )
+        sum(case when event_subtype = 'records_modified' then cast( {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['count']) }} as {{ dbt.type_int()}} )
         else 1 end) as count_events 
 
     from {{ ref('stg_fivetran_platform__log') }}

models/fivetran_platform__connector_status.sql

@@ -1,28 +1,39 @@
 with transformation_removal as (
 
-    select *
+    select 
+        *,
+        case when event_subtype in ('status', 'sync_end')
+            then message_data
+            else null 
+        end as filtered_message_data
     from {{ ref('stg_fivetran_platform__log') }}
     where transformation_id is null
+),
 
+parse_json as (
+    select
+        *,
+        {{ fivetran_log.fivetran_log_json_parse(string="filtered_message_data", string_path=["status"]) }} as log_status,
+        {{ fivetran_log.fivetran_log_json_parse(string="filtered_message_data", string_path=["reason"]) }} as log_reason
+    from transformation_removal
 ),
 
 connector_log as (
     select 
         *,
         sum( case when event_subtype in ('sync_start') then 1 else 0 end) over ( partition by connector_id 
             order by created_at rows unbounded preceding) as sync_batch_id
-    from transformation_removal
+    from parse_json
     -- only looking at errors, warnings, and syncs here
     where event_type = 'SEVERE'
         or event_type = 'WARNING'
         or event_subtype like 'sync%'
         or (event_subtype = 'status' 
-            and {{ fivetran_utils.json_parse(string="message_data", string_path=["status"]) }} = 'RESCHEDULED'
-
-            and {{ fivetran_utils.json_parse(string="message_data", string_path=["reason"]) }} like '%intended behavior%'
+            and log_status = 'RESCHEDULED'
+            and log_reason like '%intended behavior%'
             ) -- for priority-first syncs. these should be captured by event_type = 'WARNING' but let's make sure
         or (event_subtype = 'status' 
-            and {{ fivetran_utils.json_parse(string="message_data", string_path=["status"]) }} = 'SUCCESSFUL'
+            and log_status = 'SUCCESSFUL'
         )
         -- whole reason is "We have rescheduled the connector to force flush data from the forward sync into your destination. This is intended behavior and means that the connector is working as expected."
 ),
@@ -72,16 +83,16 @@ connector_metrics as (
             then connector_log.created_at else null end) as last_sync_completed_at,
 
         max(case when connector_log.event_subtype in ('status', 'sync_end')
-                and {{ fivetran_utils.json_parse(string="connector_log.message_data", string_path=["status"]) }} ='SUCCESSFUL'
+                and connector_log.log_status = 'SUCCESSFUL'
             then connector_log.created_at else null end) as last_successful_sync_completed_at,
 
 
         max(case when connector_log.event_subtype = 'sync_end' 
             then connector_log.sync_batch_id else null end) as last_sync_batch_id,
 
         max(case when connector_log.event_subtype in ('status', 'sync_end')
-                and {{ fivetran_utils.json_parse(string="connector_log.message_data", string_path=["status"]) }} ='RESCHEDULED'
-                and {{ fivetran_utils.json_parse(string="connector_log.message_data", string_path=["reason"]) }} like '%intended behavior%'
+                and connector_log.log_status = 'RESCHEDULED'
+                and connector_log.log_reason like '%intended behavior%'
             then connector_log.created_at else null end) as last_priority_first_sync_completed_at,
 
 
@@ -156,8 +167,8 @@ connector_recent_logs as (
         and connector_log.event_type != 'INFO' 
         -- need to explicitly avoid priority first statuses because they are of event_type WARNING
         and not (connector_log.event_subtype = 'status' 
-            and {{ fivetran_utils.json_parse(string="connector_log.message_data", string_path=["status"]) }} ='RESCHEDULED'
-            and {{ fivetran_utils.json_parse(string="connector_log.message_data", string_path=["reason"]) }} like '%intended behavior%')
+            and connector_log.log_status = 'RESCHEDULED'
+            and connector_log.log_reason like '%intended behavior%')
 
     group by -- remove duplicates, need explicit group by for SQL Server
         connector_health_status.connector_id,
@@ -172,7 +183,6 @@ connector_recent_logs as (
         connector_log.event_subtype,
         connector_log.event_type,
         connector_log.message_data
-
 ),
 
 final as (
@@ -213,7 +223,7 @@ final as (
         connector_recent_logs.last_sync_started_at, 
         connector_recent_logs.last_sync_completed_at, 
         connector_recent_logs.set_up_at, 
-        number_of_schema_changes_last_month
+        schema_changes.number_of_schema_changes_last_month
 )
 
 select * from final

models/fivetran_platform__schema_changelog.sql

@@ -36,12 +36,12 @@ final as (
         message_data,
 
         case 
-        when event_subtype = 'alter_table' then {{ fivetran_utils.json_parse(string='message_data', string_path=['table']) }} 
-        when event_subtype = 'create_table' then {{ fivetran_utils.json_parse(string='message_data', string_path=['name']) }} 
+        when event_subtype = 'alter_table' then {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['table']) }} 
+        when event_subtype = 'create_table' then {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['name']) }}
         else null end as table_name,
 
         case 
-        when event_subtype = 'create_schema' or event_subtype = 'create_table' then {{ fivetran_utils.json_parse(string='message_data', string_path=['schema']) }} 
+        when event_subtype = 'create_schema' or event_subtype = 'create_table' then {{ fivetran_log.fivetran_log_json_parse(string='message_data', string_path=['schema']) }}
         else null end as schema_name
 
     from add_connector_info