dbt/include/dremio/macros/materializations/twin_strategy.sql https://docs.getdbt.com/reference/dbt-jinja-functions/dispatch https://www.cnblogs.com/rongfengliang/p/18149927 https://docs.getdbt.com/docs/build/custom-schemas https://docs.getdbt.com/docs/build/custom-aliases https://docs.getdbt.c...
sql_header="<string>" ) }} 快照的 {{config( target_schema="<string>", target_database="<string>", unique_key="<column_name_or_expression>", strategy="timestamp"|"check", updated_at="<column_name>", check_cols=["<column_name>"]|"all" ) }} 获取config {%materializationincremental...
{% set column_names=columns | map(attribute='name') %} {% set base_model_sql %} # 物化判断,默认是view {%- if materialized is not none -%} {{ "{{ config(materialized='" ~ materialized ~ "') }}" }} {%- endif %} # 此处包装类似我们编写模型的模式 with source as ( select *...
{%- elif twin_strategy == 'clone' -%} {%- set sql_view -%} select * from {{ render_with_format_clause(target_relation) }} {%- endset -%} {% call statement('clone_view') -%} {{log('new view_relation' ~ view_relation , info=True)}} {{ create_view_as(view_relation, sq...
Supported functions You can use the following functions directly in dbt-tidb. For information about how to use them, seedbt-util. The following functions are supported: bool_or cast_bool_to_text dateadd datediff. Note thatdatediffis a little different from dbt-util. It rounds down rather than...
sql.functions import col udf_with_import = udf(func) data = [(1, "a"), (2, "b"), (3, "c")] cols = ["num", "alpha"] df = spark_session.createDataFrame(data, cols) return df.withColumn("udf_test_col", udf_with_import(col("alpha")))...
sql.functions import udf from pyspark.sql.functions import col udf_with_import = udf(func) data = [(1, "a"), (2, "b"), (3, "c")] cols = ["num", "alpha"] df = spark_session.createDataFrame(data, cols) return df.withColumn("udf_test_col", udf_with_import(col("alpha"))...
The two teams are already working side-by-side to bring SDF’s SQL comprehension technology into the hands of dbt users everywhere. SDF will be a massive upgrade to the very heart of the dbt user experience moving forward.Keep reading eBook How top data leaders scale analytics for business ...
The two teams are already working side-by-side to bring SDF’s SQL comprehension technology into the hands of dbt users everywhere. SDF will be a massive upgrade to the very heart of the dbt user experience moving forward.Keep reading eBook How top data leaders scale analytics for business ...
The two teams are already working side-by-side to bring SDF’s SQL comprehension technology into the hands of dbt users everywhere. SDF will be a massive upgrade to the very heart of the dbt user experience moving forward. Keep reading ...