通过

教程：在本地创建、运行和测试 dbt 模型

  • 项目

本教程将引导你了解如何在本地创建、运行和测试 dbt 模型。

开始之前的准备工作

要遵循本教程，必须先将 Azure Databricks 工作区连接到 dbt Core。 有关详细信息，请参阅连接到 dbt Core。

步骤 1：创建并运行模型

在本步骤中，需要使用喜欢的文本编辑器创建模型，这些模型是 语句，会根据同一数据库中的现有数据在数据库中创建一个新视图（默认行为）或一个新表。 此过程基于示例数据集中的示例 diamonds 表创建模型。

使用以下代码创建此表。

DROP TABLE IF EXISTS diamonds;

CREATE TABLE diamonds USING CSV OPTIONS (path "/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv", header "true")

  1. 在项目的 models 目录中，创建包含以下 SQL 语句的名为 diamonds_four_cs.sql 的文件。 此语句仅从 diamonds 表中选择每颗钻石的克拉数、切工、颜色和透明度详细信息。 config 块指示 dbt 根据此语句在数据库中创建表。

    {{ config(
  materialized='table',
  file_format='delta'
) }}

    select carat, cut, color, clarity
from diamonds

    提示

    有关其他 config 选项（例如使用 Delta 文件格式和 merge 增量策略），请参阅 dbt 文档中的 Databricks 配置。

  2. 在项目的 models 目录中，创建第二个包含以下 SQL 语句的名为 diamonds_list_colors.sql 的文件。 此语句从 colors 表中的 diamonds_four_cs 列中选择唯一值，按字母顺序依次对结果进行排序。 由于没有 config 块，此模型将指示 dbt 根据此语句在数据库中创建视图。

    select distinct color
from {{ ref('diamonds_four_cs') }}
sort by color asc

  3. 在项目的 models 目录中，创建第三个包含以下 SQL 语句的名为 diamonds_prices.sql 的文件。 此语句按颜色计算钻石的平均价格，并按平均价格从高到低对结果进行排序。 此模型指示 dbt 根据此语句在数据库中创建视图。

    select color, avg(price) as price
from diamonds
group by color
order by price desc

  4. 激活虚拟环境后，使用上述三个文件的路径运行 dbt run 命令。 在 default 数据库中（如 profiles.yml 文件中指定），dbt 会创建一个名为 diamonds_four_cs 的表和两个名为 diamonds_list_colors 和 diamonds_prices 的视图。 dbt 从相关的 .sql 文件名获取这些视图和表名称。

    dbt run --model models/diamonds_four_cs.sql models/diamonds_list_colors.sql models/diamonds_prices.sql

    ...
... | 1 of 3 START table model default.diamonds_four_cs.................... [RUN]
... | 1 of 3 OK created table model default.diamonds_four_cs............... [OK ...]
... | 2 of 3 START view model default.diamonds_list_colors................. [RUN]
... | 2 of 3 OK created view model default.diamonds_list_colors............ [OK ...]
... | 3 of 3 START view model default.diamonds_prices...................... [RUN]
... | 3 of 3 OK created view model default.diamonds_prices................. [OK ...]
... |
... | Finished running 1 table model, 2 view models ...

Completed successfully

Done. PASS=3 WARN=0 ERROR=0 SKIP=0 TOTAL=3

  5. 运行以下 SQL 代码，列出有关新视图的信息，并选择表和视图中所有行。

    如果要连接到群集，可以从连接到群集的笔记本中运行此 SQL 代码，同时指定 SQL 作为笔记本的默认语言。 如果要连接到 SQL 仓库，可以从查询运行此 SQL 代码。

    SHOW views IN default;

    +-----------+----------------------+-------------+
| namespace | viewName             | isTemporary |
+===========+======================+=============+
| default   | diamonds_list_colors | false       |
+-----------+----------------------+-------------+
| default   | diamonds_prices      | false       |
+-----------+----------------------+-------------+

    SELECT * FROM diamonds_four_cs;

    +-------+---------+-------+---------+
| carat | cut     | color | clarity |
+=======+=========+=======+=========+
| 0.23  | Ideal   | E     | SI2     |
+-------+---------+-------+---------+
| 0.21  | Premium | E     | SI1     |
+-------+---------+-------+---------+
...

    SELECT * FROM diamonds_list_colors;

    +-------+
| color |
+=======+
| D     |
+-------+
| E     |
+-------+
...

    SELECT * FROM diamonds_prices;

    +-------+---------+
| color | price   |
+=======+=========+
| J     | 5323.82 |
+-------+---------+
| I     | 5091.87 |
+-------+---------+
...

步骤 2：创建并运行更复杂的模型

在此步骤中，你将为一组相关数据表创建更复杂的模型。 这些数据表包含有关虚拟的体育联赛的信息，其中三支队伍需要在一个赛季中完成六场比赛。 此过程将创建数据表、创建模型并运行模型。

  1. 运行以下 SQL 代码以创建必要的数据表。

    如果要连接到群集，可以从连接到群集的笔记本中运行此 SQL 代码，同时指定 SQL 作为笔记本的默认语言。 如果要连接到 SQL 仓库，可以从查询运行此 SQL 代码。

    本步骤中的表和视图以 zzz_ 开头，有助于在本示例中识别它们。 对于自己的表和视图，无需遵循此模式。

    DROP TABLE IF EXISTS zzz_game_opponents;
DROP TABLE IF EXISTS zzz_game_scores;
DROP TABLE IF EXISTS zzz_games;
DROP TABLE IF EXISTS zzz_teams;

CREATE TABLE zzz_game_opponents (
game_id INT,
home_team_id INT,
visitor_team_id INT
) USING DELTA;

INSERT INTO zzz_game_opponents VALUES (1, 1, 2);
INSERT INTO zzz_game_opponents VALUES (2, 1, 3);
INSERT INTO zzz_game_opponents VALUES (3, 2, 1);
INSERT INTO zzz_game_opponents VALUES (4, 2, 3);
INSERT INTO zzz_game_opponents VALUES (5, 3, 1);
INSERT INTO zzz_game_opponents VALUES (6, 3, 2);

-- Result:
-- +---------+--------------+-----------------+
-- | game_id | home_team_id | visitor_team_id |
-- +=========+==============+=================+
-- | 1       | 1            | 2               |
-- +---------+--------------+-----------------+
-- | 2       | 1            | 3               |
-- +---------+--------------+-----------------+
-- | 3       | 2            | 1               |
-- +---------+--------------+-----------------+
-- | 4       | 2            | 3               |
-- +---------+--------------+-----------------+
-- | 5       | 3            | 1               |
-- +---------+--------------+-----------------+
-- | 6       | 3            | 2               |
-- +---------+--------------+-----------------+

CREATE TABLE zzz_game_scores (
game_id INT,
home_team_score INT,
visitor_team_score INT
) USING DELTA;

INSERT INTO zzz_game_scores VALUES (1, 4, 2);
INSERT INTO zzz_game_scores VALUES (2, 0, 1);
INSERT INTO zzz_game_scores VALUES (3, 1, 2);
INSERT INTO zzz_game_scores VALUES (4, 3, 2);
INSERT INTO zzz_game_scores VALUES (5, 3, 0);
INSERT INTO zzz_game_scores VALUES (6, 3, 1);

-- Result:
-- +---------+-----------------+--------------------+
-- | game_id | home_team_score | visitor_team_score |
-- +=========+=================+====================+
-- | 1       | 4               | 2                  |
-- +---------+-----------------+--------------------+
-- | 2       | 0               | 1                  |
-- +---------+-----------------+--------------------+
-- | 3       | 1               | 2                  |
-- +---------+-----------------+--------------------+
-- | 4       | 3               | 2                  |
-- +---------+-----------------+--------------------+
-- | 5       | 3               | 0                  |
-- +---------+-----------------+--------------------+
-- | 6       | 3               | 1                  |
-- +---------+-----------------+--------------------+

CREATE TABLE zzz_games (
game_id INT,
game_date DATE
) USING DELTA;

INSERT INTO zzz_games VALUES (1, '2020-12-12');
INSERT INTO zzz_games VALUES (2, '2021-01-09');
INSERT INTO zzz_games VALUES (3, '2020-12-19');
INSERT INTO zzz_games VALUES (4, '2021-01-16');
INSERT INTO zzz_games VALUES (5, '2021-01-23');
INSERT INTO zzz_games VALUES (6, '2021-02-06');

-- Result:
-- +---------+------------+
-- | game_id | game_date  |
-- +=========+============+
-- | 1       | 2020-12-12 |
-- +---------+------------+
-- | 2       | 2021-01-09 |
-- +---------+------------+
-- | 3       | 2020-12-19 |
-- +---------+------------+
-- | 4       | 2021-01-16 |
-- +---------+------------+
-- | 5       | 2021-01-23 |
-- +---------+------------+
-- | 6       | 2021-02-06 |
-- +---------+------------+

CREATE TABLE zzz_teams (
team_id INT,
team_city VARCHAR(15)
) USING DELTA;

INSERT INTO zzz_teams VALUES (1, "San Francisco");
INSERT INTO zzz_teams VALUES (2, "Seattle");
INSERT INTO zzz_teams VALUES (3, "Amsterdam");

-- Result:
-- +---------+---------------+
-- | team_id | team_city     |
-- +=========+===============+
-- | 1       | San Francisco |
-- +---------+---------------+
-- | 2       | Seattle       |
-- +---------+---------------+
-- | 3       | Amsterdam     |
-- +---------+---------------+

  2. 在项目的 models 目录中，创建包含以下 SQL 语句的名为 zzz_game_details.sql 的文件。 此语句会创建一个表，该表提供每场比赛的详细信息，例如队伍名称和分数。 config 块指示 dbt 根据此语句在数据库中创建表。

    -- Create a table that provides full details for each game, including
-- the game ID, the home and visiting teams' city names and scores,
-- the game winner's city name, and the game date.

    {{ config(
  materialized='table',
  file_format='delta'
) }}

    -- Step 4 of 4: Replace the visitor team IDs with their city names.
select
  game_id,
  home,
  t.team_city as visitor,
  home_score,
  visitor_score,
  -- Step 3 of 4: Display the city name for each game's winner.
  case
    when
      home_score > visitor_score
        then
          home
    when
      visitor_score > home_score
        then
          t.team_city
  end as winner,
  game_date as date
from (
  -- Step 2 of 4: Replace the home team IDs with their actual city names.
  select
    game_id,
    t.team_city as home,
    home_score,
    visitor_team_id,
    visitor_score,
    game_date
  from (
    -- Step 1 of 4: Combine data from various tables (for example, game and team IDs, scores, dates).
    select
      g.game_id,
      go.home_team_id,
      gs.home_team_score as home_score,
      go.visitor_team_id,
      gs.visitor_team_score as visitor_score,
      g.game_date
    from
      zzz_games as g,
      zzz_game_opponents as go,
      zzz_game_scores as gs
    where
      g.game_id = go.game_id and
      g.game_id = gs.game_id
  ) as all_ids,
    zzz_teams as t
  where
    all_ids.home_team_id = t.team_id
) as visitor_ids,
  zzz_teams as t
where
  visitor_ids.visitor_team_id = t.team_id
order by game_date desc

  3. 在项目的 models 目录中，创建包含以下 SQL 语句的名为 zzz_win_loss_records.sql 的文件。 此语句会创建一个视图，视图中会列出该赛季队伍的胜负记录。

    -- Create a view that summarizes the season's win and loss records by team.

-- Step 2 of 2: Calculate the number of wins and losses for each team.
select
  winner as team,
  count(winner) as wins,
  -- Each team played in 4 games.
  (4 - count(winner)) as losses
from (
  -- Step 1 of 2: Determine the winner and loser for each game.
  select
    game_id,
    winner,
    case
      when
        home = winner
          then
            visitor
      else
        home
    end as loser
  from {{ ref('zzz_game_details') }}
)
group by winner
order by wins desc

  4. 激活虚拟环境后，使用上述两个文件的路径运行 dbt run 命令。 在 default 数据库中（如 profiles.yml 文件中指定），dbt 会创建一个名为 zzz_game_details 的表和一个名为 zzz_win_loss_records 的视图。 dbt 从相关的 .sql 文件名获取这些视图和表名称。

    dbt run --model models/zzz_game_details.sql models/zzz_win_loss_records.sql

    ...
... | 1 of 2 START table model default.zzz_game_details.................... [RUN]
... | 1 of 2 OK created table model default.zzz_game_details............... [OK ...]
... | 2 of 2 START view model default.zzz_win_loss_records................. [RUN]
... | 2 of 2 OK created view model default.zzz_win_loss_records............ [OK ...]
... |
... | Finished running 1 table model, 1 view model ...

Completed successfully

Done. PASS=2 WARN=0 ERROR=0 SKIP=0 TOTAL=2

  5. 运行以下 SQL 代码，列出有关新视图的信息，并选择表和视图中所有行。

    如果要连接到群集，可以从连接到群集的笔记本中运行此 SQL 代码，同时指定 SQL 作为笔记本的默认语言。 如果要连接到 SQL 仓库，可以从查询运行此 SQL 代码。

    SHOW VIEWS FROM default LIKE 'zzz_win_loss_records';

    +-----------+----------------------+-------------+
| namespace | viewName             | isTemporary |
+===========+======================+=============+
| default   | zzz_win_loss_records | false       |
+-----------+----------------------+-------------+

    SELECT * FROM zzz_game_details;

    +---------+---------------+---------------+------------+---------------+---------------+------------+
| game_id | home          | visitor       | home_score | visitor_score | winner        | date       |
+=========+===============+===============+============+===============+===============+============+
| 1       | San Francisco | Seattle       | 4          | 2             | San Francisco | 2020-12-12 |
+---------+---------------+---------------+------------+---------------+---------------+------------+
| 2       | San Francisco | Amsterdam     | 0          | 1             | Amsterdam     | 2021-01-09 |
+---------+---------------+---------------+------------+---------------+---------------+------------+
| 3       | Seattle       | San Francisco | 1          | 2             | San Francisco | 2020-12-19 |
+---------+---------------+---------------+------------+---------------+---------------+------------+
| 4       | Seattle       | Amsterdam     | 3          | 2             | Seattle       | 2021-01-16 |
+---------+---------------+---------------+------------+---------------+---------------+------------+
| 5       | Amsterdam     | San Francisco | 3          | 0             | Amsterdam     | 2021-01-23 |
+---------+---------------+---------------+------------+---------------+---------------+------------+
| 6       | Amsterdam     | Seattle       | 3          | 1             | Amsterdam     | 2021-02-06 |
+---------+---------------+---------------+------------+---------------+---------------+------------+

    SELECT * FROM zzz_win_loss_records;

    +---------------+------+--------+
| team          | wins | losses |
+===============+======+========+
| Amsterdam     | 3    | 1      |
+---------------+------+--------+
| San Francisco | 2    | 2      |
+---------------+------+--------+
| Seattle       | 1    | 3      |
+---------------+------+--------+

步骤 3：创建并运行测试

在此步骤中，你将创建测试，这些测试是有关模型的断言。 运行这些测试时，dbt 会告诉你项目中的每个测试是通过还是失败。

有两种类型的测试。 架构测试，在 YAML 中应用，返回未通过断言的记录数。 如果此数字为零，则所有记录都通过，因此测试也通过。 数据测试是必须返回零条记录才算通过的特定查询。

  1. 在项目的 models 目录中，创建包含以下内容的名为 schema.yml 的文件。 此文件包含架构测试，用于确定指定的列是否具有唯一值、不为 null、仅具有指定值或具有组合。

    version: 2

models:
  - name: zzz_game_details
    columns:
      - name: game_id
        tests:
          - unique
          - not_null
      - name: home
        tests:
          - not_null
          - accepted_values:
              values: ['Amsterdam', 'San Francisco', 'Seattle']
      - name: visitor
        tests:
          - not_null
          - accepted_values:
              values: ['Amsterdam', 'San Francisco', 'Seattle']
      - name: home_score
        tests:
          - not_null
      - name: visitor_score
        tests:
          - not_null
      - name: winner
        tests:
          - not_null
          - accepted_values:
              values: ['Amsterdam', 'San Francisco', 'Seattle']
      - name: date
        tests:
          - not_null
  - name: zzz_win_loss_records
    columns:
      - name: team
        tests:
          - unique
          - not_null
          - relationships:
              to: ref('zzz_game_details')
              field: home
      - name: wins
        tests:
          - not_null
      - name: losses
        tests:
          - not_null

  2. 在项目的 tests 目录中，创建包含以下 SQL 语句的名为 zzz_game_details_check_dates.sql 的文件。 此文件包含一个数据测试，用于确定常规赛季外是否进行了任何比赛。

    -- This season's games happened between 2020-12-12 and 2021-02-06.
-- For this test to pass, this query must return no results.

select date
from {{ ref('zzz_game_details') }}
where date < '2020-12-12'
or date > '2021-02-06'

  3. 在项目的 tests 目录中，创建包含以下 SQL 语句的名为 zzz_game_details_check_scores.sql 的文件。 此文件包含一个数据测试，用于确定是否有任何分数为负或任何比赛为平局。

    -- This sport allows no negative scores or tie games.
-- For this test to pass, this query must return no results.

select home_score, visitor_score
from {{ ref('zzz_game_details') }}
where home_score < 0
or visitor_score < 0
or home_score = visitor_score

  4. 在项目的 tests 目录中，创建包含以下 SQL 语句的名为 zzz_win_loss_records_check_records.sql 的文件。 此文件包含一个数据测试，用于确定任何队伍是否有负数的胜场或败场记录、是否有超过进行比赛数的胜负记录，或者进行的比赛数是否多于允许的比赛数。

    -- Each team participated in 4 games this season.
-- For this test to pass, this query must return no results.

select wins, losses
from {{ ref('zzz_win_loss_records') }}
where wins < 0 or wins > 4
or losses < 0 or losses > 4
or (wins + losses) > 4

  5. 激活虚拟环境后，运行 dbt test 命令。

    dbt test --models zzz_game_details zzz_win_loss_records

    ...
... | 1 of 19 START test accepted_values_zzz_game_details_home__Amsterdam__San_Francisco__Seattle [RUN]
... | 1 of 19 PASS accepted_values_zzz_game_details_home__Amsterdam__San_Francisco__Seattle [PASS ...]
...
... |
... | Finished running 19 tests ...

Completed successfully

Done. PASS=19 WARN=0 ERROR=0 SKIP=0 TOTAL=19

步骤 4：清理

可以通过运行以下 SQL 代码来删除为此示例创建的表和视图。

如果要连接到群集，可以从连接到群集的笔记本中运行此 SQL 代码，同时指定 SQL 作为笔记本的默认语言。 如果要连接到 SQL 仓库，可以从查询运行此 SQL 代码。

DROP TABLE zzz_game_opponents;
DROP TABLE zzz_game_scores;
DROP TABLE zzz_games;
DROP TABLE zzz_teams;
DROP TABLE zzz_game_details;
DROP VIEW zzz_win_loss_records;

DROP TABLE diamonds;
DROP TABLE diamonds_four_cs;
DROP VIEW diamonds_list_colors;
DROP VIEW diamonds_prices;

故障排除

有关将 dbt Core 与 Azure Databricks 配合使用时的常见问题以及如何解决这些问题的信息，请参阅 dbt 实验室网站上的获取帮助。

其他资源

在 dbt 实验室网站上浏览以下资源：