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教學課程:在本機建立、執行及測試 dbt 模型

本教學課程將逐步引導您瞭解如何在本機建立、執行及測試 dbt 模型。 您也可以以 Azure Databricks 作業工作的形式執行 dbt 專案。 如需詳細資訊,請參閱 在 Azure Databricks 作業中使用 dbt 轉換。

開始之前

若要遵循本教學課程,您必須先將 Azure Databricks 工作區連線到 dbt Core。 如需詳細資訊,請參閱 連線到 dbt Core

步驟 1:建立和執行模型

在此步驟中,您會使用您慣用的文本編輯器來建立 模型,這些模型select 根據相同資料庫中的現有數據,建立新檢視(預設值)或資料庫中的新數據表的語句。 此程式會根據範例數據集中的範例diamonds數據表建立模型。

使用下列程式代碼來建立此數據表。

DROP TABLE IF EXISTS diamonds;

CREATE TABLE diamonds USING CSV OPTIONS (path "/databricks-datasets/Rdatasets/data-001/csv/ggplot2/diamonds.csv", header "true")
  1. 在項目的 models 目錄中,使用下列 SQL 語句建立名為 diamonds_four_cs.sql 的檔案。 此語句只會從表格中選取每個菱形的 diamonds 克拉、剪下、色彩和清晰詳細數據。 區塊 config 會指示 dbt 根據這個語句在資料庫中建立數據表。

    {{ config(
      materialized='table',
      file_format='delta'
    ) }}
    
    select carat, cut, color, clarity
    from diamonds
    

    提示

    如需其他 config 選項,例如使用 Delta 檔格式和 merge 累加策略,請參閱 dbt 檔中的 Databricks 組態

  2. 在項目的 models 目錄中,使用下列 SQL 語句建立名為 diamonds_list_colors.sql 的第二個檔案。 此語句會從 colors 數據表中的數據 diamonds_four_cs 行中選取唯一值,先依字母順序排序結果。 因為沒有 config 區塊,此模型會指示 dbt 根據這個語句在資料庫中建立檢視。

    select distinct color
    from {{ ref('diamonds_four_cs') }}
    sort by color asc
    
  3. 在項目的 models 目錄中,使用下列 SQL 語句建立名為 diamonds_prices.sql 的第三個檔案。 此語句會依色彩來平均菱形價格,並將結果依最高到最低來排序。 此模型會指示 dbt 根據這個語句在資料庫中建立檢視。

    select color, avg(price) as price
    from diamonds
    group by color
    order by price desc
    
  4. 啟用虛擬環境后,使用上述三個檔案的路徑執行 dbt run 命令。 在 default 資料庫中(如 檔案中所 profiles.yml 指定),dbt 會建立一個名為的數據表 diamonds_four_cs ,以及名為 diamonds_list_colorsdiamonds_prices的兩個檢視表。 dbt 會從其相關 .sql 文件名取得這些檢視和數據表名稱。

    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. 執行下列 SQL 程式代碼來列出新檢視的相關信息,以及從數據表和檢視中選取所有數據列。

    如果您要連線到叢集,您可以從連線到叢集的筆記本執行此 SQL 程式代碼,並將 SQL 指定為筆記本的預設語言。 如果您要連線到 SQL 倉儲,您可以從查詢執行此 SQL 程式代碼

    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 |
    +-------+---------+
    ...
    

步驟 2:建立和執行更複雜的模型

在此步驟中,您會為一組相關的數據表建立更複雜的模型。 這些數據表包含三支球隊虛構的體育聯盟六場比賽的相關信息。 此程式會建立數據表、建立模型,以及執行模型。

  1. 執行下列 SQL 程式代碼來建立必要的資料表。

    如果您要連線到叢集,您可以從連線到叢集的筆記本執行此 SQL 程式代碼,並將 SQL 指定為筆記本的預設語言。 如果您要連線到 SQL 倉儲,您可以從查詢執行此 SQL 程式代碼

    此步驟中的數據表和檢視會從 開始 zzz_ ,以協助識別它們作為此範例的一部分。 您不需要針對自己的數據表和檢視遵循此模式。

    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. 在項目的 models 目錄中,使用下列 SQL 語句建立名為 zzz_game_details.sql 的檔案。 此語句會建立一個數據表,提供每個遊戲的詳細數據,例如小組名稱和分數。 區塊 config 會指示 dbt 根據這個語句在資料庫中建立數據表。

    -- 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. 在項目的 models 目錄中,使用下列 SQL 語句建立名為 zzz_win_loss_records.sql 的檔案。 此聲明會建立一個檢視,其中列出球隊本賽季的勝負記錄。

    -- 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. 啟用虛擬環境之後,請使用上述兩個檔案的路徑執行 dbt run 命令。 default在資料庫中(如 檔案中所profiles.yml指定),dbt 會建立一zzz_game_details個名為的數據表和一個名為 的檢視zzz_win_loss_records表。 dbt 會從其相關 .sql 文件名取得這些檢視和數據表名稱。

    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. 執行下列 SQL 程式代碼來列出新檢視的相關信息,以及從數據表和檢視中選取所有數據列。

    如果您要連線到叢集,您可以從連線到叢集的筆記本執行此 SQL 程式代碼,並將 SQL 指定為筆記本的預設語言。 如果您要連線到 SQL 倉儲,您可以從查詢執行此 SQL 程式代碼

    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      |
    +---------------+------+--------+
    

步驟 3:建立和執行測試

在此步驟中,您會建立 測試,這是您對模型所做的判斷提示。 當您執行這些測試時,dbt 會告訴您專案中的每個測試是否通過或失敗。

測試有兩種類型。 YAML 中套用的架構測試會傳回未通過判斷提示的記錄數目。 當這個數位為零時,所有記錄都會通過,因此會通過測試。 數據測試 是必須傳回零筆記錄才能通過的特定查詢。

  1. 在項目的 models 目錄中,使用下列內容建立名為 schema.yml 的檔案。 此檔案包含架構測試,可判斷指定的數據行是否具有唯一值、不是 Null、只有指定的值或組合。

    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. 在項目的 tests 目錄中,使用下列 SQL 語句建立名為 zzz_game_details_check_dates.sql 的檔案。 此檔案包含數據測試,以判斷是否有任何比賽發生在常規賽之外。

    -- 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. 在項目的 tests 目錄中,使用下列 SQL 語句建立名為 zzz_game_details_check_scores.sql 的檔案。 此檔案包含數據測試,以判斷是否有任何分數為負數,或是否有任何遊戲被系結。

    -- 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. 在項目的 tests 目錄中,使用下列 SQL 語句建立名為 zzz_win_loss_records_check_records.sql 的檔案。 此檔案包含一項數據測試,以判斷任何球隊是否有負贏或輸記錄、比遊戲多贏或輸的記錄,或比允許的比賽多。

    -- 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. 啟用虛擬環境後,執行 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
    

步驟 4:清除

您可以執行下列 SQL 程式代碼,以刪除您為此範例建立的數據表和檢視。

如果您要連線到叢集,您可以從連線到叢集的筆記本執行此 SQL 程式代碼,並將 SQL 指定為筆記本的預設語言。 如果您要連線到 SQL 倉儲,您可以從查詢執行此 SQL 程式代碼

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;

疑難排解

如需搭配 Azure Databricks 使用 dbt Core 以及如何解決常見問題的相關信息,請參閱 在 dbt Labs 網站上取得協助

下一步

以 Azure Databricks 作業工作的形式執行 dbt Core 專案。 請參閱 在 Azure Databricks 作業中使用 dbt 轉換。

其他資源

探索 dbt Labs 網站上的下列資源: