CUD 데이터 모델의 샘플 쿼리

참고: 이 문서에서는 크레딧 대신 할인을 활용하는 새로운 가격 모델로 자동 이전되는 일부 지출 기반 약정 사용 할인 (CUD)을 설명합니다. 이전 날짜는 Google Cloud 콘솔 결제 개요 페이지의 알림에 표시됩니다. 개선사항, 영향을 받는 CUD, 필요한 작업에 대한 자세한 내용은 지출 기반 CUD를 참고하세요.

CUD KPI 쿼리

이러한 중요한 KPI 측정항목을 사용하여 시스템이 데이터 모델에서 잘 작동하는지 확인할 수 있습니다.

1. 약정 할인 ($): 약정으로 인해 발생한 할인액을 설명합니다. 이 측정항목은 (Cost of resources at on-demand rates - cost of resources with commitment discounts) 공식을 사용합니다.
2. 약정 할인(%): 약정으로 인해 발생한 할인 비율을 설명합니다. 이 측정항목은 (Commitment savings / costs of resources at on-demand rates)*100 공식을 사용합니다.
3. 약정 사용률(%): 약정을 얼마나 효과적으로 사용하는지 측정하며, 백분율로 표시됩니다. 이 측정항목은 (Commitment applied to eligible spend / total commitment) 공식을 사용합니다.

4. 실제 할인율(%): 약정 할인에 대한 투자수익(ROI)을 설명합니다. 이 측정항목은 (Commitment Savings / On-Demand Equivalent Spend) 공식을 사용합니다.

   비용 데이터에 대한 유용한 통계를 얻을 수 있도록 다음 BigQuery 샘플 쿼리에서는 다음 KPI에 대한 유용한 정보를 가져오는 방법을 보여줍니다.

올바른 샘플 쿼리 선택

데이터 모델 변경사항에 맞게 쿼리를 업데이트할 수 있도록 두 가지 버전의 KPI 샘플 쿼리를 제공합니다. 다음 중 하나를 선택합니다.

• 데이터 모델을 사용하는 샘플 KPI 쿼리
• 기존 데이터 모델을 사용하는 샘플 KPI 쿼리

데이터 모델을 사용하는 샘플 KPI 쿼리

데이터 모델을 채택한 경우 이 샘플 쿼리를 사용합니다.

이러한 쿼리는 Compute 가변형 CUD에만 해당합니다. 기타 지출 기반 CUD 제품을 쿼리하려면 다음 값을 변경해야 합니다.

• cud_fee_skus
• consumption_model.id

SET bigquery_billing_project = billing-project-id;

WITH
  cost_data AS (
    SELECT *
    FROM
      project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN
    WHERE invoice.month = 'month'
  ),
  cud_fee_skus AS (
    SELECT * FROM UNNEST(
      [
        '5515-81A8-03A2',
        'B22F-51BE-D599'])
      fee_sku_id
  ),
  cud_costs AS (
    SELECT
      invoice.month AS invoice_month,
      subscription.instance_id AS subscription_instance_id,
      IFNULL(
        (
          SELECT l.value
          FROM UNNEST(labels) l
          WHERE l.key = 'goog-originating-service-id'
        ),
        service.id) AS service,
      SUM(cost) AS commitment_cost,
      SUM(
        (
          SELECT SUM(credit.amount)
          FROM UNNEST(credits) credit
          WHERE credit.type = 'FEE_UTILIZATION_OFFSET'
        )) AS fee_utilization_offset
    FROM
      cost_data
    JOIN cud_fee_skus
      ON fee_sku_id = sku.id
    GROUP BY 1, 2, 3
  ),
  cud_savings AS (
    SELECT
      invoice.month AS invoice_month,
      subscription.instance_id AS subscription_instance_id,
      service.id AS service,
      SUM(cost - cost_at_effective_price_default) AS cud_savings_amount,
      SUM(cost_at_effective_price_default) AS on_demand_costs
    FROM
      cost_data
    WHERE
      consumption_model.id IS NOT NULL
      AND consumption_model.id IN ('D97B-0795-975B','70D7-D1AB-12A4')
    GROUP BY 1, 2, 3
  )
SELECT
  invoice_month,
  subscription_instance_id,
  service,
  commitment_cost,
  commitment_cost + fee_utilization_offset + IFNULL(cud_savings_amount, 0)
    AS commitment_savings,
  ABS(fee_utilization_offset) / commitment_cost * 100 AS cud_utilization_percent,
  (commitment_cost + fee_utilization_offset + IFNULL(cud_savings_amount, 0))
    / IFNULL(on_demand_costs, 1) * 100 AS effective_savings_rate
FROM cud_costs
LEFT JOIN cud_savings
  USING (invoice_month, subscription_instance_id, service);

• month는 YYYYMM 형식의 현재 연도 및 월입니다(예: '202504').

기존 데이터 모델을 사용하는 샘플 KPI 쿼리

데이터 모델을 사용하지 않는 경우 다음 샘플 쿼리를 사용합니다.

**참고:** 이전 BigQuery 내보내기 데이터 형식의 KPI 계산은 CUD 제품 (subscription_definition) 수준에서만 수행될 수 있습니다. subs_instance 수준에서 사용하는 새 KPI 측정항목과 동일하지 않습니다.

이러한 쿼리는 Compute 가변형 CUD에만 해당합니다. 기타 지출 기반 CUD 제품을 쿼리하려면 다음 값을 변경해야 합니다.

• cud_product
• sku.description
• credit.type

CUD 비용 + CUD 절감액

WITH
 cost_data AS (
   SELECT *
   FROM project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN
   WHERE invoice.month = 'month'
 ),
 cud_product_data AS (
   SELECT * FROM UNNEST(
     [
       STRUCT(
         'Compute Engine Flexible CUDs' AS cud_product,
         'Commitment - dollar based v1: GCE' AS cud_fee_regex,
         'GCE Commitments' AS cud_credit_regex)])
 ),
 cud_costs AS (
   SELECT
     invoice.month AS invoice_month,
     cud_product_data.cud_product,
     IFNULL(
       (
         SELECT l.value
         FROM UNNEST(labels) l
         WHERE l.key = 'goog-originating-service-id'
       ),
       service.id) AS service,
     SUM(cost) AS cost
   FROM
     cost_data
   JOIN cud_product_data
     ON
       REGEXP_CONTAINS(
         sku.description, cud_fee_regex)
   GROUP BY 1, 2, 3
 ),
 cud_credits AS (
   SELECT
     invoice.month AS invoice_month,
     cud_product,
     service.id AS service,
     SUM(credit.amount) AS spend_cud_credits
   FROM
     cost_data, UNNEST(credits) AS credit
   JOIN cud_product_data
     ON
       REGEXP_CONTAINS(
         credit.full_name, cud_credit_regex)
   WHERE
     credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
   GROUP BY 1, 2, 3
 )
SELECT
 invoice_month,
 cud_product,
 cost As commitment_cost,
 -1 * (cost + IFNULL(spend_cud_credits, 0)) AS commitment_savings
FROM cud_costs
LEFT JOIN cud_credits
 USING (invoice_month, cud_product, service);

• month는 YYYYMM 형식의 현재 연도 및 월입니다(예: '202504').

약정 사용량

WITH
 cost_data AS (
   SELECT *
   FROM project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN
   WHERE invoice.month = 'month'
 ),
 cud_product_data AS (
   SELECT * FROM UNNEST(
     [
       STRUCT(
         'Compute Engine Flexible CUDs' AS cud_product,
         'Commitment - dollar based v1: GCE' AS cud_fee_regex,
         'GCE Commitments' AS cud_credit_regex)])
),
 cud_commitment_amount AS (
   SELECT
     invoice.month AS invoice_month,
     cud_product_data.cud_product,
     SUM(usage.amount_in_pricing_units / 100) AS commitment_amount,
   FROM
     cost_data
   JOIN cud_product_data
     ON
       REGEXP_CONTAINS(
         sku.description, cud_fee_regex)
   GROUP BY 1, 2
 ),
 cud_utilized_commitment_amount AS (
   SELECT
     invoice.month AS invoice_month,
     cud_product,
     ABS(SUM(credit.amount / currency_conversion_rate))
       AS utilized_commitment_amount
   FROM
     cost_data, UNNEST(credits) AS credit
   JOIN cud_product_data
     ON
       REGEXP_CONTAINS(
         credit.full_name, cud_credit_regex)
   WHERE
     credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
   GROUP BY 1, 2
 )
SELECT
 invoice_month,
 cud_product,
 utilized_commitment_amount / commitment_amount *100 AS commitment_utilization
FROM cud_commitment_amount
LEFT JOIN cud_utilized_commitment_amount
 USING (invoice_month, cud_product);

• month는 YYYYMM 형식의 현재 연도 및 월입니다(예: '202504').

유효 절감률

WITH
 cost_data AS (
   SELECT *
   FROM project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN
   WHERE invoice.month = 'month'
 ),
 cud_product_data AS (
   SELECT * FROM UNNEST(
     [
       STRUCT(
         'Compute Engine Flexible CUDs' AS cud_product,
         'Commitment - dollar based v1: GCE' AS cud_fee_regex,
         'GCE Commitments' AS cud_credit_regex)])
 ),
 eligible_cud_skus AS (
   SELECT sku_id
   FROM example_project.dataset.flex_cud_skus
 ),
 eligible_cud_spend AS (
   SELECT
     invoice.month AS invoice_month,
     SUM(cost) AS cost,
     SUM(
       IFNULL(
         (
           SELECT SUM(credit.amount)
           FROM UNNEST(credits) AS credit
           WHERE
             credit.type IN (
               'COMMITTED_USAGE_DISCOUNT',
               'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE',
               'DISCOUNT',
               'FREE_TIER')
         ),
         0)) AS costs_ineligible_for_cud,
   FROM cost_data
   JOIN eligible_cud_skus
     ON sku.id = sku_id
   GROUP BY 1
 ),
 cud_costs AS (
   SELECT
     invoice.month AS invoice_month,
     cud_product_data.cud_product,
     IFNULL(
       (
         SELECT l.value
         FROM UNNEST(labels) l
         WHERE l.key = 'goog-originating-service-id'
       ),
       service.id) AS service,
     SUM(cost) AS cost
   FROM
     cost_data
   JOIN cud_product_data
     ON
       REGEXP_CONTAINS(
         sku.description, cud_fee_regex)
   GROUP BY 1, 2, 3
 ),
 cud_credits AS (
   SELECT
     invoice.month AS invoice_month,
     SUM(credit.amount) AS spend_cud_credits
   FROM
     cost_data, UNNEST(credits) AS credit
   WHERE
     credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
     AND REGEXP_CONTAINS(credit.full_name, 'GCE Commitments')
   GROUP BY 1
 ),
cud_savings AS (
  SELECT
   invoice_month,
   Cud_product,
   spend_cud_credits as spend_cud_credits,
   -1 * (cost + IFNULL(spend_cud_credits, 0)) AS commitment_savings
FROM cud_costs
LEFT JOIN cud_credits
 USING (invoice_month)
)
SELECT
 Invoice_month,
 commitment_savings * 100
   / (cost + costs_ineligible_for_cud - IFNULL(spend_cud_credits, 0))
   AS effective_savings_rate
FROM eligible_cud_spend
LEFT JOIN cud_savings
 USING (invoice_month);

• month는 YYYYMM 형식의 현재 연도 및 월입니다(예: '202504').

이전 Compute 가변형 CUD 쿼리 및 분석

다음 쿼리를 사용하면 단일 쿼리 내에서 이전 CUD를 분석할 수 있습니다. 옵트인 날짜를 감지하고 이전 CUD 모델과 새 CUD 모델 모두에 있는 데이터 유형을 처리합니다. 이 쿼리를 사용하려면 이미 새 CUD 모델로 이전되어 있어야 합니다.

이러한 쿼리는 Compute 가변형 CUD에만 해당합니다. 기타 지출 기반 CUD 제품을 쿼리하려면 다음 값을 변경해야 합니다.

• cud_product
• sku.description
• Credit.type
• Credit.full_name
• cud_fee_skus
• consumption_model.id

-- This query calculates both legacy and new model CUD KPIs, splitting the data by a migration event.
-- The migration event is defined as the first time the consumption_model.description is not 'Default'.
-- It calculates commitment cost, savings, utilization, and effective savings rate for both models.

WITH
 -- Determine the migration timestamp based on the first usage of a non-default consumption model
 migration_hour AS (
   SELECT
     MIN(t.usage_start_time) AS smallest_usage_start_time
   FROM
     `project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN` AS t
   WHERE
     t.consumption_model.description != 'Default'
 ),
 -- Filter for cost data that occurred before the migration
 legacy_cost_data AS (
   SELECT
    *
   FROM
     `project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN`
   WHERE
     usage_start_time < (
       SELECT
         smallest_usage_start_time
       FROM
         migration_hour
     )
 ),
 -- Filter for cost data that occurred at or after the migration
 new_cost_data AS (
   SELECT
    *
   FROM
     `project.dataset.gcp_billing_export_resource_v1_NNNNNN_NNNNNN_NNNNNN`
   WHERE
     usage_start_time >= (
       SELECT
         smallest_usage_start_time
       FROM
         migration_hour
     )
 ),
 -- Define CUD product metadata for matching fees and credits
 cud_product_data AS (
   SELECT
    *
   FROM
     UNNEST([ STRUCT( 'Compute Engine Flexible CUDs' AS cud_product, 'Commitment - dollar based v1: GCE' AS cud_fee_regex, 'GCE Commitments' AS cud_credit_regex)])
 ),
 -- =================================================================================================
 -- Part 1: Legacy Model Calculations (before migration)
 -- =================================================================================================
 legacy_commitment_costs AS (
   SELECT
     usage_start_time,
     pd.cud_product,
     IFNULL((
       SELECT
         l.value
       FROM
         UNNEST(labels) l
       WHERE
         l.key = 'goog-originating-service-id'
     ), service.id) AS service,
     SUM(cost) AS cost
   FROM
     legacy_cost_data
     JOIN cud_product_data AS pd ON REGEXP_CONTAINS(sku.description, pd.cud_fee_regex)
   GROUP BY
     1,
     2,
     3
 ),
 legacy_cud_credits AS (
   SELECT
     usage_start_time,
     pd.cud_product,
     service.id AS service,
     SUM(credit.amount) AS spend_cud_credits
   FROM
     legacy_cost_data,
     UNNEST(credits) AS credit
     JOIN cud_product_data AS pd ON REGEXP_CONTAINS(credit.full_name, pd.cud_credit_regex)
   WHERE
     credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
   GROUP BY
     1,
     2,
     3
 ),
 legacy_commitment_savings AS (
   SELECT
     c.usage_start_time,
     c.cud_product,
     c.service,
     SUM(c.cost) AS commitment_cost,
     SUM(-1 * (c.cost + IFNULL(cr.spend_cud_credits, 0))) AS commitment_savings
   FROM
     legacy_commitment_costs AS c
     LEFT JOIN legacy_cud_credits AS cr USING (usage_start_time, cud_product, service)
   GROUP BY
     1,
     2,
     3
 ),
 legacy_commitment_amount AS (
   SELECT
     usage_start_time,
     pd.cud_product,
     SUM(usage.amount_in_pricing_units / 100) AS commitment_amount
   FROM
     legacy_cost_data
     JOIN cud_product_data AS pd ON REGEXP_CONTAINS(sku.description, pd.cud_fee_regex)
   GROUP BY
     1,
     2
 ),
 legacy_utilized_commitment AS (
   SELECT
     usage_start_time,
     pd.cud_product,
     ABS(SUM(credit.amount / currency_conversion_rate)) AS utilized_commitment_amount
   FROM
     legacy_cost_data,
     UNNEST(credits) AS credit
     JOIN cud_product_data AS pd ON REGEXP_CONTAINS(credit.full_name, pd.cud_credit_regex)
   WHERE
     credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
   GROUP BY
     1,
     2
 ),
 legacy_cud_utilization AS (
   SELECT
     ca.usage_start_time,
     ca.cud_product,
     SAFE_DIVIDE(uc.utilized_commitment_amount, ca.commitment_amount) * 100 AS cud_utilization_percent
   FROM
     legacy_commitment_amount AS ca
     LEFT JOIN legacy_utilized_commitment AS uc USING (usage_start_time, cud_product)
 ),
 eligible_cud_skus AS (
   SELECT
     sku_id
   FROM
     UNNEST([ /* Insert the full list of CUD eligible SKUs 'F35A-5D39-DA9D', '7E09-0800-D3BA', '1641-654E-D130', 'D616-27D3-51E1'*/ ]) AS sku_id
 ),
 eligible_cud_spend AS (
   SELECT
     usage_start_time,
     SUM(cost) AS cost,
     SUM(IFNULL((
       SELECT
         SUM(credit.amount)
       FROM
         UNNEST(credits) AS credit
       WHERE
         credit.type IN ('COMMITTED_USAGE_DISCOUNT', 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE', 'DISCOUNT', 'FREE_TIER')
     ), 0)) AS costs_ineligible_for_cud
   FROM
     legacy_cost_data
     JOIN eligible_cud_skus ON sku.id = eligible_cud_skus.sku_id
   GROUP BY
     1
 ),
 total_cud_savings AS (
   SELECT
     c.usage_start_time,
     -1 * (c.cost + IFNULL(cr.spend_cud_credits, 0)) AS commitment_savings,
     cr.spend_cud_credits
   FROM (
     SELECT
       usage_start_time,
       SUM(cost) AS cost
     FROM
       legacy_cost_data
       JOIN cud_product_data pd ON REGEXP_CONTAINS(sku.description, pd.cud_fee_regex)
     GROUP BY
       1
   ) AS c
     LEFT JOIN (
       SELECT
         usage_start_time,
         SUM(credit.amount) AS spend_cud_credits
       FROM
         legacy_cost_data,
         UNNEST(credits) AS credit
       WHERE
         credit.type = 'COMMITTED_USAGE_DISCOUNT_DOLLAR_BASE'
         AND REGEXP_CONTAINS(credit.full_name, 'GCE Commitments')
       GROUP BY
         1
     ) AS cr USING (usage_start_time)
 ),
 -- =================================================================================================
 -- Part 2: New Model Calculations (at or after migration)
 -- =================================================================================================
 new_model_commitment_costs AS (
   SELECT
     usage_start_time, -- Changed from invoice.month
     subscription.instance_id AS subscription_instance_id,
     IFNULL((
       SELECT
         l.value
       FROM
         UNNEST(labels) l
       WHERE
         l.key = 'goog-originating-service-id'
     ), service.id) AS service,
     SUM(cost) AS commitment_cost,
     SUM((
       SELECT
         SUM(credit.amount)
       FROM
         UNNEST(credits) credit
       WHERE
         credit.type = 'FEE_UTILIZATION_OFFSET'
     )) AS fee_utilization_offset
   FROM
     new_cost_data
     JOIN (
       SELECT
        *
       FROM
         UNNEST(['5515-81A8-03A2', 'B22F-51BE-D599']) fee_sku_id
     ) AS cud_fee_skus ON fee_sku_id = sku.id
   GROUP BY
     1,
     2,
     3
 ),
 new_model_cud_savings AS (
   SELECT
     usage_start_time, -- Changed from invoice.month
     subscription.instance_id AS subscription_instance_id,
     service.id AS service,
     SUM(cost - cost_at_effective_price_default) AS cud_savings_amount,
     SUM(cost_at_effective_price_default) AS on_demand_costs
   FROM
     new_cost_data
   WHERE
     consumption_model.id IS NOT NULL
     AND consumption_model.id IN ('D97B-0795-975B', '70D7-D1AB-12A4')
   GROUP BY
     1,
     2,
     3
 ),
 -- =================================================================================================
 -- Final Combination
 -- =================================================================================================
 legacy_kpis AS (
   SELECT
     cs.usage_start_time,
     'legacy' AS model_version,
     CAST(NULL AS STRING) AS subscription_instance_id,
     cs.cud_product,
     cs.service,
     cs.commitment_cost,
     cs.commitment_savings,
     u.cud_utilization_percent,
     NULL AS effective_savings_rate
   FROM
     legacy_commitment_savings AS cs
     LEFT JOIN legacy_cud_utilization AS u USING (usage_start_time, cud_product)
   UNION ALL
   SELECT
     es.usage_start_time,
     'legacy' AS model_version,
     CAST(NULL AS STRING) AS subscription_instance_id,
     NULL AS cud_product,
     NULL AS service,
     NULL AS commitment_cost,
     NULL AS commitment_savings,
     NULL AS cud_utilization_percent,
     SAFE_DIVIDE(s.commitment_savings, (es.cost + es.costs_ineligible_for_cud - IFNULL(s.spend_cud_credits, 0))) * 100 AS effective_savings_rate
   FROM
     eligible_cud_spend AS es
     LEFT JOIN total_cud_savings AS s USING (usage_start_time)
 ),
 new_kpis AS (
   SELECT
     ncc.usage_start_time,
     'new' AS model_version,
     CAST(ncc.subscription_instance_id AS STRING) AS subscription_instance_id,
     CAST(NULL AS STRING) AS cud_product,
     ncc.service,
     ncc.commitment_cost,
     ncc.commitment_cost + ncc.fee_utilization_offset + IFNULL(ncs.cud_savings_amount, 0) AS commitment_savings,
     SAFE_DIVIDE(ABS(ncc.fee_utilization_offset), ncc.commitment_cost) * 100 AS cud_utilization_percent,
     SAFE_DIVIDE((ncc.commitment_cost + ncc.fee_utilization_offset + IFNULL(ncs.cud_savings_amount, 0)), IFNULL(ncs.on_demand_costs, 1)) * 100 AS effective_savings_rate
   FROM
     new_model_commitment_costs AS ncc
     LEFT JOIN new_model_cud_savings AS ncs USING (usage_start_time, subscription_instance_id, service)
 )
SELECT
*
FROM
 legacy_kpis
UNION ALL
SELECT
*
FROM
 new_kpis;

관련 주제

• 지출 기반 CUD 프로그램 개선사항
• 지출 기반 CUD 데이터 모델 변경사항
• 이전 후 할인 확인
• 구매할 CUD의 올바른 금액 선택
• 이전된 CUD SKU, 혜택, 가격 모델 ID
• 결제 사용자 인터페이스 개선사항