Syntax

• Required: FROM · SHOW · GROUP BY · SINCE
• Optional: SEGMENT BY
• Order: FROM → SHOW → GROUP BY → SINCE → SEGMENT BY

FROM products
SHOW SUM(total_sales)
GROUP BY product_id
SINCE -7d

FROM products
SHOW SUM(total_sales) * COUNT(quantity_purchased)
GROUP BY product_id
SINCE this_month
SEGMENT BY geo_city

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Clauses

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FROM

• Purpose: Selects the dataset.
• Example:
  Copy

  FROM products
  

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SHOW

• Purpose: Lists expressions to compute. Typically uses aggregation functions over metrics or fields.
• Examples:
  Copy

  SHOW SUM(total_sales)
  SHOW COUNT(quantity_purchased), MAX(total_sales)
  SHOW COUNT(*)
  

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GROUP BY

• Purpose: Defines the grouping keys for aggregation.
• Keys: Can be identifiers, dimensions, or product_attributes.* paths.
• Examples:
  Copy

  GROUP BY product_id
  GROUP BY product_attributes.color, product_attributes.size
  

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SINCE

• Purpose: Defines the time window for the query.
• Accepted forms:
  • Relative: -7d, -14d, -30d, -60d, -90d, -180d, -365d, -24h, -48h, -12m, -1y
  • Keywords: today, yesterday, this_week, last_week, this_month, last_month, this_quarter, last_quarter, this_year, last_year
  • Common rolling windows: past_7_days, past_14_days, past_30_days, past_60_days, past_90_days, past_180_days, past_365_days
  • ISO: 2025-03-15 or 2025-03-15T10:30:00Z (timezone offsets supported)
• Examples:
  Copy

  SINCE -7d
  SINCE this_month
  SINCE 2025-01-01
  SINCE 2025-01-01T00:00:00Z
  

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SEGMENT BY (optional)

• Purpose: Adds an additional segmentation dimension applied to each group.
• Examples:
  Copy

  SEGMENT BY geo_country
  SEGMENT BY marketing_campaign, geo_country
  

• Identifiers: letters, digits, underscores; start with a letter or underscore.
• Paths: dot notation (for example, product_attributes.color).

• Strings: ‘value’ or “value”
• Numbers: 10, 10.5
• Booleans: TRUE, FALSE

FROM products
SHOW SUM(total_sales)
GROUP BY product_id, product_attributes.metafields.custom.style_code
SINCE past_30_days