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advertising_marketing_small/geo_pid_facts.view.lookml 4 dims1 measure 2 warnings Repo files

LookML view · advertising-marketing-small

geo_pid_facts: a pre-aggregated geo by publisher table with an ambiguous count

At a glance

Does
Reads four columns from a pre-built table: geo, pid, ip_count and a stored count. It adds a row-count measure that is also named count.Trust: Source-defined
Why
Likely a summary of traffic per country and publisher, with distinct IPs, for checking how concentrated a publisher's traffic is by geography. No dashboard tile uses it.Trust: Inferred
Breaks
2 warnings. Top: The row count is not a traffic count
Grain
One row per geo and pid, judging by the columns. No key is declared, so the grain is not enforced.Trust: Inferred
Source
advertising_marketing_small/geo_pid_facts.view.lookml 18 lines
Source: geo_pid_facts.view.lookml L1-10
advertising_marketing_small/geo_pid_facts.view.lookmlL1-10
- view: geo_pid_facts  fields:  - dimension: count    type: int    sql: ${TABLE}.count  - dimension: geo    sql: ${TABLE}.geo  - dimension: ip_count    type: int    sql: ${TABLE}.ip_count  - dimension: pid    type: int    sql: ${TABLE}.pid

advertising-marketing-small, geo_pid_facts.view.lookml, lines 1-10

Shape

Trust: Source-defined

Every field as declared, with the dashboard tiles that read it. Computed from the source; nothing here is edited.

Table: defaults to geo_pid_facts (no sql_table_name).

Dimensions 4
NameTypeSQLUsed byTags
countL3int${TABLE}.count-name reused
geoL6string${TABLE}.geo-
ip_countL8int${TABLE}.ip_count-
pidL11int${TABLE}.pid-

Measures 1
NameTypeSQLUsed byTags
countL14countCOUNT(*) of rows-name reused

Relationships

Trust: Source-defined

No joins, no upstream views and no dashboard tiles reference this view. It is an island in the model.

Relationships of geo_pid_facts
Relationships of geo_pid_facts. Text version follows the diagram.This viewUsed by: explores, views, dashboardsbase view geo_pid_facts explore in odd_browser_and_os_analysis
  • This Block
Text version
  • geo_pid_facts is the base view of geo_pid_facts: base view

Worth noticing

Two fields share the name count

Trust: Source-defined

The dimension count reads the stored column. The measure count counts rows. In the explore field picker they appear under the same name in different sections.

Source: geo_pid_facts.view.lookml L3-16
advertising_marketing_small/geo_pid_facts.view.lookmlL3-16
- view: geo_pid_facts  fields:  - dimension: count    type: int    sql: ${TABLE}.count  - dimension: geo    sql: ${TABLE}.geo  - dimension: ip_count    type: int    sql: ${TABLE}.ip_count  - dimension: pid    type: int    sql: ${TABLE}.pid  - measure: count    type: count    detail: detail*  sets:    detail: null

advertising-marketing-small, geo_pid_facts.view.lookml, lines 3-16

pid is an integer here and a string elsewhere

Trust: Source-defined

pid is type: int. In other_browser_os_impressions, other_browser_os_impressions.pid is a string parsed from subid. Matching them needs a cast and assumes the same parsing built this table.

Source: geo_pid_facts.view.lookml L11-13
advertising_marketing_small/geo_pid_facts.view.lookmlL11-13
  - dimension: ip_count    type: int    sql: ${TABLE}.ip_count  - dimension: pid    type: int    sql: ${TABLE}.pid  - measure: count    type: count    detail: detail*

advertising-marketing-small, geo_pid_facts.view.lookml, lines 11-13

What can change the answer 2

Caution: The row count is not a traffic count

Trust: Source-defined

The measure count counts geo and pid rows. The stored count column is only a dimension, so there is no measure that sums it.

What goes wrong: A chart of count by geo shows how many publishers each geo has, not how much traffic it sends.

Read the guide: Primary keys and counts

Source: geo_pid_facts.view.lookml L14-16
advertising_marketing_small/geo_pid_facts.view.lookmlL14-16
  - dimension: pid    type: int    sql: ${TABLE}.pid  - measure: count    type: count    detail: detail*  sets:    detail: null

advertising-marketing-small, geo_pid_facts.view.lookml, lines 14-16

Note: How the table is built is not in the repo

Trust: Missing

There is no derived table or documentation for the table behind this view. Its date range, filters and PID parsing are unknown.

Read the guide: Missing tables and stale references

Source: geo_pid_facts.view.lookml L1-2
advertising_marketing_small/geo_pid_facts.view.lookmlL1-2
- view: geo_pid_facts  fields:  - dimension: count    type: int    sql: ${TABLE}.count

advertising-marketing-small, geo_pid_facts.view.lookml, lines 1-2

Parser checks 2

Trust: Source-defined

Mechanical findings from parsing the LookML. They are facts about the files. The cards above explain which ones matter.

Show all 2 checks
  • no-primary-key 1
    • geo_pid_facts.view.lookml:1 geo_pid_facts declares no primary_key.
  • name-collision 1
    • geo_pid_facts.view.lookml:14 geo_pid_facts.count is declared as both dimension and measure.

Related

Guides built on this file

Guide Checking whether a few publishers earn most of the revenue How a real ad-tech model ranks publishers by bid revenue, why a ranking is not a concentration measure, and what its parsed publisher id hides. Revenue Guide Checking the primary key before you trust a count A count is only as clear as the key behind it. How to state and test a table's grain, with real tables whose keys repeat, merge rows or are missing. Best practicesRevenueRetention Guide Why parsing ids out of strings at query time is risky An id parsed from a string at query time turns malformed values into fake ids. A real publisher id parsed from a subid, and SQL that returns NULL instead. Best practicesAcquisition Guide Catching missing tables and stale references before a dashboard breaks Models can name tables, fields and explores that do not exist, and nothing fails until a chart runs. Real examples, and how to check yours before release. Best practices

Related source files

Source file other_browser_os_impressions Exposes raw ad impression rows with browser, OS, user agent, IP, geography, subid, campaign, creative and b... view4 warnings Source file ip cluster views Four views over clustering output. ip_2_cluster.class and ip_3_cluster.class label each IP. The model views... 4 views3 warnings

Source model

Source model Inside an AdTech LookML project: traffic quality, publisher revenue and IP clustering AdTech traffic quality 9 views0 joins