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Spike generate popular tasks using BigQuery #3761
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39029ed
Add local_env to the gitignore
beccapearce 4cc4901
Initial BigQuery setup
beccapearce 046d618
Add a BigQuery query to get some initial data
beccapearce 794a1c2
Render popular tasks in view
beccapearce bcebb64
Implement basic caching for the popular tasks
beccapearce b6d0eff
Implement backup cache for popular tasks
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -28,3 +28,6 @@ | |
| # vim swap files and tags | ||
| *.sw[a-z] | ||
| /tags | ||
|
|
||
| # Ignore local config | ||
| config/local_env.yml | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,27 +1,33 @@ | ||
| module BrowseHelper | ||
| def display_popular_links_for_slug?(slug) | ||
| I18n.exists?(slug.to_s, scope: "browse.popular_links") | ||
| def slug(path = base_path) | ||
| path.sub(%r{.*(?=/browse/)}, "") | ||
| end | ||
|
|
||
| def display_popular_tasks_for_slug?(slug) | ||
| %w[benefits business].include?(slug) | ||
| end | ||
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|
||
| def popular_links_for_slug(slug) | ||
| links = I18n.t(slug.to_s, scope: "browse.popular_links") | ||
| count = links.length | ||
| links.map.with_index(1) do |link, index| | ||
| { | ||
| text: link[:title], | ||
| href: link[:url], | ||
| data_attributes: { | ||
| module: "ga4-link-tracker", | ||
| ga4_track_links_only: "", | ||
| ga4_link: { | ||
| event_name: "navigation", | ||
| type: "action", | ||
| index_link: index, | ||
| index_total: count, | ||
| text: link[:title], | ||
| }, | ||
| }, | ||
| } | ||
| browse_page = slug(slug) | ||
|
|
||
| # Cache keys for the specific browse page | ||
| cache_key_latest = "popular_tasks_#{browse_page}_#{Date.yesterday.strftime("%Y-%m-%d")}" | ||
| cache_key_backup = "popular_tasks_backup_#{browse_page}" | ||
|
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||
| # Try to fetch the latest cache first | ||
| popular_task_data = Rails.cache.read(cache_key_latest) | ||
|
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| # If the latest cache doesn't exist, fall back to the backup cache | ||
| if popular_task_data.nil? | ||
| # Falling back to backup cache | ||
| popular_task_data = Rails.cache.read(cache_key_backup) | ||
| end | ||
|
|
||
| # If both caches are empty, fetch fresh data and cache it | ||
| if popular_task_data.nil? | ||
| popular_task_data = PopularTasks.new.fetch_data("/browse/#{browse_page}") | ||
| end | ||
|
|
||
| popular_task_data | ||
| end | ||
| end |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,25 @@ | ||
| require "google/cloud/bigquery" | ||
| require "googleauth" | ||
|
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| class Bigquery | ||
| include Google::Auth | ||
|
|
||
| def self.build | ||
| new.build | ||
| end | ||
|
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| def build | ||
| credentials = { | ||
| "client_email" => ENV["BIGQUERY_CLIENT_EMAIL"], | ||
| "private_key" => ENV["BIGQUERY_PRIVATE_KEY"], | ||
| } | ||
|
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||
| Google::Cloud::Bigquery.new( | ||
| project_id: ENV["BIGQUERY_PROJECT"], | ||
| credentials: Google::Auth::ServiceAccountCredentials.make_creds( | ||
| json_key_io: StringIO.new(credentials.to_json), | ||
| scope: ["https://www.googleapis.com/auth/bigquery"], | ||
| ), | ||
| ) | ||
| end | ||
| end |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,71 @@ | ||
| class PopularTasks | ||
| CACHE_EXPIRATION = 24.hours # Set the cache expiration time | ||
| BACKUP_CACHE_EXPIRATION = 7.days # Backup cache can have a longer expiration | ||
|
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| def initialize; end | ||
|
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| def client | ||
| @client ||= Bigquery.build | ||
| end | ||
|
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| def fetch_data(browse_page, date: Date.yesterday) | ||
| @fetch_data = client | ||
| @date = date.strftime("%Y-%m-%d") | ||
|
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| cache_key_latest = "popular_tasks_#{browse_page}_#{@date}" | ||
| cache_key_backup = "popular_tasks_backup_#{browse_page}" | ||
|
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| Rails.cache.fetch(cache_key_latest, expires_in: CACHE_EXPIRATION) do | ||
| # If cache is empty, this block is executed | ||
| query = <<~SQL | ||
| WITH cte1 as (SELECT | ||
| event_date, | ||
| event_name, | ||
| search_term, | ||
| cleaned_page_location, | ||
| cleaned_page_referrer, | ||
| link_url, | ||
| count(event_name) as click, | ||
|
|
||
| FROM `ga4-analytics-352613.flattened_dataset.flattened_daily_ga_data_*` | ||
| WHERE _TABLE_SUFFIX = FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 2 DAY)) | ||
| -- WHERE _table_suffix IN ('20240708', '20240709','20240710','20240711','20240712','20240713','20240714') | ||
| group by 1,2,3,4,5,6), | ||
|
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||
| CTE2 as (SELECT | ||
| event_date, | ||
| sum(click) as clicks, | ||
| cleaned_page_referrer as BrowsePage, | ||
| search_term, | ||
| ROW_NUMBER() OVER(PARTITION BY cleaned_page_referrer ORDER BY click DESC) Rank, | ||
| link_url as SearchDestPage | ||
| FROM cte1 | ||
| WHERE event_name = 'select_item' | ||
| AND cleaned_page_referrer = '#{browse_page}' | ||
| AND cleaned_page_location = '/search/all' | ||
| group by click,event_date,cleaned_page_referrer,search_term,link_url | ||
| order by cleaned_page_referrer,Rank asc) | ||
|
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||
| SELECT | ||
| * | ||
| FROM CTE2 | ||
| WHERE Rank <6 | ||
| SQL | ||
|
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| data = @fetch_data.query(query).all | ||
| @results = data.map do |row| | ||
| { | ||
| url: row[:SearchDestPage], # Using SearchDestPage as the link URL | ||
| browse_page: row[:BrowsePage], # Using BrowsePage as the L1 browse | ||
| rank: row[:Rank], # Rank to order the links | ||
| } | ||
| end | ||
| @results.sort_by { |link| link[:rank] } # Order the links by their rank | ||
|
|
||
| # Cache the results in the backup cache as well | ||
| Rails.cache.write(cache_key_backup, @results, expires_in: BACKUP_CACHE_EXPIRATION) | ||
|
|
||
| @results | ||
| end | ||
| end | ||
| end | ||
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I think we need to think a bit more about how this would work.
If the bigquery data was unavailable for more than 7 days then what happens?
I can think of other ways to do it - but this feels like a problem that must have been solved many times before. i.e. Only expire the cache if fresh data is available to fill it.
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I've caught up now... the cache will expire regardless of whether or not the API responds so I understand the need for a backup. And I like the idea of writing to the backup at the same time as you fetch the fresh data.