297 lines
8.0 KiB
SQL
297 lines
8.0 KiB
SQL
---------------------------------------------------------------
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---------------------------- Views ----------------------------
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---------------------------------------------------------------
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--------------------------------
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--------- User Streaks ---------
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--------------------------------
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CREATE VIEW view_user_streaks AS
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WITH document_windows AS (
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SELECT
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activity.user_id,
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users.timezone,
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DATE(
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LOCAL_TIME(activity.start_time, users.timezone),
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'weekday 0', '-7 day'
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) AS weekly_read,
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DATE(LOCAL_TIME(activity.start_time, users.timezone)) AS daily_read
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FROM activity
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LEFT JOIN users ON users.id = activity.user_id
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GROUP BY activity.user_id, weekly_read, daily_read
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),
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weekly_partitions AS (
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SELECT
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user_id,
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timezone,
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'WEEK' AS "window",
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weekly_read AS read_window,
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row_number() OVER (
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PARTITION BY user_id ORDER BY weekly_read DESC
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) AS seqnum
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FROM document_windows
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GROUP BY user_id, weekly_read
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),
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daily_partitions AS (
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SELECT
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user_id,
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timezone,
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'DAY' AS "window",
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daily_read AS read_window,
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row_number() OVER (
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PARTITION BY user_id ORDER BY daily_read DESC
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) AS seqnum
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FROM document_windows
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GROUP BY user_id, daily_read
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),
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streaks AS (
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SELECT
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COUNT(*) AS streak,
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MIN(read_window) AS start_date,
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MAX(read_window) AS end_date,
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window,
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user_id,
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timezone
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FROM daily_partitions
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GROUP BY
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timezone,
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user_id,
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DATE(read_window, '+' || seqnum || ' day')
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UNION ALL
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SELECT
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COUNT(*) AS streak,
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MIN(read_window) AS start_date,
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MAX(read_window) AS end_date,
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window,
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user_id,
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timezone
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FROM weekly_partitions
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GROUP BY
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timezone,
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user_id,
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DATE(read_window, '+' || (seqnum * 7) || ' day')
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),
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max_streak AS (
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SELECT
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MAX(streak) AS max_streak,
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start_date AS max_streak_start_date,
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end_date AS max_streak_end_date,
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window,
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user_id
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FROM streaks
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GROUP BY user_id, window
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),
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current_streak AS (
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SELECT
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streak AS current_streak,
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start_date AS current_streak_start_date,
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end_date AS current_streak_end_date,
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window,
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user_id
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FROM streaks
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WHERE CASE
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WHEN window = "WEEK" THEN
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DATE(LOCAL_TIME(STRFTIME('%Y-%m-%dT%H:%M:%SZ', 'now'), timezone), 'weekday 0', '-14 day') = current_streak_end_date
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OR DATE(LOCAL_TIME(STRFTIME('%Y-%m-%dT%H:%M:%SZ', 'now'), timezone), 'weekday 0', '-7 day') = current_streak_end_date
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WHEN window = "DAY" THEN
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DATE(LOCAL_TIME(STRFTIME('%Y-%m-%dT%H:%M:%SZ', 'now'), timezone), '-1 day') = current_streak_end_date
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OR DATE(LOCAL_TIME(STRFTIME('%Y-%m-%dT%H:%M:%SZ', 'now'), timezone)) = current_streak_end_date
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END
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GROUP BY user_id, window
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)
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SELECT
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max_streak.user_id,
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max_streak.window,
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IFNULL(max_streak, 0) AS max_streak,
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IFNULL(max_streak_start_date, "N/A") AS max_streak_start_date,
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IFNULL(max_streak_end_date, "N/A") AS max_streak_end_date,
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IFNULL(current_streak, 0) AS current_streak,
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IFNULL(current_streak_start_date, "N/A") AS current_streak_start_date,
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IFNULL(current_streak_end_date, "N/A") AS current_streak_end_date
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FROM max_streak
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LEFT JOIN current_streak ON
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current_streak.user_id = max_streak.user_id
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AND current_streak.window = max_streak.window;
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--------------------------------
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------- Document Stats ---------
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--------------------------------
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CREATE VIEW view_document_user_statistics AS
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WITH intermediate_ga AS (
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SELECT
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ga1.id AS row_id,
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ga1.user_id,
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ga1.document_id,
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ga1.duration,
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ga1.start_time,
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ga1.start_percentage,
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ga1.end_percentage,
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-- Find Overlapping Events (Assign Unique ID)
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(
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SELECT MIN(id)
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FROM activity AS ga2
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WHERE
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ga1.document_id = ga2.document_id
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AND ga1.user_id = ga2.user_id
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AND ga1.start_percentage <= ga2.end_percentage
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AND ga1.end_percentage >= ga2.start_percentage
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) AS group_leader
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FROM activity AS ga1
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),
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grouped_activity AS (
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SELECT
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user_id,
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document_id,
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MAX(start_time) AS start_time,
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MIN(start_percentage) AS start_percentage,
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MAX(end_percentage) AS end_percentage,
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MAX(end_percentage) - MIN(start_percentage) AS read_percentage,
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SUM(duration) AS duration
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FROM intermediate_ga
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GROUP BY group_leader
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),
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current_progress AS (
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SELECT
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user_id,
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document_id,
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COALESCE((
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SELECT percentage
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FROM document_progress AS dp
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WHERE
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dp.user_id = iga.user_id
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AND dp.document_id = iga.document_id
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ORDER BY created_at DESC
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LIMIT 1
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), end_percentage) AS percentage
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FROM intermediate_ga AS iga
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GROUP BY user_id, document_id
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HAVING MAX(start_time)
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)
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SELECT
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ga.document_id,
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ga.user_id,
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cp.percentage,
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MAX(start_time) AS last_read,
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SUM(read_percentage) AS read_percentage,
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-- All Time WPM
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SUM(duration) AS total_time_seconds,
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(CAST(COALESCE(d.words, 0.0) AS REAL) * SUM(read_percentage))
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AS total_words_read,
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(CAST(COALESCE(d.words, 0.0) AS REAL) * SUM(read_percentage))
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/ (SUM(duration) / 60.0) AS total_wpm,
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-- Yearly WPM
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SUM(CASE WHEN start_time >= DATE('now', '-1 year') THEN duration ELSE 0 END)
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AS yearly_time_seconds,
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(
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 year') THEN read_percentage
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ELSE 0
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END
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)
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)
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AS yearly_words_read,
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COALESCE((
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 year') THEN read_percentage
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END
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)
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)
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/ (
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SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 year') THEN duration
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END
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)
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/ 60.0
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), 0.0)
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AS yearly_wpm,
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-- Monthly WPM
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SUM(
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CASE WHEN start_time >= DATE('now', '-1 month') THEN duration ELSE 0 END
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)
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AS monthly_time_seconds,
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(
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 month') THEN read_percentage
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ELSE 0
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END
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)
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)
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AS monthly_words_read,
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COALESCE((
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 month') THEN read_percentage
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END
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)
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)
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/ (
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SUM(
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CASE
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WHEN start_time >= DATE('now', '-1 month') THEN duration
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END
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)
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/ 60.0
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), 0.0)
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AS monthly_wpm,
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-- Weekly WPM
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SUM(CASE WHEN start_time >= DATE('now', '-7 days') THEN duration ELSE 0 END)
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AS weekly_time_seconds,
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(
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-7 days') THEN read_percentage
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ELSE 0
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END
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)
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)
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AS weekly_words_read,
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COALESCE((
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CAST(COALESCE(d.words, 0.0) AS REAL)
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* SUM(
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CASE
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WHEN start_time >= DATE('now', '-7 days') THEN read_percentage
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END
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)
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)
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/ (
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SUM(
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CASE
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WHEN start_time >= DATE('now', '-7 days') THEN duration
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END
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)
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/ 60.0
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), 0.0)
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AS weekly_wpm
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FROM grouped_activity AS ga
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INNER JOIN
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current_progress AS cp
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ON ga.user_id = cp.user_id AND ga.document_id = cp.document_id
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INNER JOIN
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documents AS d
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ON ga.document_id = d.id
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GROUP BY ga.document_id, ga.user_id
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ORDER BY total_wpm DESC;
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