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wip: materialized view #278

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180 changes: 180 additions & 0 deletions postgres/schemas/materialized_view.py
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from sqlalchemy import create_engine, text
import logging
from postgres.database_connection import get_db_session
# Define your database connection

session = get_db_session()

def create_materialized_views_mv_average_part_env_per_media_mobile(session):
mv_average_part_env_per_media = text("""
CREATE MATERIALIZED VIEW IF NOT EXISTS environmental_avg_yearly AS
SELECT
DATE_TRUNC('month', CAST("source"."start" AS timestamp)) AS "start",
AVG("source"."% environnement total") AS "avg"
FROM
(
SELECT
DATE_TRUNC('week', CAST("source"."start" AS timestamp)) AS "start",
"source"."Program Metadata - Channel Name__channel_title" AS "Program Metadata - Channel Name__channel_title",
CAST(100 * SUM("source"."sum") AS float) / NULLIF(
SUM(
"source"."Program Metadata - Channel Name__duration_minutes"
),
0
) AS "% environnement total"
FROM
(
SELECT
CAST("source"."start" AS date) AS "start",
"source"."Program Metadata - Channel Name__channel_program" AS "Program Metadata - Channel Name__channel_program",
"source"."Program Metadata - Channel Name__channel_title" AS "Program Metadata - Channel Name__channel_title",
"source"."Program Metadata - Channel Name__duration_minutes" AS "Program Metadata - Channel Name__duration_minutes",
SUM("source"."crise_env_minutes") AS "sum"
FROM
(
SELECT
"public"."keywords"."id" AS "id",
"public"."keywords"."start" AS "start",
"public"."keywords"."plaintext" AS "plaintext",
"public"."keywords"."theme" AS "theme",
"public"."keywords"."keywords_with_timestamp" AS "keywords_with_timestamp",
"public"."keywords"."number_of_keywords" AS "number_of_keywords",
"public"."keywords"."number_of_changement_climatique_constat" AS "number_of_changement_climatique_constat",
"public"."keywords"."number_of_changement_climatique_causes_directes" AS "number_of_changement_climatique_causes_directes",
"public"."keywords"."number_of_changement_climatique_consequences" AS "number_of_changement_climatique_consequences",
"public"."keywords"."number_of_adaptation_climatique_solutions_directes" AS "number_of_adaptation_climatique_solutions_directes",
"public"."keywords"."number_of_attenuation_climatique_solutions_directes" AS "number_of_attenuation_climatique_solutions_directes",
"public"."keywords"."number_of_biodiversite_concepts_generaux" AS "number_of_biodiversite_concepts_generaux",
"public"."keywords"."number_of_biodiversite_causes_directes" AS "number_of_biodiversite_causes_directes",
"public"."keywords"."number_of_biodiversite_consequences" AS "number_of_biodiversite_consequences",
"public"."keywords"."number_of_biodiversite_solutions_directes" AS "number_of_biodiversite_solutions_directes",
"public"."keywords"."number_of_ressources" AS "number_of_ressources",
"public"."keywords"."number_of_ressources_solutions" AS "number_of_ressources_solutions",
CAST(
"public"."keywords"."number_of_keywords" * 20 AS float
) / 60.0 AS "crise_env_minutes",
CAST(
"public"."keywords"."number_of_changement_climatique_constat" * 20 AS float
) / 60.0 AS "climat_constat_minutes",
CAST(
"public"."keywords"."number_of_changement_climatique_causes_directes" * 20 AS float
) / 60.0 AS "climat_cause_minutes",
CAST(
"public"."keywords"."number_of_changement_climatique_consequences" * 20 AS float
) / 60.0 AS "climat_consequence_minutes",
CAST(
"public"."keywords"."number_of_biodiversite_concepts_generaux" * 20 AS float
) / 60.0 AS "biodiversite_concept_minutes",
CAST(
"public"."keywords"."number_of_biodiversite_causes_directes" * 20 AS float
) / 60.0 AS "biodiversite_cause_minutes",
CAST(
"public"."keywords"."number_of_biodiversite_consequences" * 20 AS float
) / 60.0 AS "biodiversite_consequence_minutes",
CAST(
"public"."keywords"."number_of_biodiversite_solutions_directes" * 20 AS float
) / 60.0 AS "biodiversite_solution_minutes",
CAST(
"public"."keywords"."number_of_attenuation_climatique_solutions_directes" * 20 AS float
) / 60.0 AS "climat_attenuation_minutes",
CAST(
"public"."keywords"."number_of_adaptation_climatique_solutions_directes" * 20 AS float
) / 60.0 AS "climat_adaptation_minutes",
CAST(
"public"."keywords"."number_of_ressources" * 20 AS float
) / 60.0 AS "ressource_minutes",
CAST(
"public"."keywords"."number_of_ressources_solutions" * 20 AS float
) / 60.0 AS "ressource_solution_minute",
CAST(
"public"."keywords"."number_of_keywords_climat" * 20 AS float
) / 60.0 AS "climat_total_minutes",
CAST(
"public"."keywords"."number_of_keywords_biodiversite" * 20 AS float
) / 60.0 AS "biodiversite_total_minutes",
CAST(
"public"."keywords"."number_of_keywords_ressources" * 20 AS float
) / 60.0 AS "ressource_total_minutes",
"public"."keywords"."channel_name" AS "channel_name",
"Program Metadata - Channel Name"."duration_minutes" AS "Program Metadata - Channel Name__duration_minutes",
"Program Metadata - Channel Name"."weekday" AS "Program Metadata - Channel Name__weekday",
"Program Metadata - Channel Name"."public" AS "Program Metadata - Channel Name__public",
"Program Metadata - Channel Name"."infocontinue" AS "Program Metadata - Channel Name__infocontinue",
"Program Metadata - Channel Name"."radio" AS "Program Metadata - Channel Name__radio",
"Program Metadata - Channel Name"."start" AS "Program Metadata - Channel Name__start",
"Program Metadata - Channel Name"."end" AS "Program Metadata - Channel Name__end",
"Program Metadata - Channel Name"."channel_title" AS "Program Metadata - Channel Name__channel_title",
"Program Metadata - Channel Name"."channel_program" AS "Program Metadata - Channel Name__channel_program",
"Program Metadata - Channel Name"."channel_program_type" AS "Program Metadata - Channel Name__channel_program_type"
FROM
"public"."keywords"
INNER JOIN "public"."program_metadata" AS "Program Metadata - Channel Name" ON (
"public"."keywords"."channel_name" = "Program Metadata - Channel Name"."channel_name"
)
AND (
"public"."keywords"."channel_program" = "Program Metadata - Channel Name"."channel_program"
)
AND (
"public"."keywords"."channel_program_type" = "Program Metadata - Channel Name"."channel_program_type"
)
AND (
COALESCE(
NULLIF(
(
(
(
CAST(
extract(
dow
from
"public"."keywords"."start"
) AS integer
) + 1
) + 6
) % 7
),
0
),
7
) = "Program Metadata - Channel Name"."weekday"
)
AND (
CAST("public"."keywords"."start" AS date) >= CAST(
"Program Metadata - Channel Name"."program_grid_start" AS date
)
)
AND (
CAST("public"."keywords"."start" AS date) <= CAST(
"Program Metadata - Channel Name"."program_grid_end" AS date
)
)
) AS "source"
GROUP BY
CAST("source"."start" AS date),
"source"."Program Metadata - Channel Name__channel_program",
"source"."Program Metadata - Channel Name__channel_title",
"source"."Program Metadata - Channel Name__duration_minutes"
ORDER BY
CAST("source"."start" AS date) ASC,
"source"."Program Metadata - Channel Name__channel_program" ASC,
"source"."Program Metadata - Channel Name__channel_title" ASC,
"source"."Program Metadata - Channel Name__duration_minutes" ASC
) AS "source"
GROUP BY
DATE_TRUNC('week', CAST("source"."start" AS timestamp)),
"source"."Program Metadata - Channel Name__channel_title"
ORDER BY
DATE_TRUNC('week', CAST("source"."start" AS timestamp)) ASC,
"source"."Program Metadata - Channel Name__channel_title" ASC
) AS "source"
GROUP BY
DATE_TRUNC('month', CAST("source"."start" AS timestamp))
ORDER BY
DATE_TRUNC('month', CAST("source"."start" AS timestamp)) ASC;
""")
with session.connect() as connection:
logging.info(f"Creating materialized view {create_materialized_views_mv_average_part_env_per_media_mobile}")
connection.execute(create_materialized_views_mv_average_part_env_per_media_mobile)
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