Symfony Profiler

with
  totals as (
    select
      count (*) filter (
        where
          kpi_2_final_energy_consumption < 150
      ) as blg_analytics,
      count (*) as blg,
      sum(mgm.numberofdwellings) filter (
        where
          kpi_2_final_energy_consumption < 150
      ) as dwe_analytics,
      sum(mgm.numberofdwellings) as dwe,
      sum(mgm.habitantes) filter (
        where
          kpi_2_final_energy_consumption < 150
      ) as hab_analytics,
      sum(mgm.habitantes) as hab
    from
      mat_map_geo_buildings mgm
    where
      adminunit in (17170)
      and mgm.use <> '-'
  )
select
  round(
    100 * blg_analytics :: numeric / blg,
    0
  ) as blg_per,
  round(
    100 * dwe_analytics :: numeric / dwe,
    0
  ) as dwe_per,
  round(
    100 * hab_analytics :: numeric / hab,
    0
  ) as hab_per,
  *
from
  totals

with totals as (
                select
                    count (*) filter ( where kpi_2_final_energy_consumption < 150) as blg_analytics,
                    count (*) as blg,
                    sum(mgm.numberofdwellings) filter (where kpi_2_final_energy_consumption < 150 ) as dwe_analytics,
                    sum(mgm.numberofdwellings) as dwe,
                    sum(mgm.habitantes) filter (where kpi_2_final_energy_consumption < 150 ) as hab_analytics,
                    sum(mgm.habitantes) as hab
                from mat_map_geo_buildings mgm
                where adminunit in (17170) and mgm.use <> '-'
            )
            select
                round(100 * blg_analytics::numeric / blg, 0) as blg_per,
                round(100 * dwe_analytics::numeric / dwe, 0) as dwe_per,
                round(100 * hab_analytics::numeric / hab, 0) as hab_per,
                *
            from totals;

select
  inspireid,
  censalsection,
  district
from
  mat_map_geo_buildings mmgb
where
  adminunit in (17170)
  and kpi_2_final_energy_consumption < 150

select inspireid, censalsection, district
            from mat_map_geo_buildings mmgb
            where adminunit in (17170) 
            and kpi_2_final_energy_consumption < 150;

with
  totals as (
    select
      count (*) as blg_analytics,
      count (*) as blg,
      sum(mgm.numberofdwellings) as dwe_analytics,
      sum(mgm.numberofdwellings) as dwe,
      sum(mgm.habitantes) as hab_analytics,
      sum(mgm.habitantes) as hab
    from
      mat_map_geo_buildings mgm
    where
      adminunit in (17170)
  )
select
  round(
    100 * blg_analytics :: numeric / blg,
    0
  ) as blg_per,
  round(
    100 * hab_analytics :: numeric / hab,
    0
  ) as hab_per,
  round(
    100 * dwe_analytics :: numeric / dwe,
    0
  ) as dwe_per,
  *
from
  totals

with totals as (
            select
            count (*) as blg_analytics,
            count (*) as blg,
            sum(mgm.numberofdwellings) as dwe_analytics,
            sum(mgm.numberofdwellings) as dwe,
            sum(mgm.habitantes) as hab_analytics,
            sum(mgm.habitantes) as hab
            from mat_map_geo_buildings mgm where adminunit in (17170)
        )
        select
            round(100 * blg_analytics::numeric / blg, 0) as blg_per,
            round(100 * hab_analytics::numeric / hab, 0) as hab_per,
            round(100 * dwe_analytics::numeric / dwe, 0) as dwe_per,
        * from totals;

SELECT
  adminunitname,
  geom,
  Box2D(
    ST_envelope(geom)
  ) AS envelope
FROM
  public.map_geo_municipio
WHERE
  adminunit = 17170
LIMIT
  1;

SELECT adminunitname, geom, Box2D(ST_envelope(geom)) AS envelope FROM public.map_geo_municipio WHERE adminunit = 17170 LIMIT 1;;

select
  *
from
  stat_analytic_related_kpis sa
  join kpi k on k.id = sa.kpi
  left join analytic_related_kpis ark on ark.analytic_id = sa.analytic
  and ark.kpi_id = sa.kpi
where
  adminunit in (17170)
  and analytic = 2
order by
  ark.order

select *
               from stat_analytic_related_kpis sa
	       join kpi k on k.id = sa.kpi
               left join analytic_related_kpis ark on ark.analytic_id = sa.analytic and ark.kpi_id = sa.kpi 
	       where adminunit in (17170) and analytic = 2
	       order by ark.order;

select
  *
from
  stat_analytic_related_kpis sa
  join kpi k on k.id = sa.kpi
  left join analytic_related_kpis ark on ark.analytic_id = sa.analytic
  and ark.kpi_id = sa.kpi
where
  adminunit in (17170)
  and analytic = 2
order by
  category

select *
               from stat_analytic_related_kpis sa
	       join kpi k on k.id = sa.kpi
               left join analytic_related_kpis ark on ark.analytic_id = sa.analytic and ark.kpi_id = sa.kpi 
	       where adminunit in (17170) and analytic = 2
	       order by category;

SELECT
  kpi_legend.bgcolor,
  kpi_legend.min,
  kpi_legend.max,
  kpi_legend.kpi_id
FROM
  public.kpi_legend -- GROUP BY kpi_legend.kpi_id, kpi_legend.id
order by
  kpi_legend.kpi_id,
  kpi_legend.min ASC

SELECT kpi_legend.bgcolor, kpi_legend.min, kpi_legend.max, kpi_legend.kpi_id 
        FROM public.kpi_legend
        -- GROUP BY kpi_legend.kpi_id, kpi_legend.id
        order by kpi_legend.kpi_id, kpi_legend.min ASC;

select
  *
from
  public.map_geo_municipio
where
  adminunit = 17170;

select * from public.map_geo_municipio where adminunit = 17170;;

select
  *
from
  stat_analytic_ocupacion
where
  adminunit in (17170)
  and analytic = 2

select *
                  from stat_analytic_ocupacion
                  where adminunit in (17170) and analytic = 2;

SELECT
  t0.id AS id_1,
  t0.question AS question_2,
  t0.response AS response_3,
  t0.datecache AS datecache_4,
  t0.adminunit AS adminunit_5
FROM
  cache_ai t0
WHERE
  t0.question = ?
  AND t0.adminunit = ?
LIMIT
  1

SELECT t0.id AS id_1, t0.question AS question_2, t0.response AS response_3, t0.datecache AS datecache_4, t0.adminunit AS adminunit_5 FROM cache_ai t0 WHERE t0.question = 'Indicadores: tema: Edificios eficientes edificios: 513 (9%) habitantes: 2249 (10%) consumo final de energía (kWh/m²año): 129.83 (nivel: bajo)\\nconsumo de energía de calefacción (kWh/m²año): 90.84 (nivel: bajo)\\nprecio de la vivienda (€/m2): 6.48 (nivel: bajo)\\nviviendas energéticamente eficientes: 0.06 (nivel: bajo)\\nsuperficies de zonas verdes (Ha): 13.08 (nivel: bajo)\\nacceso al carril bici: 0.22 (nivel: bajo)\\npoblación con ingresos inferiores al 60% de la media: 0.00 (nivel: bajo)\\nviviendas energéticamente eficientes y recuperadoras de energía: 1.00 (nivel: alto)\\npotencial de generación solar fotovoltaica (kWh/m²año): 8231.77 (nivel: bajo)\\nacceso a puntos de recarga: 22001.37 (nivel: bajo)\\n' AND t0.adminunit = 17170 LIMIT 1;

select
  *
from
  stat_analytic_data
where
  adminunit in (17170)
  and analytic = 2

select *
                  from stat_analytic_data
                  where adminunit in (17170) and analytic = 2;

select
  *
from
  stat_analytic_buildinguse
where
  adminunit in (17170)
  and analytic = 2

select *
                  from stat_analytic_buildinguse
                  where adminunit in (17170) and analytic = 2;

select
  *
from
  public.kpi
where
  activo = 1
order by
  kpi.category,
  kpi.id ASC;

select * from public.kpi where activo = 1 order by kpi.category, kpi.id  ASC;;

SELECT
  c0_.id AS id_0,
  c0_.fk_config_id AS sclr_1,
  c0_.fk_layers_id AS sclr_2,
  c0_.style AS style_3
FROM
  config_geo_layers c0_
ORDER BY
  c0_.fk_config_id ASC

SELECT c0_.id AS id_0, c0_.fk_config_id AS sclr_1, c0_.fk_layers_id AS sclr_2, c0_.style AS style_3 FROM config_geo_layers c0_ ORDER BY c0_.fk_config_id ASC;

SELECT
  t0.id AS id_1,
  t0.name AS name_2,
  t0.filter AS filter_3,
  t0.status AS status_4,
  t0.range_min AS range_min_5,
  t0.range_max AS range_max_6,
  t0.level AS level_7,
  t0.slug AS slug_8
FROM
  analytic t0
WHERE
  t0.slug = ?

SELECT t0.id AS id_1, t0.name AS name_2, t0.filter AS filter_3, t0.status AS status_4, t0.range_min AS range_min_5, t0.range_max AS range_max_6, t0.level AS level_7, t0.slug AS slug_8 FROM analytic t0 WHERE t0.slug = 'edificios-eficientes';

SELECT
  l0_.id AS id_0,
  l0_.name AS name_1,
  l0_.name_geo_server AS name_geo_server_2,
  l0_.static AS static_3,
  l0_.zoom_min AS zoom_min_4,
  l0_.zoom_max AS zoom_max_5,
  l0_.position AS position_6,
  l0_.slug AS slug_7,
  l0_.token AS token_8,
  l0_.auth_key AS auth_key_9,
  l0_.opacity AS opacity_10,
  l0_.grouped AS grouped_11,
  l0_.visibility AS visibility_12
FROM
  layers l0_
ORDER BY
  l0_.grouped ASC

SELECT l0_.id AS id_0, l0_.name AS name_1, l0_.name_geo_server AS name_geo_server_2, l0_.static AS static_3, l0_.zoom_min AS zoom_min_4, l0_.zoom_max AS zoom_max_5, l0_.position AS position_6, l0_.slug AS slug_7, l0_.token AS token_8, l0_.auth_key AS auth_key_9, l0_.opacity AS opacity_10, l0_.grouped AS grouped_11, l0_.visibility AS visibility_12 FROM layers l0_ ORDER BY l0_.grouped ASC;

select
  *
from
  stat_analytic_year
where
  adminunit in (17170)
  and analytic = 2

select *
                  from stat_analytic_year
                  where adminunit in (17170) and analytic = 2;

select
  *
from
  stat_analytic_grossfloorarea
where
  adminunit in (17170)
  and analytic = 2

select *
                  from stat_analytic_grossfloorarea
                  where adminunit in (17170) and analytic = 2;

select
  bgcolor
from
  public.kpi_legend
where
  kpi_id = 3;

select bgcolor from public.kpi_legend where kpi_id = 3;;

SELECT
  x.*
FROM
  public.analytic x
WHERE
  x.status = 1
  AND x.id = 2;

SELECT x.* FROM public.analytic x WHERE x.status = 1 AND x.id = 2 ;;

SELECT
  x.*
FROM
  public.analytic x
WHERE
  x.status = 1

SELECT x.* FROM public.analytic x WHERE x.status = 1;