Понимание операторов EXPLAIN в аналогичных базах данных MySQL и PostgreSQL

В настоящее время я работаю над веб-службой, которая поддерживает несколько баз данных. Я пытаюсь оптимизировать таблицы и исправить отсутствующие индексы. Ниже приведен запрос MySQL:

SELECT 'UTC' AS timezone, pak.id AS package_id, rel.unique_id AS relay, sns.unique_id AS sensor, pak.rtime AS time,
   sns.units AS sensor_units, typ.name AS sensor_type, dat.data AS sensor_data,
   loc.altitude AS altitude, Y(loc.location) AS latitude, X(loc.location) as longitude,
   loc.speed as speed, loc.climb as climb, loc.track as track,
   loc.longitude_error as longitude_error, loc.latitude_error as latitude_error, loc.altitude_error as altitude_error,
   loc.speed_error as speed_error, loc.climb_error as climb_error, loc.track_error as track_error
 FROM sensor_data dat
 LEFT OUTER JOIN package_location loc on dat.package_id = loc.package_id
 LEFT OUTER JOIN data_package pak ON dat.package_id = pak.id
 LEFT OUTER JOIN relays rel ON pak.relay_id = rel.id
 LEFT OUTER JOIN sensors sns ON dat.sensor_id = sns.id
 LEFT OUTER JOIN sensor_types typ ON sns.sensor_type = typ.id
 WHERE typ.name='Temperature'
   AND rel.unique_id='OneWireTester'
   AND pak.rtime > '2015-01-01'
   AND pak.rtime < '2016-01-01'

а объяснение...

+----+-------------+-------+--------+------------------------------------------+----------------------+---------+------------------------+------+----------------------------------------------------+
| id | select_type | table | type   | possible_keys                            | key                  | key_len | ref                    | rows | Extra                                              |
+----+-------------+-------+--------+------------------------------------------+----------------------+---------+------------------------+------+----------------------------------------------------+
|  1 | SIMPLE      | rel   | ALL    | PRIMARY                                  | NULL                 | NULL    | NULL                   |    5 | Using where                                        |
|  1 | SIMPLE      | pak   | ref    | PRIMARY,fk_package_relay_id              | fk_package_relay_id  | 9       | BigSense.rel.id        |    1 | Using index condition; Using where                 |
|  1 | SIMPLE      | dat   | ref    | fk_sensor_package_id,fk_sensor_sensor_id | fk_sensor_package_id | 9       | BigSense.pak.id        |    1 | NULL                                               |
|  1 | SIMPLE      | sns   | eq_ref | PRIMARY,fk_sensors_type_id               | PRIMARY              | 8       | BigSense.dat.sensor_id |    1 | NULL                                               |
|  1 | SIMPLE      | loc   | eq_ref | PRIMARY                                  | PRIMARY              | 8       | BigSense.pak.id        |    1 | NULL                                               |
|  1 | SIMPLE      | typ   | ALL    | PRIMARY                                  | NULL                 | NULL    | NULL                   |    5 | Using where; Using join buffer (Block Nested Loop) |
+----+-------------+-------+--------+------------------------------------------+----------------------+---------+------------------------+------+----------------------------------------------------+

... кажется довольно прямолинейным. Мне нужно добавить индекс в таблицу relays и sensor_types, чтобы оптимизировать запрос.

Таблицы для версии PostgreSQL практически идентичны. Однако, когда я использую следующий запрос:

SELECT 'UTC' AS timezone, pak.id AS package_id, rel.unique_id AS relay, sns.unique_id AS sensor, pak.rtime AS time,
       sns.units AS sensor_units, typ.name AS sensor_type, dat.data AS sensor_data,
       loc.altitude AS altitude, ST_Y(loc.location::geometry) AS latitude, ST_X(loc.location::geometry) as longitude,
       loc.speed as speed, loc.climb as climb, loc.track as track,
       loc.longitude_error as longitude_error, loc.latitude_error as latitude_error, loc.altitude_error as altitude_error,
       loc.speed_error as speed_error, loc.climb_error as climb_error, loc.track_error as track_error
FROM sensor_data dat
LEFT OUTER JOIN package_location loc on dat.package_id = loc.package_id
LEFT OUTER JOIN data_package pak ON dat.package_id = pak.id
LEFT OUTER JOIN relays rel ON pak.relay_id = rel.id
LEFT OUTER JOIN sensors sns ON dat.sensor_id = sns.id
LEFT OUTER JOIN sensor_types typ ON sns.sensor_type = typ.id
WHERE typ.name='Temperature'
  AND rel.unique_id='OneWireTester'
  AND pak.rtime > '2015-01-01'
  AND pak.rtime < '2016-01-01';

Если я делаю анализ объяснения, я получаю следующее:

    QUERY PLAN                                                                          
-------------------------------------------------------------------------------------------------------------------------------------------------------------
 Nested Loop Left Join  (cost=36.23..131.80 rows=1 width=477) (actual time=0.074..3.933 rows=76 loops=1)
   ->  Nested Loop  (cost=36.09..131.60 rows=1 width=349) (actual time=0.068..3.782 rows=76 loops=1)
         ->  Nested Loop  (cost=35.94..130.58 rows=4 width=267) (actual time=0.062..2.472 rows=620 loops=1)
               ->  Hash Join  (cost=35.67..128.73 rows=4 width=247) (actual time=0.053..0.611 rows=620 loops=1)
                     Hash Cond: (dat.sensor_id = sns.id)
                     ->  Seq Scan on sensor_data dat  (cost=0.00..89.46 rows=946 width=21) (actual time=0.007..0.178 rows=1006 loops=1)
                     ->  Hash  (cost=35.64..35.64 rows=2 width=238) (actual time=0.037..0.037 rows=11 loops=1)
                           Buckets: 1024  Batches: 1  Memory Usage: 1kB
                           ->  Hash Join  (cost=20.68..35.64 rows=2 width=238) (actual time=0.019..0.035 rows=11 loops=1)
                                 Hash Cond: (sns.sensor_type = typ.id)
                                 ->  Seq Scan on sensors sns  (cost=0.00..13.60 rows=360 width=188) (actual time=0.002..0.005 rows=31 loops=1)
                                 ->  Hash  (cost=20.62..20.62 rows=4 width=66) (actual time=0.010..0.010 rows=1 loops=1)
                                       Buckets: 1024  Batches: 1  Memory Usage: 1kB
                                       ->  Seq Scan on sensor_types typ  (cost=0.00..20.62 rows=4 width=66) (actual time=0.006..0.008 rows=1 loops=1)
                                             Filter: ((name)::text = 'Temperature'::text)
                                             Rows Removed by Filter: 4
               ->  Index Scan using data_package_pkey on data_package pak  (cost=0.28..0.45 rows=1 width=20) (actual time=0.002..0.002 rows=1 loops=620)
                     Index Cond: (id = dat.package_id)
                     Filter: ((rtime > '2015-01-01 00:00:00'::timestamp without time zone) AND (rtime < '2016-01-01 00:00:00'::timestamp without time zone))
         ->  Index Scan using relays_pkey on relays rel  (cost=0.14..0.24 rows=1 width=94) (actual time=0.002..0.002 rows=0 loops=620)
               Index Cond: (id = pak.relay_id)
               Filter: ((unique_id)::text = 'OneWireTester'::text)
               Rows Removed by Filter: 1
   ->  Index Scan using package_location_pkey on package_location loc  (cost=0.14..0.18 rows=1 width=140) (actual time=0.001..0.001 rows=0 loops=76)
         Index Cond: (dat.package_id = package_id)
 Planning time: 0.959 ms
 Execution time: 4.030 ms
(27 rows)

Схема таблицы имеет те же внешние ключи и общую структуру, поэтому я ожидаю увидеть те же требуемые индексы. Однако я просмотрел несколько руководств по оператору проверки pgsql, и из того, что я собрал, операторы Seq Scan являются индикаторами отсутствующих индексов, что означает отсутствие индексов на sensors, sensor_data и sensor_type.

Правильно ли я интерпретирую результаты этих проверок? Что я должен искать, чтобы оптимизировать обе базы данных?