第 1 步：松开手刹
...如果有点慢
SELECT to_char(MIN(ts)::timestamptz, 'YYYY-MM-DD HH24:MI:SS TZ') AS min_time
,SUM(CASE WHEN sensor_id = 572 THEN value ELSE 0.0 END) AS nickname1
,SUM(CASE WHEN sensor_id = 542 THEN value ELSE 0.0 END) AS nickname2
,SUM(CASE WHEN sensor_id = 571 THEN value ELSE 0.0 END) AS nickname3
FROM sensor_values
-- LEFT JOIN sensor_values_cleaned s2 USING (sensor_id, ts)
WHERE ts >= '2013-10-14T00:00:00+00:00'::timestamptz::timestamp
AND ts < '2013-10-18T00:00:00+00:00'::timestamptz::timestamp
AND sensor_id IN (572, 542, 571, 540, 541, 573)
GROUP BY ts::date AS day
ORDER BY 1;
要点
在您的标识符中替换 reserved words（在标准 SQL 中）。
timestamp -> ts
time -> min_time
由于连接在相同的列名上，您可以在连接条件中使用更简单的USING clause：USING (sensor_id, ts)
但是，由于第二个表 sensor_values_cleaned 与此查询 100% 无关，因此我将其完全删除。
正如@joop 已经建议的那样，在您的第一个输出列中切换min() 和to_char()。这样，Postgres 可以从 原始列值 中确定最小值，这通常更快并且可能能够利用索引。在这种特定情况下，date 订购 也比 text 订购便宜，后者还必须考虑整理规则。
-
类似的考虑适用于您的WHERE 条件：
WHERE ts::timestamptz >= '2013-10-14T00:00:00+00:00'::timestamptz
WHERE ts >= '2013-10-14T00:00:00+00:00'::timestamptz::timestamp
第二个是sargable，可以在ts 上使用普通索引 - 对大表的性能有很大影响！
使用ts::date 代替date_trunc('day', ts)。更简单、更快、结果相同。
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很可能您的第二个 WHERE 条件稍微不正确。通常，您会排除上边框：
AND ts <b><=</b> '2013-10-18T00:00:00+00:00' ...
AND ts <b><</b> '2013-10-18T00:00:00+00:00' ...
当混合timestamp 和timestamptz 时，需要注意效果。例如，您的 WHERE 条件不会在当地时间 00:00 结束（除非当地时间与 UTC 重合）。详情看这里：
Ignoring timezones altogether in Rails and PostgreSQL
第 2 步：您的请求
...每个分组中最新和最早时间戳之间的差异
我想你的意思是：
...值最新和最早时间戳之间的差异 ...
否则会简单很多。
为此使用window functions，尤其是first_value() 和last_value()。小心组合，在这种情况下，您需要一个 non-standard window frame 用于 last_value() 。比较：
PostgreSQL aggregate or window function to return just the last value
我将它与DISTINCT ON 结合使用，在这种情况下它比GROUP BY 更方便（需要另一个子查询级别）：
SELECT DISTINCT ON (ts::date, sensor_id)
ts::date AS day
,to_char((min(ts) OVER (PARTITION BY ts::date))::timestamptz
,'YYYY-MM-DD HH24:MI:SS TZ') AS min_time
,sensor_id
,last_value(value) OVER (PARTITION BY ts::date, sensor_id ORDER BY ts
RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
- first_value(value) OVER (PARTITION BY ts::date, sensor_id ORDER BY ts)
AS val_range
FROM sensor_values
WHERE ts >= '2013-10-14T00:00:00+0'::timestamptz::timestamp
AND ts < '2013-10-18T00:00:00+0'::timestamptz::timestamp
AND sensor_id IN (540, 541, 542, 571, 572, 573)
ORDER BY ts::date, sensor_id;
-> SQLfiddle demo.
第 3 步：数据透视表
基于上面的查询，我使用附加模块 tablefunc 中的 crosstab()：
SELECT * FROM crosstab(
$$SELECT DISTINCT ON (1,3)
ts::date AS day
,to_char((min(ts) OVER (PARTITION BY ts::date))::timestamptz,'YYYY-MM-DD HH24:MI:SS TZ') AS min_time
,sensor_id
,last_value(value) OVER (PARTITION BY ts::date, sensor_id ORDER BY ts RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
- first_value(value) OVER (PARTITION BY ts::date, sensor_id ORDER BY ts) AS val_range
FROM sensor_values
WHERE ts >= '2013-10-14T00:00:00+0'::timestamptz::timestamp
AND ts < '2013-10-18T00:00:00+0'::timestamptz::timestamp
AND sensor_id IN (540, 541, 542, 571, 572, 573)
ORDER BY 1, 3$$
,$$VALUES (540), (541), (542), (571), (572), (573)$$
)
AS ct (day date, min_time text, s540 numeric, s541 numeric, s542 numeric, s571 numeric, s572 numeric, s573 numeric);
返回（并且比以前快得多）：
day | min_time | s540 | s541 | s542 | s571 | s572 | s573
------------+--------------------------+-------+-------+-------+-------+-------+-------
2013-10-14 | 2013-10-14 03:00:00 CEST | 18.82 | 18.98 | 19.97 | 19.47 | 17.56 | 21.27
2013-10-15 | 2013-10-15 00:15:00 CEST | 22.59 | 24.20 | 22.90 | 21.27 | 22.75 | 22.23
2013-10-16 | 2013-10-16 00:16:00 CEST | 23.74 | 22.52 | 22.23 | 23.22 | 23.03 | 22.98
2013-10-17 | 2013-10-17 00:17:00 CEST | 21.68 | 24.54 | 21.15 | 23.58 | 23.04 | 21.94