亚洲国产日韩欧美一区二区三区,精品亚洲国产成人av在线,国产99视频精品免视看7,99国产精品久久久久久久成人热,欧美日韩亚洲国产综合乱

Home Database Mysql Tutorial How Can I Calculate Working Hours Between Dates in PostgreSQL, Considering Weekends and Specific Working Hours?

How Can I Calculate Working Hours Between Dates in PostgreSQL, Considering Weekends and Specific Working Hours?

Jan 03, 2025 am 10:35 AM

How Can I Calculate Working Hours Between Dates in PostgreSQL, Considering Weekends and Specific Working Hours?

Calculating Working Hours Between Dates in PostgreSQL

Introduction

In various scenarios, determining the number of working hours between two timestamps can prove to be essential in fields such as payroll and scheduling. In PostgreSQL, this calculation requires careful consideration of weekday and time-specific parameters. This article outlines a comprehensive solution, taking into account the following criteria:

  • Weekends (Saturdays and Sundays) are excluded from working hours.
  • Working hours are defined as Monday through Friday, 8 am to 3 pm.
  • Fractional hours are to be included in the calculation.

Solution

Method 1: Rounded Results for Just Two Timestamps

This approach operates on units of 1 hour, ignoring fractional hours. It is a simple but less precise method.

Query:

SELECT count(*) AS work_hours
FROM   generate_series (timestamp '2013-06-24 13:30'
                      , timestamp '2013-06-24 15:29' - interval '1h'
                      , interval '1h') h
WHERE  EXTRACT(ISODOW FROM h) < 6
AND    h::time >= '08:00'
AND    h::time &amp;lt;= '14:00';

Example Input:

2013-06-24 13:30, 2013-06-24 15:29

Output:

2

Method 2: Rounded Results for a Table of Timestamps

This approach extends the previous method to handle a table of timestamp pairs.

Query:

SELECT t_id, count(*) AS work_hours
FROM  (
   SELECT t_id, generate_series (t_start, t_end - interval '1h', interval '1h') AS h
   FROM   t
   ) sub
WHERE  EXTRACT(ISODOW FROM h) < 6
AND    h::time >= '08:00'
AND    h::time <= '14:00'
GROUP  BY 1
ORDER  BY 1;

Method 3: More Precise Calculation

For a finer-grained calculation, smaller time units can be considered.

Query:

SELECT t_id, count(*) * interval '5 min' AS work_interval
FROM  (
   SELECT t_id, generate_series (t_start, t_end - interval '5 min', interval '5 min') AS h
   FROM   t
   ) sub
WHERE  EXTRACT(ISODOW FROM h) < 6
AND    h::time >= '08:00'
AND    h::time <= '14:55'
GROUP  BY 1
ORDER  BY 1;

Example Input:

| t_id | t_start                | t_end                  |
|------|-------------------------|-------------------------|
| 1    | 2009-12-03 14:00:00    | 2009-12-04 09:00:00    |
| 2    | 2009-12-03 15:00:00    | 2009-12-07 08:00:00    |
| 3    | 2013-06-24 07:00:00    | 2013-06-24 12:00:00    |
| 4    | 2013-06-24 12:00:00    | 2013-06-24 23:00:00    |
| 5    | 2013-06-23 13:00:00    | 2013-06-25 11:00:00    |
| 6    | 2013-06-23 14:01:00    | 2013-06-24 08:59:00    |

Output:

| t_id | work_interval |
|------|----------------|
| 1    | 1 hour         |
| 2    | 8 hours        |
| 3    | 0 hours        |
| 4    | 0 hours        |
| 5    | 6 hours        |
| 6    | 1 hour         |

Method 4: Exact Results

This approach provides exact results with microsecond precision. It is more complex but more computationally efficient.

Query:

WITH var AS (SELECT '08:00'::time  AS v_start
                  , '15:00'::time  AS v_end)
SELECT t_id
     , COALESCE(h.h, '0')  -- add / subtract fractions
       - CASE WHEN EXTRACT(ISODOW FROM t_start) < 6
               AND t_start::time > v_start
               AND t_start::time < v_end
         THEN t_start - date_trunc('hour', t_start)
         ELSE '0'::interval END
       + CASE WHEN EXTRACT(ISODOW FROM t_end) < 6
               AND t_end::time > v_start
               AND t_end::time < v_end
         THEN t_end - date_trunc('hour', t_end)
         ELSE '0'::interval END                 AS work_interval
FROM   t CROSS JOIN var
LEFT   JOIN (  -- count full hours, similar to above solutions
   SELECT t_id, count(*)::int * interval '1h' AS h
   FROM  (
      SELECT t_id, v_start, v_end
           , generate_series (date_trunc('hour', t_start)
                            , date_trunc('hour', t_end) - interval '1h'
                            , interval '1h') AS h
      FROM   t, var
      ) sub
   WHERE  EXTRACT(ISODOW FROM h) < 6
   AND    h::time >= v_start
   AND    h::time <= v_end - interval '1h'
   GROUP  BY 1
   ) h USING (t_id)
ORDER  BY 1;

This comprehensive solution addresses the need to calculate working hours accurately and efficiently in PostgreSQL.

The above is the detailed content of How Can I Calculate Working Hours Between Dates in PostgreSQL, Considering Weekends and Specific Working Hours?. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undress AI Tool

Undress AI Tool

Undress images for free

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

PHP Tutorial
1488
72
Establishing secure remote connections to a MySQL server Establishing secure remote connections to a MySQL server Jul 04, 2025 am 01:44 AM

TosecurelyconnecttoaremoteMySQLserver,useSSHtunneling,configureMySQLforremoteaccess,setfirewallrules,andconsiderSSLencryption.First,establishanSSHtunnelwithssh-L3307:localhost:3306user@remote-server-Nandconnectviamysql-h127.0.0.1-P3307.Second,editMyS

Analyzing the MySQL Slow Query Log to Find Performance Bottlenecks Analyzing the MySQL Slow Query Log to Find Performance Bottlenecks Jul 04, 2025 am 02:46 AM

Turn on MySQL slow query logs and analyze locationable performance issues. 1. Edit the configuration file or dynamically set slow_query_log and long_query_time; 2. The log contains key fields such as Query_time, Lock_time, Rows_examined to assist in judging efficiency bottlenecks; 3. Use mysqldumpslow or pt-query-digest tools to efficiently analyze logs; 4. Optimization suggestions include adding indexes, avoiding SELECT*, splitting complex queries, etc. For example, adding an index to user_id can significantly reduce the number of scanned rows and improve query efficiency.

Handling NULL Values in MySQL Columns and Queries Handling NULL Values in MySQL Columns and Queries Jul 05, 2025 am 02:46 AM

When handling NULL values ??in MySQL, please note: 1. When designing the table, the key fields are set to NOTNULL, and optional fields are allowed NULL; 2. ISNULL or ISNOTNULL must be used with = or !=; 3. IFNULL or COALESCE functions can be used to replace the display default values; 4. Be cautious when using NULL values ??directly when inserting or updating, and pay attention to the data source and ORM framework processing methods. NULL represents an unknown value and does not equal any value, including itself. Therefore, be careful when querying, counting, and connecting tables to avoid missing data or logical errors. Rational use of functions and constraints can effectively reduce interference caused by NULL.

Performing logical backups using mysqldump in MySQL Performing logical backups using mysqldump in MySQL Jul 06, 2025 am 02:55 AM

mysqldump is a common tool for performing logical backups of MySQL databases. It generates SQL files containing CREATE and INSERT statements to rebuild the database. 1. It does not back up the original file, but converts the database structure and content into portable SQL commands; 2. It is suitable for small databases or selective recovery, and is not suitable for fast recovery of TB-level data; 3. Common options include --single-transaction, --databases, --all-databases, --routines, etc.; 4. Use mysql command to import during recovery, and can turn off foreign key checks to improve speed; 5. It is recommended to test backup regularly, use compression, and automatic adjustment.

Calculating Database and Table Sizes in MySQL Calculating Database and Table Sizes in MySQL Jul 06, 2025 am 02:41 AM

To view the size of the MySQL database and table, you can query the information_schema directly or use the command line tool. 1. Check the entire database size: Execute the SQL statement SELECTtable_schemaAS'Database',SUM(data_length index_length)/1024/1024AS'Size(MB)'FROMinformation_schema.tablesGROUPBYtable_schema; you can get the total size of all databases, or add WHERE conditions to limit the specific database; 2. Check the single table size: use SELECTta

Handling character sets and collations issues in MySQL Handling character sets and collations issues in MySQL Jul 08, 2025 am 02:51 AM

Character set and sorting rules issues are common when cross-platform migration or multi-person development, resulting in garbled code or inconsistent query. There are three core solutions: First, check and unify the character set of database, table, and fields to utf8mb4, view through SHOWCREATEDATABASE/TABLE, and modify it with ALTER statement; second, specify the utf8mb4 character set when the client connects, and set it in connection parameters or execute SETNAMES; third, select the sorting rules reasonably, and recommend using utf8mb4_unicode_ci to ensure the accuracy of comparison and sorting, and specify or modify it through ALTER when building the library and table.

Aggregating data with GROUP BY and HAVING clauses in MySQL Aggregating data with GROUP BY and HAVING clauses in MySQL Jul 05, 2025 am 02:42 AM

GROUPBY is used to group data by field and perform aggregation operations, and HAVING is used to filter the results after grouping. For example, using GROUPBYcustomer_id can calculate the total consumption amount of each customer; using HAVING can filter out customers with a total consumption of more than 1,000. The non-aggregated fields after SELECT must appear in GROUPBY, and HAVING can be conditionally filtered using an alias or original expressions. Common techniques include counting the number of each group, grouping multiple fields, and filtering with multiple conditions.

Implementing Transactions and Understanding ACID Properties in MySQL Implementing Transactions and Understanding ACID Properties in MySQL Jul 08, 2025 am 02:50 AM

MySQL supports transaction processing, and uses the InnoDB storage engine to ensure data consistency and integrity. 1. Transactions are a set of SQL operations, either all succeed or all fail to roll back; 2. ACID attributes include atomicity, consistency, isolation and persistence; 3. The statements that manually control transactions are STARTTRANSACTION, COMMIT and ROLLBACK; 4. The four isolation levels include read not committed, read submitted, repeatable read and serialization; 5. Use transactions correctly to avoid long-term operation, turn off automatic commits, and reasonably handle locks and exceptions. Through these mechanisms, MySQL can achieve high reliability and concurrent control.

See all articles