gaps-and-islands

I have the following data ordered by player_id and match_date. I would like to find out the group of records that has the maximum number of consecutive runs (4 runs from 2014-04-03 till 2014-04-12 for 3 consecutive times) player_id match_date runs 1 2014-04-01 5 1 2014-04-02 55 1 2014-04-03 4 1 2014-04-10 4 1 2014-04-12 4 1 2014-04-14 3 1 2014-04-19 4 1 2014-04-20 44 2 2014-04-01 23 2 2014-04-02 23 2 2014-04-03 23 2 2014-04-10 23 2 2014-04-12 4 2 2014-04-14 3 2 2014-04-19 23 2 2014-04-20 1 I have come up with the following SQL: select *,row_number() over (partition by ranked.player_id,ranked

Ok, I have a database table of rows with a StartDate and an EndDate. What I need to do is return blocks of consumed time from that. So, for example, if I have 3 rows as follows: RowID StartDate EndDate 1 2011-01-01 2011-02-01 2 2011-01-30 2011-02-20 3 2011-03-01 2011-04-01 then the blocks of used time would be as follows: 2011-01-01 to 2011-02-20 and 2011-03-01 to 2011-04-01 Is there an easy method of extracting that from a MySql database? Any suggestions welcome! Look at the diagram below which represents some overlapping time periods X----| |--------| |------X |-------X X------------X |----|

I need to number islands in SQL Server 2012. Island is defined as a set of rows where there is no day gaps between DateFrom and DateTo within the same ItemId ). The following dataset: CREATE TABLE #Ranges (ItemId INT, DateFrom DATETIME, DateTo DATETIME) INSERT INTO #Ranges VALUES (1,'2015-01-31','2015-02-17') INSERT INTO #Ranges VALUES (1,'2015-02-18','2015-03-31') INSERT INTO #Ranges VALUES (1,'2015-04-14','2015-05-21') INSERT INTO #Ranges VALUES (2,'2015-07-12','2015-07-19') INSERT INTO #Ranges VALUES (2,'2015-07-20','2015-07-24') INSERT INTO #Ranges VALUES (2,'2015-07-26','2015-08-02')

Given a simple table with the following data: id | result | played ----+--------+------------ 7 | L | 2012-01-07 6 | L | 2012-01-06 5 | L | 2012-01-05 4 | W | 2012-01-04 3 | W | 2012-01-03 2 | L | 2012-01-02 1 | W | 2012-01-01 How would I write a query to return the lastest losing or winning streak of rows using PostgreSQL? In this case, I'm looking for a result of: id | result | played ----+--------+------------ 7 | L | 2012-01-07 6 | L | 2012-01-06 5 | L | 2012-01-05 I'm guessing the answer is to use lag() and partition syntax, but I can't seem to nail it down. Assuming (as you don't tell)

You have a table table1 that contains id column, that is int(11), not null, auto_increment and starts from 1. Suppose, you have 10,000 records. It is clear the id of the last record is 10,000. Once you removed 3 records, you have 9,997 records in the table, but the last record id value is still 10,000 (if the last record was not deleted). How to display what records have been removed using 1 sql query? Thank you. I think easiest would be to have a dummy/temp table with just ids. 1-1000 then left join to that table. But be sure to remove the "deleted" records from your dummy/temp table once you

Im trying to write a function which identifies groups of dates, and measures the size of the group. I've been doing this procedurally in Python until now but I'd like to move it into SQL. for example, the list Bill 01/01/2011 Bill 02/01/2011 Bill 03/01/2011 Bill 05/01/2011 Bill 07/01/2011 should be output into a new table as: Bill 01/01/2011 3 Bill 02/01/2011 3 Bill 03/01/2011 3 Bill 05/01/2011 1 Bill 07/01/2011 1 Ideally this should also be able to account for weekends and public holidays - the dates in my table will aways be Mon-Fri (I think I can solve this by making a new table of working