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| | | The Last Service Pack I might be presumptuous with this title, but I really think that SQL Server 2016 Service Pack 2 could be the last service pack. There's a new servicing model with SQL Server 2017, and it's working well. We see Cumulative Updates (CU) released every month, with a regular set of fixes. This new model, along with the comfort that more organizations are getting with CUs might mean that there won't be a SP3 for SQL Server 2016, or maybe not for 2014. We may not get final rollups in SPs for these platforms, especially as there could be security patches needed after any final SP. In that case, perhaps a series of CUs is the way to go. We will see if I am correct over the next few years, but for now we have SQL Server 2016 Service Pack 2, released yesterday earlier this week. If you read the announcement, there are items ported forward from SQL Server 2014, which is good. I don't think I've seen this before, but I'm glad that features and functionality is being synced across branches and versions where it makes sense. It would be easy for Microsoft to ignore this and just move changes to 2017 only. There are some improvements to monitoring and metrics as well. New DMVs, new columns in existing DMVs, new options, new ways to query information, and more. Plenty of fixes, some of which are detailed in KBs and some of which are VSTS issues that tracked internally by Microsoft. Many of these are minor fixes or changes, but they will improve the way that we work with the product. We even get the sys.dm_db_log_info DMV backported from SQL Server 2017. While I slightly bemoan the lack of service packs in the future, I am embracing the CU path for the future. However, I also applaud Microsoft for releasing some fantastic Service Packs for SQL Server 2016. SP1 gave us lots of feature parity across editions. SP2 adds lots of small DMVs and improvements that will help ensure that we can better manage our database servers. I called SQL Server 2016 one of the best ever versions, and this service pack cements how I feel. If you're looking to upgrade, you ought to be moving to SQL Server 2017, but if you're on 2016, you might stay here for quite some time. Just be sure you apply this Service Pack and take advantage of the features from both SP1 and SP2. No one should be on RTM at this point, and no vendor ought to be limiting these patches. Steve Jones from SQLServerCentral.comJoin the debate, and respond to today's editorial on the forums |
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| | | | | Additional Articles from Brent Ozar Unlimited Blog Erik Darling shows how missing index requests have different impact numbers depending on the query's join type. More » |
| | Tim Wellman from SQLServerCentral.com A basic introduction for developers about working with the DataSet object in ADO.Net to represent objects in a SQL Server database, and some of the options available. More » |
| | If you’re using SQL Server’s Read Committed Snapshot Isolation level (RCSI) to avoid long waits for a blocked resource, then you’ll want to monitor for possible side effects. This article describes one way to monitor for such problems, using an alert on version_ghost_record_count, to warn us when the number of row versions in tempdb is getting very high. More » |
| | Grant Fritchey from SQLServerCentral Blogs I use Extended Events almost exclusively for capturing query metrics. They are the most consistent and lowest cost mechanism for... More » |
| | Matthew McGiffen from SQLServerCentral Blogs If you’re starting to use cloud services, the number of options available can be confusing. Particularly when they may seem... More » |
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| | | Today's Question (by Steve Jones): When you install SQL Server 2017 Machine Learning Services with R and Python, how many new users are added to SQL Server by default? |
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| | Yesterday's Question of the Day |
| Yesterday's Question (by Steve Jones): I have this code in Python: >>> i = [1,2,3] >>> j = i If I now do this, what is returned? >>> i[1] = 4 >>> print(j)
Answer: [1,4,3] Explanation: A list in Python is mutable. The variables, i and j, refer to a memory location that stores the list. In this case, both refer to the location that contains [1,2,3] after the second line. The third line (i[1]) assigns a new value to the second element in the list. Python lists are 0 based, so the 2 is changed to a 4. Since both i and j point to this location, when j is printed, [1, 4, 3] is returned. Ref: Facts and myths about Python Names and values - click here Python Lists - click here » Discuss this question and answer on the forums |
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| | | | Sean Smith from SQLServerCentral.com Over the years I have had some of the strangest / most complex requirements for data querying / reporting that you could imagine. The most difficult often involves some type of strange business rule or requirement surrounding a date parameter, logic, range, etc. I've put this code together in order to pre-calculate many elements of a date's attributes and be able to quickly determine various date characteristics / values without the need to break my head every time things get hairy. To run it, simply choose the database in which you want the table to reside, assign the @Date_Start and @Date_End variables with the date range you want populated in the calendar, and execute. Below is a listing of the output fields and their description using a date of 10/06/2009 (MM/DD/YYYY) as the reference example (the code should compensate for how any SQL Server instance is set up to handle the internal settings for start / end of week, weekdays, etc.). All values after the calendar_date field are specific to the date value found in each individual record. calendar_date: calendar date value (2009-10-06 00:00:00.000) calendar_year: year portion of the date (2009) calendar_month: month portion of the date (10) calendar_day: day portion of the date (6) calendar_quarter: quarter in which the date value falls under (4) first_day_in_week: first day of the week in which the date value is found (2009-10-04 00:00:00.000) last_day_in_week: last day of the week in which the date value is found (2009-10-10 00:00:00.000) is_week_in_same_month: is the first_day_in_week and last_day_in_week value contained within the same month (1) first_day_in_month: first day of the month (2009-10-01 00:00:00.000) last_day_in_month: last day of the month (2009-10-31 00:00:00.000) is_last_day_in_month: is the date value the last day of the month (0) first_day_in_quarter: first day of the quarter (2009-10-01 00:00:00.000) last_day_in_quarter: last day of the quarter (2009-12-31 00:00:00.000) is_last_day_in_quarter: is the date value the last day of the quarter (0) day_of_week: day of the week (3) week_of_month: week of the month (2) week_of_quarter: week of the quarter (2) week_of_year: week of the year (41) days_in_month: total days in the month (31) month_days_remaining: number of days remaining in the month (25) weekdays_in_month: number of weekdays in the the month (22) month_weekdays_remaining: number of weekdays remaining in the month (18) month_weekdays_completed: number of weekdays completed in the month (4) days_in_quarter: total days in the quarter (92) quarter_days_remaining: number of days remaining in the quarter (86) quarter_days_completed: number of days completed in the quarter (6) weekdays_in_quarter: number of weekdays in the the quarter (66) quarter_weekdays_remaining: number of weekdays remaining in the quarter (62) quarter_days_completed: number of days completed in the quarter (6) day_of_year: number of days completed in the year (279) year_days_remaining: number of days remaining in the year (86) is_weekday: is the date a weekday (1) is_leap_year: is the date contained within a leap year (0) day_name: full name of the day (Tuesday) month_day_name_instance: number of occurrences of the day_name within the month up until and including the specified date (1) quarter_day_name_instance: number of occurrences of the day_name within the quarter up until and including the specified date (1) year_day_name_instance: number of occurrences of the day_name within the year up until and including the specified date (40) month_name: full name of the month (October) year_week: calendar_year and week_of_year (left padded with zeros) values concatenated (200941) year_month: calendar_year and calendar_month (left padded with zeros) values concatenated (200910) year_quarter: calendar_year and calendar_quarter (prefixed with a "Q") values concatenated (2009Q4) Any friendly feedback is always welcome. Enjoy! More » |
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