As you may know, TLS 1.0 is being deprecated due to various known exploits and will no longer be PCI compliant as of June 30th, 2018 (see PCI DSS v3.1 and SSL: What you should do NOW below). You may also know that Microsoft has provided TLS 1.1/1.2 patches for the SQL Server Database Engine (2008+) as well as the client connectivity components (see TLS 1.2 support for Microsoft SQL Server below). What you may NOT know is that there is a popular feature in Excel to import data from SQL Server. See the screen print below from Excel 2016.
The problem with this feature lies in the fact that this menu option will, by default, leverage SQLOLEDB.1 as the OLE DB provider when connecting to SQL Server. This provider is an older MDAC/WDAC provider (see Data Access Technologies Road Map below) that comes built into the Operating System (including Windows 10) but DOES NOT support TLS 1.1+. So, if you have SQL Servers that have TLS 1.0 Server disabled, you will no longer be able to use this feature. You will receive an error similar to the one below. You will also receive the same or similar error if you have existing workbooks that use this feature and attempt to refresh those workbooks.
Chris has a workaround for current versions of Excel and notes that future versions will hide this particular import option behind a legacy wizards menu.
I was playing around with a nonclustered columnstore index on a disk-based table. Here’s what I was doing:
Session 1: this session repeatedly changed the value for a single row, back and forth. This puts it into the delta store.
Session 2: this session repeatedly counted the number of rows in the table, using the columnstore index.
With my sample data in this scenario, I found I frequently generated deadlocks.
Read on for more.
So there I was building this massive VARCHAR(MAX) string and concatenated at various points in my code were Database names of the datatype NVARCHAR(128).
The interesting part was that I was expecting SQL server to use my largest data type – the VARCHAR(MAX) and just concatenate the NVARCHAR(128) values into it
this was not the case – what actually happened was my string of VARCHAR(MAX) characters being truncated down to an NVARCHAR(4000)!
There is a reason for this and its all to do with Data Type Precedence in this case the NVARCHAR is preceding my VARCHAR unless of course I explicitly convert the NVARCHAR to a VARCHAR.
Read the whole thing.
Consider for a minute all the built-in capabilities that power the speed of SQL Server. From a SQLOS scheduling engine that minimizes OS context switches to read-ahead scanning to automatic scaling as you add NUMA and CPUs. And we parallelize everything! From queries to indexes to statistics to backups to recovery to background threads like LogWriter. We partition and parallelize our engine to scale from your laptop to the biggest servers in the world.
Like the enhancements we made as described in It Just Runs Faster, in SQL Server 2016, we are always looking to tune our engine for speed, all based on customer experiences. Take, for example, indirect checkpoint, which is designed to provide a more predictable recovery time for a database. We boosted scalability of this feature based on customer feedback. We also made scalability improvements for parallel scanning and consistency check performance. No knobs required. Just built-in for speed.
One of the coolest performance aspects to built-in speed is online operations. We know you need to perform other maintenance tasks than just run queries, but keep your application up and running, so we support online backups, consistency checks, and index rebuilds. SQL Server 2017 enhances this functionality with resumable online index builds allowing you to pause an index build and resume it at any time (even after a failure).
I saw the performance improvements in 2016 and am looking forward to the ones in 2017.
Ribbon Chart shows bigger value in each column at the top, then the next value comes after. Look at the sales amount value for female and male in 2005 and 2006. In 2005, Female (Black) had more sales than Male. However, in 2006, Male (Green) generated more revenue than the female, so it is on the top for the 2006 column.
The main benefit of the ribbon chart is in this re-ordering, so it’s easier to tell which categories are largest in a specific time period.