# Day: September 6, 2018

Now we can see not only when Arsenal picked up points, but when they dropped points as well. For example, on the 27th of August, they got beat by 4 goals as their goal difference shifted from 0 to -4.

We’re not done there! For the gif, we want to be able to display the current status of the team on each day i.e. Champions League (4th or above), Europa League (5th – 7th), Top Half (8th – 10th), Bottom Half (11th – 17th) or Relgations Zone (18th or below). To do this, on each day, we first need to retrieve the order of each team based on their points and goal difference

Click through to see the example.

In languages based on the Latin alphabet, we read horizontally, from left to right. Reading on a diagonal produces cramped necks. Reading vertical text is just not going to happen. So, as much as possible, the text in our graphs should be horizontal.

Let’s walk through a demo. I was trying to combat my sense of hopelessness about the world by exploring the latest dataviz related to the Sustainable Development Goals (don’t we all?). The vast majority of their viz is pretty awesome, especially given how complicated the data can be. I saw this graph about how few developing countries have representation on international development councils.

Watch as Stephanie starts with a column chart with diagonal (and cut-off) text and converts it to a visual which is much easier to read.

So what causes Range Locks? Just ask Sunil. He knows everything (this assumes the serializable isolation level):

Equality Predicate

If the key value exists, then the range lock is only taken if the index is non-unique. In the non-unique index case, the ‘range’ lock is taken on the requested key and on the ‘next’ key.

If the ‘next’ key does not exist, then a range lock is taken on the ‘infinity’ value. If the index is unique then a regular S lock on the key.

If the key does not exist, then the ‘range’ lock is taken on the ‘next’ key both for unique and non-unique index.

If the ‘next’ key does not exist, then a range lock is taken on the ‘infinity’ value.

Range Predicate (key between the two values)

‘range lock on all the key values in the range when using ‘between’

‘range’ lock on the ‘next’ key that is outside the range. This is true both for unique and non-unique indexes. This is to ensure that no row can be inserted between the requested key and the one after that. If the ‘next’ key does not exist, then a range lock is taken on the ‘infinity’ value.

Erik has an interesting example and lets us see a potential concurrency problem with multi-table indexed views.

So, a question that should be asked is: How secure are your client connections? Here are a couple common misconceptions about SQL server client connections.

Misconception: Usernames & passwords (SQL or Windows) are used to connect to SQL server databases, which means the client-server connection is secure.

Explanation
Usernames & passwords are used to control who has what level of permission (read/write/modify) to the data & database. By default, the information being transmitted is not encrypted. As John Martin shows in this article, it is relatively easy for someone with access to a network (wireless access point or LAN connection) to read the unencrypted data that is being sent between a SQL server and client.

Definitely read the whole thing.  We’re at a point where the overhead cost of encrypting connections is low enough that there’s not much reason to leave production servers transmitting openly over the wire.

1. When a user performs an AD connection, internally the user connects to a service principal name (SPN). The SPNs are in the form “MSSQLSvc/host.contoso.com:1433”, and they must be registered when setting up AD logins for SQL Server on Linux. When a client app requests a connection (e.g. sqlcmd), it takes the server users wish to connect to, prepends “MSSQLSvc/” and appends “:**<port>**”, and this is the SPN which the connection attempts to authenticate with.

So, if user connects with “sqlcmd -E -S host.contoso.com”, it authenticates with the SPN “MSSQLSvc/host.contoso.com:1433”, and everything succeeds. If user connects with “sqlcmd -E -S host”, it authenticates with “MSSQLSvc/host:1433”. If the SPN the client is authenticating with does not exist, the connection will fail. So, if the SPNs in the mssql.keytab are only “MSSQLSvc/host.contoso.com:1433”, users can only connect to “host.contoso.com”, not “host” and not to the IP. If user needs to be able to connect with variations of host name and IP address, then all appropriate SPNs should be created and configured in the mssql.keytab file.

Read on for more common issues and their solutions.

The time zone name is taken from a list maintained in the following Windows registry hive: `HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Time Zones`

Note: For SQL Server on Linux (and Docker containers), a registry shim performs the same function as the Windows registry by intercepting the API calls and returning the expected value(s).

We can also use a Transact-SQL (T-SQL) query against the system view `sys.time_zone_info`, which uses the information from the registry hive. This is the recommended method if you do not have access to the registry hive.

Click through for a couple of examples.

I wanted a way to automate the integration testing of my repositories and stored procedures so I developed the solution described below using NUnit as the test framework and SQL Server LocalDB as the database to run my tests against.

I had the following requirements for my solution which NUnit has been able to satisfy:

• Quick – tests should run quickly and not require massive amounts of set up / tear down

• Independent – all tests should be independent from one another and responsible for their own set up / tear down

• Simple – the test code should be simple to understand and easy to work with when writing new tests.

• Work Everywhere – the tests should be able to work anywhere and not require huge dependencies like a full SQL Server instance, they should be able to work with SQL LocalDB