1. An Introduction to SQL Server 2017
Warwick Rudd
An Introduction to SQL Server 2017

2. Warwick Rudd @Warwick_Rudd Warwick@sqlmastersconsulting.com.au
Blogger on SimpleTalk
Speaker at TechEd Australia
Speaker at Ignite Australia
Speaker at Ignite New Zealand
Speaker at Difinity New Zealand
Speaker at SQL Saturday events
Speaker at Local User Groups
Host DBA Fundamentals VC
@Warwick_Rudd

3. Thanks to our Sponsors

4. SQL Server 2017 being released brings to the table some new features and improvements in quick succession from SQL Server In this session we will look at a subset of the new and/or improved features that SQL Server 2017 brings to the table.
From Analytics, Availability, Configuration and Performance there is something for everyone in this session to introduce you to the latest version of SQL Server.
Abstract
So my abstract for this session which hopefully you previously read which is why you are here in my session. Now I am not going to read this slide but just wanted to draw your attention to a couple of key points which we can see highlighted.

5. With introducing you to the new or improved features, this session will allow you to walk away with an understanding of what they mean and can do for you in your environment, allowing you to include SQL Server 2017 into your roadmap.
You will learn about:
New support for Data Analytics
Configuration changes
New DMVs
New support around Availability
New and enhanced Performance features
Goals

6. SQL Server 2017

7. Overview Analytics SQL Graph Availability New Cluster Type
Cross Platform Support
Cluster-less AGs
Configuration
TempDB
DMVs
Performance
Resumable Online Index Rebuilds
Identity Cache Options
Automatic Tuning
Querystore Wait Stats
Adaptive Query
Backup Speed improvements
Smart backups
DMVs

8. Data Analytics

9. Many-to-Many relationships
Node
Node
User 1
User 2
User 3
User 4
Song 1
Song 2
Song 3
Song 4
SQL Graph
Edge
Nodes (Entities) : Person or a Song
Edges (Relationships between Nodes)
SQL Graph is new as part of SQL server 2017, Graph database however has been around for quite sometime. So what is a SQL Graph? Well it is the ability to store and show many-to-many relationships to assist with data analysis. This can be achieved with relational databases, however the traversing of relationships is not that simple.
Easily and graphically show a visualisation that Select statements are not able to

10. Nodes Create Table dbo.Person (
ID Int Not Null identity(1,1) Primary Key,
Name Varchar(100) Not Null
) As Node;
Nodes
Graph_ID | 1 | BigInt | graph_ID_GUID
Graph_ID_Computed | 2 | nVarchar | $node_id_GUID
Graph_type_desc | Graph_type | Data Type | ColumneName

11. Edges Create Table dbo.FriendsWith ( YearsOfFriendship TinyInt Null
) As Edge;
Edges
Graph_ID | 1 | BigInt | graph_ID_GUID
Graph_ID_Computed | 2 | nVarchar | $node_id_GUID
Graph_From_Obj_id | 4 | Int | from_obj_id_GUID
Graph_From_id | 3 | BigInt | from_id_GUID
Graph_From_ID_Computed | 5 | nVarchar | $from_id_GUID
Graph_To_Obj_id | 7 | int | to_obj_id_GUID
Graph_To_Id | 6 | BigInt | to_id_GUID
Graph_To_Id_Computed | 8 | nVarchar | $to_id_GUID
Graph_type_desc | Graph_type | Data Type | ColumneName

12. Query Person FriendsWith Select p1.Name, Count(*) As ‘FriendsCount’
From dbo.Person P1, dbo.FriendsWith F1, dbo.Person P2
Where Match (p1-(friend)-> P2)
Group By P1.Name
Order By FriendsCount

13. Demo 1 Arvind Shyamsundar Twitter - @ArviSam Shreya Verma
This demo is attributed to Arvind Shyamsunday and Shreya Verma from Microsoft. This demo is available to undertake yourself and is in the references page at the end of this slide deck.
Arvind Shyamsundar
Twitter
Shreya Verma
Twitter

14. Availability

15. Availability Create Availability Group - Cluster Type WSFC External
None
AGs on Linux
Redhat
SUSE Linux Enterprise
Ubuntu
Availability
Cross Platform Support
Windows
Linux
Create Availability Group now comes with the option – Cluster_type. This indicates what the Availability Group is created on.
WSFC – Traditional WSFC
External – Value for a cluster that has been created on Linux using Pacemaker
None – For a Cluster-less or Read-Scale AG
There is no mechanism for a Cluster to have A windows node and a Linux node. But we can utilize a distributed AG to migrate data from a Windows based AG to a Linux based AG.

16. Cluster-less High Availability Synchronous Data Transfer Brisbane2
(Primary) AG
Brisbane2
(Secondary) AG
Synchronous Data
Transfer
Cluster-less
We saw on the previous slide the new cluster type option with the create availability group. This allows us to create a Cluster-Less Availability Group.
No Failover Cluster
No Availability Group Listener
Readable Secondary
Communication via Certificates
Read Scale-out
Direct connection to Secondary
Probably Enterprise Only
Manual Failover Only

17. Support 2 Synchronous Secondaries Max Secondaries - 1
Create Availability Group
Alter Availability Group
Full support for Distributed Transactions
With this new option configured either at creation or altering later, this changes the functionality of the Availability Groups compared to how we currently understand them.
The transactions on the primary will not commit and continue unless at the value configured Ie. 1 secondary is available to be committed to. If it is not then the transactions will not proceed.
We now get full support for DTC with Availability Groups.

18. Support Sys.dm_linux_proc_all_stat Sys.dm_linux_proc_meminfo
Sys.dm_linux_proc_sql_threads
Sys.dm_linux_proc_cpuinfo
Sys.dm_linux_proc_sql_maps
Sys.dm_linux_proc_all_stat – provides information about the processes running on your system
Sys.dm_linux_proc_meminfo – provides information about your systems memory
Sys.dm_linux_proc_sql_threads – provides information about threads on the environment
Sys.dm_linux_proc_cpuinfo – provides information about the processors on the system
Sys.dm_linux_proc_sql_maps – provides information about the mapped memory regions

19. Demo 2

20. Configuration

21. SQL Server Management Studio

22. SQL Server Reporting Services

23. Configurations TempDB Max Filesize 1 GB -> 256 GB DMVs
Sys.dm_tran_version_store_space_used
Sys.dm_os_sys_info
Sys.dm_tran_version_store_space_used tracks the version store space used in tempdb per database. Will assist with capacity planning of tempdb.
Sys.dm_os_sys_info has 3 new columns:
Socket_count
Core_per_socket
Numa_node_count

24. Performance

25. Resumable Online Index Rebuild
Resume after failure
Pause / Resume
Log Truncation
Performance Hit
MaxDOP
Max Duration
Support limitations
If you are configured in a HA environment (FCI/AG/DBMirroring) when a failure occurs that instigates a failover or we run out of disk space while the Index Rebuild is running the process will fail and stop, in 2017 we can now resume the Online Index Rebuild.
If you are running low on resources, and some important processing is needed, then we can manually pause and resume in a better window.
Because of the change in approach to undertaking the index rebuild, we can now run transaction log backups and control the space utilization during an index rebuild.
Some performance degredation may be experienced during paused state or during the rebuild process as both structures need to be maintained and updated.
Statement level maxdop option is available with the rebuild. However the maxdop value used in the initial execution of the rebuild statement is not able to be changed on the resume execution.
The max duration indicates the amount of time the online rebuild will execute for before it pauses.
This resumable index rebuild does not support:
Rebuilding a disabled index
Alter Index Rebuild All
Rebuilding an index that has a computed or timestamp columns as keys
Sort in TempDB

26. Pause / Resume Restart MaxDOP settings use first setting Pause
Execute the Online Index Rebuild Statement Again
Alter Index Resume
MaxDOP settings use first setting
Pause
Alter Index Pause
Kill
Sys.index_resumable_operations
0 – Running
1 - Paused
Pause / Resume
Alter Index [IndexName] On [TableName]
Rebuild With (Online=On, Resumable=On, Max_Duration=5);
Alter Index [IndexName] On [TableName] Pause;
Alter Index [IndexName] On [TableName] Resume;
Alter Index [IndexName] On [TableName] Abort;

27. Identity Cache Options
Identity Scoped Configuration that now allows the individual configuration.
Table in a Database that is configured for High Availability utilising the Identity type will experience gaps in the identity range after a failover event.
To assist with performance of Inserts, Identity values are cached by the server.
Enabling this feature on a Database by Database requirement will cause a performance impact on inserts but give you a continuous range of values.
“Alter Database Scoped Configuration Set Identity_Cache = Off”

28. Query Store Automatic Tuning Wait Stats
Sys.dm_db_tuning_recommendations
Off by Default
Force_Last_Good_Plan = On
Wait Stats
sys.query_store_wait_stats
Groupings of Waits
SQL Server 2016 introduced the query store to capture compile time and run time information takes that one step further by utilizing this captured information and provides insight into query performance.
The new dmv provides information around plan choice regressions. However unlike the Query store but like all DMVs the data in this DMV is not persistent.
Can enable this option by using the Alter Database command with the option Force_Last_Good_Plan
To further assist you with performance investigations, a new DMV – sys.query_store_wait_stats has been created that captures rolled up information around Waits occurring for statements. This is a grouping of the stats as an indicator, and not the collection and storing of all of the waits due to overhead on the system and the bloat this would cause.

29. Adaptive Query MSTVF – Multi-Statement Table Valued Function Reusable
Encapsulate code in 1 spot
Use Fixed Estimates
Bad plan choices
Poor Query Performance

30. Interleaved Execution
Adaptive Query
Interleaved Execution
Materialise estimates for MSTVFs
Iterative approach to execution tasks
More accurate resource utilisation
Batch-Mode
Memory Grant Feedback
Adaptive Joins
When the engine identifies the statement is utilizing a MSTVF, in 2017 it will look at this operator and retrieve the estimates for the data being retrieved from MSTVF. The actual number of rows are then used for the plan estimates downstream in the execution plan operators.
Batch-Mode Memory Grant Feedback adjusts the amount of memory grants required based on the execution feedback, and adjusts the amount for subsequent executions, which then use the new amount of memory grants. This is an ongoing process of adjustment to get the correct memory grant required. This will allow for the reduction in spills to tempdb thus leading to improved performance and improved concurrency of statements running because the memory resources available are able to be used more efficiently.
Batch-Mode Adaptive Joins defer the choice of using a Hash-Join or Nested Loop Join until after the first join input has been scanned.
Nested Loop Joins are used for small inputs of data
Hash Joins are used for large inputs of data

31. Backups Smart Backups Sys.dm_db_file_space
Diff Vs Full based on % Threshold
Sys.dm_db_log_stats
LSN Details
VLF Details
Transaction Log Size
Active VLF’s
Active Log Size
Backup details
Backup Performance
Sys.dm_db_file_space has been modified with a new column – modified_extent_page_count that is able to be used to track changes in each database file. This allows for smart backups to be created by looking at the % of change and comparing it to a threshold and determining whether to create a differential backup or a full backup.
A differential backup on a data file that is say 70-80% full will be close to the same amount of time potentially for a full backup to complete. But this can currently have an impact on your recovery time as you need to restore the additional backup to achieve recovery.
Sys.dm_db_log_stats now replaces DBCC Loginfo and provides us a very quick and simple way of looking into the state of play of the Transaction log file.
With the introduction of bigger servers, there is the potential for small to medium sized databases to havea slow down in backup time due to the backup process having to iterate through the buffer pool to drain the transactions. Work has been undertaken to change this to assist in improving the backup time.
The graph here shows testing that has been undertaken on a raft of databases of various sizes on a server with 2TB of memory.
8 MB – 642 * improvement (104 seconds - .4 second)
256 MB – 108 * improvement (108 seconds – 1 second)
1 GB – 27.5 * improvement (110 seconds – 4 seconds)
8 GB – 5.79 * improvement (139 seconds – 24 seconds)
16 GB – 2.85 * improvement (168 seconds – 59 seconds)
32 GB – 2.12 * improvement (216 seconds – 108 seconds
64 GB – 66% improvement (332 seconds – 200 seconds)
128 GB – 21.32% improvement (569 seconds – 469 seconds)
256 GB – 10.7 % improvement (1055 seconds – 953 seconds)

32. Demo 3

33. Summary Analytics SQL Graph Availability New Cluster Type
Cross Platform Support
Cluster-less AGs
Configuration
TempDB
DMVs
Performance
Resumable Online Index Rebuilds
Identity Cache Options
Automatic Tuning
Querystore Wait Stats
Adaptive Query
Backup Speed improvements
Smart backups
DMVs

34. References

35. Thank You
Questions ?