What I Learned About SQL Server at Ignite 2015

v.1, May 7, 2015

About this deck

• Author: Brent Ozar• Original source:

BrentOzar.com/go/ignite• License: public domain.

(You can do anything with this deck, even take out this slide and sell it,and you don’t have to credit Brent.)

SQL Server 2016 is coming.

• The first public preview will be this summer.• Will support Win2016, up to 12TB RAM

• We yet don’t know:– Final release dates– Pricing– Licensing/editions (what features will be in Std)

2016: ALWAYSON AG IMPROVEMENTS

AlwaysOn Availability Groups

• Like database mirroring, but:– Handles groups of databases, fails them over

together– Can have multiple readable secondaries– Can offload your backups to secondaries– Can be done with physical machines or VMs– Built atop Windows Server Failover Clustering

SQL Server 2016 Improvements

• Adds Distributed Transaction Coordinator (DTC) support

• Faster throughput• Load balancing for readable secondaries• Database-level health detection, failover• Available in Standard Edition, but:– Only one replica– Only one database per Availability Group

(you can set up multiple AGs per server though)– Secondaries aren’t readable, can’t do backups

2016: COLUMNSTORE INDEX IMPROVEMENTS

What are ColumnStore Indexes?

• Kinda like each column getting its own index.• In SQL Server 2012: – Nonclustered only– Made the table read-only when created

• In SQL Server 2014:– Clustered columnstore introduced, writeable– Massive compression (60-90%)– Nonclustered still read-only

2016 Columnstore Improvements

• Nonclustered CS indexes now updateable, can be filtered

• Clustered CS indexes can get regular b-tree indexes atop them– That improves concurrency with row-level locking

Both clustered and non-clustered:

• Better performance for:– Aggregates (MIN, MAX, SUM, COUNT, AVG)– String predicates (myfieldnamem LIKE ‘%foo’)

• Better concurrency (support of snapshot isolation and RCSI)

• Readable on AlwaysOn Availability Group secondary replicas

• Better index reorganize results (removes deleted rows, less memory pressure)

2016: SECURITY IMPROVEMENTS

Row-Level Security (RLS)

• In a data warehouse, you need to filter data so not everybody sees all of it– Store managers: see just their stores– Regional managers: see just their sales– Accounting: sees all the stores

• In the past, we had to roll our own using views• SQL 2016 builds this into the product

Dynamic Data Masking

• Sometimes, developers or report users need to query production.

• We just don’t want them to see private data like social security number, credit card, etc.

• The old way: restore the database to another server, then scramble the data with SSIS or T-SQL.– Slow, painful: did a lot of disk writes.

Dynamic Data Masking

• Available in both SQL Server 2016 and Azure SQL Database

• You define privileged logins,everybody else sees the masked data

• You pick the tables and columns to be masked• You pick the mask (like fake dates or email addresses

or XXX)• This only applies to data being returned to the app.

You can still query for the right data, like SELECT * FROM Users WHERE SSN = ‘123456789’

Always Encrypted

• When you store personally identifiable information (PII) like social security number or credit card, you want it encrypted.

• If you use Transparent Data Encryption, it’s encrypted at rest, but the DBA and reporting users can still see it unencrypted.

• In the past, we had to roll our own encryption in the app layer, and it was hard work.

Always Encrypted, continued

• SQL Server 2016 enables it by doing the encryption in the client layer – ADO.NET.– The company’s security officer creates keys– Keys are stored securely (like in an HSM, a

certificate store, Azure Key Vault, etc)– Application connects to the store for the keys– Database server never actually gets the keys

• Ideally, minimal app code changes required.

WATCH BRENT TUNE SERVERS(SQL SERVER 2012/2014)

Watch Brent Tune Servers

• Brent Ozar showed several workloads, and how they could be sped up by config tweaks

• Use sp_AskBrent® to check:– Batch Requests per Second – SQL’s speedometer– Wait Time per Second – the tachometer, how hard

SQL is working and what it’s waiting on

Brent’s Fixes for Common Waits

• PAGEIOLATCH – in data warehouse style tables, columnstore indexes help (and get better in 2016)

• LCK* - with Read Committed Snapshot Isolation, readers don’t block writers, writers don’t block readers

• SOS_SCHEDULER_YIELD – get better execution plans with SQL 2014 compat level, or trace flag 4199 in 2012

• WRITELOG – SQL 2014’s Delayed Durability

NEXT YEAR’S IGNITE:CHICAGO, MAY 9-16, 2016