1. UFC #1433 In-Memory tables 2014 vs 2016
Alejandro Cordero
Lead Database Consultant – Pythian
LinkedIn:
BLOG: Sqlturbo.com
MCTS, MCSA, CSM

2. Speaker Bio - Alejandro Cordero
SQLTURBO.COM
Lead database consultant at Pythian
Scrum Master Certified
MCSA

3. Agenda Understanding In-Memory Tables Features in SQL2014
Limitations in SQL2014
Demo of SQL2014 In-Memory Tables
Features 2016
Limitations in SQL2016
Demo of SQL2016 In-Memory tables
Conclusions

4. In Memory Tables Tables that will reside in –Memory
With 30x Performance boost
Both Table and Index structures in memory
No index and no Data Pages, single rows in memory instead
All rows addressed by pointers
Latch and Lock Free
Consistency trough row versioning and conflict detection
write-ahead logging (WAL)

5. Access trough natively compiled stored procedures
Queries available to SQL Server trough dll binaries
Query optimization at creation time, fixed execution plan
For OLTP style Operations
Optimization of performance critical business logic
Cons> Limited Built-in Functions, join trough in memory tables only

6. Access trough Ad-hoc Queries
Regular TSQL
Mainly for reporting style operations
Or when options needed are not available in Natively Compiled Sprocs
Cons> less performance improvement than Natively Compiled Sprocs

7. SQL 2014 In-Memory Indexes No fragmentation Don’t Contain Data
No Included Columns
All Indexes are Covering ( the full row is returned) – No Lookups
NonClustered
Range Lookups
Order Scans
Seeks
Hash (bucket count)
Point lookups

8. SQL 2014 In-Memory Indexes ..cont
CREATE TABLE t1_1
(c1 INT NOT NULL,
INDEX IDX HASH (c1) WITH (BUCKET_COUNT = 100))
WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_ONLY)
CREATE TABLE t3_3
INDEX IDX NONCLUSTERED (c1))

9. Operations per Index Type

10. SQL 2014 Limitations No triggers
Data Types Limitations > no LOBS, no XML, no CLR, no Spatial data types
Constraints > No Foreign Keys, no check contraints
No Schema Changes > need to drop and create
No add/remove index > need to drop and create
Natively Compiled Sprocs > no distinct, no case, just basic built-in math/string/date functions

11. SQL 2014 In-Memory in Action

12. SQL Server 2016 – In-Memory Storage and memory Algorithms improved
Concurrency handling improved
Garbage collection Improved
Available Operators Improved
Modifications of structures

13. Size, Collation, Alter statements, TDE, Parallel Plans
From 256Gb to 2TB
Collation from BIN2 to ANY collation ( with performance trade)
Structure modification available to drop, add column, alter, rebuild indexes
TDE available for data on disk
Parallel Plans for certain hash index operations

14. Natively Compiled Stored Procedures
LEFT and RIGHT OUTER JOIN
SELECT DISTINCT
OR and NOT operators
Subqueries in all clauses of a select statement
Nested stored procedure calls
UNION and UNION ALL
ALL built-in math functions

15. Dependency File stream Processing
File stream used to commit changes into physical files
Dependency is now removed and In Memory tables will use an NTFS API directly

16. Log Reader Threads
In SQL 2014 there was just one log reader thread per database to read transactions affecting memory optimized tables from the transaction log
In SQL 2016 multiple log readers are now available scalable by the number of cores

17. Always On and Garbage Collector
Data from Memory Optimized tables had a delay to be available in a Always On replica.
Data will now be available almost immediately.
When deleting a huge number of row versions due to lots of changes or deleting a big memory optimized table, space wasn’t released immediately, with the new garbage collector space is made available almost immediately.

18. SQL 2016 In-Memory in Action

19. Conclusions In-memory Performance Improvements
Less limitations in SQL2016
Great algorithms based on optimistic concurrency
Improved Natively Compiled Stored Procedures

20. Thanks! Correo electrónico: alejandro@sqlturbo.com
LinkedIn:
BLOG: Sqlturbo.com
MCTS, MCSA, CSM