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SQL SERVER ENTERPRISE AWARENESS

Copyrights © 2016 Fard Solutions Sdn Bhd, All rights reserved.

About MeHamid J. Fard

I am SQL Server Data Platform Expert with more than 9 years’ of professionalexperience, I am currently Microsoft Certified Master: SQL Server 2008,Microsoft Certified Solutions Master: Charter-Data Platform, Microsoft DataPlatform MVP and CIW Database Design Specialist. After a few years of being aproduction database administrator I jumped into the role of Data PlatformExpert. Being a consultant allows me to work directly with customers to helpsolve questions regarding database issues for SQL Server.

Agenda• What Matters To You?

• Do You Believe in High End Hardware?

• SQL Server Enterprise Edition (Internal Features)

• SQL Server 2016 Enterprise Edition New Features

• Questions and Answers


What Matters To You?

Manageability Performance Storage Space Disaster Recovery Cost


Do You Believe in High End Hardware?

YES

NO

Without High End Software, Your High End Hardware Is Worthless.


SQL Server Internal Features vs. EditionsFeature Enterprise Standard

Advance Scan (Merry-Go-Round)

Fast Recovery

Prefetching

Single Scatter Scan

Automation Matching

Role Reversal

Partitioning

Data Compression

Deferred Transaction

Resource Governor

Vardecimal Storage Formatting


Advance Scan (Marry-Go-Round)


Table A

User A

User B

SQL Server Optimizer Engine

Query Buffer

Query Buffer

Query BufferRead

Fast Recovery

Analysis Phase Redo Phase Undo Phase

Database Recovery Lifecycle

Database is AvailableBy Lock-Logging

Database is Under Recovery Uncommitted Transactionsare Roll-Backed


PrefetchingSelect E.ID, E.FN, E.LN, D.Designation From Employee E Inner Join Designation D On E.Designation_ID = D.ID

Designation

Employee

Read Synchronously

Read Asynchronously

Project Resultset


Single Scatter Scan


465

308

488

489

Lis

t o

f L

eaf

Pag

es

Automation MatchingCreate Table dbo.Test (ID Bigint, Batch Char(10), BatchID As Cast(ID As Char) + Batch Persisted)

Select ID, Batch From dbo.Test Where Cast ( ID As Char ) + Batch = ‘1045623’

Select ID, Batch From dbo.Test Where BatchID = ‘1045623’

Converts To


Role Reversal


Build Input

Probe Input

Hash MatchResultset

Partitioning


Dbo.Sales2016-2017Filegroup 1



Query

Dbo.Sales

Data Compression


dbo.Sales1 Billion Rows186GB Data Size23,250,000,000,000 Data Pages

dbo.Sales1 Billion Rows108GB Data Size1,4557,760,000 Data Pages

Data Compression Up to 40%

Deferred Transaction


In Other Editions, A Corrupted Transaction Causes Database Startup To Fail

Analysis Phase Roll Forward Phase Roll Back Phase

Transaction Recovery Lifecycle

Transaction Uncommitted Transaction Not Rolled BackDue to Corrupted Transaction Log I/O

Resource Governor


Memory: 64GBProcessor: 8 Logical Processor

DB_AMax Memory: 12GBMax Processor: 2 Logical ProcessorsMax IOPS: 500

DB_BMax Memory: 24GBMax Processor: 4 Logical ProcessorsMax IOPS: 2000

App A

App B

Vardecimal Storage Formatting


ID Full Name Savings

1 John Smith 50,000

2 Bill Gates 97,000,000,000

3 Kevin Wood 500

20 Bytes20 Bytes20 Bytes

ID Full Name Savings

1 John Smith 50,000

2 Bill Gates 97,000,000,000

3 Kevin Wood 500

5 Bytes20 Bytes5 Bytes

SQL SERVER 2016ENTERPRISE EDITION

NEW FEATURES


Columnstore Index

• Batch execution for single-threaded queries.

• Snapshot isolation and read-committed snapshot isolation.

• Specify columnstore index when creating a table.

• AlwaysOn readable secondary supports updateable columnstore indexes.

• Updateable nonclustered columnstore index on heap or btree.

• Btree index on a clustered columnstore index.

• Columnstore index on a memory-optimized table. ***

• Nonclustered columnstore index definition supports using a filtered condition.


In-Memory OLTP• ALTER operations for memory-optimized tables & natively compiled stored

procedures.

• Use MARS connections to access memory-optimized tables and natively compiled stored procedures.

• Support for natively compiled, scalar user-defined functions.

• Complete support for collations (No more limited to code page 1252).

• Memory-Optimized Table size increase to 2TB.


What is In-Memory OLTP?


In-Memory Table

Disk Based Table

Benefits:• Eliminate contention.• Reduce logging.• Lower latency data retrieval.• Minimize code execution time.• Efficient data retrieval.• Optional IO reduction or removal, when

using non-durable tables

Implementation Scenarios:• High data insertion rate from multiple

concurrent connections.• Read performance and scale with periodic

batch inserts and updates.• Intensive business logic processing in the

database server.• Low latency.• Session state management.

In-Memory OLTP Components


In-MemoryPerformance

Memory-Optimized Table Requirements.


Hardware Software

• X64 Architecture Processor• <60 Processor Cores• Enough Memory (x2 Table Size)• Enough Storage (x2 Table Size)• Processor Needs to Support cmpxchg16b

• X64 Architecture Edition• Enterprise or Developer Edition• Hyper-V to Support cmpxchg16b (If needed)• Enable Instant File Initialization

Memory Optimized Tables.

SQL Server CLR In-Memory Table


Memory Optimized Indexes.


Made for point lookups Made for range scans and ordered scans

In-Memory Query Processing


Disk Based Query Plan SQL Server Query Processing for Disk-Based Tables

INTerpreted Transact-SQL Access to Memory-Optimized TablesMemory Optimized Query Plan

In-Memory Query Processing (Cont.)


Native compilation of stored procedures

Execution of natively compiled stored procedures

In-Memory Transactions


Lifetime of a transaction that accesses memory-optimized tables

Regular Processing Validation Phase Commit Processing

• Commit Dependency• Repeatable Read Validation• Serialization Validation

In-Memory Memory EstimationCREATE TABLE IMOLTP (col1 INT NOT NULL PRIMARY KEY NONCLUSTERED,col2 INT NOT NULL INDEX INDEX_1 HASH WITH (BUCKET_COUNT = 5000000),col3 INT NOT NULL INDEX INDEX_2 HASH WITH (BUCKET_COUNT = 5000000),col4 INT NOT NULL INDEX INDEX_3 HASH WITH (BUCKET_COUNT = 5000000),col5 INT NOT NULL INDEX INDEX_4 NONCLUSTERED,col6 CHAR (50) NOT NULL, col7 CHAR (50) NOT NULL, col8 CHAR (30) NOT NULL, col9 CHAR (50) NOT NULL)WITH (MEMORY_OPTIMIZED = ON)

Memory for Table: Timestamps + Index Pointers + Row Data => 24 + (8+8+8+8) + (4+4+4+4+4+50+50+30+50) => 256 x 5000000 => 1.28GB

Memory for Hash Indexes: Round Up Bucket Count x Index Pointer => 223 x 8 => 67,108,864 Bytes => 64MB x 3 => 192MB

Memory for Non-Clustered Index: (Index Pointer + SUM(Key Column Data Type Size)) x Unique Rows => (8 + 4) x 5000000 => 57MB

Memory for Row Versioning: (Longest Trans. Duration in Sec. x Peak No. of Row Updates & Deletes in Sec.) x Row Size=> ( 1 x 10) x 256 => 2560 Bytes => 2560 x (0.3 x 5000000) => 3.66GB


http://fard-solutions.com/sql-server-memory-table-size-estimation-script/

http://fard-solutions.com/sql-server-memory-table-size-estimation-script/

In-Memory Filegroup Configuration


In-Memory Data & Delta File Population


Live Query Statistics

Query Store

Temporal Tables

JSON Format Query Result

Always Encrypted

Stretch DB

Row Level Security

Dynamic Data Masking

Questions and Answers


Contact for Expert Advice

Copyrights © 2016 Fard Solutions Sdn Bhd, All Rights Reserved.

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Tel: +603-89946788 - +603-79725433

Web: www.Fard-Solutions.com

Email: [email protected]

Contact Us For 30 Minutes Free Consultation.

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