• Home
  • SQL Server
    • Articles
    • T-SQL Puzzles
    • Output Puzzles
    • Interview Questions
    • Performance Tuning
    • SQL SERVER On Linux
    • Resources
  • SSRS
    • SSRS Articles
    • Interview Questions
  • SSAS
    • SSAS Articles
    • DAX
  • SQL Puzzles
  • Interview Questions
    • SQL Interview Questions
    • Data Interview Questions
  • Python Interview Puzzles
  • New Features(SQL SERVER)
    • SQL SERVER 2017
    • SQL SERVER 2016
    • SQL SERVER On Linux
  • Social
    • Expert Exchange
      • Top Expert in SQL
      • Yearly Award
      • Certifications
      • Achievement List
      • Top Expert of the Week
    • HackerRank (SQL)
    • StackOverflow
    • About Me
      • Contact Me
      • Blog Rules

Improving my SQL BI Skills

Improving my SQL BI Skills

Daily Archives: April 12, 2015

SQL Server 2014 In-Memory OLTP

12 Sunday Apr 2015

Posted by Pawan Kumar Khowal in SQL Concepts, SQL SERVER, SQL Server Interview Questions

≈ Leave a comment

Tags

In memory oltp, Interview Qs.SQL SERVER Questions, Interview Questions on SQL, InterviewQuestions, InterviewQuestions for SQL, puzzle sql developer, QL, SQL 2012, SQL 2014, SQL 2014 Interview Questions, SQL 2014 new features, SQL In memory oltp, SQL Interesting Interview Questions, SQL Interview Questions, SQL New Features, SQL Server, SQL SERVER 2014, SQL SERVER 2014 New Features, SQL Server Database, SQL SERVER Interview questions, SQL Skills, SQL Tricky question, SQLSERVER, Tricky Questions, TSQL, TSQL Interview questions, TSQL Queries


SQL Server 2014 In-Memory OLTP

Hekaton (also known as SQL Server In-Memory OLTP) is an in-memory database for OLTP workloads built into Microsoft SQL Server. Hekaton was designed in collaboration with Microsoft Research and was released in SQL Server 2014. Traditional RDBMS systems were designed when memory resources were expensive, and was optimized for disk storage. Hekaton is instead optimized for a working set stored entirely in main memory, but is still accessible via T-SQL like normal tables.

The SQL Server 2014 In-Memory OLTP engine (a.k.a. Hekaton) is a huge change for relational databases.

Now consider memory as your new disk

Notes-

• In SQL Server 2014 you can create memory-optimized tables and indexes. Everything will be present in the memory that why we need more memory.

• Here we can also have disk-based tables and indexes. (SQL 2012 & before.)

• A memory-optimized table is a one where SQL Server will always store in memory the whole table and its indexes.

• The storage of memory-optimized tables is different from conventional storage mechanism hence there are no data pages, and no extents. There are just “data rows,” written to memory.

• For memory-optimized tables, SQL Server will never have to acquire latches nor perform I/O in order to retrieve data.

• SQL Server guarantees ACID properties of all transactions without acquiring any locks. Therefore no transaction will ever be blocked, waiting to acquire a lock.

• In the order the transactions occurred, with each row containing an index “pointer” to the next row. All “I/O” is in-memory scanning of these structures.

• Many versions of the same row can coexist at any given time. This allows concurrent access of the same row, during data modifications, with SQL Server making available the row version relevant to each transaction according to the time the transaction started relative to the timestamp values stored in the header of each row version.

Now we will have a small demo of how we can create in memory DB and in memory table.

In memory DB should have MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specially created to store the checkpoint files needed by SQL Server to recover the memory-optimized tables. The syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, We just have to mention the option CONTAINS MEMORY_OPTIMIZED_DATA.

—


--Create an In Memory Database

/*


FILEGROUP [InMem_FG] CONTAINS MEMORY_OPTIMIZED_DATA

*/

CREATE DATABASE Mem
ON PRIMARY
(
	NAME = Mem,
	FILENAME = 'C:\Mem.mdf', size=2000 MB
)
,	FILEGROUP [InMem_FG] CONTAINS MEMORY_OPTIMIZED_DATA
	(
		NAME = [Mem_dir],
		FILENAME = 'C:\Mem_dir'
	)
	LOG ON (name = [InMem_demo_log], Filename='c:\Mem.ldf', size=1000MB
)
GO

--CREATE an In Memory table


/*
There are some syntactical differences between creating a disk based table 
and a memory optimized table. All memory-optimized table should use the 
MEMORY_OPTIMIZED = ON clause as shown in the Create Table query below.
*/


CREATE TABLE TestMem
(
   [ID] [INT] NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH ( BUCKET_COUNT = 10000 ) 
  ,[Name] [int] NOT NULL  
)
WITH ( MEMORY_OPTIMIZED = ON , DURABILITY = SCHEMA_AND_DATA )


--Insert Data in a In Memory Table
DECLARE @cntr bigint = 1
WHILE @cntr<= 100000
BEGIN
	INSERT INTO dbo.TestMem(Id,Name) VALUES(@cntr,@cntr)
	SET @cntr+=1
END

--Time taken here is -- 15 Sec

—

Now since we heard that this memory things if faster than the old ways to doing things. Lets create a disk based table and insert the same no of rows and checkout the timings.

—-


CREATE TABLE TestNONMem
(
   [ID] [INT] NOT NULL PRIMARY KEY NONCLUSTERED
  ,[Name] [int] NOT NULL  
)
GO

DECLARE @cntr1 bigint = 1
WHILE @cntr1 <= 100000
BEGIN
	INSERT INTO dbo.TestNONMem(Id,Name) 
        VALUES(@cntr1,@cntr1)
	SET @cntr1+=1
END

--Time taken -- 22 Sec

—

We can see that the Memory optimzed insertion took less time than the old version. See the attached snap below.

Comparisions

Keep Learning. We all need to learn.

http://MSBISkills.com

Share this

  • LinkedIn
  • Facebook
  • Twitter
  • WhatsApp
  • Email

Blog Stats

  • 1,084,601 hits

Enter your email address to follow this blog and receive notifications of new posts by email.

Join 1,131 other subscribers

Pawan Khowal

502 SQL Puzzles with answers

Achievement - 500 PuzzlesJuly 18, 2018
The big day is here. Finally presented 500+ puzzles for SQL community.

200 SQL Server Puzzle with Answers

The Big DayAugust 19, 2016
The big day is here. Completed 200 SQL Puzzles today

Archives

April 2015
M T W T F S S
 12345
6789101112
13141516171819
20212223242526
27282930  
« Mar   May »

Top Articles

  • pawankkmr.wordpress.com/2…
  • pawankkmr.wordpress.com/2…
  • pawankkmr.wordpress.com/2…
  • pawankkmr.wordpress.com/2…
  • pawankkmr.wordpress.com/2…

Archives

  • October 2020 (29)
  • September 2018 (2)
  • August 2018 (6)
  • July 2018 (25)
  • June 2018 (22)
  • May 2018 (24)
  • April 2018 (33)
  • March 2018 (35)
  • February 2018 (53)
  • January 2018 (48)
  • December 2017 (32)
  • November 2017 (2)
  • October 2017 (20)
  • August 2017 (8)
  • June 2017 (2)
  • March 2017 (1)
  • February 2017 (18)
  • January 2017 (2)
  • December 2016 (5)
  • November 2016 (23)
  • October 2016 (2)
  • September 2016 (14)
  • August 2016 (6)
  • July 2016 (22)
  • June 2016 (27)
  • May 2016 (15)
  • April 2016 (7)
  • March 2016 (5)
  • February 2016 (7)
  • December 2015 (4)
  • October 2015 (23)
  • September 2015 (31)
  • August 2015 (14)
  • July 2015 (16)
  • June 2015 (29)
  • May 2015 (25)
  • April 2015 (44)
  • March 2015 (47)
  • November 2012 (1)
  • July 2012 (8)
  • September 2010 (26)
  • August 2010 (125)
  • July 2010 (2)

Article Categories

  • Analysis Services (6)
    • DAX (6)
  • Data (2)
    • Data warehousing (2)
  • Integration Services (2)
  • Magazines (3)
  • Python (29)
  • Reporting Services (4)
  • SQL SERVER (820)
    • Download SQL Interview Q's (212)
    • SQL Concepts (323)
    • SQL Performance Tuning (155)
    • SQL Puzzles (331)
    • SQL SERVER 2017 Linux (6)
    • SQL Server Interview Questions (308)
    • SQL SERVER Puzzles (332)
    • T SQL Puzzles (547)
    • Tricky SQL Queries (439)
  • UI (30)
    • ASP.NET (5)
    • C# (13)
    • CSS (9)
    • OOPS (3)
  • Uncategorized (5)

Recent Posts

  • Python | The Print and Divide Puzzle October 30, 2020
  • Python | Count consecutive 1’s from a list of 0’s and 1’s October 30, 2020
  • Python | How to convert a number into a list of its digits October 26, 2020
  • Python | Validate an IP Address-IPV6(Internet Protocol version 6) October 26, 2020
  • Python | Print the first non-recurring element in a list October 26, 2020
  • Python | Print the most recurring element in a list October 26, 2020
  • Python | Find the cumulative sum of elements in a list October 26, 2020
  • Python | Check a character is present in a string or not October 26, 2020
  • Python | Check whether a string is palindrome or not October 26, 2020
  • Python | Find the missing number in the array of Ints October 26, 2020
  • Python | How would you delete duplicates in a list October 26, 2020
  • Python | Check whether an array is Monotonic or not October 26, 2020
  • Python | Check whether a number is prime or not October 26, 2020
  • Python | Print list of prime numbers up to a number October 26, 2020
  • Python | Print elements from odd positions in a list October 26, 2020
  • Python | Print positions of a string present in another string October 26, 2020
  • Python | How to sort an array in ascending order October 26, 2020
  • Python | How to reverse an array October 26, 2020
  • Python | Find un-common words from two strings October 26, 2020
  • Python | How to convert a string to a list October 26, 2020
  • Python | Find unique words from a string October 26, 2020
  • Python | Calculate average word length from a string October 26, 2020
  • Python | Find common words from two strings October 26, 2020
  • Python | Find the number of times a substring present in a string October 26, 2020
  • Python | Find maximum value from a list October 26, 2020
  • Python | How to find GCF of two numbers October 26, 2020
  • Python | How to find LCM of two numbers October 26, 2020
  • Python | How to convert a list to a string October 26, 2020
  • Python | Replace NONE by its previous NON None value October 26, 2020
  • Microsoft SQL Server 2019 | Features added to SQL Server on Linux September 26, 2018

Create a website or blog at WordPress.com

  • Follow Following
    • Improving my SQL BI Skills
    • Join 231 other followers
    • Already have a WordPress.com account? Log in now.
    • Improving my SQL BI Skills
    • Customize
    • Follow Following
    • Sign up
    • Log in
    • Report this content
    • View site in Reader
    • Manage subscriptions
    • Collapse this bar
 

Loading Comments...
 

You must be logged in to post a comment.