Search Results

Search found 19 results on 1 pages for 'hekaton'.

Page 1/1 | 1 

  • Geek City: SQL Server 2014 In-Memory OLTP (“Hekaton”) Whitepaper for CTP2

    - by Kalen Delaney
    Last week at the PASS Summit in Charlotte, NC, the update of my whitepaper for CTP2 was released. The manager supervising the paper at Microsoft told me that David DeWitt himself said some very nice things about the technical quality of the paper, which was one of the most ego enhancing compliments I have ever gotten! Unfortunately, Dr. DeWitt said those things at his “After-the-keynote” session, not in the keynote that was recorded, so I only have my manager’s word for it. But I’ll take what I can...(read more)

    Read the article

  • What the Hekaton?

    - by Tony Davis
    Hekaton, the power behind SQL Server 2014′s In-Memory OLTP technology, is intended to make data operations run orders of magnitude faster on SQL Server. This works its magic partly by serving database workloads entirely from main memory, using memory-optimized table structures. It replaces the relational engine’s standard locking model with an optimistic concurrency model based on time-stamped row versions. Deeper down the Hekaton engine uses new, ‘latch free’ data structures. So far, so good, but performance improvements on this scale require a compromise, and the compromise is that these aren’t tables as we understand them. For the database developer, these differences are painful because they involve sacrificing some very important bits of the relational model. Most importantly, Hekaton tables don’t currently support FOREIGN KEY constraints or CHECK constraints, and you can’t put the checks in triggers because there aren’t any DML triggers either. Constraints allow a relational designer to enforce relational integrity and data integrity. Without them, of course, ‘bad data’ can get into our Hekaton tables. There is no easy way of preventing it. For several classes of database and data, this is a show-stopper. One may regard all these restrictions regretfully, seeing limited opportunity to try out Hekaton with current databases, but perhaps there is also a sudden glow of recognition. Isn’t this how we all originally imagined table variables were going to be, back in SQL 2005? And they have much the same restrictions. Maybe, instead of pretending that a currently-designed database can be ‘Hekatonized’ with a few mouse clicks, we should redesign databases for SQL 2014 to replace table variables with Hekaton tables, exploiting this technology for fast intermediate processing, and for the most part forget, for now, the idea of trying to convert our base relational tables into Hekaton tables. Few database developers would be averse to having their working tables running an order of magnitude faster, as long as it didn’t compromise the integrity of the data in the base tables.

    Read the article

  • Exploring In-memory OLTP Engine (Hekaton) in SQL Server 2014 CTP1

    The continuing drop in the price of memory has made fast in-memory OLTP increasingly viable. SQL Server 2014 allows you to migrate the most-used tables in an existing database to memory-optimised 'Hekaton' technology, but how you balance between disk tables and in-memory tables for optimum performance requires judgement and experiment. What is this technology, and how can you exploit it? Rob Garrison explains.

    Read the article

  • Why Hekaton In-Memory OLTP Truly is Revolutionary

    - by merrillaldrich
    I just returned from the PASS Summit in Charlotte, NC – which was excellent, among the best I have attended – and I have had Dr. David DeWitt’s talk rolling around in my head since he gave it on Thursday. (Dr. DeWitt starts at 27:00 at that link.) I probably cannot do it justice, but I wanted to recap why Hekaton really is revolutionary, and not just a marketing buzzword. I am normally skeptical of product announcements, and I find too often that real technical innovation can be overwhelmed by the...(read more)

    Read the article

  • Hekaton – SQL Server’s in-memory database engine

    - by Christian
    Microsoft have just gone public at the PASS Summit in Seattle about a new SQL Server engine that they’re working on which is optimized for high-memory servers – an in-memory OLTP database engine which is built-in to SQL Server rather than a separate entity.  This means that you can move just the performance critical parts of your database to Hekaton. The new engine really pushes the performance boundaries by eliminating as many instructions as possible: Main memory optimized tables which are decoupled from on-disk structures; Everything is lock and latch free; More work is pushed to compile time so your T-SQL code is compiled natively into low-level code. We’re already working with a customer on an early adoption program so expect to hear from us on what we learn about implementing it!   Christian Bolton - MCA, MCM, MVP Technical Director http://coeo.com - SQL Server Consulting & Managed Services

    Read the article

  • SQLBeat Podcast – Episode 7 – Niko Neugebauer, Linguist, SQL MVP and Hekaton Lover

    - by SQLBeat
    In this episode of the SQLBeat Podcast I steal Niko Neugebaur away from his guarded post at the PASS Community Zone at Summit 2012 in Seattle to chat with me about several intriguing topics. Mainly we discuss Hekaton and in memory databases, languages of all sorts, Microsoft’s direction, Reporting Services and Java. Or was that Java Script? Probably best that I stick with what I know and that is SQL Server. Niko, as always, is thoughtful and straightforward, congenial and honest. I like that about him and I know you will too. Enjoy! Download the MP3

    Read the article

  • SQLAuthority News – Download Whitepaper – A Case Study on “Hekaton” against RPM – SQL Server 2014 CTP1

    - by Pinal Dave
    In this new world of social media, apps and mobile devices, we are all now getting impatient. Automatic updates have spoiled few of our habits. When a new feature is released everybody wants to immediately adopt the feature and start using it. Though this is true in the world of apps and smart phones, but it is still not possible in the developer’s world. When new features are around, before we start using it, we need to spend quite a lots of time to understand it and test it. Once we are sold on the feature we refer the feature to our manager and eventually the entire organization makes decisions on upgrading to use the new feature. Similarly, when the new feature of In-Memory OLTP was announced, pretty much every SQL Server DBA wanted to implement that on their server. Through the implementation of the feature is not hard, it is not that easy as well. One has to do proper research about their own environment and workload before implementing this feature. Microsoft has recently released a Case Study on In-Memory OLTP feature. Here is the abstract from the white paper itself. I/O latch can cause session delays that impact application performance. This white paper describes the procedures and common I/O latch issues when migrating to Hekaton in SQL Server 2014. It also includes challenges that occurred during the migration and the performance analysis at different stages.  If you are going to implement In-Memory OLTP database, this is a good case study to refer. Download white paper from here. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL

    Read the article

  • T-SQL Tuesday #33: Trick Shots: Undocumented, Underdocumented, and Unknown Conspiracies!

    - by Most Valuable Yak (Rob Volk)
    Mike Fal (b | t) is hosting this month's T-SQL Tuesday on Trick Shots.  I love this choice because I've been preoccupied with sneaky/tricky/evil SQL Server stuff for a long time and have been presenting on it for the past year.  Mike's directives were "Show us a cool trick or process you developed…It doesn’t have to be useful", which most of my blogging definitely fits, and "Tell us what you learned from this trick…tell us how it gave you insight in to how SQL Server works", which is definitely a new concept.  I've done a lot of reading and watching on SQL Server Internals and even attended training, but sometimes I need to go explore on my own, using my own tools and techniques.  It's an itch I get every few months, and, well, it sure beats workin'. I've found some people to be intimidated by SQL Server's internals, and I'll admit there are A LOT of internals to keep track of, but there are tons of excellent resources that clearly document most of them, and show how knowing even the basics of internals can dramatically improve your database's performance.  It may seem like rocket science, or even brain surgery, but you don't have to be a genius to understand it. Although being an "evil genius" can help you learn some things they haven't told you about. ;) This blog post isn't a traditional "deep dive" into internals, it's more of an approach to find out how a program works.  It utilizes an extremely handy tool from an even more extremely handy suite of tools, Sysinternals.  I'm not the only one who finds Sysinternals useful for SQL Server: Argenis Fernandez (b | t), Microsoft employee and former T-SQL Tuesday host, has an excellent presentation on how to troubleshoot SQL Server using Sysinternals, and I highly recommend it.  Argenis didn't cover the Strings.exe utility, but I'll be using it to "hack" the SQL Server executable (DLL and EXE) files. Please note that I'm not promoting software piracy or applying these techniques to attack SQL Server via internal knowledge. This is strictly educational and doesn't reveal any proprietary Microsoft information.  And since Argenis works for Microsoft and demonstrated Sysinternals with SQL Server, I'll just let him take the blame for it. :P (The truth is I've used Strings.exe on SQL Server before I ever met Argenis.) Once you download and install Strings.exe you can run it from the command line.  For our purposes we'll want to run this in the Binn folder of your SQL Server instance (I'm referencing SQL Server 2012 RTM): cd "C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn" C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn> strings *sql*.dll > sqldll.txt C:\Program Files\Microsoft SQL Server\MSSQL11\MSSQL\Binn> strings *sql*.exe > sqlexe.txt   I've limited myself to DLLs and EXEs that have "sql" in their names.  There are quite a few more but I haven't examined them in any detail. (Homework assignment for you!) If you run this yourself you'll get 2 text files, one with all the extracted strings from every SQL DLL file, and the other with the SQL EXE strings.  You can open these in Notepad, but you're better off using Notepad++, EditPad, Emacs, Vim or another more powerful text editor, as these will be several megabytes in size. And when you do open it…you'll find…a TON of gibberish.  (If you think that's bad, just try opening the raw DLL or EXE file in Notepad.  And by the way, don't do this in production, or even on a running instance of SQL Server.)  Even if you don't clean up the file, you can still use your editor's search function to find a keyword like "SELECT" or some other item you expect to be there.  As dumb as this sounds, I sometimes spend my lunch break just scanning the raw text for anything interesting.  I'm boring like that. Sometimes though, having these files available can lead to some incredible learning experiences.  For me the most recent time was after reading Joe Sack's post on non-parallel plan reasons.  He mentions a new SQL Server 2012 execution plan element called NonParallelPlanReason, and demonstrates a query that generates "MaxDOPSetToOne".  Joe (formerly on the Microsoft SQL Server product team, so he knows this stuff) mentioned that this new element was not currently documented and tried a few more examples to see what other reasons could be generated. Since I'd already run Strings.exe on the SQL Server DLLs and EXE files, it was easy to run grep/find/findstr for MaxDOPSetToOne on those extracts.  Once I found which files it belonged to (sqlmin.dll) I opened the text to see if the other reasons were listed.  As you can see in my comment on Joe's blog, there were about 20 additional non-parallel reasons.  And while it's not "documentation" of this underdocumented feature, the names are pretty self-explanatory about what can prevent parallel processing. I especially like the ones about cursors – more ammo! - and am curious about the PDW compilation and Cloud DB replication reasons. One reason completely stumped me: NoParallelHekatonPlan.  What the heck is a hekaton?  Google and Wikipedia were vague, and the top results were not in English.  I found one reference to Greek, stating "hekaton" can be translated as "hundredfold"; with a little more Wikipedia-ing this leads to hecto, the prefix for "one hundred" as a unit of measure.  I'm not sure why Microsoft chose hekaton for such a plan name, but having already learned some Greek I figured I might as well dig some more in the DLL text for hekaton.  Here's what I found: hekaton_slow_param_passing Occurs when a Hekaton procedure call dispatch goes to slow parameter passing code path The reason why Hekaton parameter passing code took the slow code path hekaton_slow_param_pass_reason sp_deploy_hekaton_database sp_undeploy_hekaton_database sp_drop_hekaton_database sp_checkpoint_hekaton_database sp_restore_hekaton_database e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\hkproc.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\matgen.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\matquery.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\sqlmeta.cpp e:\sql11_main_t\sql\ntdbms\hekaton\sqlhost\sqllang\resultset.cpp Interesting!  The first 4 entries (in red) mention parameters and "slow code".  Could this be the foundation of the mythical DBCC RUNFASTER command?  Have I been passing my parameters the slow way all this time? And what about those sp_xxxx_hekaton_database procedures (in blue)? Could THEY be the secret to a faster SQL Server? Could they promise a "hundredfold" improvement in performance?  Are these special, super-undocumented DIB (databases in black)? I decided to look in the SQL Server system views for any objects with hekaton in the name, or references to them, in hopes of discovering some new code that would answer all my questions: SELECT name FROM sys.all_objects WHERE name LIKE '%hekaton%' SELECT name FROM sys.all_objects WHERE object_definition(OBJECT_ID) LIKE '%hekaton%' Which revealed: name ------------------------ (0 row(s) affected) name ------------------------ sp_createstats sp_recompile sp_updatestats (3 row(s) affected)   Hmm.  Well that didn't find much.  Looks like these procedures are seriously undocumented, unknown, perhaps forbidden knowledge. Maybe a part of some unspeakable evil? (No, I'm not paranoid, I just like mysteries and thought that punching this up with that kind of thing might keep you reading.  I know I'd fall asleep without it.) OK, so let's check out those 3 procedures and see what they reveal when I search for "Hekaton": sp_createstats: -- filter out local temp tables, Hekaton tables, and tables for which current user has no permissions -- Note that OBJECTPROPERTY returns NULL on type="IT" tables, thus we only call it on type='U' tables   OK, that's interesting, let's go looking down a little further: ((@table_type<>'U') or (0 = OBJECTPROPERTY(@table_id, 'TableIsInMemory'))) and -- Hekaton table   Wellllll, that tells us a few new things: There's such a thing as Hekaton tables (UPDATE: I'm not the only one to have found them!) They are not standard user tables and probably not in memory UPDATE: I misinterpreted this because I didn't read all the code when I wrote this blog post. The OBJECTPROPERTY function has an undocumented TableIsInMemory option Let's check out sp_recompile: -- (3) Must not be a Hekaton procedure.   And once again go a little further: if (ObjectProperty(@objid, 'IsExecuted') <> 0 AND ObjectProperty(@objid, 'IsInlineFunction') = 0 AND ObjectProperty(@objid, 'IsView') = 0 AND -- Hekaton procedure cannot be recompiled -- Make them go through schema version bumping branch, which will fail ObjectProperty(@objid, 'ExecIsCompiledProc') = 0)   And now we learn that hekaton procedures also exist, they can't be recompiled, there's a "schema version bumping branch" somewhere, and OBJECTPROPERTY has another undocumented option, ExecIsCompiledProc.  (If you experiment with this you'll find this option returns null, I think it only works when called from a system object.) This is neat! Sadly sp_updatestats doesn't reveal anything new, the comments about hekaton are the same as sp_createstats.  But we've ALSO discovered undocumented features for the OBJECTPROPERTY function, which we can now search for: SELECT name, object_definition(OBJECT_ID) FROM sys.all_objects WHERE object_definition(OBJECT_ID) LIKE '%OBJECTPROPERTY(%'   I'll leave that to you as more homework.  I should add that searching the system procedures was recommended long ago by the late, great Ken Henderson, in his Guru's Guide books, as a great way to find undocumented features.  That seems to be really good advice! Now if you're a programmer/hacker, you've probably been drooling over the last 5 entries for hekaton (in green), because these are the names of source code files for SQL Server!  Does this mean we can access the source code for SQL Server?  As The Oracle suggested to Neo, can we return to The Source??? Actually, no. Well, maybe a little bit.  While you won't get the actual source code from the compiled DLL and EXE files, you'll get references to source files, debugging symbols, variables and module names, error messages, and even the startup flags for SQL Server.  And if you search for "DBCC" or "CHECKDB" you'll find a really nice section listing all the DBCC commands, including the undocumented ones.  Granted those are pretty easy to find online, but you may be surprised what those web sites DIDN'T tell you! (And neither will I, go look for yourself!)  And as we saw earlier, you'll also find execution plan elements, query processing rules, and who knows what else.  It's also instructive to see how Microsoft organizes their source directories, how various components (storage engine, query processor, Full Text, AlwaysOn/HADR) are split into smaller modules. There are over 2000 source file references, go do some exploring! So what did we learn?  We can pull strings out of executable files, search them for known items, browse them for unknown items, and use the results to examine internal code to learn even more things about SQL Server.  We've even learned how to use command-line utilities!  We are now 1337 h4X0rz!  (Not really.  I hate that leetspeak crap.) Although, I must confess I might've gone too far with the "conspiracy" part of this post.  I apologize for that, it's just my overactive imagination.  There's really no hidden agenda or conspiracy regarding SQL Server internals.  It's not The Matrix.  It's not like you'd find anything like that in there: Attach Matrix Database DM_MATRIX_COMM_PIPELINES MATRIXXACTPARTICIPANTS dm_matrix_agents   Alright, enough of this paranoid ranting!  Microsoft are not really evil!  It's not like they're The Borg from Star Trek: ALTER FEDERATION DROP ALTER FEDERATION SPLIT DROP FEDERATION   #tsql2sday

    Read the article

  • Migrate to Natively Compiled SQL Server Stored Procedures for Hekaton

    In order to take full advantage of the In-Memory OLTP options in SQL Server 2014, you should migrate standard stored procedures that references Memory-Optimized tables to natively compiled ones. In this tip we will see how to achieve this goal. New! SQL Prompt 6 – now with tab historyWriting, exploring, and editing SQL just became even more effortless with SQL Prompt 6. Download a free trial.

    Read the article

  • In-Memory OLTP Sample for SQL Server 2014 RTM

    - by Damian
    I have just found a very good resource about Hekaton (In-memory OLTP feature in the SQL Server 2014). On the Codeplex site you can find the newest Hekaton samples - https://msftdbprodsamples.codeplex.com/releases/view/114491. The latest samples we have were related to the CTP2 version but the newest will work with the RTM version.There are some issues fixed you might find if you tried to run the previous samples on the RTM version:Update (Apr 28, 2014): Fixed an issue where the isolation level for sample stored procedures demonstrating integrity checks was too low. The transaction isolation level for the following stored procedures was updated: Sales.uspInsertSpecialOfferProductinmem, Sales.uspDeleteSpecialOfferinmem, Production.uspInsertProductinmem, and Production.uspDeleteProductinmem. 

    Read the article

  • In-Memory OLTP Sample for SQL Server 2014 RTM

    - by Damian
    I have just found a very good resource about Hekaton (In-memory OLTP feature in the SQL Server 2014). On the Codeplex site you can find the newest Hekaton samples - https://msftdbprodsamples.codeplex.com/releases/view/114491. The latest samples we have were related to the CTP2 version but the newest will work with the RTM version.There are some issues fixed you might find if you tried to run the previous samples on the RTM version:Update (Apr 28, 2014): Fixed an issue where the isolation level for sample stored procedures demonstrating integrity checks was too low. The transaction isolation level for the following stored procedures was updated: Sales.uspInsertSpecialOfferProductinmem, Sales.uspDeleteSpecialOfferinmem, Production.uspInsertProductinmem, and Production.uspDeleteProductinmem. 

    Read the article

  • Live from the #summit13 keynote : 2013-10-17

    - by AaronBertrand
    Douglas McDowell (EVP Finance) takes the stage (no kilt), and talks numbers. PASS has an impressive $1MM in reserves as a "rainy day" fund. Last fiscal year they spent $7.6MM on community; 30% of that internationally. Bill Graziano comes on (no kilt) to say goodbye and thanks to the outgoing board members, Douglas McDowell, Rob Farley and Rushabh Mehta. Thomas LaRock comes on. No kilt , but he did tuck his shirt in . He introduces the incoming executive team. The 2014 PASS Business Analytics Conference...(read more)

    Read the article

  • PASS 13 Dispatches: Memory Optimized = On

    - by Tony Davis
    I'm at the PASS Summit in Charlotte for the Day 1 keynote by Quentin Clarke, Corporate VP of the data platform group at Microsoft. He's talking about how SQL Server 2014 is “pushing boundaries” and first up is SQL Server 2014's In-Memory OLTP technology (former codename “hekaton”) It is a feature that provokes a lot of interest and for good reason as, without any need for application rewrites or hardware updates, it can enable us to ensure that an application can find in memory most or all of the data it needs, and can lead to huge improvements in processing times. A good recent hekaton use cases article talks about applications that need a “Shock Absorber” when either spikes or just a high rate of incoming workload (including data in ETL scenarios) become a primary bottleneck. To get a really deep look at this technology, I would check out David DeWitt's summit keynote tomorrow (it will be live streamed). Other than that, to get started I'd recommend Kalen Delaney's whitepaper. She offers a lot of insight into how it works and how to start to define memory-optimized tables, and natively compiled stored procedures. These memory-optimized tables uses completely optimistic multi-version concurrency control – no waiting on locks! After that, Tom LaRock has compiled a useful set of links to drill deeper, and includes one to Microsoft's AMR tool to help you gauge the tables that might benefit most. Tony.

    Read the article

  • Delayed Durability–I start to like it!

    - by Michael Zilberstein
    In my previous post about the subject I’ve complained that according to BOL , this feature is enabled for Hekaton only. Panagiotis Antonopoulos from Microsoft commented that actually BOL is wrong – delayed durability can be used with all sorts of transactions, not just In-Memory ones. There is a database-level setting for delayed durability: default value is “Disabled”, other two options are “Allowed” and “Forced”. We’ll switch between “Disabled” and “Forced” and measure IO generated by a simple...(read more)

    Read the article

  • SQL 2014 does data the way developers want

    - by Rob Farley
    A post I’ve been meaning to write for a while, good that it fits with this month’s T-SQL Tuesday, hosted by Joey D’Antoni (@jdanton) Ever since I got into databases, I’ve been a fan. I studied Pure Maths at university (as well as Computer Science), and am very comfortable with Set Theory, which undergirds relational database concepts. But I’ve also spent a long time as a developer, and appreciate that that databases don’t exactly fit within the stuff I learned in my first year of uni, particularly the “Algorithms and Data Structures” subject, in which we studied concepts like linked lists. Writing in languages like C, we used pointers to quickly move around data, without a database in sight. Of course, if we had a power failure all this data was lost, as it was only persisted in RAM. Perhaps it’s why I’m a fan of database internals, of indexes, latches, execution plans, and so on – the developer in me wants to be reassured that we’re getting to the data as efficiently as possible. Back when SQL Server 2005 was approaching, one of the big stories was around CLR. Many were saying that T-SQL stored procedures would be a thing of the past because we now had CLR, and that obviously going to be much faster than using the abstracted T-SQL. Around the same time, we were seeing technologies like Linq-to-SQL produce poor T-SQL equivalents, and developers had had a gutful. They wanted to move away from T-SQL, having lost trust in it. I was never one of those developers, because I’d looked under the covers and knew that despite being abstracted, T-SQL was still a good way of getting to data. It worked for me, appealing to both my Set Theory side and my Developer side. CLR hasn’t exactly become the default option for stored procedures, although there are plenty of situations where it can be useful for getting faster performance. SQL Server 2014 is different though, through Hekaton – its In-Memory OLTP environment. When you create a table using Hekaton (that is, a memory-optimized one), the table you create is the kind of thing you’d’ve made as a developer. It creates code in C leveraging structs and pointers and arrays, which it compiles into fast code. When you insert data into it, it creates a new instance of a struct in memory, and adds it to an array. When the insert is committed, a small write is made to the transaction to make sure it’s durable, but none of the locking and latching behaviour that typifies transactional systems is needed. Indexes are done using hashes and using bw-trees (which avoid locking through the use of pointers) and by handling each updates as a delete-and-insert. This is data the way that developers do it when they’re coding for performance – the way I was taught at university before I learned about databases. Being done in C, it compiles to very quick code, and although these tables don’t support every feature that regular SQL tables do, this is still an excellent direction that has been taken. @rob_farley

    Read the article

  • AdventureWorks 2014 Sample Databases Are Now Available

    - by aspiringgeek
      Where in the World is AdventureWorks? Recently, SQL Community feedback from twitter prompted me to look in vain for SQL Server 2014 versions of the AdventureWorks sample databases we’ve all grown to know & love. I searched Codeplex, then used the bing & even the google in an effort to locate them, yet all I could find were samples on different sites highlighting specific technologies, an incomplete collection inconsistent with the experience we users had learned to expect.  I began pinging internally & learned that an update to AdventureWorks wasn’t even on the road map.  Fortunately, SQL Marketing manager Luis Daniel Soto Maldonado (t) lent a sympathetic ear & got the update ball rolling; his direct report Darmodi Komo recently announced the release of the shiny new sample databases for OLTP, DW, Tabular, and Multidimensional models to supplement the extant In-Memory OLTP sample DB.  What Success Looks Like In my correspondence with the team, here’s how I defined success: 1. Sample AdventureWorks DBs hosted on Codeplex showcasing SQL Server 2014’s latest-&-greatest features, including:  In-Memory OLTP (aka Hekaton) Clustered Columnstore Online Operations Resource Governor IO 2. Where it makes sense to do so, consolidate the DBs (e.g., showcasing Columnstore likely involves a separate DW DB) 3. Documentation to support experimenting with these features As Microsoft Senior SDE Bonnie Feinberg (b) stated, “I think it would be great to see an AdventureWorks for SQL 2014.  It would be super helpful for third-party book authors and trainers.  It also provides a common way to share examples in blog posts and forum discussions, for example.”  Exactly.  We’ve established a rich & robust tradition of sample databases on Codeplex.  This is what our community & our customers expect.  The prompt response achieves what we all aim to do, i.e., manifests the Service Design Engineering mantra of “delighting the customer”.  Kudos to Luis’s team in SQL Server Marketing & Kevin Liu’s team in SQL Server Engineering for doing so. Download AdventureWorks 2014 Download your copies of SQL Server 2014 AdventureWorks sample databases here.

    Read the article

  • How SQL Server 2014 impacts Red Gate’s SQL Compare

    - by Michelle Taylor
    SQL Compare 10.7 successfully connects to SQL Server 2014, but it doesn’t yet cover the SQL Server 2014 features which would require us to make major changes to SQL Compare to support. In this post I’m going to talk about the SQL Server 2014 features we’ve already begun supporting, and which ones we’re working on for the next release of SQL Compare (v11). From SQL Compare’s perspective, the new memory-optimized table functionality (some might know it as ‘Hekaton’) has been the most important change. It can’t be described as its own object type, but the new functionality is split across two existing object types (three if you count indexes), as it also comes with native stored procedures and inline indexes. Along with connectivity support, the SQL Compare team has already implemented the first part of the puzzle – inline specification of indexes. These are essential for memory-optimized tables because it’s not possible to alter the memory optimized table’s structure, and so indexes can’t be added after the fact without dropping the table. Books Online  shows this in more detail in the table_index and column_index clauses of http://msdn.microsoft.com/en-us/library/ms174979(v=sql.120).aspx. SQL Compare 10.7 currently supports reading the new inline index specification from script folders and source control repositories, and will write out inline indexes where it’s necessary to do so (i.e. in UDDTs or when attempting to write projects compatible with the SSDT database project format). However, memory-optimized tables themselves are not yet supported in 10.7. The team is actively working on making them available in the v11 release with full support later in the year, and in a beta version before that. Fortunately, SQL Compare already has some ways of handling tables that have to be dropped and created rather than altered, which are being adapted to handle this new kind of table. Because it’s one of the largest new database engine features, there’s an equally large Books Online section on memory-optimized tables, but for us the most important parts of the documentation are the normal table features that are changed or unsupported and the new syntax found in the T-SQL reference pages. We are treating SQL Compare’s support of Natively Compiled Stored Procedures as a separate unit of work, which will be available in a subsequent beta and also feed into the v11 release. This new type of stored procedure is designed to work with memory-optimized tables to maintain the performance improvements gained by them – but you can still also access memory-optimized tables from normal stored procedures and ad-hoc queries. To us, they’re essentially a limited-syntax stored procedure with a few extra options in the create statement, embodied in the updated CREATE PROCEDURE documentation and with the detailed limitations. They should be easier to handle than memory-optimized tables simply because the handling of stored procedures is less sensitive to dropping the object than the handling of tables. However, both share an incompatibility with DDL triggers and Event Notifications which mean we’ll need to temporarily disable these during the specific deployment operations that involve them – don’t worry, we’ll supply a warning if this is the case so that you can check your auditing arrangements can handle the situation. There are also a handful of other improvements in SQL Server 2014 which affect SQL Compare and SQL Data Compare that are not connected to memory optimized tables. The largest of these are the improvements to columnstore indexes, with the capability to create clustered columnstore indexes and update columnstore tables through them – for more detail, take a look at the new syntax reference. There’s also a new index option for better compression of columnstores (COLUMNSTORE_ARCHIVE) and a new statistics option for incremental per-partition statistics, plus the 90 compatibility level is being retired. We’re planning to finish up these small clean-up features last, and be ready to release SQL Compare 11 with full SQL 2014 support early in Q3 this year. For a more thorough overview of what’s new in SQL Server 2014, Books Online’s What’s New section is a good place to start (although almost all the changes in this version are in the Database Engine).

    Read the article

  • PASS Summit 2012: keynote and Mobile BI announcements #sqlpass

    - by Marco Russo (SQLBI)
    Today at PASS Summit 2012 there have been several announcements during the keynote. Moreover, other news have not been highlighted in the keynote but are equally if not more important for the BI community. Let’s start from the big news in the keynote (other details on SQL Server Blog): Hekaton: this is the codename for in-memory OLTP technology that will appear (I suppose) in the next release of the SQL Server relational engine. The improvement in performance and scalability is impressive and it enables new scenarios. I’m curious to see whether it can be used also to improve ETL performance and how it differs from using SSD technology. Updates on Columnstore: In the next major release of SQL Server the columnstore indexes will be updatable and it will be possible to create a clustered index with Columnstore index. This is really a great news for near real-time reporting needs! Polybase: in 2013 it will debut SQL Server 2012 Parallel Data Warehouse (PDW), which will include the Polybase technology. By using Polybase a single T-SQL query will run queries across relational data and Hadoop data. A single query language for both. Sounds really interesting for using BigData in a more integrated way with existing relational databases. And, of course, to load a data warehouse using BigData, which is the ultimate goal that we all BI Pro have, right? SQL Server 2012 SP1: the Service Pack 1 for SQL Server 2012 is available now and it enable the use of PowerPivot for SharePoint and Power View on a SharePoint 2013 installation with Excel 2013. Power View works with Multidimensional cube: the long-awaited feature of being able to use PowerPivot with Multidimensional cubes has been shown by Amir Netz in an amazing demonstration during the keynote. The interesting thing is that the data model behind was based on a many-to-many relationship (something that is not fully supported by Power View with Tabular models). Another interesting aspect is that it is Analysis Services 2012 that supports DAX queries run on a Multidimensional model, enabling the use of any future tool generating DAX queries on top of a Multidimensional model. There are still no info about availability by now, but this is *not* included in SQL Server 2012 SP1. So what about Mobile BI? Well, even if not announced during the keynote, there is a dedicated session on this topic and there are very important news in this area: iOS, Android and Microsoft mobile platforms: the commitment is to get data exploration and visualization capabilities working within June 2013. This should impact at least Power View and SharePoint/Excel Services. This is the type of UI experience we are all waiting for, in order to satisfy the requests coming from users and customers. The important news here is that native applications will be available for both iOS and Windows 8 so it seems that Android will be supported initially only through the web. Unfortunately we haven’t seen any demo, so it’s not clear what will be the offline navigation experience (and whether there will be one). But at least we know that Microsoft is working on native applications in this area. I’m not too surprised that HTML5 is not the magic bullet for all the platforms. The next PASS Business Analytics conference in 2013 seems a good place to see this in action, even if I hope we don’t have to wait other six months before seeing some demo of native BI applications on mobile platforms! Viewing Reporting Services reports on iPad is supported starting with SQL Server 2012 SP1, which has been released today. This is another good reason to install SP1 on SQL Server 2012. If you are at PASS Summit 2012, come and join me, Alberto Ferrari and Chris Webb at our book signing event tomorrow, Thursday 8 2012, at the bookstore between 12:00pm and 12:30pm, or follow one of our sessions!

    Read the article

  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

    Read the article

1