1. drsql.org How In-Memory Affects Database Design Louis Davidson Certified Nerd 1

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3. drsql.org SQL Server vNext Wednesday, October 15 6:00 PM Nova Southeastern University 4850 Millenia Blvd http://magicpassopass.eventbrite.com Mark Souza General Manager, Cloud and Enterprise Engineering Team FREE!

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5. drsql.org 5 Who am I? Been in IT for over 19 years Microsoft MVP For 10 Years Corporate Data Architect Written five books on database design Ok, so they were all versions of the same book. They at least had slightly different titles each time Basically: I love Database Design, and In-Memory technologies are changing the game

6. drsql.org Questions are Welcome Please limit questions to one’s I know the answer to. 6

7. drsql.org A tasty allegory… Bacon is awesome Bacon is an extremely powerful tool for rapid fat and calorie intake Even bacon isn't good for everything 7 http://www.lazygamer.net/general-news/diablo-iii-players-burned-off-820-968-kgs-of-bacon/ https://www.flickr.com/photos/runnerone/6232183896/in/photostream/

8. drsql.org 8 The process I went through Start with basic requirements – Sales system – Stream of customer and order data – Apply In-Memory OLTP to see how it changed things – Keep it very simple Learn a lot – This presentation was borne out of what I learned from that process (and Kalen Delaney’s precon, whitepaper, and other reading that is linked throughout the slides) Build a test and apply what I have learned and morph until I get to what works Build something real in my day job, if applicable 8

9. drsql.org Attention: There Is Homework (lots of it) I can’t teach you everything about In-Memory in 1 mere hour, particularly the internals The code will be available/demonstrated, but it is still very rudimentary It will get you started, but is only just the tip of the iceberg 9

10. drsql.org Introduction: What exactly is In-Memory OLTP in SQL Server 2014? A totally new, revamped engine for data storage, co-located in the same database with the existing engine – Obviously Enterprise Only… Purpose built for certain scenarios Terminology can be confusing – Existing tables: Home - On-Disk, but ideally cached In-Memory – In-Memory tables: Home - In-Memory: but backed up by On-Disk Structures If you have enough RAM, On-Disk tables are also in memory – But the implementation is very very different In-Memory is both very easy, and very difficult to use 10

11. drsql.org Design Basics (And no, I am not stalling for time due to lack of material) Designing and Coding is Like the Chicken and the Egg – Design is what you do before coding – Coding patterns can greatly affect design – Engine implementation can greatly affect design and coding patterns – Developing software follows a natural process We will discuss how In-Memory technologies affect the entire design/development lifecycle As if… Children I was first Relics 11

12. drsql.org Design Basics - Separate your design mind into three phases 1.Logical (Overall data requirements in a data model format) 2.Physical Implementation Choice A.Type of database system: Paper, Excel, Access, SQL Server, NoSQL, etc B.Engine choices: In-Memory, On-Disk, Compression, Partitioning, etc Note: Bad choices usually involve pointy hair and a magazine article with very little thinking and testing 3.Physical (Relational Code) Before the engine choice I always suggested 3 before 2 We will look at each of these phases and how in-mem may affect your design of each output 12

13. drsql.org Logical Design (Though Not Everyone’s Is) This is the easiest part of the presentation You still need to model – Entities and Attributes – Uniqueness Conditions – General Predicates As I see it, nothing changes… 13

14. drsql.org Logical Data Model 14

15. drsql.org SQL Server.exe Data Filegroup TDS Handler and Session Management Physical Implementation Overview Buffer Pool for Tables & Indexes Proc/Plan cache for ad- hoc T-SQL and SPs Client App Transaction Log Interpreter for TSQL, query plans, expressions Access Methods Parser, Catalog, Algebrizer, Optimizer 10-30x more efficient (Real Apps see 2-30x) 10-30x more efficient (Real Apps see 2-30x) Reduced log bandwidth & contention. Log latency remains Memory-optimized Table Filegroup Engine for Memory_optimized Tables & Indexes Natively Compiled SPs and Schema Hekaton Compiler Query Interop Checkpoints are background sequential IO No improvements in communication stack, parameter passing, result set generation Hekaton Component Key Existing SQL Component Generated.dll http://download.microsoft.com/documents/hk/technet/techdays2014/Day2/Session2/DBI394-SQL%20Server%202014%20In-Memory%20OLTP%20-%20Depp%20Dive.pdf

16. drsql.org Physical Implementation (Technically it’s all software!) Everything is different, and I am going to give just an overview of physical details… In-Mem data structures coexist in the database alongside On- Disk ones Data is housed in RAM, and backed up in Delta Files and Transaction Logs – Delta files are stored as filestream storage – The transaction log is the same one as you are used to (with lighter utilization) Tables and Indexes are extremely coupled MVCC (Multi-Valued Concurrency Control) used for all isolation 16

17. drsql.org Physical Design (No, let’s not get physical) Your physical design will almost certainly need to be affected So much changes, even just changing the internal table structure In this section, we will discuss: – Creating storage objects Table Creation Index Creation (which is technically part of the table creation) Altering a Table’s Structure – Accessing (Modifying/Creating) data Using Normal T-SQL (Interop) Using Compiled Code (Native) Using a Hybrid Approach No Locks, No Latches, No Waiting 17

18. drsql.org Creating Storage Objects - Tables The syntax is the same as on-disk, with a few additional settings You have a durability choices – Individual In-Mem Table: Schema_Only or Schema_and_Data – Database level for transactions: Delayed (also for on-disk tables) Basically Asynchronous Log Writes Aaron Bertrand has a great article on this here: http://sqlperformance.com/2014/04/io-subsystem/delayed-durability-in-sql- server-2014http://sqlperformance.com/2014/04/io-subsystem/delayed-durability-in-sql- server-2014 You also have less to work with... – Rowsize limited to 8060 bytes (Enforced at Create Time) Not all datatypes allowed (LOB types,CLR,sql_variant, datetimeoffset, rowversion) – No check constraints – No foreign keys – Limited unique constraints (just one unique index per table) Every durable (Schema_and_Data) table must have a primary key Note: There are memory optimized temporary tables too: See Kendra Little’s article here: http://www.brentozar.com/archive/2014/04/table-variables-good-temp-tables-sql-2014/ http://www.brentozar.com/archive/2014/04/table-variables-good-temp-tables-sql-2014/ 18

19. drsql.org Dealing with Un-Supported Datatypes… Say you have a table with 10 columns, but 1 is not allowed in a In-Memory table First: Ask yourself if the table really fits the criteria we aren’t done covering Second: If so, consider vertically partitioning CREATE TABLE In_Mem (KeyValue, Column1, Column2, Column3) CREATE TABLE On_Disk (KeyValue, Column4) It is likely that uses of disallowed types wouldn’t be good for the OLTP aspects of the table in any case. 19

20. drsql.org Creating Storage Objects - Index creation Syntax is inline with CREATE TABLE Indexes are linked directly to the table – 8 indexes max per table due to internals – Only one unique index allowed (the primary key) – Indexes are never persisted, but are rebuilt on restart String index columns must be a binary collation (case AND accent sensitive) Cannot index nullable column Two types – Hash Ideal for single row lookups Fixed size, you choose the number of hash buckets (approx 1-2 * # of unique values http://msdn.microsoft.com/en-us/library/dn494956.aspx) http://msdn.microsoft.com/en-us/library/dn494956.aspx – Bw Tree Best for range searches Very similar to a BTree index as you (hopefully) know it, but optimized for MVCC and pointer connection to table 20

21. drsql.org 21 A Taste of the Physical Structures Basic data record for a row Record Header 21

22. drsql.org 22 Hash Index - Simplified 22 TableNameIdCountryOtherColumns 1USAValues 2USAValues 3CanadaValues

23. drsql.org 23 Hash Index - Simplified 23 TableNameIdCountryOtherColumns 1USAValues 2CanadaValues 3CanadaValues

24. drsql.org 24 Bw Tree Index – Even More Simplified 24

25. drsql.org Do you want to know more? For more in-depth coverage – check Kalen Delaney's white paper... http://t.co/T6zToWc6y6http://t.co/T6zToWc6y6 – Or for an even deeper (nerdier?) versions: “Hekaton: SQL Server’s Memory- Optimized OLTP Engine” http://research.microsoft.com/apps/pubs/default.aspx?id=193594 or The Bw- Tree: A B-tree for New Hardware Platforms (http://research.microsoft.com/pubs/178758/bw-tree-icde2013-final.pdf) http://research.microsoft.com/apps/pubs/default.aspx?id=193594http://research.microsoft.com/pubs/178758/bw-tree-icde2013-final.pdf – Books Online: http://technet.microsoft.com/en-us/library/dn133186.aspxhttp://technet.microsoft.com/en-us/library/dn133186.aspx – TechDays Presentation: http://download.microsoft.com/documents/hk/technet/techdays2014/Day2/Session 2/DBI394-SQL%20Server%202014%20In-Memory%20OLTP%20- %20Depp%20Dive.pdf http://download.microsoft.com/documents/hk/technet/techdays2014/Day2/Session 2/DBI394-SQL%20Server%202014%20In-Memory%20OLTP%20- %20Depp%20Dive.pdf 25

26. drsql.org Creating Storage Objects - Altering a Table The is the second easiest slide in the deck No alterations allowed - Strictly Drop and Recreate – You can rename a table, which makes this at east easier ALTER 26

27. drsql.org DEMO IN SLIDES – PREPARING TO (AND ACTUALLY) CREATING TABLES 27

28. drsql.org 28 Setting the Database To Allow In-Mem CREATE DATABASE HowInMemObjectsAffectDesign ON PRIMARY ( NAME = N'HowInMemObjectsAffectDesign', FILENAME = N‘Drive:\HowInMemObjectsAffectDesign.mdf', SIZE = 2GB, MAXSIZE = UNLIMITED, FILEGROWTH = 10% ), FILEGROUP [MemoryOptimizedFG] CONTAINS MEMORY_OPTIMIZED_DATA ( NAME = N'HowInMemObjectsAffectDesign_inmemFiles', FILENAME = N'Drive:\InMemfiles', MAXSIZE = UNLIMITED) LOG ON ( NAME = N'HowInMemObjectsAffectDesign_log', FILENAME = N'Drive:\HowInMemObjectsAffectDesign_log.ldf', SIZE = 1GB, MAXSIZE = 2GB, FILEGROWTH = 10%); GO 28 Add a filegroup to hold the delta files

29. drsql.org 29 Creating a Memory Optimized Permanent Table CREATE TABLE [Customers].[Customer] ( [CustomerId] integer NOT NULL IDENTITY ( 1,1 ), [CustomerNumber] char(10) COLLATE Latin1_General_100_BIN2 NOT NULL, CONSTRAINT [XPKCustomer] PRIMARY KEY NONCLUSTERED HASH ( [CustomerId]) WITH ( BUCKET_COUNT = 50000), INDEX [CustomerNumber] NONCLUSTERED ( [CustomerNumber]) ) WITH ( MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) go 29 Character column must be binary to index/compare in native code Hash Index used for Primary Key. Estimated Rows in Table 25000-50000 Bw Tree Index on Customer Number This table is memory optimized (ok, that was kind of obvious) This table is as durable as the database settings allow

30. drsql.org Accessing the Data - Using Normal T-SQL (Interop) Using typical interpreted T-SQL Most T-SQL will work with no change (you may need to add isolation level hints, particularly in explicit transaction) A few Exceptions that will not work – TRUNCATE TABLE - This one is really annoying :) – MERGE (In-Mem table cannot be the target) – Cross Database Transactions (other than tempdb) – Locking Hints 30

31. drsql.org Accessing the Data using Compiled Code (Native) Instead of being interpreted, the stored procedure is compiled to machine code Limited syntax (Like programming with both hands tied behind your back) Allowed syntax is listed in what is available, not what isn't – http://msdn.microsoft.com/en-us/library/dn452279.aspx http://msdn.microsoft.com/en-us/library/dn452279.aspx Some really extremely annoying ones: – SUBSTRING supported; LEFT, RIGHT, not so much – No Subqueries – OR, NOT, IN, not supported in WHERE clause – Can’t use on-disk objects (tables, sequences, views, etc) – String Comparisons must be with columns of Binary Collation So you may have to write some "interesting" code 31

32. drsql.org DEMO IN SLIDES – NATIVE STORED PROCEDURE 32

33. drsql.org Creating a Natively Optimized (I write my C# the new fashioned way, with T-SQL) CREATE PROCEDURE Customers.Customer$CreateAndReturn @Parameter1 Parameter1Type = 'defaultValue1', @Parameter2 Parameter2Type = 'defaultValue2', … @ParameterN ParameterNType = 'defaultValueN‘ WITH NATIVE_COMPILATION, SCHEMABINDING, EXECUTE AS OWNER AS BEGIN ATOMIC WITH ( TRANSACTION ISOLATION LEVEL = SNAPSHOT, LANGUAGE = N'us_english' ) END 33 Alert parser that this will be a natively compiled object Works just like for views and functions. Can’t change the underlying object while this object references it There is no Ownership chaining. All code executes as the procedure owner Procedures are atomic transactions

34. drsql.org Accessing Data Using a Hybrid Approach Native code is very fast but very limited Use Native code where it makes sense, and not where it doesn’t Example: Creating a sequential value – In the demo code I started out by using RAND() to create CustomerNumbers and SalesOrderNumbers. – Using a SEQUENCE is far more straightforward – So I made one Interpreted procedure that uses the SEQUENCE outside of native code, then calls the native procedure 34

35. drsql.org Accessing the Data - No Locks, No Latches, No Waiting On-Disk Structures use Latches and Locks to implement isolation In-Mem use Optimistic-MVCC You have 3 Isolation Levels: – SNAPSHOT, REPEATABLE READ, SERIALIZABLE – Evaluated before, or when the transaction is committed – This makes data integrity checking "interesting" Essential difference, your code now must handle errors 35

36. drsql.org Concurrency is the #1 difference you will deal with Scenario1: 2 Connections - Update Every Row In 1 Million Rows Any Isolation Level On-Disk – Either: 1 connection blocks the other – Or: Deadlock In-Mem – One connection will fail, saying: “the row you are trying to update has been updated since this transaction started” EVEN if it never commits. 36

37. drsql.org Another slide on Concurrency (Because if I had presented it concurrently with the other one, you wouldn’t have liked that) Scenario2: 1 Connection Updates All Rows, Another Reads All Rows (In an explicit transaction) On-Disk – Either: 1 connection blocks the other – Or: Deadlock In-Mem – Both Queries Execute Immediately – In SNAPSHOT ISOLATION the reader will always succeed – In REPEATABLE READ or SERIALIZABLE Commits transaction BEFORE updater commits: Success Commits transaction AFTER updater commits: Fails 37

38. drsql.org The Difficulty of Data Integrity With on-disk structures, we used constraints for most issues (Uniqueness, Foreign Key, Simple Predicates) With in-memory code, we have to implement in stored procedure – Uniqueness on > 1 column set suffers from timing (If N connections are inserting the same data...MVCC will let them) – Foreign Key can't reliably be done because: In Snapshot Isolation Level, the row may have been deleted while you check In Higher Levels, the transaction will fail if the row has been updated – Check constraint style work can be done in stored procedures for the most part. 38

39. drsql.org Problem: How to Implement Uniqueness on > 1 Column Set: INDEXED VIEW? CREATE VIEW Customers.Customers$UniquenessEnforcement WITH SCHEMABINDING AS SELECT customerId, emailAddress, customerNumber FROM customers.Customer GO CREATE UNIQUE CLUSTERED INDEX emailAddress ON Customers.Customers$UniquenessEnforcement (emailAddress) GO Msg 10794, Level 16, State 12, Line 8 The operation 'CREATE INDEX' is not supported with memory optimized tables. 39

40. drsql.org Problem: How to Implement Uniqueness on > 1 Column Set: Multiple Tables? Wow, that seems messy… And what about duplicate customerId values in the two subordinate tables? 40

41. drsql.org Problem: How to Implement Uniqueness on > 1 Column Set: Simple code You can’t…exactly. But what if EVERY caller has to go through the following block: DECLARE @CustomerId INT SELECT @CustomerId = CustomerId FROM Customers.Customer WHERE EmailAddress = @EmailAddress IF @customerId is null… Do your insert This will stop MOST duplication, but not all. Two inserters can check at the same time, and with no blocks, app locks, or constraints even available, you may get duplicates. Remember the term: Optimistic Concurrency Control 41

42. drsql.org When Should You Make Tables In-Memory - Microsoft's Advice From http://msdn.microsoft.com/en-us/library/dn133186.aspxhttp://msdn.microsoft.com/en-us/library/dn133186.aspx Implementation Scenario Benefits of In-Memory OLTP High data insertion rate from multiple concurrent connections. Primarily append-only store. Unable to keep up with the insert workload. Eliminate contention. Reduce logging. Read performance and scale with periodic batch inserts and updates. High performance read operations, especially when each server request has multiple read operations to perform. Unable to meet scale-up requirements. Eliminate contention when new data arrives. Lower latency data retrieval. Minimize code execution time. Intensive business logic processing in the database server. Insert, update, and delete workload. Intensive computation inside stored procedures. Read and write contention. Eliminate contention. Minimize code execution time for reduced latency and improved throughput. Low latency. Require low latency business transactions which typical database solutions cannot achieve. Eliminate contention. Minimize code execution time. Low latency code execution. Efficient data retrieval. Session state management. Frequent insert, update and point lookups. High scale load from numerous stateless web servers. Eliminate contention. Efficient data retrieval. Optional IO reduction or removal, when using non-durable tables 42

43. drsql.org When Should You Make Tables In-Memory Louis's Advice More or less the same as Microsoft's really (duh!) Things to factor in – High concurrency needs/Low chance of collisions – Minimal uniqueness protection requirements – Minimal data integrity concerns (minimal key update/deletes) – Limited searching of data (binary comparisons only) – Limited need for transaction isolation/Short transactions Basically, the “hot” tables in a strict OLTP workload... 43

44. drsql.org The Choices I made Louis has improved his methods for estimating performance, but your mileage will still vary. Louis’ tests are designed to reflect only one certain usage conditions and user behavior, but several factors may affect your mileage significantly: How & Where You Put Your Logs Computer Condition & Maintenance CPU Variations Programmer Coding Variations Hard Disk Break In Therefore, Louis’ performance ratings are a minimally useful tool for comparing the performance of different strategies but may not accurately predict the average performance you will get. I seriously suggest you test the heck out of the technologies yourself using my code, your code, and anyone else’s code you can to make sure you are getting the best performance possible.

45. drsql.org Model Choices – Logical Model 45

46. drsql.org Model Choices – Physical Model 46

47. drsql.org Model Choices – Tables to Make In-Mem (First Try) 47

48. drsql.org Model Choices – Tables to Make In-Mem (Final)

49. drsql.org The Grand Illusion (So you think your life is complete confusion) Performance gains are not exactly what you may expect, even when they are massive In my examples (which you have seen), I discovered when loading 20000 rows (10 connections of 2000 each) – (Captured using Adam Machanic's http://www.datamanipulation.net/SQLQueryStress/ tool)http://www.datamanipulation.net/SQLQueryStress/ A.On-Disk Tables with FK, Instead Of Trigger - 0.0472 seconds per row - Total Time – 1:12 B.On-Disk Tables withOUT FK, Instead Of Trigger - 0.0271 seconds per row - Total Time – 0:51 C.In-Mem Tables using Interop code - 0.0202 seconds per row - Total Time 0:44 D.In-Mem Tables with Native Code - 0.0050 second per row - Total Time – 0:31 E.In-Mem Tables, Native Code, SCHEMA_ONLY – 0.0003 seconds per row - Total Time – 00:30 F.In-Mem Tables (except CustomerAddress), Hybrid code – 0.0163 – Total Time – 0:55 But should it be a lot better? Don't forget the overhead... (And SQLQueryStress has extra for gathering stats)

50. drsql.org 50 Contact info Louis Davidson - louis@drsql.orglouis@drsql.org Website – http://drsql.org <-- Get slides herehttp://drsql.org Twitter – http://twitter.com/drsqlhttp://twitter.com/drsql SQL Blog http://sqlblog.com/blogs/louis_davidsonhttp://sqlblog.com/blogs/louis_davidson Simple Talk Blog – What Counts for a DBA http://www.simple-talk.com/community/blogs/drsql/default.aspx http://www.simple-talk.com/community/blogs/drsql/default.aspx 50

51. drsql.org Demo As Much Code Review As We Have Time For!