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How In-Memory Affects Database Design Louis Davidson drsql.org 1 Who am I? drsql.org • Been in IT for over 19 years • Microsoft MVP For 11 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 InMemory technologies are changing the game 2 Contact info • Louis Davidson - [email protected] • Website – http://drsql.org <-- Get slides here • Twitter – http://twitter.com/drsql(@drsql) • SQL Blog http://sqlblog.com/blogs/louis_davidson • Simple Talk Blog – What Counts for a DBA http://www.simple-talk.com/community/blogs/drsql/default.aspx drsql.org 3 3 Questions are Welcome • Please limit questions to one’s I know the answer to. drsql.org 4 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 drsql.org 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/ 5 Attention! • This presentation was originally based on SQL Server 2014 • SQL Server 2016 promises to greatly improve the feature set • I will note where this does and does not affect your database design experience as I go along with asterisks * drsql.org 6 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) drsql.org • 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 7 7 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 drsql.org –But the implementation is very very different • In-Memory is both very easy, and very difficult to use 9 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 I was first –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 As if… drsql.org • We will discuss how In-Memory technologies affect the entire design/development lifecycle Children Relics 10 Design Basics - Separate your design mind into (minimally) three phases • Conceptual/Logical (Overall data requirements in a data model format) • Physical Implementation Choice –Type of database system: Paper, Excel, Access, SQL Server, NoSQL, etc –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 • Physical (Relational Code) drsql.org • We will look at each of these phases and how in-mem may affect your design of each output 11 Conceptual/Logical Design (Though Not Everyone’s Is) • This is the easiest part of the presentation …to type • You still need to understand the customers needs and model –Entities and Attributes –Uniqueness Conditions –General Predicates • As I see it, nothing changes… drsql.org 12 Logical Data Model drsql.org 13 Physical Implementation Overview Client App TDS Handler and Session Management No improvements in communication stack, parameter passing, result set generation 10-30x more efficient (Real Apps see 2-30x) Reduced log bandwidth & contention. Log latency remains Natively Compiled SPs and Schema Engine for Memory_optimized Tables & Indexes Query Interop Proc/Plan cache for ad-hoc T-SQL and SPs Interpreter for TSQL, query plans, expressions Access Methods Existing SQL Component In-Memory OLTP Component Buffer Pool for Tables & Indexes SQL Server.exe Memory-optimized Table Filegroup Transaction Log Data Filegroup http://download.microsoft.com/documents/hk/technet/techdays2014/Day2/Session2/DBI394-SQL%20Server%202014%20In-Memory%20OLTP%20-%20Depp%20Dive.pdf drsql.org Checkpoints are background sequential IO Native Compiler Parser, Catalog, Algebrizer, Optimizer Key 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 drsql.org 15 Physical Design (No, let’s not get physical) • Your physical design will almost certainly need to be altered from “normal” • 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 drsql.org • Using Normal T-SQL (Interop) • Using Compiled Code (Native) • Using a Hybrid Approach • No Locks, No Latches, No Waiting 16 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-sqlserver-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)* drsql.org – No check constraints * – No foreign keys * – Just one unique index per table * • Every durable (SCHEMA_AND_DATA) table must have a unique index/ 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/ 17 Data quality…What if? Troublesome Two people are travelling to Indianapolis via train, and both order chicken from two different wait persons, but there is only one order of chicken still available Extremely Troublesome Note: The “what if?” test ought to be applied to all of your designs drsql.org If Train A is given access to Location L on Track 1 at 11:30 AM, and Train B is given access to the same Location at the same time going in a different direction. 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 LOB types wouldn’t be good for the OLTP aspects of the table in any case. drsql.org • Note: 2016 allows LOB (varbinary(max), nvarchar(max), varchar(max)) but it is still something you may need to consider, as memory isn’t free… 20 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 drsql.org • 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) – 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 21 A Taste of the Physical Structures • Basic data record for a row Record Header Data For Columns (Payload) • Record Header Begin Timestamp End Timestamp StatementId IndexCount IndexPointers ... 8 3 2 1 drsql.org 22 22 Hash Index - Simplified TableNameId Country OtherColumns 1 USA Values 2 USA Values 3 Canada Values Identity Column Country 1 1 2 0 Φ 1 USA 2 3 3 4 4 0 Φ Φ 2 USA 0 Φ Φ 3 Canada 5 drsql.org 5 6 7 8 9 10 23 23 Hash Index - Simplified TableNameId Country OtherColumns 1 USA Values 2 Canada Values 3 Canada Values Identity Column 1 Country 0 Φ 1 USA 2 2 3 1 3 0 100 Φ 2 USA 4 4 5 5 100 Φ Φ 2 Canada Φ 3 Canada drsql.org 6 7 8 9 0 10 24 24 Bw Tree Index – Even More Simplified Page 0 Page Mapping Table C R Z Non-Leaf Pages By Page ID Page 0 Page 1 Page 1 A B Page 2 C D Page 3 G J S T Z Leaf Pages Page 2 Page 3 0 240 240 Φ OtherVals B DifferentRow B JustDifferent Data Pages 0 Φ D drsql.org 0 B AnotherRow 25 25 Do you want to know more? • For more in-depth coverage –check Kalen Delaney's white paper ... http://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) –Books Online: http://technet.microsoft.com/en-us/library/dn133186.aspx –TechDays Presentation: http://download.microsoft.com/documents/hk/technet/techdays2014/Day2/Session2/DBI394SQL%20Server%202014%20In-Memory%20OLTP%20-%20Depp%20Dive.pdf drsql.org –Buy Kalen Delaney’s Ebook: http://www.amazon.com/gp/product/B00QMWX8PO/ref=docs-os-doi_0 –SQL Server 2016: In-Memory OLTP Enhancementss http://sqlperformance.com/2015/05/sql-server-2016/in-memory-oltp-enhancements 26 Creating Storage Objects - Altering a Table * • The is the second easiest slide in the deck (to write!) • No alterations allowed - Strictly Drop and Recreate* • Cannot rename table ALTER drsql.org 27 DEMO IN SLIDES – PREPARING TO (AND ACTUALLY) CREATING TABLES drsql.org 28 Setting the Database To Allow In-Mem 29 29 drsql.org CREATE DATABASE HowInMemObjectsAffectDesign ON PRIMARY a filegroup to hold the delta ( NAME = N'HowInMemObjectsAffectDesign',Add FILENAME = N‘Drive:\HowInMemObjectsAffectDesign.mdf' , SIZE = 2GB , files 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 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) drsql.org ) WITH ( MEMORY_OPTIMIZED = ON , DURABILITY = SCHEMA_AND_DATA) go 30 30 Creating a Memory Optimized Permanent Table CREATE TABLE Customers.Customer Character column must be binary ( to index/compare in native code * Hash Index used for CustomerId integer NOT NULL IDENTITY ( 1,1 ) , Primary Key. Estimated CustomerNumber Rows in Table 25000 char(10) COLLATE Latin1_General_100_BIN2 NOT NULL, CONSTRAINT XPKCustomer PRIMARY Bw Tree Index on KEY NONCLUSTERED CustomerWITH Number HASH ( This CustomerId) ( BUCKET_COUNT = 50000), table is memory INDEX drsql.org optimized Thisoftable is as durable as (ok, that was kind CustomerNumber NONCLUSTERED ( CustomerNumber) obvious) the database settings allow ) WITH ( MEMORY_OPTIMIZED = ON , DURABILITY = SCHEMA_AND_DATA) go 31 31 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 drsql.org 32 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 • Some really extremely annoying ones: drsql.org –SUBSTRING supported; LEFT, RIGHT, not so much –No Subqueries * –OR, NOT, IN, not supported in WHERE clause * –String Comparisons must be with columns of Binary Collation * –Can’t use on-disk objects (tables, sequences, views, etc) –Can’t call a stored procedures from another stored procedure * • So you may have to write some "interesting" code 33 DEMO IN SLIDES – NATIVE STORED PROCEDURE drsql.org 34 Creating a Natively Optimized Procedure (I write my C# the new fashioned way, with T-SQL) Works just like for views CREATE PROCEDURE Customers.Customer$CreateAndReturnThere is no Ownership and functions. Can’t @Parameter1 Parameter1Type = change 'defaultValue1', chaining. All code the underlying @Parameter2 Parameter2Type =object 'defaultValue2', executes as the while this object Alert parser that this will procedure owner … references it be a natively compiled @ParameterNobject ParameterNType = 'defaultValueN‘ WITH NATIVE_COMPILATION, SCHEMABINDING, EXECUTE AS OWNER AS BEGIN ATOMIC WITH ( TRANSACTION ISOLATION LEVEL = SNAPSHOT, LANGUAGE = N'us_english' ) <code> drsql.org END Procedures are atomic transactions 35 Accessing Data Using a Hybrid Approach • Native code is very fast but very limited (* Still true, but less so) • Use Native code where it makes sense, and not where it doesn’t • Example: Creating a sequential value drsql.org –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 36 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 manual data integrity checking "interesting" • Essential difference, your code now must handle errors drsql.org 37 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. drsql.org 38 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 drsql.org –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 39 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 procedures –Uniqueness on > 1 column set suffers from timing (If N connections are inserting the same data...MVCC will let them) * –Foreign Key type checks 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. drsql.org • Note: Constraints in 2016 will often be more important that for on disk tables because of the lack of blocking operations 40 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 drsql.org • Msg 10794, Level 16, State 12, Line 8 The operation 'CREATE INDEX' is not supported with memory optimized tables. 41 Problem: How to Implement Uniqueness on > 1 Column Set: Multiple Tables? drsql.org • Wow, that seems messy… And what about duplicate customerId values in the two subordinate tables? 42 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 drsql.org 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 • Even still, this sort of code is reducing the value, isn’t it? 43 Foreign Keys and Unique Index/Constraints in 2016 (Pure conjecture based on how things work now) • In the traditional engine, these are implemented with locks • In the in-mem engine, you have to expect that it will be implemented much like the isolation levels • Basically, if two transactions do operations that would have blocked, the other connection will likely fail either: –At COMMIT (Currently PRIMARY KEY Violations fail at COMMIT) –At first sign of trouble (As is the case when you modify existing resources) drsql.org 44 When Should You Make Tables In-Memory Louis's Advice • Read Microsoft’s Opinion Here: http://msdn.microsoft.com/en-us/library/dn133186.aspx • 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 – You are able to answer all “What If?” scenarios successfully. • Basically, the “very hot” tables in a strict OLTP workload... drsql.org – I don’t see this changing, but the scenarios where it fits will expand in 2016 • NOT a way to “FIX” bad code… Not at all… • In fact, most applications will need to be re-engineered to deal with MVCC. 46 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 drsql.org • 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. • The Choices (For Me) will differ in 2016… Model Choices – Logical Model drsql.org 48 Model Choices – Physical Model drsql.org 49 Model Choices – Tables to Make In-Mem (First Try) drsql.org 50 Model Choices – Tables to Make In-Mem (Final 2014 Thinking) 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 is available on my website), I discovered when loading 20000 rows (10 connections of 2000 each) – (Captured using Adam Machanic's http://www.datamanipulation.net/SQLQueryStress/ tool) – On-Disk Tables with FK and Instead Of Trigger - 0.0472 seconds per row - Total Time – 1:12 – On-Disk Tables without FK or Instead Of Trigger - 0.0271 seconds per row - Total Time – 0:51 – In-Mem Tables using Interop code - 0.0202 seconds per row - Total Time 0:44 – In-Mem Tables with Native Code - 0.0050 second per row - Total Time – 0:31 – In-Mem Tables, Native Code, SCHEMA_ONLY – 0.0003 seconds per row - Total Time – 00:30 – In-Mem Tables (except CustomerAddress), Hybrid code – 0.0163 – Total Time – 0:42 • But should it be a lot better? Don't forget the overhead... (And SQLQueryStress has extra for gathering stats) drsql.org – In-Mem Tables using 2016 enhancements – Coming soon to a SQLblog near you when enough features available Contact info • Louis Davidson - [email protected] • Website – http://drsql.org <-- Get slides here • Twitter – http://twitter.com/drsql (@drsql) • SQL Blog http://sqlblog.com/blogs/louis_davidson • Simple Talk Blog – What Counts for a DBA http://www.simple-talk.com/community/blogs/drsql/default.aspx drsql.org 53 53